Multisensor data fusion across time and space

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Reed, Robert A.

2014-06-01

Field measurement campaigns typically deploy numerous sensors having different sampling characteristics for spatial, temporal, and spectral domains. Data analysis and exploitation is made more difficult and time consuming as the sample data grids between sensors do not align. This report summarizes our recent effort to demonstrate feasibility of a processing chain capable of "fusing" image data from multiple independent and asynchronous sensors into a form amenable to analysis and exploitation using commercially-available tools. Two important technical issues were addressed in this work: 1) Image spatial registration onto a common pixel grid, 2) Image temporal interpolation onto a common time base. The first step leverages existing image matching and registration algorithms. The second step relies upon a new and innovative use of optical flow algorithms to perform accurate temporal upsampling of slower frame rate imagery. Optical flow field vectors were first derived from high-frame rate, high-resolution imagery, and then finally used as a basis for temporal upsampling of the slower frame rate sensor's imagery. Optical flow field values are computed using a multi-scale image pyramid, thus allowing for more extreme object motion. This involves preprocessing imagery to varying resolution scales and initializing new vector flow estimates using that from the previous coarser-resolution image. Overall performance of this processing chain is demonstrated using sample data involving complex too motion observed by multiple sensors mounted to the same base. Multiple sensors were included, including a high-speed visible camera, up to a coarser resolution LWIR camera.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

NASA Astrophysics Data System (ADS)

Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.

2018-02-01

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.

Emotion-induced trade-offs in spatiotemporal vision.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-05-01

It is generally assumed that emotion facilitates human vision in order to promote adaptive responses to a potential threat in the environment. Surprisingly, we recently found that emotion in some cases impairs the perception of elementary visual features (Bocanegra & Zeelenberg, 2009b). Here, we demonstrate that emotion improves fast temporal vision at the expense of fine-grained spatial vision. We tested participants' threshold resolution with Landolt circles containing a small spatial or brief temporal discontinuity. The prior presentation of a fearful face cue, compared with a neutral face cue, impaired spatial resolution but improved temporal resolution. In addition, we show that these benefits and deficits were triggered selectively by the global configural properties of the faces, which were transmitted only through low spatial frequencies. Critically, the common locus of these opposite effects suggests a trade-off between magno- and parvocellular-type visual channels, which contradicts the common assumption that emotion invariably improves vision. We show that, rather than being a general "boost" for all visual features, affective neural circuits sacrifice the slower processing of small details for a coarser but faster visual signal.

Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, G.; Lin, T.

2013-12-01

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ; 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7-8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals. The retrieved soundings are also tested in a regional data assimilation WRF 3D-var system to evaluate the potential assist in the NWP model.

Downscaling of Seasonal Landsat-8 and MODIS Land Surface Temperature (LST) in Kolkata, India

NASA Astrophysics Data System (ADS)

Garg, R. D.; Guha, S.; Mondal, A.; Lakshmi, V.; Kundu, S.

2017-12-01

The quality of life of urban people is affected by urban heat environment. The urban heat studies can be carried out using remotely sensed thermal infrared imagery for retrieving Land Surface Temperature (LST). Currently, high spatial resolution (<200 m) thermal images are limited and their temporal resolution is low (e.g., 17 days of Landsat-8). Coarse spatial resolution (1000 m) and high temporal resolution (daily) thermal images of MODIS (Moderate Resolution Imaging Spectroradiometer) are frequently available. The present study is to downscale spatially coarser resolution of the thermal image to fine resolution thermal image using regression based downscaling technique. This method is based on the relationship between (LST) and vegetation indices (e.g., Normalized Difference Vegetation Index or NDVI) over a heterogeneous landscape. The Kolkata metropolitan city, which experiences a tropical wet-and-dry type of climate has been selected for the study. This study applied different seasonal open source satellite images viz., Landsat-8 and Terra MODIS. The Landsat-8 images are aggregated at 960 m resolution and downscaled into 480, 240 120 and 60 m. Optical and thermal resolution of Landsat-8 and MODIS are 30 m and 60 m; 250 m and 1000 m respectively. The homogeneous land cover areas have shown better accuracy than heterogeneous land cover areas. The downscaling method plays a crucial role while the spatial resolution of thermal band renders it unable for advanced study. Key words: Land Surface Temperature (LST), Downscale, MODIS, Landsat, Kolkata

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact.

PubMed

Khanna, Shruti; Santos, Maria J; Ustin, Susan L; Shapiro, Kristen; Haverkamp, Paul J; Lay, Mui

2018-02-12

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact

PubMed Central

Santos, Maria J.; Ustin, Susan L.; Haverkamp, Paul J.; Lay, Mui

2018-01-01

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills. PMID:29439504

Exploiting MISR products at the full spatial resolution (275m) to document changes in land properties in and around the Kruger National Park, South Africa

NASA Astrophysics Data System (ADS)

Verstraete, M. M.; Hunt, L. A.; Pinty, B.; Clerici, M.; Scholes, R. J.

2009-12-01

The MISR instrument on NASA's Terra platform has been acquiring data globally and continuously for almost 10 years. A wide range of atmospheric and land products are operationally generated at the LaRC ASDC, at spatial resolutions of 1.1 km or coarser. Yet, the intrinsic spatial resolution of that sensor is 275m and 12 out of the 36 spectro-directional data channels are transmitted to the ground segment at that resolution. Recent algorithmic developments have permitted us to reconstruct reasonable estimates of the other 24 channels and to account for atmospheric effects at the full original spatial resolution. Spectro-directional reflectances have been processed to characterize the anisotropy of observed land surfaces and then optimally estimate various geophysical properties of the environment such as the fluxes of radiation in and out of plant canopies, the albedo, FAPAR, etc. These detailed products allow us to investigate ecological and environmental changes in much greater spatial and thematic detail than was previously possible. The paper outlines the various methodological steps implemented and exhibits concrete results for a region of moderate size (280 by 380 km) in South Africa. Practical downstream applications of this approach include monitoring desertification and biomass burning, documenting urbanization or characterizing the phenology of vegetation.

Super-resolution mapping using multi-viewing CHRIS/PROBA data

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

High-spatial resolution Remote Sensing (RS) data provides detailed information which ensures high-definition visual image analysis of earth surface features. These data sets also support improved information extraction capabilities at a fine scale. In order to improve the spatial resolution of coarser resolution RS data, the Super Resolution Reconstruction (SRR) technique has become widely acknowledged which focused on multi-angular image sequences. In this study multi-angle CHRIS/PROBA data of Kutch area is used for SR image reconstruction to enhance the spatial resolution from 18 m to 6m in the hope to obtain a better land cover classification. Various SR approaches like Projection onto Convex Sets (POCS), Robust, Iterative Back Projection (IBP), Non-Uniform Interpolation and Structure-Adaptive Normalized Convolution (SANC) chosen for this study. Subjective assessment through visual interpretation shows substantial improvement in land cover details. Quantitative measures including peak signal to noise ratio and structural similarity are used for the evaluation of the image quality. It was observed that SANC SR technique using Vandewalle algorithm for the low resolution image registration outperformed the other techniques. After that SVM based classifier is used for the classification of SRR and data resampled to 6m spatial resolution using bi-cubic interpolation. A comparative analysis is carried out between classified data of bicubic interpolated and SR derived images of CHRIS/PROBA and SR derived classified data have shown a significant improvement of 10-12% in the overall accuracy. The results demonstrated that SR methods is able to improve spatial detail of multi-angle images as well as the classification accuracy.

Stennis Space Center Verification & Validation Capabilities

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Ryan, Robert E.; Holekamp, Kara; ONeal, Duane; Knowlton, Kelly; Ross, Kenton; Blonski, Slawomir

2005-01-01

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Stennis Space Center Verification & Validation Capabilities

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Ryan, Robert E.; Holekamp, Kara; O'Neal, Duane; Knowlton, Kelly; Ross, Kenton; Blonski, Slawomir

2007-01-01

Scientists within NASA#s Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists have used the SSC V&V site to characterize thermal infrared systems. Enhancements are being considered to characterize active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. Similar techniques are used to characterize moderate spatial resolution sensing systems at selected nearby locations. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Simulation of population-based commuter exposure to NO₂ using different air pollution models.

PubMed

Ragettli, Martina S; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C

2014-05-12

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model

NASA Astrophysics Data System (ADS)

Thomas Steven Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2016-11-01

Where high-resolution topographic data are available, modelers are faced with the decision of whether it is better to spend computational resource on resolving topography at finer resolutions or on running more simulations to account for various uncertain input factors (e.g., model parameters). In this paper we apply global sensitivity analysis to explore how influential the choice of spatial resolution is when compared to uncertainties in the Manning's friction coefficient parameters, the inflow hydrograph, and those stemming from the coarsening of topographic data used to produce Digital Elevation Models (DEMs). We apply the hydraulic model LISFLOOD-FP to produce several temporally and spatially variable model outputs that represent different aspects of flood inundation processes, including flood extent, water depth, and time of inundation. We find that the most influential input factor for flood extent predictions changes during the flood event, starting with the inflow hydrograph during the rising limb before switching to the channel friction parameter during peak flood inundation, and finally to the floodplain friction parameter during the drying phase of the flood event. Spatial resolution and uncertainty introduced by resampling topographic data to coarser resolutions are much more important for water depth predictions, which are also sensitive to different input factors spatially and temporally. Our findings indicate that the sensitivity of LISFLOOD-FP predictions is more complex than previously thought. Consequently, the input factors that modelers should prioritize will differ depending on the model output assessed, and the location and time of when and where this output is most relevant.

Prescription of land-surface boundary conditions in GISS GCM 2: A simple method based on high-resolution vegetation data bases

NASA Technical Reports Server (NTRS)

Matthews, E.

1984-01-01

A simple method was developed for improved prescription of seasonal surface characteristics and parameterization of land-surface processes in climate models. This method, developed for the Goddard Institute for Space Studies General Circulation Model II (GISS GCM II), maintains the spatial variability of fine-resolution land-cover data while restricting to 8 the number of vegetation types handled in the model. This was achieved by: redefining the large number of vegetation classes in the 1 deg x 1 deg resolution Matthews (1983) vegetation data base as percentages of 8 simple types; deriving roughness length, field capacity, masking depth and seasonal, spectral reflectivity for the 8 types; and aggregating these surface features from the 1 deg x 1 deg resolution to coarser model resolutions, e.g., 8 deg latitude x 10 deg longitude or 4 deg latitude x 5 deg longitude.

Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

PubMed Central

Losch, Martin; Menemenlis, Dimitris

2018-01-01

Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

PubMed

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

NASA Astrophysics Data System (ADS)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

USGS Publications Warehouse

Dell’Acqua, F.; Gamba, P.; Jaiswal, K.

2012-01-01

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

A Petascale Non-Hydrostatic Atmospheric Dynamical Core in the HOMME Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tufo, Henry

The High-Order Method Modeling Environment (HOMME) is a framework for building scalable, conserva- tive atmospheric models for climate simulation and general atmospheric-modeling applications. Its spatial discretizations are based on Spectral-Element (SE) and Discontinuous Galerkin (DG) methods. These are local methods employing high-order accurate spectral basis-functions that have been shown to perform well on massively parallel supercomputers at any resolution and scale particularly well at high resolutions. HOMME provides the framework upon which the CAM-SE community atmosphere model dynamical-core is constructed. In its current incarnation, CAM-SE employs the hydrostatic primitive-equations (PE) of motion, which limits its resolution to simulations coarser thanmore » 0.1 per grid cell. The primary objective of this project is to remove this resolution limitation by providing HOMME with the capabilities needed to build nonhydrostatic models that solve the compressible Euler/Navier-Stokes equations.« less

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical levels

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2011-12-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2012-05-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

Simulation of Population-Based Commuter Exposure to NO2 Using Different Air Pollution Models

PubMed Central

Ragettli, Martina S.; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E.; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C.

2014-01-01

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61) than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51), and a land use regression model (41 ± 5 µg m−3; range: 24–54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas. PMID:24823664

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Spatio-temporal representativeness of ground-based downward solar radiation measurements

NASA Astrophysics Data System (ADS)

Schwarz, Matthias; Wild, Martin; Folini, Doris

2017-04-01

Surface solar radiation (SSR) is most directly observed with ground based pyranometer measurements. Besides measurement uncertainties, which arise from the pyranometer instrument itself, also errors attributed to the limited spatial representativeness of observations from single sites for their large-scale surrounding have to be taken into account when using such measurements for energy balance studies. In this study the spatial representativeness of 157 homogeneous European downward surface solar radiation time series from the Global Energy Balance Archive (GEBA) and the Baseline Surface Radiation Network (BSRN) were examined for the period 1983-2015 by using the high resolution (0.05°) surface solar radiation data set from the Satellite Application Facility on Climate Monitoring (CM-SAF SARAH) as a proxy for the spatiotemporal variability of SSR. By correlating deseasonalized monthly SSR time series form surface observations against single collocated satellite derived SSR time series, a mean spatial correlation pattern was calculated and validated against purely observational based patterns. Generally decreasing correlations with increasing distance from station, with high correlations (R2 = 0.7) in proximity to the observational sites (±0.5°), was found. When correlating surface observations against time series from spatially averaged satellite derived SSR data (and thereby simulating coarser and coarser grids), very high correspondence between sites and the collocated pixels has been found for pixel sizes up to several degrees. Moreover, special focus was put on the quantification of errors which arise in conjunction to spatial sampling when estimating the temporal variability and trends for a larger region from a single surface observation site. For 15-year trends on a 1° grid, errors due to spatial sampling in the order of half of the measurement uncertainty for monthly mean values were found.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

2004-08-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.

Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions

NASA Astrophysics Data System (ADS)

Yu, Karen; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Miller, Christopher C.; Travis, Katherine R.; Zhu, Lei; Yantosca, Robert M.; Sulprizio, Melissa P.; Cohen, Ron C.; Dibb, Jack E.; Fried, Alan; Mikoviny, Tomas; Ryerson, Thomas B.; Wennberg, Paul O.; Wisthaler, Armin

2016-04-01

Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.

Measurement Sets and Sites Commonly Used for Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Measurement Sets and Sites Commonly used for Characterizations

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Blonski, Slawomir; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

Effect of Spatial Resolution for Characterizing Soil Properties from Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Dutta, D.; Kumar, P.; Greenberg, J. A.

2015-12-01

The feasibility of quantifying soil constituents over large areas using airborne hyperspectral data [0.35 - 2.5 μm] in an ensemble bootstrapping lasso algorithmic framework has been demonstrated previously [1]. However the effects of coarsening the spatial resolution of hyperspectral data on the quantification of soil constituents are unknown. We use Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected at 7.6m resolution over Birds Point New Madrid (BPNM) floodway for up-scaling and generating multiple coarser resolution datasets including the 60m Hyperspectral Infrared Imager (HyspIRI) like data. HyspIRI is a proposed visible shortwave/thermal infrared mission, which will provide global data over a spectral range of 0.35 - 2.5μm at a spatial resolution of 60m. Our results show that the lasso method, which is based on point scale observational data, is scalable. We found consistent good model performance (R2) values (0.79 < R2 < 0.82) and correct classifications as per USDA soil texture classes at multiple spatial resolutions. The results further demonstrate that the attributes of the pdf for different soil constituents across the landscape and the within-pixel variance are well preserved across scales. Our analysis provides a methodological framework with a sufficient set of metrics for assessing the performance of scaling up analysis from point scale observational data and may be relevant for other similar remote sensing studies. [1] Dutta, D.; Goodwell, A.E.; Kumar, P.; Garvey, J.E.; Darmody, R.G.; Berretta, D.P.; Greenberg, J.A., "On the Feasibility of Characterizing Soil Properties From AVIRIS Data," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.9, pp.5133,5147, Sept. 2015. doi: 10.1109/TGRS.2015.2417547.

Biomechanics meets the ecological niche: the importance of temporal data resolution.

PubMed

Kearney, Michael R; Matzelle, Allison; Helmuth, Brian

2012-03-15

The emerging field of mechanistic niche modelling aims to link the functional traits of organisms to their environments to predict survival, reproduction, distribution and abundance. This approach has great potential to increase our understanding of the impacts of environmental change on individuals, populations and communities by providing functional connections between physiological and ecological response to increasingly available spatial environmental data. By their nature, such mechanistic models are more data intensive in comparison with the more widely applied correlative approaches but can potentially provide more spatially and temporally explicit predictions, which are often needed by decision makers. A poorly explored issue in this context is the appropriate level of temporal resolution of input data required for these models, and specifically the error in predictions that can be incurred through the use of temporally averaged data. Here, we review how biomechanical principles from heat-transfer and metabolic theory are currently being used as foundations for mechanistic niche models and consider the consequences of different temporal resolutions of environmental data for modelling the niche of a behaviourally thermoregulating terrestrial lizard. We show that fine-scale temporal resolution (daily) data can be crucial for unbiased inference of climatic impacts on survival, growth and reproduction. This is especially so for species with little capacity for behavioural buffering, because of behavioural or habitat constraints, and for detecting temporal trends. However, coarser-resolution data (long-term monthly averages) can be appropriate for mechanistic studies of climatic constraints on distribution and abundance limits in thermoregulating species at broad spatial scales.

Landsat 7 thermal-IR image sharpening using an artificial neural network and sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; Schowengerdt, R.A.; ,

2001-01-01

The enhanced thematic mapper (plus) (ETM+) instrument on Landsat 7 shares the same basic design as the TM sensors on Landsats 4 and 5, with some significant improvements. In common are six multispectral bands with a 30-m ground-projected instantaneous field of view (GIFOV). However, the thermaL-IR (TIR) band now has a 60-m GIFOV, instead of 120-m. Also, a 15-m panchromatic band has been added. The artificial neural network (NN) image sharpening method described here uses data from the higher spatial resolution ETM+ bands to enhance (sharpen) the spatial resolution of the TIR imagery. It is based on an assumed correlation over multiple scales of resolution, between image edge contrast patterns in the TIR band and several other spectral bands. A multilayer, feedforward NN is trained to approximate TIR data at 60m, given degraded (from 30-m to 60-m) spatial resolution input from spectral bands 7, 5, and 2. After training, the NN output for full-resolution input generates an approximation of a TIR image at 30-m resolution. Two methods are used to degrade the spatial resolution of the imagery used for NN training, and the corresponding sharpening results are compared. One degradation method uses a published sensor transfer function (TF) for Landsat 5 to simulate sensor coarser resolution imagery from higher resolution imagery. For comparison, the second degradation method is simply Gaussian low pass filtering and subsampling, wherein the Gaussian filter approximates the full width at half maximum amplitude characteristics of the TF-based spatial filter. Two fixed-size NNs (that is, number of weights and processing elements) were trained separately with the degraded resolution data, and the sharpening results compared. The comparison evaluates the relative influence of the degradation technique employed and whether or not it is desirable to incorporate a sensor TF model. Preliminary results indicate some improvements for the sensor model-based technique. Further evaluation using a higher resolution reference image and strict application of sensor model to data is recommended.

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over Valencia Anchor Station by Using Downscaling Technique

NASA Astrophysics Data System (ADS)

Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali

2016-07-01

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE PAGES

Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...

2016-07-22

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Sha; Lauvaux, Thomas; Newman, Sally

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.

The use of thematic mapper data for land cover discrimination: Preliminary results from the UK SATMaP programme

NASA Technical Reports Server (NTRS)

Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.

1983-01-01

The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8-bit quantization is not being effectively utilized for all the bands.

Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, S.; Martin, R. V.; Keller, C. A.

2015-11-01

Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements. Part I; MODIS Brightness Temperatures in the Thermal Infrared

NASA Technical Reports Server (NTRS)

Fauchez, Thomas; Platnick, Steven; Meyer, Kerry; Cornet, Celine; Szczap, Frederic; Varnai, Tamas

2017-01-01

This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 meters to 10 kilometers. A realistic 3-D (three-dimensional) cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloudtop and base altitudes at 10 and 12 kilometers, respectively, consisting of aggregate column crystals of D (sub eff) equals 20 microns), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL (3-D Monte Carlo Polarized) code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D (one-dimensional) RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB); and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial resolution results (above approximately 250 meters), with averaged values of up to 5-7 K (thousand), while the IPAE mainly impacts the high-spatial resolution results (below approximately 250 meters) with average values of up to 1-2 K (thousand). A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 meters. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-05-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In this study, 16 simulations are conducted using WRF-Fire to examine the sensitivity of resolving VDLS to spatial resolution and atmosphere-fire coupling within the WRF-Fire model framework. The horizontal grid spacing is varied between 25 and 90 m, and the two-way atmosphere-fire coupling is either enabled or disabled. At high spatial resolution, the atmosphere-fire coupling increases the peak uphill and lateral spread rate by a factor of up to 2.7 and 9.5. The enhancement of the uphill and lateral spread rate diminishes at coarser spatial resolution, and VDLS is not modelled for a horizontal grid spacing of 90 m. The laterally spreading fire fronts become the dominant contributors of the extreme pyro-convection. The resolved fire-induced vortices responsible for driving the lateral spread in the coupled simulations have non-zero vorticity along each unit vector direction, and develop due to an interaction between the background winds and vertical return circulations generated at the flank of the fire front as part of the pyro-convective updraft. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to reproduce VDLS within the current WRF-Fire model framework.

The application of Global Sensitivity Analysis to quantify the dominant input factors for hydraulic model simulations

NASA Astrophysics Data System (ADS)

Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2015-04-01

Predicting flood inundation extents using hydraulic models is subject to a number of critical uncertainties. For a specific event, these uncertainties are known to have a large influence on model outputs and any subsequent analyses made by risk managers. Hydraulic modellers often approach such problems by applying uncertainty analysis techniques such as the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. However, these methods do not allow one to attribute which source of uncertainty has the most influence on the various model outputs that inform flood risk decision making. Another issue facing modellers is the amount of computational resource that is available to spend on modelling flood inundations that are 'fit for purpose' to the modelling objectives. Therefore a balance needs to be struck between computation time, realism and spatial resolution, and effectively characterising the uncertainty spread of predictions (for example from boundary conditions and model parameterisations). However, it is not fully understood how much of an impact each factor has on model performance, for example how much influence changing the spatial resolution of a model has on inundation predictions in comparison to other uncertainties inherent in the modelling process. Furthermore, when resampling fine scale topographic data in the form of a Digital Elevation Model (DEM) to coarser resolutions, there are a number of possible coarser DEMs that can be produced. Deciding which DEM is then chosen to represent the surface elevations in the model could also influence model performance. In this study we model a flood event using the hydraulic model LISFLOOD-FP and apply Sobol' Sensitivity Analysis to estimate which input factor, among the uncertainty in model boundary conditions, uncertain model parameters, the spatial resolution of the DEM and the choice of resampled DEM, have the most influence on a range of model outputs. These outputs include whole domain maximum inundation indicators and flood wave travel time in addition to temporally and spatially variable indicators. This enables us to assess whether the sensitivity of the model to various input factors is stationary in both time and space. Furthermore, competing models are assessed against observations of water depths from a historical flood event. Consequently we are able to determine which of the input factors has the most influence on model performance. Initial findings suggest the sensitivity of the model to different input factors varies depending on the type of model output assessed and at what stage during the flood hydrograph the model output is assessed. We have also found that initial decisions regarding the characterisation of the input factors, for example defining the upper and lower bounds of the parameter sample space, can be significant in influencing the implied sensitivities.

Small scale H I structure and the soft X-ray background

NASA Technical Reports Server (NTRS)

Jahoda, K.; Mccammon, D.; Lockman, F. J.

1986-01-01

The observed anticorrelation between diffuse soft X-ray flux and H I column density has been explained as absorption of soft X-rays produced in a hot galactic halo, assuming that the neutral interstellar material is sufficiently clumped to reduce the soft X-ray absorption cross section by a factor of two to three. A 21 cm emission line study of H I column density variations at intermediate and high galactic latitudes to 10' spatial resolution has been done. The results confirm conclusions from preliminary work at coarser resolution, and in combination with other data appear to rule out the hypothesis that clumping of neutral interstellar matter on any angular scale significantly reduces X-ray absorption cross sections in the 0.13 - 0.28 keV energy range. It is concluded therefore that the observed anticorrelation is not primarily a consequence of absorption of soft X-rays produced in a hot galactic halo.

Simulation of a 7.7 MW onshore wind farm with the Actuator Line Model

NASA Astrophysics Data System (ADS)

Guggeri, A.; Draper, M.; Usera, G.

2017-05-01

Recently, the Actuator Line Model (ALM) has been evaluated with coarser resolution and larger time steps than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition. The aim of the present paper is to continue these studies, assessing the capability of the ALM to represent the wind turbines’ interactions in an onshore wind farm. The ‘Libertad’ wind farm, which consists of four 1.9MW Vestas V100 wind turbines, was simulated considering different wind directions, and the results were compared with the wind farm SCADA data, finding good agreement between them. A sensitivity analysis was performed to evaluate the influence of the spatial resolution, finding acceptable agreement, although some differences were found. It is believed that these differences are due to the characteristics of the different Atmospheric Boundary Layer (ABL) simulations taken as inflow condition (precursor simulations).

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth J.

2013-01-01

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

Assessing representation errors of IAGOS CO2, CO and CH4 profile observations: the impact of spatial variations in near-field emissions

NASA Astrophysics Data System (ADS)

Boschetti, Fabio; Thouret, Valerie; Nedelec, Philippe; Chen, Huilin; Gerbig, Christoph

2015-04-01

Airborne platforms have their main strength in the ability of collecting mixing ratio and meteorological data at different heights across a vertical profile, allowing an insight in the internal structure of the atmosphere. However, rental airborne platforms are usually expensive, limiting the number of flights that can be afforded and hence on the amount of data that can be collected. To avoid this disadvantage, the MOZAIC/IAGOS (Measurements of Ozone and water vapor by Airbus In-service airCraft/In-service Aircraft for a Global Observing System) program makes use of commercial airliners, providing data on a regular basis. It is therefore considered an important tool in atmospheric investigations. However, due to the nature of said platforms, MOZAIC/IAGOS's profiles are located near international airports, which are usually significant emission sources, and are in most cases close to major urban settlements, characterized by higher anthropogenic emissions compared to rural areas. When running transport models at finite resolution, these local emissions can heavily affect measurements resulting in biases in model/observation mismatch. Model/observation mismatch can include different aspects in both horizontal and vertical direction, for example spatial and temporal resolution of the modeled fluxes, or poorly represented convective transport or turbulent mixing in the boundary layer. In the framework of the IGAS (IAGOS for GMES Atmospheric Service) project, whose aim is to improve connections between data collected by MOZAIC/IAGOS and Copernicus Atmospheric Service, the present study is focused on the effect of the spatial resolution of emission fluxes, referred to here as representation error. To investigate this, the Lagrangian transport model STILT (Stochastic Time Inverted Lagrangian Transport) was coupled with EDGAR (Emission Database for Global Atmospheric Research) version-4.3 emission inventory at European regional scale. EDGAR's simulated fluxes for CO, CO2 and CH4 with a spatial resolution of 10x10 km for the time frame 2006-2011 was be aggregated into coarser and coarser grid cells in order to evaluate the representation error at different spatial scales. The dependence of representation error from wind direction and month of the year was evaluated for different location in the European domain, for both random and bias component. The representation error was then validated against the model-data mismatch derived from the comparison of MACC (Monitoring Atmospheric Composition and Climate) reanalysis with IAGOS observations for CO to investigate its suitability for modeling applications. We found that the random and bias components of the representation error show a similar pattern dependent on wind direction. In addition, we found a clear linear relationship between the representation error and the model-data mismatch for both (random and bias) components, indicating that about 50% of the model-data mismatch is related to the representation error. This suggests that the representation error derived using STILT provides useful information for better understanding causes for model-data mismatch.

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Estes, Maurice, Jr.; Estes, Sue; Quattrochi, Dale; Johnson, Daniel

2013-01-01

This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

Evaluation of Statistical Downscaling Skill at Reproducing Extreme Events

NASA Astrophysics Data System (ADS)

McGinnis, S. A.; Tye, M. R.; Nychka, D. W.; Mearns, L. O.

2015-12-01

Climate model outputs usually have much coarser spatial resolution than is needed by impacts models. Although higher resolution can be achieved using regional climate models for dynamical downscaling, further downscaling is often required. The final resolution gap is often closed with a combination of spatial interpolation and bias correction, which constitutes a form of statistical downscaling. We use this technique to downscale regional climate model data and evaluate its skill in reproducing extreme events. We downscale output from the North American Regional Climate Change Assessment Program (NARCCAP) dataset from its native 50-km spatial resolution to the 4-km resolution of University of Idaho's METDATA gridded surface meterological dataset, which derives from the PRISM and NLDAS-2 observational datasets. We operate on the major variables used in impacts analysis at a daily timescale: daily minimum and maximum temperature, precipitation, humidity, pressure, solar radiation, and winds. To interpolate the data, we use the patch recovery method from the Earth System Modeling Framework (ESMF) regridding package. We then bias correct the data using Kernel Density Distribution Mapping (KDDM), which has been shown to exhibit superior overall performance across multiple metrics. Finally, we evaluate the skill of this technique in reproducing extreme events by comparing raw and downscaled output with meterological station data in different bioclimatic regions according to the the skill scores defined by Perkins et al in 2013 for evaluation of AR4 climate models. We also investigate techniques for improving bias correction of values in the tails of the distributions. These techniques include binned kernel density estimation, logspline kernel density estimation, and transfer functions constructed by fitting the tails with a generalized pareto distribution.

Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany

NASA Astrophysics Data System (ADS)

Bechtel, Benjamin; Zakšek, Klemen

2013-04-01

Land surface temperature (LST) is an important parameter for the urban radiation and heat balance and a boundary condition for the atmospheric urban heat island (UHI). The increase in urban surface temperatures compared to the surrounding area (surface urban heat island, SUHI) has been described and analysed with satellite-based measurements for several decades. Besides continuous progress in the development of new sensors, an operational monitoring is still severely limited by physical constraints regarding the spatial and temporal resolution of the satellite data. Essentially, two measurement concepts must be distinguished: Sensors on geostationary platforms have high temporal (several times per hour) and poor spatial resolution (~ 5 km) while those on low earth orbiters have high spatial (~ 100-1000 m) resolution and a long return period (one day to several weeks). To enable an observation with high temporal and spatial resolution, a downscaling scheme for LST from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard the geostationary meteorological Meteosat 9 to spatial resolutions between 100 and 1000 m was developed and tested for Hamburg in this case study. Therefore, various predictor sets (including parameters derived from multi-temporal thermal data, NDVI, and morphological parameters) were tested. The relationship between predictors and LST was empirically calibrated in the low resolution domain and then transferred to the high resolution domain. The downscaling was validated with LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for the same time. Aggregated parameters from multi-temporal thermal data (in particular annual cycle parameters and principal components) proved particularly suitable. The results for the highest resolution of 100 m showed a high explained variance (R² = 0.71) and relatively low root mean square errors (RMSE = 2.2 K). Larger predictor sets resulted in higher errors, because they tended to overfit. As expected the results were better for coarser spatial resolutions (R² = 0.80, RMSE = 1.8 K for 500 m). These results are similar or slightly better than in previous studies, although we are not aware of any study with a comparably large downscaling factor. A considerable percentage of the error is systematic due to the different viewing geometry of the sensors (the high resolution LST was overestimated about 1.3 K). The study shows that downscaling of SEVIRI LST is possible up to a resolution of 100 m for urban areas and that multi-temporal thermal data are particularly suitable as predictors.

GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice

PubMed Central

Dolinoy, Dana C.; Miranda, Marie Lynn

2004-01-01

The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines. PMID:15579419

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape

NASA Astrophysics Data System (ADS)

Kganyago, Mahlatse; Odindi, John; Adjorlolo, Clement; Mhangara, Paidamoyo

2018-05-01

Globally, there is paucity of accurate information on the spatial distribution and patch sizes of Invasive Alien Plants (IAPs) species. Such information is needed to aid optimisation of control mechanisms to prevent further spread of IAPs and minimize their impacts. Recent studies have shown the capability of very high spatial (<1 m) and spectral resolution (<10 nm) data for discriminating vegetation species. However, very high spatial resolution may introduce significant intra-species spectral variability and result in reduced mapping accuracy, while higher spectral resolution data are commonly limited to smaller areas, are costly and computationally expensive. Alternatively, medium and high spatial resolution data are available at low or no cost and have limitedly been evaluated for their potential in determining invasion patterns relevant for invasion ecology and aiding effective IAPs management. In this study medium and high resolution datasets from Landsat Operational Land Imager (OLI) and SPOT 6 sensors respectively, were evaluated for mapping the distribution and patch sizes of IAP, Parthenium hysterophorus in the savannah landscapes of KwaZulu-Natal, South Africa. Support Vector Machines (SVM) classifier was used for classification of both datasets. Results indicated that SPOT 6 had a higher overall accuracy (86%) than OLI (83%) in mapping P. hysterophorus. The study found larger distributions and patch sizes in OLI than in SPOT 6 as a result of possible P. hysterophorus expansion due to temporal differences between images and coarser pixels were insufficient to delineate gaps inside larger patches. On the other hand, SPOT 6 showed better capabilities of delineating gaps and boundaries of patches, hence had better estimates of distribution and patch sizes. Overall, the study showed that OLI may be suitable for mapping well-established patches for the purpose of large scale monitoring, while SPOT 6 can be used for mapping small patches and prioritising them for eradication to prevent further spread at a landscape scale.

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Predicting Near-surface Winds with WindNinja for Wind Energy Applications

NASA Astrophysics Data System (ADS)

Wagenbrenner, N. S.; Forthofer, J.; Shannon, K.; Butler, B.

2016-12-01

WindNinja is a high-resolution diagnostic wind model widely used by operational wildland fire managers to predict how near-surface winds may influence fire behavior. Many of the features which have made WindNinja successful for wildland fire are also important for wind energy applications. Some of these features include flexible runtime options which allow the user to initialize the model with coarser scale weather model forecasts, sparse weather station observations, or a simple domain-average wind for what-if scenarios; built-in data fetchers for required model inputs, including gridded terrain and vegetation data and operational weather model forecasts; relatively fast runtimes on simple hardware; an extremely user-friendly interface; and a number of output format options, including KMZ files for viewing in Google Earth and GeoPDFs which can be viewed in a GIS. The recent addition of a conservation of mass and momentum solver based on OpenFOAM libraries further increases the utility of WindNinja to modelers in the wind energy sector interested not just in mean wind predictions, but also in turbulence metrics. Here we provide an evaluation of WindNinja forecasts based on (1) operational weather model forecasts and (2) weather station observations provided by the MesoWest API. We also compare the high-resolution WindNinja forecasts to the coarser operational weather model forecasts. For this work we will use the High Resolution Rapid Refresh (HRRR) model and the North American Mesoscale (NAM) model. Forecasts will be evaluated with data collected in the Birch Creek valley of eastern Idaho, USA between June-October 2013. Near-surface wind, turbulence data, and vertical wind and temperature profiles were collected at very high spatial resolution during this field campaign specifically for use in evaluating high-resolution wind models like WindNinja. This work demonstrates the ability of WindNinja to generate very high-resolution wind forecasts for wind energy applications and evaluates the forecasts produced by two different initialization methods with data collected in a broad valley surrounded by complex terrain.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

NASA Astrophysics Data System (ADS)

Manson, F. J.; Loneragan, N. R.; Phinn, S. R.

2003-07-01

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.

Analysis of improved government geological map information for mineral exploration: Incorporating efficiency, productivity, effectiveness, and risk considerations

USGS Publications Warehouse

Bernknopf, R.L.; Wein, A.M.; St-Onge, M. R.; Lucas, S.B.

2007-01-01

This bulletin/professional paper focuses on the value of geoscientific information and knowledge, as provided in published government bedrock geological maps, to the mineral exploration sector. An economic model is developed that uses an attribute- ranking approach to convert geological maps into domains of mineral favourability. Information about known deposits in these (or analogous) favourability domains allow the calculation of exploration search statistics that provide input into measures of exploration efficiency, productivity, effectiveness, risk, and cost stemming from the use of the published geological maps. Two case studies, the Flin Flon Belt (Manitoba and Saskatchewan) and the south Baffin Island area (Nunavut), demonstrate that updated, finer resolution maps can be used to identify more exploration campaign options, and campaigns thats are more efficient, more effective, and less risky than old, coarser resolution maps when used as a guide for mineral exploration. The Flin Flon Belt study illustrates that an updated, coarser resolution bedrock map enables improved mineral exploration efficiency, productivity, and effectiveness by locating 60% more targets and supporting an exploration campaign that is 44% more efficient. Refining the map resolution provides an additional 17% reduction in search effort across all favourable domains and a 55% reduction in search effort in the most favourable domain. The south Baffin Island case study projects a 40% increase in expected targets and a 27% reduction in search effort when the updated, finer resolution map is used in lieu of the old, coarser resolution map. On southern Baffin Island, the economic value of the up dated map ranges from CAN$2.28 million to CAN$15.21 million, which can be compared to the CAN$1.86 million that it cost to produce the map (a multiplier effect of up to eight).

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

DOE PAGES

Campbell, Patrick; Zhang, Yang; Wang, Kai; ...

2017-09-08

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32°N and 42°N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. In conclusion, results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, Patrick; Zhang, Yang; Wang, Kai

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32N and 42N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. Results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, Patrick; Zhang, Yang; Wang, Kai

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32°N and 42°N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. In conclusion, results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Potential Long-Term Records of Surface Albedo at Fine Spatiotemporal Resolution from Landsat/Sentinle-2A Surface Reflectance and MODIS/VIIRS BRDF

NASA Astrophysics Data System (ADS)

Li, Z.; Schaaf, C.; Shuai, Y.; Liu, Y.; Sun, Q.; Erb, A.; Wang, Z.

2016-12-01

The land surface albedo products at fine spatial resolutions are generated by coupling surface reflectance (SR) from Landsat (30 m) or Sentinel-2A (20 m) with concurrent surface anisotropy information (the Bidirectional Reflectance Distribution Function - BRDF) at coarser spatial resolutions from sequential multi-angular observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) or its successor, the Visible Infrared Imaging Radiometer Suite (VIIRS). We assess the comparability of four types of fine-resolution albedo products (black-sky and white-sky albedos over the shortwave broad band) generated by coupling, (1) Landsat-8 Optical Land Imager (OLI) SR with MODIS BRDF; (2) OLI SR with VIIRS BRDF; (3) Sentinel-2A MultiSpectral Instrument (MSI) SR with MODIS BRDF; and (4) MSI SR with VIIRS BRDF. We evaluate the accuracy of these four types of fine-resolution albedo products using ground tower measurements of surface albedo over six SURFace RADiation Network (SURFRAD) sites in the United States. For comparison with the ground measurements, we estimate the actual (blue-sky) albedo values at the six sites by using the satellite-based retrievals of black-sky and white-sky albedos and taking into account the proportion of direct and diffuse solar radiation from the ground measurements at the sites. The coupling of the OLI and MSI SR with MODIS BRDF has already been shown to provide accurate fine-resolution albedo values. With demonstration of a high agreement in BRDF products from MODIS and VIIRS, we expect to see consistency between all four types of fine-resolution albedo products. This assurance of consistency between the couplings of both OLI and MSI with both MODIS and VIIRS guarantees the production of long-term records of surface albedo at fine spatial resolutions and an increased temporal resolution. Such products will be critical in studying land surface changes and associated surface energy balance over the dynamic and heterogeneous landscapes most susceptible to climate change (such as arctic, coastal, and high-elevation zones).

Reconstruction of a Three Hourly 1-km Land Surface Air Temperature Dataset in the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Zhou, J.; Ding, L.

2017-12-01

Land surface air temperature (SAT) is an important parameter in the modeling of radiation balance and energy budget of the earth surface. Generally, SAT is measured at ground meteorological stations; then SAT mapping is possible though a spatial interpolation process. The interpolated SAT map relies on the spatial distribution of ground stations, the terrain, and many other factors; thus, it has great uncertainties in regions with complicated terrain. Instead, SAT map can also be obtained through physical modeling of interactions between the land surface and the atmosphere. Such dataset generally has coarse spatial resolution (e.g. coarser than 0.1°) and cannot satisfy the applications at fine scales, e.g. 1 km. This presentation reports the reconstruction of a three hourly 1-km SAT dataset from 2001 to 2015 over the Qinghai-Tibet Plateau. The terrain in the Qinghai-Tibet Plateau, especially in the eastern part, is extremely complicated. Two SAT datasets with good qualities are used in this study. The first one is from the 3h China Meteorological Forcing Dataset with a 0.1° resolution released by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (Yang et al., 2010); the second one is from the ERA-Interim product with the same temporal resolution and a 0.125° resolution. A statistical approach is developed to downscale the spatial resolution of the derived SAT to 1-km. The elevation and the normalized difference vegetation index (NDVI) are selected as two scaling factors in the downscaling approach. Results demonstrate there is significantly negative correlation between the SAT and elevation in all seasons; there is also significantly negative correlation between the SAT and NDVI in the vegetation growth seasons, while the correlation decreases in the other seasons. Therefore, a temporally dynamic downscaling approach is feasible to enhance the spatial resolution of the SAT. Compared with the SAT at the 0.1° or 0.125°, the reconstructed 1-km SAT can provide much more spatial details in areas with complicated terrain. Additionally, the 1-km SAT agrees well with the ground measured air temperatures as well as the SAT before downscaling. The reconstructed SAT will be beneficial for the modeling of surface radiation balance and energy budget over the Qinghai-Tibet Plateau.

Exploring the Usefulness of MISR-HR Products to Estimate Maize Crop Extent and Using Field Evidence to Evaluate the Results in South Africa's Free State Province

NASA Astrophysics Data System (ADS)

Verstraete, M. M.; Knox, N. M.; Hunt, L. A.; Kleyn, L.

2014-12-01

The MISR instrument on NASA's Terra platform has been operating for almost 15 years. Standard products are generated at a spatial resolution of 1.1 km or coarser, but a recently developed method to re-analyze the Level-1B2 data allows the retrieval of biogeophysical products at the native spatial resolution of the instrument (275 m). This development opens new opportunities to better address issues such as the management of agricultural production and food security. South African maize production is of great economic and social importance, not only nationally, but on the global market too, being one of the top ten maize producing countries. Seasonal maize production statistics are currently based on a combination of field measurements and estimates derived from manually digitizing high resolution imagery from the SPOT satellite. The field measurements are collected using the Producer Independent Crop Estimate System (PICES) developed by Crop Estimates Committee of the Department of Agriculture, Forestry and Fisheries. There is a strong desire to improve the quality of these statistics, to generate those earlier, and to automate the process to encompass larger areas. This paper will explore the feasibility of using the MISR-HR spectral and directional products, combined with the finer spatial resolution and the relatively frequent coverage afforded by that instrument, to address these needs. The study area is based in the Free State, South Africa, one of the primary maize growing areas in the country, and took place during the 2012-2013 summer growing season. The significance of the outcomes will be evaluated in the context of the 14+ years of available MISR data.

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

Drone based estimation of actual evapotranspiration over different forest types

NASA Astrophysics Data System (ADS)

Marzahn, Philip; Gampe, David; Castro, Saulo; Vega-Araya, Mauricio; Sanchez-Azofeifa, Arturo; Ludwig, Ralf

2017-04-01

Actual evapotranspiration (Eta) plays an important role in surface-atmosphere interactions. Traditionally, Eta is measured by means of lysimeters, eddy-covariance systems or fiber optics, providing estimates which are spatially restricted to a footprint from a few square meters up to several hectares . In the past, several methods have been developed to derive Eta by means of multi-spectral remote sensing data using thermal and VIS/NIR satellite imagery of the land surface. As such approaches do have their justification on coarser scales, they do not provide Eta information on the fine resolution plant level over large areas which is mandatory for the detection of water stress or tree mortality. In this study, we present a comparison of a drone based assessment of Eta with eddy-covariance measurements over two different forest types - a deciduous forest in Alberta, Canada and a tropical dry forest in Costa Rica. Drone based estimates of Eta were calculated applying the Triangle-Method proposed by Jiang and Islam (1999). The Triangle-Method estimates actual evapotranspiration (Eta) by means of the Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) provided by two camera systems (MicaSense RedEdge, FLIR TAU2 640) flown simultaneously on an octocopter. . Results indicate a high transferability of the original approach from Jiang and Islam (1999) developed for coarse to medium resolution satellite imagery tothe high resolution drone data, leading to a deviation in Eta estimates of 10% compared to the eddy-covariance measurements. In addition, the spatial footprint of the eddy-covariance measurement can be detected with this approach, by showing the spatial heterogeneities of Eta due to the spatial distribution of different trees and understory vegetation.

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

CROSS-SCALE CORRELATIONS AND THE DESIGN AND ANALYSIS OF AVIAN HABITAT SELECTION STUDIES

EPA Science Inventory

It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large ...

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

A data mining approach for sharpening satellite thermal imagery over land

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

NASA Astrophysics Data System (ADS)

Tullos, D. D.; Walter, C.; Dunham, J.

2016-12-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: 1) the velocities considered to be representative of habitat units; 2) patterns of use of the hydraulic environment by fish; and 3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution, reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, Sajeev; Martin, Randall V.; Keller, Christoph A.

2016-05-01

Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typically used by global chemistry-transport models, and identify the operator durations that optimize both computational expense and simulation accuracy. We find that longer continuous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but increases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, secondary inorganic aerosols, ozone and carbon monoxide with a finer temporal or spatial resolution taken as "truth". Relative simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) operator duration. Chemical operator duration twice that of the transport operator duration offers more simulation accuracy per unit computation. However, the relative simulation error from coarser spatial resolution generally exceeds that from longer operator duration; e.g., degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different operator durations in offline chemistry-transport models. We encourage chemistry-transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Comparisons of Anvil Cirrus Spatial Characteristics between Airborne Observations in DC3 Campaign and WRF Simulations

NASA Astrophysics Data System (ADS)

D'Alessandro, J.; Diao, M.; Chen, M.

2015-12-01

John D'Alessandro1, Minghui Diao1, Ming Chen2, George Bryan2, Hugh Morrison21. Department of Meteorology and Climate Science, San Jose State University2. Mesoscale & Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, CO, 80301 Ice crystal formation requires the prerequisite condition of ice supersaturation, i.e., relative humidity with respect to ice (RHi) greater than 100%. The formation and evolution of ice supersaturated regions (ISSRs) has large impact on the subsequent formation of ice clouds. To examine the characteristics of simulated ice supersaturated regions at various model spatial resolutions, case studies between airborne in-situ measurements in the NSF Deep Convective, Clouds and Chemistry (DC3) campaign (May - June 2012) and WRF simulations are conducted in this work. Recent studies using ~200 m in-situ observations showed that ice supersaturated regions are mostly around 1 km in horizontal scale (Diao et al. 2014). Yet it is still unclear if such observed characteristics can be represented by WRF simulations at various spatial resolutions. In this work, we compare the WRF simulated anvil cirrus spatial characteristics with those observed in the DC3 campaign over the southern great plains in US. The WRF model is run at 1 km and 3 km horizontal grid spacing with a recent update of Thompson microphysics scheme. Our comparisons focus on the spatial characteristics of ISSRs and cirrus clouds, including the distributions of their horizontal scales, the maximum relative humidity with respect to ice (RHi) and the relationship between RHi and temperature. Our previous work on the NCAR CM1 cloud-resolving model shows that the higher resolution runs (i.e., 250m and 1km) generally have better agreement with observations than the coarser resolution (4km) runs. We will examine if similar trend exists for WRF simulations in deep convection cases. In addition, we will compare the simulation results between WRF and CM1, particularly for spatial correlations between ISSRs and cirrus and their evolution (based on the method of Diao et al. 2013). Overall, our work will help to assess the representation of ISSRs and cirrus in WRF simulation based on comparisons with in-situ observations.

Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Bing

Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-09-01

Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecasting) coupled atmosphere-fire model is used to examine the sensitivity of resolving VLS to both the horizontal and vertical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the dominant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to model VLS with WRF-Fire.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Potential for Small Unmanned Aircraft Systems applications for identifying groundwater-surface water exchange in a meandering river reach

USGS Publications Warehouse

Pai, H.; Malenda, H.; Briggs, Martin A.; Singha, K.; González-Pinzón, R.; Gooseff, M.; Tyler, S.W.; ,

2017-01-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here, we describe the use of a suite of high spatial-resolution remote-sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index (NDVI) mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW “shortcutting” through meander necks, which was corroborated by temperature data at the riverbed interface.

Potential for Small Unmanned Aircraft Systems Applications for Identifying Groundwater-Surface Water Exchange in a Meandering River Reach

NASA Astrophysics Data System (ADS)

Pai, H.; Malenda, H. F.; Briggs, M. A.; Singha, K.; González-Pinzón, R.; Gooseff, M. N.; Tyler, S. W.

2017-12-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here we describe the use of a suite of high spatial resolution remote sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW "shortcutting" through meander necks, which was corroborated by temperature data at the riverbed interface.

Multi-scale coupled modelling of waves and currents on the Catalan shelf.

NASA Astrophysics Data System (ADS)

Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

2012-04-01

Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

Integrating biodiversity distribution knowledge: toward a global map of life.

PubMed

Jetz, Walter; McPherson, Jana M; Guralnick, Robert P

2012-03-01

Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses. The ultimate aim is a public, online, quality-vetted 'Map of Life' that for every species integrates and visualizes available distributional knowledge, while also facilitating user feedback and dynamic biodiversity analyses. First milestones toward such an infrastructure have now been implemented. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Effects of Fine-Scale Landscape Variability on Satellite-Derived Land Surface Temperature Products Over Sparse Vegetation Canopies

NASA Astrophysics Data System (ADS)

Powell, R. L.; Goulden, M.; Peterson, S.; Roberts, D. A.; Still, C. J.

2015-12-01

Temperature is a primary environmental control on biological systems and processes at a range of spatial and temporal scales, from controlling biochemical processes such as photosynthesis to influencing continental-scale species distribution. The Landsat satellite series provides a long record (since the mid-1980s) of relatively high spatial resolution thermal infrared (TIR) imagery, from which we derive land surface temperature (LST) grids. Here, we investigate fine spatial resolution factors that influence Landsat-derived LST over a spectrally and spatially heterogeneous landscape. We focus on paired sites (inside/outside a 1994 fire scar) within a pinyon-juniper scrubland in Southern California. The sites have nearly identical micro-meteorology and vegetation species composition, but distinctly different vegetation abundance and structure. The tower at the unburned site includes a number of in-situ imaging tools to quantify vegetation properties, including a thermal camera on a pan-tilt mount, allowing hourly characterization of landscape component temperatures (e.g., sunlit canopy, bare soil, leaf litter). We use these in-situ measurements to assess the impact of fine-scale landscape heterogeneity on estimates of LST, including sensitivity to (i) the relative abundance of component materials, (ii) directional effects due to solar and viewing geometry, (iii) duration of sunlit exposure for each compositional type, and (iv) air temperature. To scale these properties to Landsat spatial resolution (~100-m), we characterize the sub-pixel composition of landscape components (in addition to shade) by applying spectral mixture analysis (SMA) to the Landsat Operational Land Imager (OLI) spectral bands and test the sensitivity of the relationships established with the in-situ data at this coarser scale. The effects of vegetation abundance and cover height versus other controls on satellite-derived estimates of LST will be assessed by comparing estimates at the burned vs. unburned sites across multiple seasons (~30 dates).

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

PubMed

Beeson, Peter C; Sadeghi, Ali M; Lang, Megan W; Tomer, Mark D; Daughtry, Craig S T

2014-01-01

Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Evaluation of lidar-derived DEMs through terrain analysis and field comparison

Treesearch

Cody P. Gillin; Scott W. Bailey; Kevin J. McGuire; Stephen P. Prisley

2015-01-01

Topographic analysis of watershed-scale soil and hydrological processes using digital elevation models (DEMs) is commonplace, but most studies have used DEMs of 10 m resolution or coarser. Availability of higher-resolution DEMs created from light detection and ranging (lidar) data is increasing but their suitability for such applications has received little critical...

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

USGS Publications Warehouse

Tullos, Desiree D.; Walter, Cara; Dunham, Jason B.

2016-01-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: (1) the velocities considered to be representative of habitat units; (2) patterns of use of the hydraulic environment by fish; and (3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution (grid spacing from 10 to 100 cm), reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Evaluation of the Actuator Line Model with coarse resolutions

NASA Astrophysics Data System (ADS)

Draper, M.; Usera, G.

2015-06-01

The aim of the present paper is to evaluate the Actuator Line Model (ALM) in spatial resolutions coarser than what is generally recommended, also using larger time steps. To accomplish this, the ALM has been implemented in the open source code caffa3d.MBRi and validated against experimental measurements of two wind tunnel campaigns (stand alone wind turbine and two wind turbines in line, case A and B respectively), taking into account two spatial resolutions: R/8 and R/15 (R is the rotor radius). A sensitivity analysis in case A was performed in order to get some insight into the influence of the smearing factor (3D Gaussian distribution) and time step size in power and thrust, as well as in the wake, without applying a tip loss correction factor (TLCF), for one tip speed ratio (TSR). It is concluded that as the smearing factor is larger or time step size is smaller the power is increased, but the velocity deficit is not as much affected. From this analysis, a smearing factor was obtained in order to calculate precisely the power coefficient for that TSR without applying TLCF. Results with this approach were compared with another simulation choosing a larger smearing factor and applying Prandtl's TLCF, for three values of TSR. It is found that applying the TLCF improves the power estimation and weakens the influence of the smearing factor. Finally, these 2 alternatives were tested in case B, confirming that conclusion.

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Tracking stormwater discharge plumes and water quality of the Tijuana River with multispectral aerial imagery

NASA Astrophysics Data System (ADS)

Svejkovsky, Jan; Nezlin, Nikolay P.; Mustain, Neomi M.; Kum, Jamie B.

2010-04-01

Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline.

Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

PubMed

Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian

2017-11-15

Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

NASA Astrophysics Data System (ADS)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91. In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI.

Resolving Tropical Cyclone Intensity in Models

NASA Astrophysics Data System (ADS)

Davis, C. A.

2018-02-01

In recent years, global weather forecast models and global climate models have begun to depict intense tropical cyclones, even up to category 5 on the Saffir-Simpson scale. In light of the limitation of horizontal resolution in such models, the author performs calculations, using the extended Best Track data for Atlantic tropical cyclones, to estimate the ability of models with differing grid spacing to represent Atlantic tropical cyclone intensity statistically. Results indicate that, under optimistic assumptions, models with horizontal grid spacing of one fourth degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, the case of Irma (2017) is used to demonstrate the importance of a realistic depiction of angular momentum and to motivate the use of angular momentum in model evaluation.

A new, multi-resolution bedrock elevation map of the Greenland ice sheet

NASA Astrophysics Data System (ADS)

Griggs, J. A.; Bamber, J. L.; Grisbed Consortium

2010-12-01

Gridded bedrock elevation for the Greenland ice sheet has previously been constructed with a 5 km posting. The true resolution of the data set was, in places, however, considerably coarser than this due to the across-track spacing of ice-penetrating radar transects. Errors were estimated to be on the order of a few percent in the centre of the ice sheet, increasing markedly in relative magnitude near the margins, where accurate thickness is particularly critical for numerical modelling and other applications. We use new airborne and satellite estimates of ice thickness and surface elevation to determine the bed topography for the whole of Greenland. This is a dynamic product, which will be updated frequently as new data, such as that from NASA’s Operation Ice Bridge, becomes available. The University of Kansas has in recent years, flown an airborne ice-penetrating radar system with close flightline spacing over several key outlet glacier systems. This allows us to produce a multi-resolution bedrock elevation dataset with the high spatial resolution needed for ice dynamic modelling over these key outlet glaciers and coarser resolution over the more sparsely sampled interior. Airborne ice thickness and elevation from CReSIS obtained between 1993 and 2009 are combined with JPL/UCI/Iowa data collected by the WISE (Warm Ice Sounding Experiment) covering the marginal areas along the south west coast from 2009. Data collected in the 1970’s by the Technical University of Denmark were also used in interior areas with sparse coverage from other sources. Marginal elevation data from the ICESat laser altimeter and the Greenland Ice Mapping Program were used to help constrain the ice thickness and bed topography close to the ice sheet margin where, typically, the terrestrial observations have poor sampling between flight tracks. The GRISBed consortium currently consists of: W. Blake, S. Gogineni, A. Hoch, C. M. Laird, C. Leuschen, J. Meisel, J. Paden, J. Plummer, F. Rodriguez-Morales and L. Smith, CReSIS, University of Kansas; E. Rignot, JPL and University of California, Irvine; Y. Gim, JPL; J. Mouginot, University of California, Irvine; D. Kirchner, University of Iowa; I. Howat, Byrd Polar Research Center, Ohio State University; I. Joughin and B. Smith, University of Washington; T. Scambos, NSIDC; S. Martin, University of Washington; T. Wagner, NASA.

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a single storm system. It is suggested that the next generation spaceborne radar have a minimum sensitivity of -5 dBZ and spatial resolution of at least 3 km at all frequencies to adequately sample liquid and ice phase precipitation processes globally.

Comparison of S-NPP VIIRS land surface temperature with SEVIRI

NASA Astrophysics Data System (ADS)

Ermida, Sofia L.; Trigo, Isabel F.; Liu, Yuling; Yu, Yunyue

2017-04-01

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes. LST can be globally measured from space by infrared radiometers, with a wide range of spatial and temporal resolutions depending on the sensor design and orbit. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is the primary sensor onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite, which was launched in recent years. VIIRS was designed to improve upon the capabilities of the operational AVHRR and provide observation continuity with MODIS. A Split Window approach has been applied to the VIIRS moderate resolution channels M15 and M16 centered at 10.76 µm and 12.01 µm, respectively. VIIRS has a swath of 3000 km and a spatial resolution of 745m (nadir) up to about 1600 m (limb view), leading to relatively high re-visiting frequency. LST is retrieved for a wide range of viewing angles along the VIIRS path, allowing the study of the variability of LST with viewing geometry for various land cover types. Here we present a comparison of VIRS LST data with data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG). SEVIRI-based LST is available every 15-minute, but at coarser spatial resolution (3-km at nadir) when compared to VIIRS LST. The analysis is performed over 6 areas over the SEVIRI disk characterized by different surface conditions. VIIRS has generally slightly warmer night-time LST compared with SEVIRI, with differences smaller than 2K. Larger differences are found during daytime, with VIIRS presenting overall lower LST values up to 5K. These differences are also analysed taking into account the surface type, view zenith angle (VZA) and topography. As seen in previous comparison studies, high VZA and elevation values are associated to higher discrepancies of the LST products.

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

The Effects of Dissipation and Coarse Grid Resolution for Multigrid in Flow Problems

NASA Technical Reports Server (NTRS)

Eliasson, Peter; Engquist, Bjoern

1996-01-01

The objective of this paper is to investigate the effects of the numerical dissipation and the resolution of the solution on coarser grids for multigrid with the Euler equation approximations. The convergence is accomplished by multi-stage explicit time-stepping to steady state accelerated by FAS multigrid. A theoretical investigation is carried out for linear hyperbolic equations in one and two dimensions. The spectra reveals that for stability and hence robustness of spatial discretizations with a small amount of numerical dissipation the grid transfer operators have to be accurate enough and the smoother of low temporal accuracy. Numerical results give grid independent convergence in one dimension. For two-dimensional problems with a small amount of numerical dissipation, however, only a few grid levels contribute to an increased speed of convergence. This is explained by the small numerical dissipation leading to dispersion. Increasing the mesh density and hence making the problem over resolved increases the number of mesh levels contributing to an increased speed of convergence. If the steady state equations are elliptic, all grid levels contribute to the convergence regardless of the mesh density.

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

In Situ Validation of the Soil Moisture Active Passive (SMAP) Satellite Mission

NASA Technical Reports Server (NTRS)

Jackson, T.; Cosh, M.; Crow, W.; Colliander, A.; Walker, J.

2011-01-01

SMAP is a new NASA mission proposed for 2014 that would provide a number of soil moisture and freeze/thaw products. The soil moisture products span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data from the currently available set of soil moisture observing sites and networks need improvement if they are to be useful. Problems include a lack of standardization of instrumentation and installation and the disparity in spatial scale between the point-scale in situ data (a few centimeters) and the coarser satellite products. SMAP has initiated activities to resolve these issues for some of the existing resources. The other challenge to soil moisture validation is the need to expand the number of sites and their geographic distribution. SMAP is attempting to increase the number of sites and their value in validation through collaboration. The issues and solutions involving in situ validation being investigated will be described along with recent results from SMAP validation projects.

Lidar-based multinomial classification algorithms for tropical forest degradation status: Implications for biomass estimation

NASA Astrophysics Data System (ADS)

Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.

2017-12-01

There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.

Digital Mapping and Environmental Characterization of National Wild and Scenic River Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

McManamay, Ryan A; Bosnall, Peter; Hetrick, Shelaine L

2013-09-01

Spatially accurate geospatial information is required to support decision-making regarding sustainable future hydropower development. Under a memorandum of understanding among several federal agencies, a pilot study was conducted to map a subset of National Wild and Scenic Rivers (WSRs) at a higher resolution and provide a consistent methodology for mapping WSRs across the United States and across agency jurisdictions. A subset of rivers (segments falling under the jurisdiction of the National Park Service) were mapped at a high resolution using the National Hydrography Dataset (NHD). The spatial extent and representation of river segments mapped at NHD scale were compared withmore » the prevailing geospatial coverage mapped at a coarser scale. Accurately digitized river segments were linked to environmental attribution datasets housed within the Oak Ridge National Laboratory s National Hydropower Asset Assessment Program database to characterize the environmental context of WSR segments. The results suggest that both the spatial scale of hydrography datasets and the adherence to written policy descriptions are critical to accurately mapping WSRs. The environmental characterization provided information to deduce generalized trends in either the uniqueness or the commonness of environmental variables associated with WSRs. Although WSRs occur in a wide range of human-modified landscapes, environmental data layers suggest that they provide habitats important to terrestrial and aquatic organisms and recreation important to humans. Ultimately, the research findings herein suggest that there is a need for accurate, consistent, mapping of the National WSRs across the agencies responsible for administering each river. Geospatial applications examining potential landscape and energy development require accurate sources of information, such as data layers that portray realistic spatial representations.« less

Synthetic aperture radar images with composite azimuth resolution

DOEpatents

Bielek, Timothy P; Bickel, Douglas L

2015-03-31

A synthetic aperture radar (SAR) image is produced by using all phase histories of a set of phase histories to produce a first pixel array having a first azimuth resolution, and using less than all phase histories of the set to produce a second pixel array having a second azimuth resolution that is coarser than the first azimuth resolution. The first and second pixel arrays are combined to produce a third pixel array defining a desired SAR image that shows distinct shadows of moving objects while preserving detail in stationary background clutter.

Landslide model performance in a high resolution small-scale landscape

NASA Astrophysics Data System (ADS)

De Sy, V.; Schoorl, J. M.; Keesstra, S. D.; Jones, K. E.; Claessens, L.

2013-05-01

The frequency and severity of shallow landslides in New Zealand threatens life and property, both on- and off-site. The physically-based shallow landslide model LAPSUS-LS is tested for its performance in simulating shallow landslide locations induced by a high intensity rain event in a small-scale landscape. Furthermore, the effect of high resolution digital elevation models on the performance was tested. The performance of the model was optimised by calibrating different parameter values. A satisfactory result was achieved with a high resolution (1 m) DEM. Landslides, however, were generally predicted lower on the slope than mapped erosion scars. This discrepancy could be due to i) inaccuracies in the DEM or in other model input data such as soil strength properties; ii) relevant processes for this environmental context that are not included in the model; or iii) the limited validity of the infinite length assumption in the infinite slope stability model embedded in the LAPSUS-LS. The trade-off between a correct prediction of landslides versus stable cells becomes increasingly worse with coarser resolutions; and model performance decreases mainly due to altering slope characteristics. The optimal parameter combinations differ per resolution. In this environmental context the 1 m resolution topography resembles actual topography most closely and landslide locations are better distinguished from stable areas than for coarser resolutions. More gain in model performance could be achieved by adding landslide process complexities and parameter heterogeneity of the catchment.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

Representativeness of regional and global mass-balance measurement networks (Invited)

NASA Astrophysics Data System (ADS)

Cogley, J. G.; Moholdt, G.; Gardner, A. S.

2013-12-01

We showed in a recent publication that regional estimates of glacier mass budgets, obtained by interpolation from in-situ measurements, were markedly more negative than corresponding estimates by satellite gravimetry (GRACE) and satellite altimetry (ICESat) during 2003-2009. Examining the ICESat data in more detail, we found that in-situ records tend to be located in areas where glaciers are thinning more rapidly than as observed in their regional surroundings. Because neither GRACE nor ICESat can provide information for times before 2002-2003, and may not operate without interruption in the future, we explore possible explanations of and remedies for the identified bias in the in-situ network. Sparse spatial sampling, coupled with previously undetected spatial variability of mass balance at scales between the 10-km in-situ scale and the 350-km gravimetric scale, appears to be the leading explanation. Satisfactory remedies are not obvious. Selecting glaciers for in-situ measurement that are more representative will yield only incremental improvements. There appears to be no alternative to mass-balance modelling as a versatile tool for estimation of regional mass balance. However the meteorological data for forcing the surface components of glacier models have coarser resolution than is desirable and are themselves uncertain, especially in the remote regions where much of the glacier ice is found. Measurements of frontal (dynamic) mass changes are still difficult, and modelling of these changes remains underdeveloped in spite of recent advances. Thus research on a broad scale is called for in order to meet the challenge of producing more accurate hindcasts and projections of glacier mass budgets with fine spatial and temporal resolution.

Potential for using regional and global datasets for national scale ecosystem service modelling

NASA Astrophysics Data System (ADS)

Maxwell, Deborah; Jackson, Bethanna

2016-04-01

Ecosystem service models are increasingly being used by planners and policy makers to inform policy development and decisions about national-level resource management. Such models allow ecosystem services to be mapped and quantified, and subsequent changes to these services to be identified and monitored. In some cases, the impact of small scale changes can be modelled at a national scale, providing more detailed information to decision makers about where to best focus investment and management interventions that could address these issues, while moving toward national goals and/or targets. National scale modelling often uses national (or local) data (for example, soils, landcover and topographical information) as input. However, there are some places where fine resolution and/or high quality national datasets cannot be easily obtained, or do not even exist. In the absence of such detailed information, regional or global datasets could be used as input to such models. There are questions, however, about the usefulness of these coarser resolution datasets and the extent to which inaccuracies in this data may degrade predictions of existing and potential ecosystem service provision and subsequent decision making. Using LUCI (the Land Utilisation and Capability Indicator) as an example predictive model, we examine how the reliability of predictions change when national datasets of soil, landcover and topography are substituted with coarser scale regional and global datasets. We specifically look at how LUCI's predictions of where water services, such as flood risk, flood mitigation, erosion and water quality, change when national data inputs are replaced by regional and global datasets. Using the Conwy catchment, Wales, as a case study, the land cover products compared are the UK's Land Cover Map (2007), the European CORINE land cover map and the ESA global land cover map. Soils products include the National Soil Map of England and Wales (NatMap) and the European Soils Database. NEXTmap elevation data, which covers the UK and parts of continental Europe, are compared to global AsterDEM and SRTM30 topographical products. While the regional and global datasets can be used to fill gaps in data requirements, the coarser resolution of these datasets means that there is greater aggregation of information over larger areas. This loss of detail impacts on the reliability of model output, particularly where significant discrepancies between datasets exist. The implications of this loss of detail in terms of spatial planning and decision making is discussed. Finally, in the context of broader development the need for better nationally and globally available data to allow LUCI and other ecosystem models to become more globally applicable is highlighted.

Water level observations from Unmanned Aerial Vehicles (UAVs) for improving probabilistic estimations of interaction between rivers and groundwater

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Butts, Michael; Vammen Jacobsen, Torsten; Bauer-Gottwein, Peter

2016-04-01

Integrated hydrological models are generally calibrated against observations of river discharge and piezometric head in groundwater aquifers. Integrated hydrological models are rarely calibrated against spatially distributed water level observations measured by either in-situ stations or spaceborne platforms. Indeed in-situ observations derived from ground-based stations are generally spaced too far apart to capture spatial patterns in the water surface. On the other hand spaceborne observations have limited spatial resolution. Additionally satellite observations have a temporal resolution which is not ideal for observing the temporal patterns of the hydrological variables during extreme events. UAVs (Unmanned Aerial Vehicles) offer several advantages: i) high spatial resolution; ii) tracking of the water body better than any satellite technology; iii) timing of the sampling merely depending on the operators. In this case study the Mølleåen river (Denmark) and its catchment have been simulated through an integrated hydrological model (MIKE 11-MIKE SHE). This model was initially calibrated against observations of river discharge retrieved by in-situ stations and against piezometric head of the aquifers. Subsequently the hydrological model has been calibrated against dense spatially distributed water level observations, which could potentially be retrieved by UAVs. Error characteristics of synthetic UAV water level observations were taken from a recent proof-of-concept study. Since the technology for ranging water level is under development, UAV synthetic water level observations were extracted from another model of the river with higher spatial resolution (cross sections located every 10 m). This model with high resolution is assumed to be absolute truth for the purpose of this work. The river model with the coarser resolution has been calibrated against the synthetic water level observations through Differential Evolution Adaptive Metropolis (DREAM) algorithm, an efficient global Markov Chain Monte Carlo (MCMC) in high-dimensional spaces. Calibration against water level has demonstrated a significant improvement of the estimation of the exchange flow between groundwater and river branch. Groundwater flux and direction are now better simulated. Reliability and sharpness of the probabilistic forecasts are assessed with the sharpness, the interval skill score (ISS) of the 95{%} confidence interval, and with the root mean square error (RMSE) of the maximum a posteriori probability (MAP). The binary outcome (either gaining or loosing stream) of the flow direction is assessed with Brier score (BS). After water level calibration the sharpness of the estimations is approximately doubled with respect to the model calibrated only against discharge, ISS has improved from 2.4-7to 7.8-8 m^3/s\\cdot m, RMSE from 9.2-8 to 2.4-8 m^3/s\\cdot m^and BS is halved from 0.58 to 0.25.

Observation-Corrected Precipitation Estimates in GEOS-5

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing

2014-01-01

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Is there potential added value in COSMO-CLM forced by ERA reanalysis data?

NASA Astrophysics Data System (ADS)

Lenz, Claus-Jürgen; Früh, Barbara; Adalatpanah, Fatemeh Davary

2017-12-01

An application of the potential added value (PAV) concept suggested by Di Luca et al. (Clim Dyn 40:443-464, 2013a) is applied to ERA Interim driven runs of the regional climate model COSMO-CLM. They are performed for the time period 1979-2013 for the EURO-CORDEX domain at horizontal grid resolutions 0.11°, 0.22°, and 0.44° such that the higher resolved model grid fits into the next coarser grid. The concept of the potential added value is applied to annual, seasonal, and monthly means of the 2 m air temperature. Results show the highest potential added value at the run with the finest grid and generally increasing PAV with increasing resolution. The potential added value strongly depends on the season as well as the region of consideration. The gain of PAV is higher enhancing the resolution from 0.44° to 0.22° than from 0.22° to 0.11°. At grid aggregations to 0.88° and 1.76° the differences in PAV between the COSMO-CLM runs on the mentioned grid resolutions are maximal. They nearly vanish at aggregations to even coarser grids. In all cases the PAV is dominated by at least 80% by its stationary part.

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

NASA Technical Reports Server (NTRS)

Holdaway, Daniel; Yang, Yuekui

2016-01-01

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

Leveraging North Carolina's QL2 Lidar to Quantify Sensitivity of National Water Model Derived Flood Inundation Extent to DEM Resolution

NASA Astrophysics Data System (ADS)

Lovette, J. P.; Lenhardt, W. C.; Blanton, B.; Duncan, J. M.; Stillwell, L.

2017-12-01

The National Water Model (NWM) has provided a novel framework for near real time flood inundation mapping across CONUS at a 10m resolution. In many regions, this spatial scale is quickly being surpassed through the collection of high resolution lidar (1 - 3m). As one of the leading states in data collection for flood inundation mapping, North Carolina is currently improving their previously available 20 ft statewide elevation product to a Quality Level 2 (QL2) product with a nominal point spacing of 0.7 meters. This QL2 elevation product increases the ground points by roughly ten times over the previous statewide lidar product, and by over 250 times when compared to the 10m NED elevation grid. When combining these new lidar data with the discharge estimates from the NWM, we can further improve statewide flood inundation maps and predictions of at-risk areas. In the context of flood risk management, these improved predictions with higher resolution elevation models consistently represent an improvement on coarser products. Additionally, the QL2 lidar also includes coarse land cover classification data for each point return, opening the possibility for expanding analysis beyond the use of only digital elevation models (e.g. improving estimates of surface roughness, identifying anthropogenic features in floodplains, characterizing riparian zones, etc.). Using the NWM Height Above Nearest Drainage approach, we compare flood inundation extents derived from multiple lidar-derived grid resolutions to assess the tradeoff between precision and computational load in North Carolina's coastal river basins. The elevation data distributed through the state's new lidar collection program provide spatial resolutions ranging from 5-50 feet, with most inland areas also including a 3 ft product. Data storage increases by almost two orders of magnitude across this range, as does processing load. In order to further assess the validity of the higher resolution elevation products on flood inundation, we examine the NWM outputs from Hurricane Matthew, which devastated southeastern North Carolina in October 2016. When compared with numerous surveyed high water marks across the coastal plain, this assessment provides insight on the impacts of grid resolution on flood inundation extent.

Studies of Inviscid Flux Schemes for Acoustics and Turbulence Problems

NASA Technical Reports Server (NTRS)

Morris, Chris

2013-01-01

Five different central difference schemes, based on a conservative differencing form of the Kennedy and Gruber skew-symmetric scheme, were compared with six different upwind schemes based on primitive variable reconstruction and the Roe flux. These eleven schemes were tested on a one-dimensional acoustic standing wave problem, the Taylor-Green vortex problem and a turbulent channel flow problem. The central schemes were generally very accurate and stable, provided the grid stretching rate was kept below 10%. As near-DNS grid resolutions, the results were comparable to reference DNS calculations. At coarser grid resolutions, the need for an LES SGS model became apparent. There was a noticeable improvement moving from CD-2 to CD-4, and higher-order schemes appear to yield clear benefits on coarser grids. The UB-7 and CU-5 upwind schemes also performed very well at near-DNS grid resolutions. The UB-5 upwind scheme does not do as well, but does appear to be suitable for well-resolved DNS. The UF-2 and UB-3 upwind schemes, which have significant dissipation over a wide spectral range, appear to be poorly suited for DNS or LES.

A New High-Resolution N2O Emission Inventory for China in 2008

NASA Astrophysics Data System (ADS)

Shang, Z.; Zhou, F.; Ciais, P.; Tao, S.; Piao, S.; Raymond, P. A.; He, C.; Li, B.; Wang, R.; Wang, X.; Peng, S.; Zeng, Z.; Chen, H.; Ying, N.; Hou, X.; Xu, P.

2014-12-01

The amount and geographic distribution of N2O emissions over China remain largely uncertain. Most of existing emission inventories use uniform emission factors (EFs) and the associated parameters and apply spatial proxies to downscale national or provincial data, resulting in the introduction of spatial bias. In this study, county-level and 0.1° × 0.1° gridded anthropogenic N2O emission inventories for China (PKU-N2O) in 2008 are developed based on high-resolution activity data and regional EFs and parameters. These new estimates are compared with estimates from EDGAR v4.2, GAINS-China, National Development and Reform Commission of China (NDRC), and with two sensitivity tests: one that uses high-resolution activity data but the default IPCC methodology (S1) and the other that uses regional EFs and parameters but starts from coarser-resolution activity data. The total N2O emissions are 2150 GgN2O/yr (interquartile range from 1174 to 2787 GgN2O/yr). Agriculture contributes 64% of the total, followed by energy (17%), indirect emissions (12%), wastes (5%), industry (2.8%), and wildfires (0.2%). Our national emission total is 17% greater than that of the EDGAR v4.2 global product sampled over China and is also greater than the GAINS-China, NDRC, and S1 estimates by 10%, 50%, and 17%, respectively. We also found that using uniform EFs and parameters or starting from national/provincial data causes systematic spatial biases compared to PKU-N2O. In addition, the considerable differences between the relative contributions of the six sectors across the six Agro-Climate Zones primarily reflect the different distributions of industrial activities and land use. Eastern China (8.7% area of China) is the largest contributor of N2O emissions and accounts for nearly 25% of the total. Spatial analysis also shows nonlinear relationships between N2O emission intensities and urbanization. Per-capita and per-GDP N2O emissions increase gradually with an increase in the urban population fraction from 0.3 to 0.9 among 2884 counties, and N2O emission density increases with urban expansion. Moreover, additional experiments and the use of a reliable data-driven approach or process-based models can improve the spatial resolution and reduce the uncertainties in PKU-N2O, especially from agricultural soils and manure management.

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drover, Damion, Ryan

2011-12-01

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would thereforemore » be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.« less

Marine Stratocumulus Cloud Fields off the Coast of Southern California Observed Using LANDSAT Imagery. Part II: Textural Analysis.

NASA Astrophysics Data System (ADS)

Welch, R. M.; Sengupta, S. K.; Kuo, K. S.

1988-04-01

Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.

The Modularized Software Package ASKI - Full Waveform Inversion Based on Waveform Sensitivity Kernels Utilizing External Seismic Wave Propagation Codes

NASA Astrophysics Data System (ADS)

Schumacher, F.; Friederich, W.

2015-12-01

We present the modularized software package ASKI which is a flexible and extendable toolbox for seismic full waveform inversion (FWI) as well as sensitivity or resolution analysis operating on the sensitivity matrix. It utilizes established wave propagation codes for solving the forward problem and offers an alternative to the monolithic, unflexible and hard-to-modify codes that have typically been written for solving inverse problems. It is available under the GPL at www.rub.de/aski. The Gauss-Newton FWI method for 3D-heterogeneous elastic earth models is based on waveform sensitivity kernels and can be applied to inverse problems at various spatial scales in both Cartesian and spherical geometries. The kernels are derived in the frequency domain from Born scattering theory as the Fréchet derivatives of linearized full waveform data functionals, quantifying the influence of elastic earth model parameters on the particular waveform data values. As an important innovation, we keep two independent spatial descriptions of the earth model - one for solving the forward problem and one representing the inverted model updates. Thereby we account for the independent needs of spatial model resolution of forward and inverse problem, respectively. Due to pre-integration of the kernels over the (in general much coarser) inversion grid, storage requirements for the sensitivity kernels are dramatically reduced.ASKI can be flexibly extended to other forward codes by providing it with specific interface routines that contain knowledge about forward code-specific file formats and auxiliary information provided by the new forward code. In order to sustain flexibility, the ASKI tools must communicate via file output/input, thus large storage capacities need to be accessible in a convenient way. Storing the complete sensitivity matrix to file, however, permits the scientist full manual control over each step in a customized procedure of sensitivity/resolution analysis and full waveform inversion.

Image Simulation and Assessment of the Colour and Spatial Capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter

NASA Astrophysics Data System (ADS)

Tornabene, Livio L.; Seelos, Frank P.; Pommerol, Antoine; Thomas, Nicholas; Caudill, C. M.; Becerra, Patricio; Bridges, John C.; Byrne, Shane; Cardinale, Marco; Chojnacki, Matthew; Conway, Susan J.; Cremonese, Gabriele; Dundas, Colin M.; El-Maarry, M. R.; Fernando, Jennifer; Hansen, Candice J.; Hansen, Kayle; Harrison, Tanya N.; Henson, Rachel; Marinangeli, Lucia; McEwen, Alfred S.; Pajola, Maurizio; Sutton, Sarah S.; Wray, James J.

2018-02-01

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally ( i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ˜18-36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18-36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three "fully"-simulated image cubes of thirty unique locations on Mars ( i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (˜9.4 × 50 km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.

Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model

NASA Technical Reports Server (NTRS)

Cullather, Richard I.; Nowicki, Sophie M. J.; Zhao, Bin; Suarez, Max J.

2014-01-01

Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.

Lightning Forcing in Global Fire Models: The Importance of Temporal Resolution

NASA Astrophysics Data System (ADS)

Felsberg, A.; Kloster, S.; Wilkenskjeld, S.; Krause, A.; Lasslop, G.

2018-01-01

In global fire models, lightning is typically prescribed from observational data with monthly mean temporal resolution while meteorological forcings, such as precipitation or temperature, are prescribed in a daily resolution. In this study, we investigate the importance of the temporal resolution of the lightning forcing for the simulation of burned area by varying from daily to monthly and annual mean forcing. For this, we utilize the vegetation fire model JSBACH-SPITFIRE to simulate burned area, forced with meteorological and lightning data derived from the general circulation model ECHAM6. On a global scale, differences in burned area caused by lightning forcing applied in coarser temporal resolution stay below 0.55% compared to the use of daily mean forcing. Regionally, however, differences reach up to 100%, depending on the region and season. Monthly averaged lightning forcing as well as the monthly lightning climatology cause differences through an interaction between lightning ignitions and fire prone weather conditions, accounted for by the fire danger index. This interaction leads to decreased burned area in the boreal zone and increased burned area in the Tropics and Subtropics under the coarser temporal resolution. The exclusion of interannual variability, when forced with the lightning climatology, has only a minor impact on the simulated burned area. Annually averaged lightning forcing causes differences as a direct result of the eliminated seasonal characteristics of lightning. Burned area is decreased in summer and increased in winter where fuel is available. Regions with little seasonality, such as the Tropics and Subtropics, experience an increase in burned area.

Spatial assessment of intertidal seagrass meadows using optical imaging systems and a lightweight drone

NASA Astrophysics Data System (ADS)

Duffy, James P.; Pratt, Laura; Anderson, Karen; Land, Peter E.; Shutler, Jamie D.

2018-01-01

Seagrass ecosystems are highly sensitive to environmental change. They are also in global decline and under threat from a variety of anthropogenic factors. There is now an urgency to establish robust monitoring methodologies so that changes in seagrass abundance and distribution in these sensitive coastal environments can be understood. Typical monitoring approaches have included remote sensing from satellites and airborne platforms, ground based ecological surveys and snorkel/scuba surveys. These techniques can suffer from temporal and spatial inconsistency, or are very localised making it hard to assess seagrass meadows in a structured manner. Here we present a novel technique using a lightweight (sub 7 kg) drone and consumer grade cameras to produce very high spatial resolution (∼4 mm pixel-1) mosaics of two intertidal sites in Wales, UK. We present a full data collection methodology followed by a selection of classification techniques to produce coverage estimates at each site. We trialled three classification approaches of varying complexity to investigate and illustrate the differing performance and capabilities of each. Our results show that unsupervised classifications perform better than object-based methods in classifying seagrass cover. We also found that the more sparsely vegetated of the two meadows studied was more accurately classified - it had lower root mean squared deviation (RMSD) between observed and classified coverage (9-9.5%) compared to a more densely vegetated meadow (RMSD 16-22%). Furthermore, we examine the potential to detect other biotic features, finding that lugworm mounds can be detected visually at coarser resolutions such as 43 mm pixel-1, whereas smaller features such as cockle shells within seagrass require finer grained data (<17 mm pixel-1).

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Representing soil moisture - precipitation feedbacks in the Sahel: spatial scale and parameterisation

NASA Astrophysics Data System (ADS)

Taylor, C.; Birch, C.; Parker, D.; Guichard, F.; Nikulin, G.; Dixon, N.

2013-12-01

Land surface properties influence the life cycle of convective systems across West Africa via space-time variability in sensible and latent heat fluxes. Previous observational and modelling studies have shown that areas with strong mesoscale variability in vegetation cover or soil moisture induce coherent structures in the daytime planetary boundary layer. In particular, horizontal gradients in sensible heat flux can induce convergence zones which favour the initiation of deep convection. A recent study based on satellite data (Taylor et al. 2011), illustrated the climatological importance of soil moisture gradients in the initiation of long-lived Mesoscale Convective Systems (MCS) in the Sahel. Here we provide a unique assessment of how models of different spatial resolutions represent soil moisture - precipitation feedbacks in the region, and compare their behaviour to observations. Specifically we examine whether the inability of large-scale models to capture the observed preference for afternoon rain over drier soil in semi-arid regions [Taylor et al., 2012] is due to inadequate spatial resolution and/or systematic bias in convective parameterisations. Firstly, we use a convection-permitting simulation at 4km resolution to explore the underlying mechanisms responsible for soil moisture controls on daytime convective initiation in the Sahel. The model reproduces very similar spatial structure as the observations in terms of antecedent soil moisture in the vicinity of a large sample of convective initiations. We then examine how this same model, run at coarser resolution, simulates the feedback of soil moisture on daily rainfall. In particular we examine the impact of switching on the convective parameterisation on rainfall persistence, and compare the findings with 10 regional climate models (RCMs). Finally, we quantify the impact of the feedback on dry-spell return times using a simple statistical model. The results highlight important weaknesses in convective parameterisations which are likely to impact land surface sensitivity studies and hydroclimatic variability on certain time and space scales. Taylor, C.M., Gounou, A., Guichard, F., Harris, P.P., Ellis, R.J.,Couvreux, F., and M. De Kauwe. 2011, Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns, Nature Geoscience, 4, 430-433, doi:10.1038/ngeo1173 Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P, and W.A. Dorigo. 2012, Afternoon rain more likely over drier soils, Nature, 489, 423-426, doi:10.1038/nature11377

Developing a regional retrospective ensemble precipitation dataset for watershed hydrology modeling, Idaho, USA

NASA Astrophysics Data System (ADS)

Flores, A. N.; Smith, K.; LaPorte, P.

2011-12-01

Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically downscaled using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. Downscaled precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an ensemble-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.

Development of the Vista Methane Emissions Inventory for Southern California: A GIS-Based Approach for Mapping Methane Emissions

NASA Astrophysics Data System (ADS)

Carranza, V.; Frausto-Vicencio, I.; Rafiq, T.; Verhulst, K. R.; Hopkins, F. M.; Rao, P.; Duren, R. M.; Miller, C. E.

2016-12-01

Atmospheric methane (CH4) is the second most prevalent anthropogenic greenhouse gas. Improved estimates of CH4 emissions from cities is essential for carbon cycle science and climate mitigation efforts. Development of spatially-resolved carbon emissions data sets may offer significant advances in understanding and managing carbon emissions from cities. Urban CH4 emissions in particular require spatially resolved emission maps to help resolve uncertainties in the CH4 budget. This study presents a Geographic Information System (GIS)-based approach to mapping CH4 emissions using locations of infrastructure known to handle and emit methane. We constrain the spatial distribution of sources to the facility level for the major CH4 emitting sources in the South Coast Air Basin. GIS spatial modeling was combined with publicly available datasets to determine the distribution of potential CH4 sources. The datasets were processed and validated to ensure accuracy in the location of individual sources. This information was then used to develop the Vista emissions prior, which is a one-year long, spatially-resolved CH4 emissions estimate. Methane emissions were calculated and spatially allocated to produce 1 km x 1 km gridded CH4 emission map spanning the Los Angeles Basin. In future work, the Vista CH4 emissions prior will be compared with existing, coarser-resolution emissions estimates and will be evaluated in inverse modeling studies using atmospheric observations. The Vista CH4 emissions inventory presents the first detailed spatial maps of CH4 sources and emissions estimates in the Los Angeles Basin and is a critical step towards sectoral attribution of CH4 emissions at local to regional scales.

Coupled Ocean-Atmosphere Nested Modeling of the Adriatic Sea During Winter and Spring 2001

DTIC Science & Technology

2003-10-15

Breivik and Saetra, 2001]. Here major axis decorrelation scales are much longer for the Adriatic Sea simulation forced by the coarser-resolution...Volkert, The MAP special observing period, Bull. Am. Meteorol. Soc., 82, 433–462, 2001. Breivik , O., and O. Saetra, Real time assimilation of HF radar

Forest carbon dynamics associated with growth and disturbances in Oklahoma and Texas, 1992-2006

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2013-01-01

Quantifying forest carbon changes associated with growth and major disturbances is important for management of greenhouse gas emissions related to forests. Regional-level approaches with improved local growth data may refine estimates obtained using coarser resolution information. This study integrates remote-sensing-derived land cover change products, harvest data,...

Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

NASA Astrophysics Data System (ADS)

Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

2017-05-01

Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

NASA Astrophysics Data System (ADS)

Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao

2017-02-01

Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

Multi-resolution MPS method

NASA Astrophysics Data System (ADS)

Tanaka, Masayuki; Cardoso, Rui; Bahai, Hamid

2018-04-01

In this work, the Moving Particle Semi-implicit (MPS) method is enhanced for multi-resolution problems with different resolutions at different parts of the domain utilising a particle splitting algorithm for the finer resolution and a particle merging algorithm for the coarser resolution. The Least Square MPS (LSMPS) method is used for higher stability and accuracy. Novel boundary conditions are developed for the treatment of wall and pressure boundaries for the Multi-Resolution LSMPS method. A wall is represented by polygons for effective simulations of fluid flows with complex wall geometries and the pressure boundary condition allows arbitrary inflow and outflow, making the method easier to be used in flow simulations of channel flows. By conducting simulations of channel flows and free surface flows, the accuracy of the proposed method was verified.

Recent advances in time series InSAR

NASA Astrophysics Data System (ADS)

Hooper, Andrew; Bekaert, David; Spaans, Karsten

2010-05-01

Despite the multiple successes of InSAR at measuring surface displacement, in many instances the signal over much of an image either decorrelates too quickly to be useful or is swamped by atmospheric noise. Time series InSAR methods seek to address these issues by essentially increasing the signal-to-noise ratio (SNR) through the use of more data. These techniques are particularly useful for applications where the strain rates detected at the surface are low, such as postseismic/interseismic motion, magma/fluid movement, landslides and reservoir exploitation. Our previous developments in this field have included a persistent scatterer algorithm based on spatial correlation, a full resolution small baseline approach based on the same strategy, and procedure for combining the two [Hooper, GRL, 2008]. This combined method works well on small areas (up to one frame) at ERS or Envisat strip-map resolution. However, in applying it to larger areas, such as the Guerrero region of Mexico and western Anatolia in Turkey, or when processing data at higher resolution, e.g. from TerraSAR-X, computer resource problems can arise. We have therefore altered the processing strategy to involve smarter use of computer memory. Further improvement is achieved by the resampling of the selected pixels (whether persistent scatterers or distributed scatterers) to a coarser resolution - usually we do not require a resolution on the scale of individual resolution cells for geophysical applications. Aliasing is avoided by summing the phase of nearby selected pixels, weighted according to their estimated SNR. This is akin to smart multilooking, but note that better results can be achieved than by starting the analysis with low-resolution (multilooked) data. Another development concerns selecting pixels only in images where they appear reliable. This allows for resolution cells that become correlated/decorrelated either in a temporary fashion, e.g., due to snow cover, or in a permanent way due to the appearance or removal of scatterers. The detection algorithm relies on the degree of spatial correlation for the pixel of interest in each image. We have also modified our 3-D phase-unwrapping algorithms to allow for the resulting differing combinations of coherent pixels in every interferogram. We demonstrate our improved techniques on volcanoes in Iceland and the 2006 slow-slip event in Guerrero, Mexico.

Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter

USGS Publications Warehouse

Tornabene, Livio L.; Seelos, Frank P.; Pommerol, Antoine; Thomas, Nicolas; Caudill, Christy M.; Becerra, Patricio; Bridges, John C.; Byrne, Shane; Cardinale, Marco; Chojnacki, Matthew; Conway, Susan J.; Cremonese, Gabriele; Dundas, Colin M.; El-Maarry, M. R.; Fernando, Jennifer; Hansen, Candice J.; Hansen, Kayle; Harrison, Tanya N.; Henson, Rachel; Marinangeli, Lucia; McEwen, Alfred S.; Pajola, Maurizio; Sutton, Sarah S.; Wray, James J.

2018-01-01

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three “fully”-simulated image cubes of thirty unique locations on Mars (i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (∼9.4×50">∼9.4×50∼9.4×50 km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.

SU-F-T-179: Fast and Accurate Profile Acquisition for Proton Beam Using Multi-Ion Chamber Arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, X; Zou, J; Chen, T

2016-06-15

Purpose: Proton beam profile measurement is more time-consuming than photon beam. Due to the energy modulation during proton delivery, chambers have to move step-by-step instead of continuously. Multi-ion chamber arrays are appealing to this task since multiple measurements can be performed at once. However, their utilization suffers from sparse spatial resolution and potential intrinsic volume-averaging effect of the disk-shaped ion chambers. We proposed an approach to measure proton beam profiles accurately and efficiently. Methods: Mevion S250 proton system and IBA Matrixx ion chamber arrays were used in this study. Matrixx has interchamber distance of 7.62 mm, and chamber diameter ofmore » 4.5 mm. We measured the same beam profile by moving the Matrixx seven times with 1 mm each time along y axis. All 7 measurements were superimposed to get a “finer” profile with 1 mm spatial resolution. Coarser resolution profiles of 2 mm and 3 mm were also generated by using subsets of measurements. Those profiles were compared to the TPS calculated beam profile. Gamma analysis was performed for 2D dose maps to evaluate the difference to TPS dose plane. Results: Preliminary results showed a large discrepancy between the TPS calculated profile and the single measurement profile with 7.6 mm resolution. A good match could be achieved when the resolution reduced to 3 mm by adding one extra measurement. Gamma analysis for 2D dose map of a 10×10 field showed a passing rate (γ ≤ 1) of 90.6% using a 3% and 3mm criterion for single measurement, which increased to 92.3% for 2-measurement superimposition, and slightly further increased to 92.9% for 7-measurement superimposition. Conclusion: The results indicated that 2 measurements shifted by 3mm using Matrixx generated a smooth proton beam profile with good matching to Eclipse beam profile. We suggest using this 2-measurement approach in clinic for double scattering proton beam profile measurement.« less

GIS interpolations of witness tree records (1839-1866) for northern Wisconsin at multiple scales

USGS Publications Warehouse

He, H.S.; Mladenoff, D.J.; Sickley, T.A.; Guntenspergen, G.R.

2000-01-01

To construct forest landscape of pre-European settlement periods, we developed a GIS interpolation approach to convert witness tree records of the U.S. General Land Office (GLO) survey from point to polygon data, which better described continuously distributed vegetation. The witness tree records (1839-1866) were processed for a 3-million ha landscape in northern Wisconsin, U.S.A. at different scales. We provided implications of processing results at each scale. Compared with traditional GLO mapping that has fixed mapping scales and generalized classifications, our approach allows presettlement forest landscapes to be analysed at the individual species level and reconstructed under various classifications. We calculated vegetation indices including relative density, dominance, and importance value for each species, and quantitatively described the possible outcomes when GLO records are analysed at three different scales (resolution). The 1 x 1-section resolution preserved spatial information but derived the most conservative estimates of species distributions measured in percentage area, which increased at coarser resolutions. Such increases under the 2 x 2-section resolution were in the order of three to four times for the least common species, two to three times for the medium to most common species, and one to two times for the most common or highly contagious species. We marred the distributions of hemlock and sugar maple from the pre-European settlement period based on their witness tree locations and reconstructed presettlement forest landscapes based on species importance values derived for all species. The results provide a unique basis to further study land cover changes occurring after European settlement.

Assessing the impacts of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system

NASA Astrophysics Data System (ADS)

Perroy, Ryan L.; Sullivan, Timo; Stephenson, Nathan

2017-03-01

Small unmanned aerial systems (sUAS) have great potential to facilitate the early detection and management of invasive plants. Here we show how very high-resolution optical imagery, collected from small consumer-grade multirotor UAS platform at altitudes of 30-120 m above ground level (agl), can be used to detect individual miconia (Miconia calvescens) plants in a highly invaded tropical rainforest environment on the island of Hawai'i. The central aim of this research was to determine how overstory vegetation cover, imagery resolution, and camera look-angle impact the aerial detection of known individual miconia plants. For our finest resolution imagery (1.37 cm ground sampling distance collected at 30 m agl), we obtained a 100% detection rate for sub-canopy plants with above-crown openness values >40% and a 69% detection rate for those with >20% openness. We were unable to detect any plants with <10% above crown openness. Detection rates progressively declined with coarser spatial resolution imagery, ending in a 0% detection rate for the 120 m agl flights (ground sampling distance of 5.31 cm). The addition of forward-looking oblique imagery improved detection rates for plants below overstory vegetation, though this effect decreased with increasing flight altitude. While dense overstory canopy cover, limited flight times, and visual line of sight regulations present formidable obstacles for detecting miconia and other invasive plant species, we show that sUAS platforms carrying optical sensors can be an effective component of an integrated management plan within challenging subcanopy forest environments.

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

NASA Technical Reports Server (NTRS)

Wang, James S.; Kawa, S. Randolph; Eluszkiewicz, Janusz; Collatz, G. J.; Mountain, Marikate; Henderson, John; Nehrkorn, Thomas; Aschbrenner, Ryan; Zaccheo, T. Scott

2012-01-01

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, M. P.; Nijssen, B.

2017-12-01

Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and weaknesses of each strategy map onto the requirements for different types of forecasting services (e.g., flash flooding, river flooding, seasonal water supply prediction).

Neural Summation in the Hawkmoth Visual System Extends the Limits of Vision in Dim Light.

PubMed

Stöckl, Anna Lisa; O'Carroll, David Charles; Warrant, Eric James

2016-03-21

Most of the world's animals are active in dim light and depend on good vision for the tasks of daily life. Many have evolved visual adaptations that permit a performance superior to that of manmade imaging devices [1]. In insects, a major model visual system, nocturnal species show impressive visual abilities ranging from flight control [2, 3], to color discrimination [4, 5], to navigation using visual landmarks [6-8] or dim celestial compass cues [9, 10]. In addition to optical adaptations that improve their sensitivity in dim light [11], neural summation of light in space and time-which enhances the coarser and slower features of the scene at the expense of noisier finer and faster features-has been suggested to improve sensitivity in theoretical [12-14], anatomical [15-17], and behavioral [18-20] studies. How these summation strategies function neurally is, however, presently unknown. Here, we quantified spatial and temporal summation in the motion vision pathway of a nocturnal hawkmoth. We show that spatial and temporal summation combine supralinearly to substantially increase contrast sensitivity and visual information rate over four decades of light intensity, enabling hawkmoths to see at light levels 100 times dimmer than without summation. Our results reveal how visual motion is calculated neurally in dim light and how spatial and temporal summation improve sensitivity while simultaneously maximizing spatial and temporal resolution, thus extending models of insect motion vision derived predominantly from diurnal flies. Moreover, the summation strategies we have revealed may benefit manmade vision systems optimized for variable light levels [21]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-year mapping of irrigated croplands over the US High Plains Aquifer using satellite data

NASA Astrophysics Data System (ADS)

Deines, J.; Kendall, A. D.; Hyndman, D. W.

2016-12-01

Irrigated agriculture is the largest consumer of freshwater globally. Effective water management is crucial to support ongoing agricultural intensification to meet increasing demand for food, fuel, and fiber production. Knowledge of where and when irrigation occurs is critical for effective management and hydrological modeling, yet data on patterns of irrigation through time are surprisingly rare. Existing regional datasets in the United States tend to be either aspatial county-level estimates or static, single-year remotely sensed products with relatively low spatial resolution ( 250 m or coarser). Spatially explicit, dynamic maps are needed to understand water use trends, create accurate hydrological models, and inform forecasts of future water availability under projected climate change. In the High Plains Aquifer (HPA), repeat mapping efforts in 2002 and 2007 indicated only 60% of irrigated lands were static between these periods. To better understand annual irrigation dynamics, we used remote sensing to produce annual maps of irrigated cropland across the HPA region from a data fusion of Landsat satellites, annual time series of vegetation indices, and ancillary data such as precipitation, soil properties, and terrain slope. We performed machine learning classification using Google Earth Engine, allowing efficient image processing over a large region for multiple years. We then analyzed maps for water use trends and found that although total irrigated area has increased only slightly, there was substantial variability in the spatial pattern of irrigated lands over time. This dataset will support efforts towards groundwater sustainability by providing consistent, spatially explicit tracking of irrigation dynamics over time.

Numerical simulations and parameterizations of volcanic plumes observed at Reunion Island

NASA Astrophysics Data System (ADS)

Gurwinder Sivia, Sandra; Gheusi, Francois; Mari, Celine; DiMuro, Andrea; Tulet, Pierre

2013-04-01

Volcanoes are natural composite hazards. The volcanic ejecta can have considerable impact on human health. Volcanic gases and ash, can be especially harmful to people with lung disease such as asthma. Volcanic gases that pose the greatest potential hazards are sulfur dioxide, carbon dioxide, and hydrogen fluoride. Locally, sulfur dioxide gas can lead to acid rain and air pollution downwind from a volcano. These gases can come from lava flows as well as volcano eruptive plumes. This acidic pollution can be transported by wind over large distances. To comply with regulatory rules, modeling tools are needed to accurately predict the contribution of volcanic emissions to air quality degradation. Unfortunately, the ability of existing models to simulate volcanic plume production and dispersion is currently limited by inaccurate volcanic emissions and uncertainties in plume-rise estimates. The present work is dedicated to the study of deep injections of volcanic emissions into the troposphere developed as consequence of intense but localized input of heat near eruptive mouths. This work covers three aspects. First a precise quantification of heat sources in terms of surface, geometry and heat source intensity is done for the Piton de la Fournaise volcano. Second, large eddy simulation (LES) are performed with the Meso-NH model to determine the dynamics and vertical development of volcanic plumes. The estimated energy fluxes and the geometry of the heat source is used at the bottom boundary to generate and sustain the plume, while, passive tracers are used to represent volcanic gases and their injection into the atmosphere. The realism of the simulated plumes is validated on the basis of plume observations. The LES simulations finally serve as references for the development of column parameterizations for the coarser resolution version of the model which is the third aspect of the present work. At spatial resolution coarser than ~1km, buoyant volcanic plumes are sub-grid processes. A new parameterization for the injection height is presented which is based on a modified version of the eddy-diffusivity/mass-flux scheme initially developed for the simulation of convective boundary layer.

Sensitivity of mesoscale-model forecast skill to some initial-data characteristics, data density, data position, analysis procedure and measurement error

NASA Technical Reports Server (NTRS)

Warner, Thomas T.; Key, Lawrence E.; Lario, Annette M.

1989-01-01

The effects of horizontal and vertical data resolution, data density, data location, different objective analysis algorithms, and measurement error on mesoscale-forecast accuracy are studied with observing-system simulation experiments. Domain-averaged errors are shown to generally decrease with time. It is found that the vertical distribution of error growth depends on the initial vertical distribution of the error itself. Larger gravity-inertia wave noise is produced in forecasts with coarser vertical data resolution. The use of a low vertical resolution observing system with three data levels leads to more forecast errors than moderate and high vertical resolution observing systems with 8 and 14 data levels. Also, with poor vertical resolution in soundings, the initial and forecast errors are not affected by the horizontal data resolution.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Understanding Multifunctional Agricultural Land by Using Low Cost and Open Source Solutions to Quantify Ecosystem Function and Services

NASA Astrophysics Data System (ADS)

Forsmoo, Joel; Anderson, Karen; Brazier, Richard; Macleod, Kit; Wilkinson, Mark

2016-04-01

There is a need to advance our understanding of how the spatial structure of farmed landscapes contributes to the provision of functions and services. Agricultural land is of critical importance in NW Europe, covering large parts of NW Europe's temperate land. Moreover, these agricultural areas are primarily intensively managed, with a focus on maximizing food and fibre production. Such landscapes therefore can provide a wealth of ecosystem goods and services (ESs) including regulation of climate, erosion regulation, hydrology, water quality, nutrient cycling and biodiversity conservation. However, it has been shown they are key sources of sediment, phosphorous, nitrogen and storm runoff contributing to flooding, and therefore it is likely that most agricultural landscapes do not maximize the services or benefits that they might provide. The focus of this study is the spatio-temporal assessment of carbon sequestration (particularly through proxies such as above-ground biomass) and hydrological processes on agricultural land. Understanding and quantifying both of these is important to (a) inform payments for ecosystem services frameworks, (b) evaluate and improve carbon sequestration models, (c) manage the flood risk, (d) downstream water security and (e) water quality. Quantifying both of these ESs is dependent on data describing the fine spatial and temporal structure and function of the landscape. Common practice has been to use remote sensing techniques, e.g. satellites, providing coarse spatial resolution (around 30cm at 20° off nadir) and/or temporal resolution (around 5 days revisit time at <20° off nadir). In this paper we will explain how imaging data from lightweight and easily deployed unmanned aerial vehicles (UAVs) can be used to generate structure from motion (SFM) products describing the very fine detailed (<3 cm pixel resolution) structure of the agricultural environment. We will demonstrate how these products can be delivered using advanced free and open source post-processing alternatives and low cost sensors (digital cameras) and platforms (UAVs). We furthermore draw attention to the influence post-processing solutions have on the accuracy of the final product, the digital surface model (DSM), by using recently acquired data. Specifically, when applied in a structurally complex field site with irregular surface roughness patterns, over a land use gradient, from livestock grazing to agricultural crops. We will demonstrate the added value of using very fine detail data, highlighting important structural properties and patterns overlooked with coarser spatial resolution data.

Estimation of Spatial Trends in LAI in Heterogeneous Semi-arid Ecosystems using Full Waveform Lidar

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Ilangakoon, N.; Spaete, L.; Dashti, H.

2017-12-01

Leaf area index (LAI) is a key structural trait that is defined by the plant functional type (PFT) and controlled by prevailing climate- and human-driven ecosystem stresses. Estimates of LAI using remote sensing techniques are limited by the uncertainties of vegetation inter and intra-gap fraction estimates; this is especially the case in sparse, low stature vegetated ecosystems. Small footprint full waveform lidar digitizes the total amount of return energy with the direction information as a near continuous waveform at a high vertical resolution (1 ns). Thus waveform lidar provides additional data matrices to capture vegetation gaps as well as PFTs that can be used to constrain the uncertainties of LAI estimates. In this study, we calculated a radiometrically calibrated full waveform parameter called backscatter cross section, along with other data matrices from the waveform to estimate vegetation gaps across plots (10 m x 10 m) in a semi-arid ecosystem in the western US. The LAI was then estimated using empirical relationships with directional gap fraction. Full waveform-derived gap fraction based LAI showed a high correlation with field observed shrub LAI (R2 = 0.66, RMSE = 0.24) compared to discrete return lidar based LAI (R2 = 0.01, RMSE = 0.5). The data matrices derived from full waveform lidar classified a number of deciduous and evergreen tree species, shrub species, and bare ground with an overall accuracy of 89% at 10 m. A similar analysis was performed at 1m with overall accuracy of 80%. The next step is to use these relationships to map the PFTs LAI at 10 m spatial scale across the larger study regions. The results show the exciting potential of full waveform lidar to identify plant functional types and LAI in low-stature vegetation dominated semi-arid ecosystems, an ecosystem in which many other remote sensing techniques fail. These results can be used to assess ecosystem state, habitat suitability as well as to constrain model uncertainties in vegetation dynamic models with a combination of other remote sensing techniques. Multi-spatial resolution (1 m and 10 m) studies provide basic information on the applicability and detection thresholds of future global satellite sensors designed at coarser spatial resolutions (e.g. GEDI, ICESat-2) in semi-arid ecosystems.

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

USGS Publications Warehouse

Barrett, Kirsten; Valentim, Judson; Turner, B. L.

2013-01-01

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The area-weighted fractional tree cover for the study area was 1.85 %, corrected for a slight bias associated with the coarser sampling resolution. The pastures sampled for fractional tree cover were divided between ‘high’ and ‘low’ tree cover, which may be the result of intentional incorporation of arboreal species in pasture. Further research involving those ranchers that have a higher fractional tree cover may indicate ways to promote the practice on a broader scale in the region.

Tracking fronts in solutions of the shallow-water equations

NASA Astrophysics Data System (ADS)

Bennett, Andrew F.; Cummins, Patrick F.

1988-02-01

A front-tracking algorithm of Chern et al. (1986) is tested on the shallow-water equations, using the Parrett and Cullen (1984) and Williams and Hori (1970) initial state, consisting of smooth finite amplitude waves depending on one space dimension alone. At high resolution the solution is almost indistinguishable from that obtained with the Glimm algorithm. The latter is known to converge to the true frontal solution, but is 20 times less efficient at the same resolution. The solutions obtained using the front-tracking algorithm at 8 times coarser resolution are quite acceptable, indicating a very substantial gain in efficiency, which encourages application in realistic ocean models possessing two or three space dimensions.

Bathymetry Estimations Using Vicariously Calibrated HICO Data

DTIC Science & Technology

2013-07-16

prototype sensor installed on the International Space Station (ISS) designed to explore the management and capability of a space-borne hyperspectral sensor ...management of the HICO sensor . Bathymetry information is essential for naval operations in coastal regions. However, bathymetry may not be available in... sensors with coarser resolutions. Furthermore, its contiguous hyperspectral range is well suited to be used as input to the Hyperspectral Optimization

A new gridded on-road CO2 emissions inventory for the United States, 1980-2011

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.

2013-12-01

On-road transportation is responsible for 28% of all U.S. fossil fuel CO2 emissions. However, mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories have used spatial proxies such as population and road density to downscale national or state level data, which may introduce errors where the proxy variables and actual emissions are weakly correlated. We have developed a national on-road emissions inventory product based on roadway-level traffic data obtained from the Highway Performance Monitoring System. We produce annual estimates of on-road CO2 emissions at a 1km spatial resolution for the contiguous United States for the years 1980 through 2011. For the year 2011 we also produce an hourly emissions product at the 1km scale using hourly traffic volumes from hundreds of automated traffic counters across the country. National on-road emissions rose at roughly 2% per year from 1980 to 2006, with emissions peaking at 1.71 Tg CO2 in 2007. However, while national emissions have declined 6% since the peak, we observe considerable regional variation in emissions trends post-2007. While many states show stable or declining on-road emissions, several states and metropolitan areas in the Midwest, mountain west and south had emissions increases of 3-10% from 2008 to 2011. Our emissions estimates are consistent with state-reported totals of gasoline and diesel fuel consumption. This is in contrast to on-road CO2 emissions estimated by the Emissions Database of Global Atmospheric Research (EDGAR), which we show to be inconsistent in matching on-road emissions to published fuel consumption at the scale of U.S. states, due to the non-linear relationships between emissions and EDGAR's chosen spatial proxies at these scales. Since our emissions estimates were generated independent of population density and other demographic data, we were able to conduct a panel regression analysis to estimate the relationship between these variables and on-road CO2 at various spatial scales. In the case of Massachusetts we find a non-linear relationship between emissions and population density indicating that increasing density resulted in increased emissions when density is less than 2000 persons-km-2. These results highlight the value of using an emissions inventory with high spatial and temporal resolution. At coarser spatial scales, much of the variation in population density and on-road emissions between towns is lost due to aggregation. The high spatial resolution and broad temporal scope of our CO2 estimates provides a basis for analyses to support emissions monitoring, verification and mitigation policies at regional, state and local scale.

Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

NASA Astrophysics Data System (ADS)

Lyra, Andre; Tavares, Priscila; Chou, Sin Chan; Sueiro, Gustavo; Dereczynski, Claudine; Sondermann, Marcely; Silva, Adan; Marengo, José; Giarolla, Angélica

2018-04-01

The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961-1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.

WRF added value to capture the spatio-temporal drought variability

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Data Assimilation of AirSWOT and Synthetically Derived SWOT Observations of Water Surface Elevation in a Multichannel River

NASA Astrophysics Data System (ADS)

Altenau, E. H.; Pavelsky, T.; Andreadis, K.; Bates, P. D.; Neal, J. C.

2017-12-01

Multichannel rivers continue to be challenging features to quantify, especially at regional and global scales, which is problematic because accurate representations of such environments are needed to properly monitor the earth's water cycle as it adjusts to climate change. It has been demonstrated that higher-complexity, 2D models outperform lower-complexity, 1D models in simulating multichannel river hydraulics at regional scales due to the inclusion of the channel network's connectivity. However, new remote sensing measurements from the future Surface Water and Ocean Topography (SWOT) mission and it's airborne analog AirSWOT offer new observations that can be used to try and improve the lower-complexity, 1D models to achieve accuracies closer to the higher-complexity, 2D codes. Here, we use an Ensemble Kalman Filter (EnKF) to assimilate AirSWOT water surface elevation (WSE) measurements from a 2015 field campaign into a 1D hydrodynamic model along a 90 km reach of Tanana River, AK. This work is the first to test data assimilation methods using real SWOT-like data from AirSWOT. Additionally, synthetic SWOT observations of WSE are generated across the same study site using a fine-resolution 2D model and assimilated into the coarser-resolution 1D model. Lastly, we compare the abilities of AirSWOT and the synthetic-SWOT observations to improve spatial and temporal model outputs in WSEs. Results indicate 1D model outputs of spatially distributed WSEs improve as observational coverage increases, and improvements in temporal fluctuations in WSEs depend on the number of observations. Furthermore, results reveal that assimilation of AirSWOT observations produce greater error reductions in 1D model outputs compared to synthetic SWOT observations due to lower measurement errors. Both AirSWOT and the synthetic SWOT observations significantly lower spatial and temporal errors in 1D model outputs of WSEs.

Infrared and Passive Microwave Radiometric Sea Surface Temperatures and Their Relationships to Atmospheric Forcing

NASA Technical Reports Server (NTRS)

Castro, Sandra L.

2004-01-01

The current generation of infrared (IR) and passive microwave (MW) satellite sensors provides highly complementary information for monitoring sea surface temperature (SST). On the one hand, infrared sensors provide high resolution and high accuracy but are obscured by clouds. Microwave sensors on the other hand, provide coverage through non-precipitating clouds but have coarser resolution and generally poorer accuracy. Assuming that the satellite SST measurements do not have spatially variable biases, they can be blended combining the merits of both SST products. These factors have motivated recent work in blending the MW and IR data in an attempt to produce high-accuracy SST products with improved coverage in regions with persistent clouds. The primary sources of retrieval uncertainty are, however, different for the two sensors. The main uncertainty in the MW retrievals lies in the effects of wind-induced surface roughness and foam on emissivity, whereas the IR retrievals are more sensitive to the atmospheric water vapor and aerosol content. Average nighttime differences between the products for the month periods of January 1999 and June 2000 are shown. These maps show complex spatial and temporal differences as indicated by the strong spatially coherent features in the product differences and the changes between seasons. Clearly such differences need to be understood and accounted for if the products are to be combined. The overall goals of this project are threefold: (1) To understand the sources of uncertainty in the IR and MW SST retrievals and to characterize the errors affecting the two types of retrieval as a fiction of atmospheric forcing; (2) To demonstrate how representative the temperature difference between the two satellite products is of Delta T; (3) To apply bias adjustments and to device a comprehensive treatment of the behavior of the temperature difference across the oceanic skin layer to determine the best method for blending thermal infrared and passive microwave measurements of SSTs.

Comparison of Large eddy dynamo simulation using dynamic sub-grid scale (SGS) model with a fully resolved direct simulation in a rotating spherical shell

NASA Astrophysics Data System (ADS)

Matsui, H.; Buffett, B. A.

2017-12-01

The flow in the Earth's outer core is expected to have vast length scale from the geometry of the outer core to the thickness of the boundary layer. Because of the limitation of the spatial resolution in the numerical simulations, sub-grid scale (SGS) modeling is required to model the effects of the unresolved field on the large-scale fields. We model the effects of sub-grid scale flow and magnetic field using a dynamic scale similarity model. Four terms are introduced for the momentum flux, heat flux, Lorentz force and magnetic induction. The model was previously used in the convection-driven dynamo in a rotating plane layer and spherical shell using the Finite Element Methods. In the present study, we perform large eddy simulations (LES) using the dynamic scale similarity model. The scale similarity model is implement in Calypso, which is a numerical dynamo model using spherical harmonics expansion. To obtain the SGS terms, the spatial filtering in the horizontal directions is done by taking the convolution of a Gaussian filter expressed in terms of a spherical harmonic expansion, following Jekeli (1981). A Gaussian field is also applied in the radial direction. To verify the present model, we perform a fully resolved direct numerical simulation (DNS) with the truncation of the spherical harmonics L = 255 as a reference. And, we perform unresolved DNS and LES with SGS model on coarser resolution (L= 127, 84, and 63) using the same control parameter as the resolved DNS. We will discuss the verification results by comparison among these simulations and role of small scale fields to large scale fields through the role of the SGS terms in LES.

Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0)

NASA Astrophysics Data System (ADS)

Huscroft, Jordan; Gleeson, Tom; Hartmann, Jens; Börker, Janine

2018-02-01

The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high-resolution permeability maps distinguish solely fine-grained and coarse-grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two-layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is -12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at regional to global scales.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Albedo, Land Cover, and Daytime Surface Temperature Variation Across an Urbanized Landscape

NASA Astrophysics Data System (ADS)

Trlica, A.; Hutyra, L. R.; Schaaf, C. L.; Erb, A.; Wang, J. A.

2017-11-01

Land surface albedo is a key parameter controlling the local energy budget, and altering the albedo of built surfaces has been proposed as a tool to mitigate high near-surface temperatures in the urban heat island. However, most research on albedo in urban landscapes has used coarse-resolution data, and few studies have attempted to relate albedo to other urban land cover characteristics. This study provides an empirical description of urban summertime albedo using 30 m remote sensing measurements in the metropolitan area around Boston, Massachusetts, relating albedo to metrics of impervious cover fraction, tree canopy coverage, population density, and land surface temperature (LST). At 30 m spatial resolution, median albedo over the study area (excluding open water) was 0.152 (0.112-0.187). Trends of lower albedo with increasing urbanization metrics and temperature emerged only after aggregating data to 500 m or the boundaries of individual towns, at which scale a -0.01 change in albedo was associated with a 29 (25-35)% decrease in canopy cover, a 27 (24-30)% increase in impervious cover, and an increase in population from 11 to 386 km-2. The most intensively urbanized towns in the region showed albedo up to 0.035 lower than the least urbanized towns, and mean mid-morning LST 12.6°C higher. Trends in albedo derived from 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) measurements were comparable, but indicated a strong contribution of open water at this coarser resolution. These results reveal linkages between albedo and urban land cover character, and offer empirical context for climate resilient planning and future landscape functional changes with urbanization.

Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

Treesearch

Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

2009-01-01

We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

Marine ice sheet model performance depends on basal sliding physics and sub-shelf melting

NASA Astrophysics Data System (ADS)

Gladstone, Rupert Michael; Warner, Roland Charles; Galton-Fenzi, Benjamin Keith; Gagliardini, Olivier; Zwinger, Thomas; Greve, Ralf

2017-01-01

Computer models are necessary for understanding and predicting marine ice sheet behaviour. However, there is uncertainty over implementation of physical processes at the ice base, both for grounded and floating glacial ice. Here we implement several sliding relations in a marine ice sheet flow-line model accounting for all stress components and demonstrate that model resolution requirements are strongly dependent on both the choice of basal sliding relation and the spatial distribution of ice shelf basal melting.Sliding relations that reduce the magnitude of the step change in basal drag from grounded ice to floating ice (where basal drag is set to zero) show reduced dependence on resolution compared to a commonly used relation, in which basal drag is purely a power law function of basal ice velocity. Sliding relations in which basal drag goes smoothly to zero as the grounding line is approached from inland (due to a physically motivated incorporation of effective pressure at the bed) provide further reduction in resolution dependence.A similar issue is found with the imposition of basal melt under the floating part of the ice shelf: melt parameterisations that reduce the abruptness of change in basal melting from grounded ice (where basal melt is set to zero) to floating ice provide improved convergence with resolution compared to parameterisations in which high melt occurs adjacent to the grounding line.Thus physical processes, such as sub-glacial outflow (which could cause high melt near the grounding line), impact on capability to simulate marine ice sheets. If there exists an abrupt change across the grounding line in either basal drag or basal melting, then high resolution will be required to solve the problem. However, the plausible combination of a physical dependency of basal drag on effective pressure, and the possibility of low ice shelf basal melt rates next to the grounding line, may mean that some marine ice sheet systems can be reliably simulated at a coarser resolution than currently thought necessary.

Transitional hemodynamics in intracranial aneurysms - Comparative velocity investigations with high resolution lattice Boltzmann simulations, normal resolution ANSYS simulations, and MR imaging.

PubMed

Jain, Kartik; Jiang, Jingfeng; Strother, Charles; Mardal, Kent-André

2016-11-01

Blood flow in intracranial aneurysms has, until recently, been considered to be disturbed but still laminar. Recent high resolution computational studies have demonstrated, in some situations, however, that the flow may exhibit high frequency fluctuations that resemble weakly turbulent or transitional flow. Due to numerous assumptions required for simplification in computational fluid dynamics (CFD) studies, the occurrence of these events, in vivo, remains unsettled. The detection of these fluctuations in aneurysmal blood flow, i.e., hemodynamics by CFD, poses additional challenges as such phenomena cannot be captured in clinical data acquisition with magnetic resonance (MR) due to inadequate temporal and spatial resolutions. The authors' purpose was to address this issue by comparing results from highly resolved simulations, conventional resolution laminar simulations, and MR measurements, identify the differences, and identify their causes. Two aneurysms in the basilar artery, one with disturbed yet laminar flow and the other with transitional flow, were chosen. One set of highly resolved direct numerical simulations using the lattice Boltzmann method (LBM) and another with adequate resolutions under laminar flow assumption were conducted using a commercially available ANSYS Fluent solver. The velocity fields obtained from simulation results were qualitatively and statistically compared against each other and with MR acquisition. Results from LBM, ANSYS Fluent, and MR agree well qualitatively and quantitatively for one of the aneurysms with laminar flow in which fluctuations were <80 Hz. The comparisons for the second aneurysm with high fluctuations of > ∼ 600 Hz showed vivid differences between LBM, ANSYS Fluent, and magnetic resonance imaging. After ensemble averaging and down-sampling to coarser space and time scales, these differences became minimal. A combination of MR derived data and CFD can be helpful in estimating the hemodynamic environment of intracranial aneurysms. Adequately resolved CFD would suffice gross assessment of hemodynamics, potentially in a clinical setting, and highly resolved CFD could be helpful in a detailed and retrospective understanding of the physiological mechanisms.

Spatial Resolution Effect on Forest Road Gradient Calculation and Erosion Modelling

NASA Astrophysics Data System (ADS)

Cao, L.; Elliot, W.

2017-12-01

Road erosion is one of the main sediment sources in a forest watershed and should be properly evaluated. With the help of GIS technology, road topography can be determined and soil loss can be predicted at a watershed scale. As a vector geographical feature, the road gradient should be calculated following road direction rather than hillslope direction. This calculation might be difficult with a coarse (30-m) DEM which only provides the underlying topography information. This study was designed to explore the effect of road segmentation and DEM resolution on the road gradient calculation and erosion prediction at a watershed scale. The Water Erosion Prediction Project (WEPP) model was run on road segments of 9 lengths ranging from 40m to 200m. Road gradient was calculated from three DEM data sets: 1m LiDAR, and 10m and 30m USGS DEMs. The 1m LiDAR DEM calculated gradients were very close to the field observed road gradients, so we assumed the 1m LiDAR DEM predicted the true road gradient. The results revealed that longer road segments skipped detail topographical undulations and resulted in lower road gradients. Coarser DEMs computed steeper road gradients as larger grid cells covered more adjacent areas outside road resulting in larger elevation differences. Field surveyed results also revealed that coarser DEM might result in more gradient deviation in a curved road segment when it passes through a convex or concave slope. As road segment length increased, the gradient difference between three DEMs was reduced. There were no significant differences between road gradients of different segment lengths and DEM resolution when segments were longer than 100m. For long segments, the 10m DEM calculated road gradient was similar to the 1m LiDAR gradient. When evaluating the effects of road segment length, the predicted erosion rate decreased with increasing length when road gradient was less than 3%. In cases where the road gradients exceed 3% and rill erosion dominates, predicted erosion rates exponentially increased with segment length. At the watershed scale, most of the predicted soil loss occurred on segments with gradients ranging from 3% to 9%. Based on the road gradient calculated with the 10-m and 30-m DEMs, soil loss was overestimated when compared to the 1m LiDAR DEM. Both the 10m and 30m DEM result in similar total road soil loss.

Ensemble forecasting for renewable energy applications - status and current challenges for their generation and verification

NASA Astrophysics Data System (ADS)

Pinson, Pierre

2016-04-01

The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.

Surface Soil Moisture Retrieval Using SSM/I and Its Comparison with ESTAR: A Case Study Over a Grassland Region

NASA Technical Reports Server (NTRS)

Jackson, T.; Hsu, A. Y.; ONeill, P. E.

1999-01-01

This study extends a previous investigation on estimating surface soil moisture using the Special Sensor Microwave/Imager (SSM/I) over a grassland region. Although SSM/I is not optimal for soil moisture retrieval, it can under some conditions provide information. Rigorous analyses over land have been difficult due to the lack of good validation data sets. A scientific objective of the Southern Great Plains 1997 (SGP97) Hydrology Experiment was to investigate whether the retrieval algorithms for surface soil moisture developed at higher spatial resolution using truck-and aircraft-based passive microwave sensors can be extended to the coarser resolutions expected from satellite platform. With the data collected for the SGP97, the objective of this study is to compare the surface soil moisture estimated from the SSM/I data with those retrieved from the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) data, the core sensor for the experiment, using the same retrieval algorithm. The results indicated that an error of estimate of 7.81% could be achieved with SSM/I data as contrasted to 2.82% with ESTAR data over three intensive sampling areas of different vegetation regimes. It confirms the results of previous study that SSM/I data can be used to retrieve surface soil moisture information at a regional scale under certain conditions.

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

NASA Astrophysics Data System (ADS)

Chen, Xingchao; Pauluis, Olivier M.; Zhang, Fuqing

2018-01-01

Simulations of the Indian summer monsoon by the cloud-permitting Weather Research and Forecasting (WRF) model at gray-zone resolution are described in this study, with a particular emphasis on the model ability to capture the monsoon intraseasonal oscillations (MISOs). Five boreal summers are simulated from 2007 to 2011 using the ERA-Interim reanalysis as the lateral boundary forcing data. Our experimental setup relies on a horizontal grid spacing of 9 km to explicitly simulate deep convection without the use of cumulus parameterizations. When compared to simulations with coarser grid spacing (27 km) and using a cumulus scheme, the 9 km simulations reduce the biases in mean precipitation and produce more realistic low-frequency variability associated with MISOs. Results show that the model at the 9 km gray-zone resolution captures the salient features of the summer monsoon. The spatial distributions and temporal evolutions of monsoon rainfall in the WRF simulations verify qualitatively well against observations from the Tropical Rainfall Measurement Mission (TRMM), with regional maxima located over Western Ghats, central India, Himalaya foothills, and the west coast of Myanmar. The onset, breaks, and withdrawal of the summer monsoon in each year are also realistically captured by the model. The MISO-phase composites of monsoon rainfall, low-level wind, and precipitable water anomalies in the simulations also agree qualitatively with the observations. Both the simulations and observations show a northeastward propagation of the MISOs, with the intensification and weakening of the Somali Jet over the Arabian Sea during the active and break phases of the Indian summer monsoon.

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

High resolution mapping of NO2 column densities along the western shore of Lake Michigan and the Los Angeles Basin during May/June 2017

NASA Astrophysics Data System (ADS)

Judd, L. M.; Al-Saadi, J. A.; Janz, S. J.; Kowalewski, M. G.; Szykman, J.; Swap, R.; Abuhassan, N.; Cede, A.; Valin, L.; Williams, D.; Stanier, C. O.

2017-12-01

The airborne Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) UV/VIS mapping spectrometer was used to make measurements for the Lake Michigan Ozone Study (LMOS) along the western shore of Lake Michigan and for the Student Airborne Research Program (SARP) in the Los Angeles Basin during May and June 2017. This instrument has the capability of retrieving NO2 column densities at sub-urban spatial scales (nominally 250 m x 250 m) and is being used as a testbed for future geostationary air quality retrievals. LMOS was a multi-agency collaborative observational effort to better understand ozone pollution along Lake Michigan's western shore, where coastal monitors exceed current ozone standards. With 21 science flights during the 5-week campaign period, GeoTASO acquired data for constraining emissions along the western coast of Lake Michigan and observed how these emissions dispersed and influenced the local air quality. During SARP flights, GeoTASO was used to map the Los Angeles Basin five times over two days, observing NO2 Differential Slant Column densities (DSCs) ranging from over 50x1015 molecules cm-2 down to GeoTASO's detection limit ( 1.5x1015 molecules cm-2 at 250 m x 250 m). This work presents the spatial distribution of preliminary NO2 DSCs observations over both research areas, and shows how this it changed at hourly to multi-day timescales under varying meteorological conditions. Both LMOS and SARP included coincident column NO2 measurements from networks of ground-based Pandora spectrometers specifically set up for these campaigns, and a comparison of coincident observations will be shown. Consistent features were observed throughout these flights, including continual emission `hot-spots' and the redistribution of NO2 plumes by land-water circulations. One goal of this work is to investigate how the fine spatial features observed (e.g. power plant plumes) will be depicted in satellite observations at coarser spatial resolutions. These results will help the community understand how to interpret space-based observations in areas subject to large NO2 spatial heterogeneity, as well as what we can expect to detect with future geostationary air quality sensors over a range of pollution environments.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Development of High-Resolution Dynamic Dust Source Function - A Case Study with a Strong Dust Storm in a Regional Model

NASA Technical Reports Server (NTRS)

Kim, Dongchul; Chin, Mian; Kemp, Eric M.; Tao, Zhining; Peters-Lidard, Christa D.; Ginoux, Paul

2017-01-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model

PubMed Central

Kim, Dongchul; Chin, Mian; Kemp, Eric M.; Tao, Zhining; Peters-Lidard, Christa D.; Ginoux, Paul

2018-01-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events. PMID:29632432

Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model.

PubMed

Kim, Dongchul; Chin, Mian; Kemp, Eric M; Tao, Zhining; Peters-Lidard, Christa D; Ginoux, Paul

2017-06-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

From individual spiking neurons to population behavior: Systematic elimination of short-wavelength spatial modes

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.

2016-02-01

Mean-field models of the brain approximate spiking dynamics by assuming that each neuron responds to its neighbors via a naive spatial average that neglects local fluctuations and correlations in firing activity. In this paper we address this issue by introducing a rigorous formalism to enable spatial coarse-graining of spiking dynamics, scaling from the microscopic level of a single type 1 (integrator) neuron to a macroscopic assembly of spiking neurons that are interconnected by chemical synapses and nearest-neighbor gap junctions. Spiking behavior at the single-neuron scale ℓ ≈10 μ m is described by Wilson's two-variable conductance-based equations [H. R. Wilson, J. Theor. Biol. 200, 375 (1999), 10.1006/jtbi.1999.1002], driven by fields of incoming neural activity from neighboring neurons. We map these equations to a coarser spatial resolution of grid length B ℓ , with B ≫1 being the blocking ratio linking micro and macro scales. Our method systematically eliminates high-frequency (short-wavelength) spatial modes q ⃗ in favor of low-frequency spatial modes Q ⃗ using an adiabatic elimination procedure that has been shown to be equivalent to the path-integral coarse graining applied to renormalization group theory of critical phenomena. This bottom-up neural regridding allows us to track the percolation of synaptic and ion-channel noise from the single neuron up to the scale of macroscopic population-average variables. Anticipated applications of neural regridding include extraction of the current-to-firing-rate transfer function, investigation of fluctuation criticality near phase-transition tipping points, determination of spatial scaling laws for avalanche events, and prediction of the spatial extent of self-organized macrocolumnar structures. As a first-order exemplar of the method, we recover nonlinear corrections for a coarse-grained Wilson spiking neuron embedded in a network of identical diffusively coupled neurons whose chemical synapses have been disabled. Intriguingly, we find that reblocking transforms the original type 1 Wilson integrator into a type 2 resonator whose spike-rate transfer function exhibits abrupt spiking onset with near-vertical takeoff and chaotic dynamics just above threshold.

Identifying, characterizing and predicting spatial patterns of lacustrine groundwater discharge

NASA Astrophysics Data System (ADS)

Tecklenburg, Christina; Blume, Theresa

2017-10-01

Lacustrine groundwater discharge (LGD) can significantly affect lake water balances and lake water quality. However, quantifying LGD and its spatial patterns is challenging because of the large spatial extent of the aquifer-lake interface and pronounced spatial variability. This is the first experimental study to specifically study these larger-scale patterns with sufficient spatial resolution to systematically investigate how landscape and local characteristics affect the spatial variability in LGD. We measured vertical temperature profiles around a 0.49 km2 lake in northeastern Germany with a needle thermistor, which has the advantage of allowing for rapid (manual) measurements and thus, when used in a survey, high spatial coverage and resolution. Groundwater inflow rates were then estimated using the heat transport equation. These near-shore temperature profiles were complemented with sediment temperature measurements with a fibre-optic cable along six transects from shoreline to shoreline and radon measurements of lake water samples to qualitatively identify LGD patterns in the offshore part of the lake. As the hydrogeology of the catchment is sufficiently homogeneous (sandy sediments of a glacial outwash plain; no bedrock control) to avoid patterns being dominated by geological discontinuities, we were able to test the common assumptions that spatial patterns of LGD are mainly controlled by sediment characteristics and the groundwater flow field. We also tested the assumption that topographic gradients can be used as a proxy for gradients of the groundwater flow field. Thanks to the extensive data set, these tests could be carried out in a nested design, considering both small- and large-scale variability in LGD. We found that LGD was concentrated in the near-shore area, but alongshore variability was high, with specific regions of higher rates and higher spatial variability. Median inflow rates were 44 L m-2 d-1 with maximum rates in certain locations going up to 169 L m-2 d-1. Offshore LGD was negligible except for two local hotspots on steep steps in the lake bed topography. Large-scale groundwater inflow patterns were correlated with topography and the groundwater flow field, whereas small-scale patterns correlated with grain size distributions of the lake sediment. These findings confirm results and assumptions of theoretical and modelling studies more systematically than was previously possible with coarser sampling designs. However, we also found that a significant fraction of the variance in LGD could not be explained by these controls alone and that additional processes need to be considered. While regression models using these controls as explanatory variables had limited power to predict LGD rates, the results nevertheless encourage the use of topographic indices and sediment heterogeneity as an aid for targeted campaigns in future studies of groundwater discharge to lakes.

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

PubMed Central

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Román, Miguel O.

2018-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems. PMID:29769751

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data.

PubMed

Wang, Zhuosen; Erb, Angela M; Schaaf, Crystal B; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A; Román, Miguel O

2016-11-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion (Short Term Innovative Research Program)

DTIC Science & Technology

2018-02-15

conservation equations. The closure problem hinges on the evaluation of the filtered chemical production rates. In MRA/MSR, simultaneous large-eddy...simulations of a reactive flow are performed at different mesh resolution levels. The solutions at each coarser mesh level are constrained by the filtered ...include the replacement of chemical production rates with those filtered from the underlying fine mesh and the construction of ‘exact’ forms for

Comparison and validation of gridded precipitation datasets for Spain

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Míguez-Macho, Gonzalo

2016-04-01

In this study, two gridded precipitation datasets are compared and validated in Spain: the recently developed SAFRAN dataset and the Spain02 dataset. These are validated using rain gauges and they are also compared to the low resolution ERA-Interim reanalysis. The SAFRAN precipitation dataset has been recently produced, using the SAFRAN meteorological analysis, which is extensively used in France (Durand et al. 1993, 1999; Quintana-Seguí et al. 2008; Vidal et al., 2010) and which has recently been applied to Spain (Quintana-Seguí et al., 2015). SAFRAN uses an optimal interpolation (OI) algorithm and uses all available rain gauges from the Spanish State Meteorological Agency (Agencia Estatal de Meteorología, AEMET). The product has a spatial resolution of 5 km and it spans from September 1979 to August 2014. This dataset has been produced mainly to be used in large scale hydrological applications. Spain02 (Herrera et al. 2012, 2015) is another high quality precipitation dataset for Spain based on a dense network of quality-controlled stations and it has different versions at different resolutions. In this study we used the version with a resolution of 0.11°. The product spans from 1971 to 2010. Spain02 is well tested and widely used, mainly, but not exclusively, for RCM model validation and statistical downscliang. ERA-Interim is a well known global reanalysis with a spatial resolution of ˜79 km. It has been included in the comparison because it is a widely used product for continental and global scale studies and also in smaller scale studies in data poor countries. Thus, its comparison with higher resolution products of a data rich country, such as Spain, allows us to quantify the errors made when using such datasets for national scale studies, in line with some of the objectives of the EU-FP7 eartH2Observe project. The comparison shows that SAFRAN and Spain02 perform similarly, even though their underlying principles are different. Both products are largely better than ERA-Interim, which has a much coarser representation of the relief, which is crucial for precipitation. These results are a contribution to the Spanish Case Study of the eartH2Observe project, which is focused on the simulation of drought processes in Spain using Land-Surface Models (LSM). This study will also be helpful in the Spanish MARCO project, which aims at improving the ability of RCMs to simulate hydrometeorological extremes.

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

NASA Astrophysics Data System (ADS)

Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.

2018-01-01

Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.

Finding the best resolution for the Kingman-Tajima coalescent: theory and applications.

PubMed

Sainudiin, Raazesh; Stadler, Tanja; Véber, Amandine

2015-05-01

Many summary statistics currently used in population genetics and in phylogenetics depend only on a rather coarse resolution of the underlying tree (the number of extant lineages, for example). Hence, for computational purposes, working directly on these resolutions appears to be much more efficient. However, this approach seems to have been overlooked in the past. In this paper, we describe six different resolutions of the Kingman-Tajima coalescent together with the corresponding Markov chains, which are essential for inference methods. Two of the resolutions are the well-known n-coalescent and the lineage death process due to Kingman. Two other resolutions were mentioned by Kingman and Tajima, but never explicitly formalized. Another two resolutions are novel, and complete the picture of a multi-resolution coalescent. For all of them, we provide the forward and backward transition probabilities, the probability of visiting a given state as well as the probability of a given realization of the full Markov chain. We also provide a description of the state-space that highlights the computational gain obtained by working with lower-resolution objects. Finally, we give several examples of summary statistics that depend on a coarser resolution of Kingman's coalescent, on which simulations are usually based.

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2017-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2016-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

PubMed

Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

Forecast of drifter trajectories using a Rapid Environmental Assessment based on CTD observations

NASA Astrophysics Data System (ADS)

Sorgente, R.; Tedesco, C.; Pessini, F.; De Dominicis, M.; Gerin, R.; Olita, A.; Fazioli, L.; Di Maio, A.; Ribotti, A.

2016-11-01

A high resolution submesoscale resolving ocean model was implemented in a limited area north of Island of Elba where a maritime exercise, named Serious Game 1 (SG1), took place on May 2014 in the framework of the project MEDESS-4MS (Mediterranean Decision Support System for Marine Safety). During the exercise, CTD data have been collected responding to the necessity of a Rapid Environmental Assessment, i.e. to a rapid evaluation of the marine conditions able to provide sensible information for initialisation of modelling tools, in the scenario of possible maritime accidents. The aim of this paper is to evaluate the impact of such mesoscale-resolving CTD observations on short-term forecasts of the surface currents, within the framework of possible oil-spill related emergencies. For this reason, modelling outputs were compared with Lagrangian observations at sea: the high resolution modelled currents, together with the ones of the coarser sub-regional model WMED, are used to force the MEDSLIK-II oil-spill model to simulate drifter trajectories. Both ocean models have been assessed by comparing the prognostic scalar and vector fields as an independent CTD data set and with real drifter trajectories acquired during SG1. The diagnosed and prognosed circulation reveals that the area was characterised by water masses of Atlantic origin influenced by small mesoscale cyclonic and anti-cyclonic eddies, which govern the spatial and temporal evolution of the drifter trajectories and of the water masses distribution. The assimilation of CTD data into the initial conditions of the high resolution model highly improves the accuracy of the short-term forecast in terms of location and structure of the thermocline and positively influence the ability of the model in reproducing the observed paths of the surface drifters.

High-resolution modelling of atmospheric dispersion of dense gas using TWODEE-2.1: application to the 1986 Lake Nyos limnic eruption

NASA Astrophysics Data System (ADS)

Folch, Arnau; Barcons, Jordi; Kozono, Tomofumi; Costa, Antonio

2017-06-01

Atmospheric dispersal of a gas denser than air can threat the environment and surrounding communities if the terrain and meteorological conditions favour its accumulation in topographic depressions, thereby reaching toxic concentration levels. Numerical modelling of atmospheric gas dispersion constitutes a useful tool for gas hazard assessment studies, essential for planning risk mitigation actions. In complex terrains, microscale winds and local orographic features can have a strong influence on the gas cloud behaviour, potentially leading to inaccurate results if not captured by coarser-scale modelling. We introduce a methodology for microscale wind field characterisation based on transfer functions that couple a mesoscale numerical weather prediction model with a microscale computational fluid dynamics (CFD) model for the atmospheric boundary layer. The resulting time-dependent high-resolution microscale wind field is used as input for a shallow-layer gas dispersal model (TWODEE-2.1) to simulate the time evolution of CO2 gas concentration at different heights above the terrain. The strategy is applied to review simulations of the 1986 Lake Nyos event in Cameroon, where a huge CO2 cloud released by a limnic eruption spread downslopes from the lake, suffocating thousands of people and animals across the Nyos and adjacent secondary valleys. Besides several new features introduced in the new version of the gas dispersal code (TWODEE-2.1), we have also implemented a novel impact criterion based on the percentage of human fatalities depending on CO2 concentration and exposure time. New model results are quantitatively validated using the reported percentage of fatalities at several locations. The comparison with previous simulations that assumed coarser-scale steady winds and topography illustrates the importance of high-resolution modelling in complex terrains.

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data

NASA Astrophysics Data System (ADS)

Robinson, Emma L.; Blyth, Eleanor M.; Clark, Douglas B.; Finch, Jon; Rudd, Alison C.

2017-02-01

Observations of climate are often available on very different spatial scales from observations of the natural environments and resources that are affected by climate change. In order to help bridge the gap between these scales using modelling, a new dataset of daily meteorological variables was created at 1 km resolution over Great Britain for the years 1961-2012, by interpolating coarser resolution climate data and including the effects of local topography. These variables were used to calculate atmospheric evaporative demand (AED) at the same spatial and temporal resolution. Two functions that represent AED were chosen: one is a standard form of potential evapotranspiration (PET) and the other is a derived PET measure used by hydrologists that includes the effect of water intercepted by the canopy (PETI). Temporal trends in these functions were calculated, with PET found to be increasing in all regions, and at an overall rate of 0.021 ± 0.021 mm day-1 decade-1 in Great Britain. PETI was found to be increasing at a rate of 0.019 ± 0.020 mm day-1 decade-1 in Great Britain, but this was not statistically significant. However, there was a trend in PETI in England of 0.023 ± 0.023 mm day-1 decade-1. The trends were found to vary by season, with spring PET increasing by 0.043 ± 0.019 mm day-1 decade-1 (0.038 ± 0.018 mm day-1 decade-1 when the interception correction is included) in Great Britain, while there is no statistically significant trend in other seasons. The trends were attributed analytically to trends in the climate variables; the overall positive trend was predominantly driven by rising air temperature, although rising specific humidity had a negative effect on the trend. Recasting the analysis in terms of relative humidity revealed that the overall effect is that falling relative humidity causes the PET to rise. Increasing downward short- and longwave radiation made an overall positive contribution to the PET trend, while decreasing wind speed made a negative contribution to the trend in PET. The trend in spring PET was particularly strong due to a strong decrease in relative humidity and increase in downward shortwave radiation in the spring.

Formal Solutions for Polarized Radiative Transfer. II. High-order Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janett, Gioele; Steiner, Oskar; Belluzzi, Luca, E-mail: gioele.janett@irsol.ch

When integrating the radiative transfer equation for polarized light, the necessity of high-order numerical methods is well known. In fact, well-performing high-order formal solvers enable higher accuracy and the use of coarser spatial grids. Aiming to provide a clear comparison between formal solvers, this work presents different high-order numerical schemes and applies the systematic analysis proposed by Janett et al., emphasizing their advantages and drawbacks in terms of order of accuracy, stability, and computational cost.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Environmental drivers of epibenthic megafauna on a deep temperate continental shelf: A multiscale approach

NASA Astrophysics Data System (ADS)

Lacharité, Myriam; Metaxas, Anna

2018-03-01

Evaluating the role of abiotic factors in influencing the distribution of deep-water (>75-100 m depth) epibenthic megafaunal communities at mid-to-high latitudes is needed to estimate effects of environmental change, and support marine spatial planning since these factors can be effectively mapped. Given the disparity in scales at which these factors operate, incorporating multiple spatial and temporal scales is necessary. In this study, we determined the relative importance of 3 groups of environmental drivers at different scales (sediment, geomorphology, and oceanography) on epibenthic megafauna on a deep temperate continental shelf in the eastern Gulf of Maine (northwest Atlantic). Twenty benthic photographic transects (range: 611-1021 m; total length surveyed: 18,902 m; 996 images; average of 50 ± 16 images per transect) were performed in July and August 2009 to assess the abundance, composition and diversity of these communities. Surficial geology was assessed using seafloor imagery processed with a novel approach based on computer vision. A bathymetric terrain model (horizontal resolution: 100 m) was used to derive bathymetric variability in the vicinity of transects (1.5, 5 km). Oceanography at the seafloor (temperature, salinity, current speed, current direction) over 10 years (1999-2008) was determined using empirical (World Ocean Database 2013) and modelled data (Finite-Volume Community Ocean Model; 45 vertical layers; horizontal resolution: 1.7-9.5 km). The relative influence of environmental drivers differed between community traits. Abundance was enhanced primarily by swift current speeds, while higher diversity was observed in coarser and more heterogeneous substrates. In both cases, the role of geomorphological features was secondary to these drivers. Environmental variables were poor predictors of change in community composition at the scale of the eastern Gulf of Maine. This study demonstrated the need for explicitly incorporating scales into habitat modelling studies in these regions, and targeting specific drivers for community traits of interest.

Assessing biomass of diverse coastal marsh ecosystems using statistical and machine learning models

NASA Astrophysics Data System (ADS)

Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis; Zhao, Feng; Tilley, David R.

2018-06-01

The importance and vulnerability of coastal marshes necessitate effective ways to closely monitor them. Optical remote sensing is a powerful tool for this task, yet its application to diverse coastal marsh ecosystems consisting of different marsh types is limited. This study samples spectral and biophysical data from freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops statistical and machine learning models to assess the marshes' biomass with combined ground, airborne, and spaceborne remote sensing data. It is found that linear models derived from NDVI and EVI are most favorable for assessing Leaf Area Index (LAI) using multispectral data (R2 = 0.7 and 0.67, respectively), and the random forest models are most useful in retrieving LAI and Aboveground Green Biomass (AGB) using hyperspectral data (R2 = 0.91 and 0.84, respectively). It is also found that marsh type and plant species significantly impact the linear model development (P < .05 in both cases). Sensors with coarser spatial resolution yield lower LAI values because the fine water networks are not detected and mixed into the vegetation pixels. The Landsat OLI-derived map shows the LAI of coastal mashes in Louisiana mostly ranges from 0 to 5.0, and is highest for freshwater marshes and for marshes in the Atchafalaya Bay delta. The CASI-derived maps show that LAI of saline marshes at Bay Batiste typically ranges from 0.9 to 1.5, and the AGB is mostly less than 900 g/m2. This study provides solutions for assessing the biomass of Louisiana's coastal marshes using various optical remote sensing techniques, and highlights the impacts of the marshes' species composition on the model development and the sensors' spatial resolution on biomass mapping, thereby providing useful tools for monitoring the biomass of coastal marshes in Louisiana and diverse coastal marsh ecosystems elsewhere.

Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Angler effort and catch within a spatially complex system of small lakes.

USGS Publications Warehouse

Pope, Kevin L.; Chizinski, Christopher J.; Martin, Dustin R.; Barada, Tony J.; Schuckman, Jeffrey J.

2014-01-01

Spatial layout of waterbodies and waterbody size can affect a creel clerk’s ability to intercept anglers for interviews and to accurately count anglers, which will affect the accuracy and precision of estimates of effort and catch. This study aimed to quantify angling effort and catch across a spatially complex system of 19 small (<100 ha) lakes, the Fremont lakes. Total (±SE) angling effort (hours) on individual lakes ranged from 0 (0) to 7,137 (305). Bank anglers utilized 18 of the 19 lakes, and their mean (±SE) trip lengths (hours) ranged from 0.80 (0.31) to 7.75 (6.75), depending on the waterbody. In contrast, boat anglers utilized 14 of the 19 lakes, and their trip lengths ranged from 1.39 (0.24) to 4.25 (0.71), depending on the waterbody. The most sought fishes, as indexed by number of lakes on which effort was exerted, were anything (17 of 19 lakes), largemouth bassMicropterus salmoides (15 of 19 lakes), and channel catfish Ictalurus punctatus (13 of 19 lakes). Bluegill Lepomis machrochirus, crappie Pomoxis spp., and largemouth bass were caught most frequently across the lakes, but catch rates varied considerably by lake. Of the 1,138 parties interviewed, most parties (93%) visited a single lake but there were 77 (7%) parties that indicated that they had visited multiple lakes during a single day. The contingent of parties that visited more than one lake a day were primarily (87%) bank anglers.. The number of lake-to-lake connections made by anglers visiting more than one waterbody during a single day was related to catch rates and total angling effort. The greater resolution that was achieved with a lake specific creel survey at Fremont lakes revealed a system of lakes with a large degree of spatial variation in angler effort and catch that would be missed by a coarser, system-wide survey that did not differentiate individual lakes.

Influence of permeability on nanoscale zero-valent iron particle transport in saturated homogeneous and heterogeneous porous media.

PubMed

Strutz, Tessa J; Hornbruch, Götz; Dahmke, Andreas; Köber, Ralf

2016-09-01

Nanoscale zero-valent iron (NZVI) particles can be used for in situ groundwater remediation. The spatial particle distribution plays a very important role in successful and efficient remediation, especially in heterogeneous systems. Initial sand permeability (k 0) influences on spatial particle distributions were investigated and quantified in homogeneous and heterogeneous systems within the presented study. Four homogeneously filled column experiments and a heterogeneously filled tank experiment, using different median sand grain diameters (d 50), were performed to determine if NZVI particles were transported into finer sand where contaminants could be trapped. More NZVI particle retention, less particle transport, and faster decrease in k were observed in the column studies using finer sands than in those using coarser sands, reflecting a function of k 0. In heterogeneous media, NZVI particles were initially transported and deposited in coarse sand areas. Increasing the retained NZVI mass (decreasing k in particle deposition areas) caused NZVI particles to also be transported into finer sand areas, forming an area with a relatively homogeneous particle distribution and converged k values despite the different grain sizes present. The deposited-particle surface area contribution to the increasing of the matrix surface area (θ) was one to two orders of magnitude higher for finer than coarser sand. The dependency of θ on d 50 presumably affects simulated k changes and NZVI distributions in numerical simulations of NZVI injections into heterogeneous aquifers. The results implied that NZVI can in principle also penetrate finer layers.

Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery. [Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.

1982-01-01

Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.

Impact of surface coupling grids on tropical cyclone extremes in high-resolution atmospheric simulations

DOE PAGES

Zarzycki, Colin M.; Reed, Kevin A.; Bacmeister, Julio T.; ...

2016-02-25

This article discusses the sensitivity of tropical cyclone climatology to surface coupling strategy in high-resolution configurations of the Community Earth System Model. Using two supported model setups, we demonstrate that the choice of grid on which the lowest model level wind stress and surface fluxes are computed may lead to differences in cyclone strength in multi-decadal climate simulations, particularly for the most intense cyclones. Using a deterministic framework, we show that when these surface quantities are calculated on an ocean grid that is coarser than the atmosphere, the computed frictional stress is misaligned with wind vectors in individual atmospheric gridmore » cells. This reduces the effective surface drag, and results in more intense cyclones when compared to a model configuration where the ocean and atmosphere are of equivalent resolution. Our results demonstrate that the choice of computation grid for atmosphere–ocean interactions is non-negligible when considering climate extremes at high horizontal resolution, especially when model components are on highly disparate grids.« less

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Star formation in M 33: the radial and local relations with the gas

NASA Astrophysics Data System (ADS)

Verley, S.; Corbelli, E.; Giovanardi, C.; Hunt, L. K.

2010-02-01

Aims: In the Local Group spiral galaxy M 33, we investigate the correlation between the star formation rate (SFR) surface density, Σ_SFR, and the gas density Σ_gas (molecular, atomic, and total). We also explore whether there are other physical quantities, such as the hydrostatic pressure and dust optical depth, which establish a good correlation with Σ_SFR. Methods: We use the Hα, far-ultraviolet (FUV), and bolometric emission maps to infer the SFR locally at different spatial scales, and in radial bins using azimuthally averaged values. Most of the local analysis is done using the highest spatial resolution allowed by gas surveys, 180 pc. The Kennicutt-Schmidt (KS) law, Σ_SFR ∝ Σ_gas^n is analyzed by three statistical methods. Results: At all spatial scales, with Hα emission as a SFR tracer, the KS indices n are always steeper than those derived with the FUV and bolometric emissions. We attribute this to the lack of Hα emission in low luminosity regions where most stars form in small clusters with an incomplete initial mass function at their high mass end. For azimuthally averaged values the depletion timescale for the molecular gas is constant, and the KS index is n_H_2=1.1 ±0.1. Locally, at a spatial resolution of 180 pc, the correlation between Σ_SFR and Σ_gas is generally poor, even though it is tighter with the molecular and total gas than with the atomic gas alone. Considering only positions where the CO J=1-0 line is above the 2-σ detection threshold and taking into account uncertainties in Σ_H_2 and Σ_SFR, we obtain a steeper KS index than obtained with radial averages: n_H_2=2.22 ±0.07 (for FUV and bolometric SFR tracers), flatter than that relative to the total gas (n_Htot=2.59 ±0.05). The gas depletion timescale is therefore larger in regions of lower Σ_SFR. Lower KS indices (n_H_2=1.46 ±0.34 and n_H_2=1.12) are found using different fitting techniques, which do not account for individual position uncertainties. At coarser spatial resolutions these indices get slightly steeper, and the correlation improves. We find an almost linear relation and a better correlation coefficient between the local Σ_SFR and the ISM hydrostatic pressure or the gas volume density. This suggests that the stellar disk, gravitationally dominant with respect to the gaseous disk in M 33, has a non-marginal role in driving the SFR. However, the tight local correlation that exists between the dust optical depth and the SFR sheds light on the alternative hypothesis that the dust column density is a good tracer of the gas that is prone to star formation.

Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations.

NASA Astrophysics Data System (ADS)

López López, Patricia; Wanders, Niko; Sutanudjaja, Edwin; Renzullo, Luigi; Sterk, Geert; Schellekens, Jaap; Bierkens, Marc

2015-04-01

The coarse spatial resolution of global hydrological models (typically > 0.25o) often limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tunes river models. A possible solution to the problem may be to drive the coarse resolution models with high-resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the modelling resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigated the impact that assimilating streamflow and satellite soil moisture observations have on global hydrological model estimation, driven by coarse- and high-resolution meteorological observations, for the Murrumbidgee river basin in Australia. The PCR-GLOBWB global hydrological model is forced with downscaled global climatological data (from 0.5o downscaled to 0.1o resolution) obtained from the WATCH Forcing Data (WFDEI) and local high resolution gauging station based gridded datasets (0.05o), sourced from the Australian Bureau of Meteorology. Downscaled satellite derived soil moisture (from 0.5o downscaled to 0.1o resolution) from AMSR-E and streamflow observations collected from 25 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global climatological data. Results show that the assimilation of streamflow observations result in the largest improvement of the model estimates. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improved in streamflow simulations (10% reduction in RMSE), mainly in the headwater catchments (up to 10,000 km2). Results also show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. This study demonstrates that it is possible to improve hydrological simulations forced by coarse resolution meteorological data with downscaled satellite soil moisture and streamflow observations and bring them closer to a hydrological model forced with local climatological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can significantly help to advance this research.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Integrated Blowoff and Breakup Calculations for Asteroid Deflection by Nuclear Ablation

NASA Astrophysics Data System (ADS)

Bruck Syal, M.; Owen, M.; Dearborn, D. S.; Miller, P. L.

2016-12-01

When the warning timing is short, hazardous asteroids or comets can only be deflected off of an Earth-impacting trajectory by a nuclear device [1]. Here we model asteroid response to a standoff nuclear explosion, a problem which requires sub-millimeter spatial resolution at the body's surface to fully capture x-ray energy deposition. The first stage of the calculation focuses on modeling blowoff momentum from vaporized material, using a problem domain confined to the uppermost surface of the asteroid. Once the blowoff momentum transfer process is complete, the problem is remapped into a coarser resolution and the remainder of the asteroid body is added to the calculation, so that asteroid response can be tracked over longer timescales. This two-stage approach enables an integrated assessment of both the efficacy of momentum delivery and damage incurred by the bulk of the asteroid. Investigating the degree of post-ablation fracture, fragmentation, and fragment dispersion is necessary for modeling the outcomes of cases intended to fully fragment and disperse the body (disruption), as well as cases where the bulk of the asteroid should remain intact (deflection). We begin with 500-m spherical asteroids but also extend our analysis to radar-derived asteroid shape models. [1] Dearborn, D.S.P., Miller, P.L., 2014. Deflecting or Disrupting a Threatening Object, in: Pelton, J.N., Allahdadi, F. (Eds.), Handbook of Cosmic Hazards and Planetary Defense, Springer. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52- 07NA27344. LLNL-ABS-699631.

Landsat-based Earth Observations and Crowd-sourced Data Provide Near Real-time Monitoring of Chimpanzee Habitat

NASA Astrophysics Data System (ADS)

Nackoney, J.; Pintea, L.; Jantz, S.; Hansen, M.

2015-12-01

The endangered chimpanzee (Pan troglodytes) is threatened by habitat loss from resource extraction and land conversion, as well as hunting, disease and the illegal pet trade. It has been estimated that more than 70% of chimpanzee's tropical forest habitats in Africa are now threatened by land use change. Recent developments in remote sensing and cloud computing enable the use of satellite observations to provide a synoptic view of chimpanzee habitats at finer spatial and temporal resolutions that are locally relevant and consistent across the entire species' range. We present a practical Decision Support System to be used by the Jane Goodall Institute and partners to annually monitor and forecast chimpanzee habitat health in Africa. The system integrates Earth observations from 30-meter resolution Landsat data with a species-specific habitat model and a model forecasting future land use change, enhanced by crowd-sourced field data collected by local communities and rangers using the Open Data Kit app and Android mobile smartphones and tablets. While coarser-scale and static chimpanzee habitat models have been previously developed, this project is the first to develop a dynamic monitoring system updated annually via Earth observations data that will systematically monitor threats and changes in habitat over time. Since the chimpanzee is an important keystone, flagship and umbrella species, an annual chimpanzee habitat health index would support conservation goals of other species within its large 2.5 million sq. km range and could be an important indicator of overall ecosystem health of tropical forests in Africa.

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

NASA Astrophysics Data System (ADS)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

Grid Sensitivity Study for Slat Noise Simulations

NASA Technical Reports Server (NTRS)

Lockard, David P.; Choudhari, Meelan M.; Buning, Pieter G.

2014-01-01

The slat noise from the 30P/30N high-lift system is being investigated through computational fluid dynamics simulations in conjunction with a Ffowcs Williams-Hawkings acoustics solver. Many previous simulations have been performed for the configuration, and the case was introduced as a new category for the Second AIAA workshop on Benchmark problems for Airframe Noise Configurations (BANC-II). However, the cost of the simulations has restricted the study of grid resolution effects to a baseline grid and coarser meshes. In the present study, two different approaches are being used to investigate the effect of finer resolution of near-field unsteady structures. First, a standard grid refinement by a factor of two is used, and the calculations are performed by using the same CFL3D solver employed in the majority of the previous simulations. Second, the OVERFLOW code is applied to the baseline grid, but with a 5th-order upwind spatial discretization as compared with the second-order discretization used in the CFL3D simulations. In general, the fine grid CFL3D simulation and OVERFLOW calculation are in very good agreement and exhibit the lowest levels of both surface pressure fluctuations and radiated noise. Although the smaller scales resolved by these simulations increase the velocity fluctuation levels, they appear to mitigate the influence of the larger scales on the surface pressure. These new simulations are used to investigate the influence of the grid on unsteady high-lift simulations and to gain a better understanding of the physics responsible for the noise generation and radiation.

Landscape influences on climate-related lake shrinkage at high latitudes

USGS Publications Warehouse

Roach, Jennifer K.; Griffith, Brad; Verbyla, David

2013-01-01

Climate-related declines in lake area have been identified across circumpolar regions and have been characterized by substantial spatial heterogeneity. An improved understanding of the mechanisms underlying lake area trends is necessary to predict where change is most likely to occur and to identify implications for high latitude reservoirs of carbon. Here, using a population of ca. 2300 lakes with statistically significant increasing and decreasing lake area trends spanning longitudinal and latitudinal gradients of ca. 1000 km in Alaska, we present evidence for a mechanism of lake area decline that involves the loss of surface water to groundwater systems. We show that lakes with significant declines in lake area were more likely to be located: (1) in burned areas; (2) on coarser, well-drained soils; and (3) farther from rivers compared to lakes that were increasing. These results indicate that postfire processes such as permafrost degradation, which also results from a warming climate, may promote lake drainage, particularly in coarse-textured soils and farther from rivers where overland flooding is less likely and downslope flow paths and negative hydraulic gradients between surface water and groundwater systems are more common. Movement of surface water to groundwater systems may lead to a deepening of subsurface flow paths and longer hydraulic residence time which has been linked to increased soil respiration and CO2 release to the atmosphere. By quantifying relationships between statewide coarse resolution maps of landscape characteristics and spatially heterogeneous responses of lakes to environmental change, we provide a means to identify at-risk lakes and landscapes and plan for a changing climate.

Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for different altitudes and land cover in this remote area with significant hazards from snow melt and glacier discharge. The improved spatial resolution, enhanced to 3-6 km, and retaining twice daily observations is a key improvement to fully analyze snowpack melt characteristics in remote mountainous regions.

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

Smoking-related emphysema is associated with idiopathic pulmonary fibrosis and rheumatoid lung.

PubMed

Antoniou, Katerina M; Walsh, Simon L; Hansell, David M; Rubens, Michael R; Marten, Katharina; Tennant, Rachel; Hansel, Trevor; Desai, Sujal R; Siafakas, Nikolaos M; du Bois, Roland M; Wells, Athol U

2013-11-01

A combined pulmonary fibrosis/emphysema syndrome has been proposed, but the basis for this syndrome is currently uncertain. The aim was to evaluate the prevalence of emphysema in idiopathic pulmonary fibrosis (IPF) and rheumatoid lung (rheumatoid arthritis-interstitial lung disease (RA-ILD)), and to compare the morphological features of lung fibrosis between smokers and non-smokers. Using high-resolution computed tomography, the prevalence of emphysema and the pack-year smoking histories associated with emphysema were compared between current/ex-smokers with IPF (n = 186) or RA-ILD (n = 46), and non-chronic obstructive pulmonary disease (COPD) controls (n = 103) and COPD controls (n = 34). The coarseness of fibrosis was compared between smokers and non-smokers. Emphysema, present in 66/186 (35%) patients with IPF and 22/46 (48%) smokers with RA-ILD, was associated with lower pack-year smoking histories than in control groups (P < 0.05 for all comparisons). The presence of emphysema in IPF was positively linked to the pack-year smoking history (odds ratio 1.04, 95% confidence interval (CI) 1.02-1.06, P < 0.0005). In IPF, fibrosis was coarser in smokers than in non-smokers on univariate and multivariate analysis (P < 0.01 for all comparisons). In RA-ILD, fibrosis was coarser in patients with emphysema but did not differ significantly between smokers and non-smokers. In IPF and RA-ILD, a high prevalence of concurrent emphysema, in association with low pack-year smoking histories, and an association between coarser pulmonary fibrosis and a history of smoking in IPF together provide support for possible pathogenetic linkage to smoking in both diseases. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Integrating expert- and algorithm-derived data to generate a hemispheric ice edge

NASA Astrophysics Data System (ADS)

Tsatsoulis, C.; Komp, E.

The Arctic ice edge is the area of the Arctic where sea ice concentration is less than 15%, and is considered navigable by most vessels. Experts at the National Ice Center generate a daily ice edge product that is available to the public. Data of preference is that of active, high resolution satellite sensors such as RADARSAT which yields all-weather images of 100m resolution, and a second source is OLS data with 550m resolution. Unfortunately, RADARSAT does not provide full, daily coverage of the Arctic and OLS can be obscured by clouds. The SSM/I sensor provides complete coverage of the Arctic at 25km resolution and is independent of cloud cover and solar illumination during the Arctic winter. SSM/I data is analyzed by the NASA Team algorithm to establish ice concentration. Our work integrates the ice edge created by experts using high resolution data with the ice edge generated out of the coarser SSM/I microwave data. The result is a product that combines human and algorithmic outputs, deals with gross differences in resolution of the underlying data sets, and results in a useful, operational product.

Near-infrared spectral mapping of Titan's mountains and channels

USGS Publications Warehouse

Barnes, J.W.; Radebaugh, J.; Brown, R.H.; Wall, S.; Soderblom, L.; Lunine, J.; Burr, D.; Sotin, Christophe; Le, Mouelic S.; Rodriguez, S.; Buratti, B.J.; Clark, R.; Baines, K.H.; Jaumann, R.; Nicholson, P.D.; Kirk, R.L.; Lopes, R.; Lorenz, R.D.; Mitchell, Ken; Wood, C.A.

2007-01-01

We investigate the spectral reflectance properties of channels and mountain ranges on Titan using data from Cassini's Visual and Infrared Mapping Spectrometer (VIMS) obtained during the T9 encounter (26 December 2005). We identify the location of channels and mountains using synthetic aperture radar maps obtained from Cassini's RADAR instrument during the T13 (30 April 2006) flyby. Channels are evident even in VIMS imaging with spatial resolution coarser than the channel size. The channels share spectral characteristics with Titan's dark blue terrain (e.g., the Huygens landing site) that is consistent with an enhancement in water ice content relative to the rest of Titan. We use this fact to measure widths of ???1 km for the largest channels. Comparison of the data sets shows that in our study area within the equatorial bright spectral unit east of Xanadu, mountains are darker and bluer than surrounding smooth terrain. These results are consistent with the equatorial bright terrain possessing a veneer of material that is thinner in the regions where there are mountains and streambeds that have likely undergone more recent and extensive erosion. We suggest a model for the geographic relationship of the dark blue, dark brown, and equatorial bright spectral units based on our findings. Copyright 2007 by the American Geophysical Union.

Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

NASA Astrophysics Data System (ADS)

Pan, Xin; Cao, Chen; Yang, Yingbao; Li, Xiaolong; Shan, Liangliang; Zhu, Xi

2018-04-01

The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of +/-0.02 predictor perturbances, respectively.

Differences in soluble organic carbon chemistry in pore waters sampled from different pore size domains

DOE PAGES

Bailey, Vanessa L.; Smith, A. P.; Tfaily, Malak; ...

2017-01-11

Spatial isolation of soil organic carbon (SOC) in different sized pores may be a mechanism by which otherwise labile carbon (C) could be protected in soils. When soil water content increases, the hydrologic connectivity of soil pores also increases, allowing greater transport of SOC and other resources from protected locations, to microbially colonized locations more favorable to decomposition. The heterogeneous distribution of specialized decomposers, C, and other resources throughout the soil indicates that the metabolism or persistence of soil C compounds is highly dependent on short-distance transport processes. The objective of this research was to characterize the complexity of Cmore » in pore waters held at weak and strong water tensions (effectively soil solution held behind coarse- and fine-pore throats, respectively) and evaluate the microbial decomposability of these pore waters. We saturated intact soil cores and extracted pore waters with increasing suction pressures to sequentially sample pore waters from increasingly fine pore domains. Ultrahigh resolution mass spectrometry of the SOC was used to profile the major biochemical classes (i.e., lipids, proteins, lignin, carbohydrates, and condensed aromatics) of compounds present in the pore waters; some of these samples were then used as substrates for growth of Cellvibrio japonicus (DSMZ 16018), Streptomyces cellulosae (ATCC ® 25439™), and Trichoderma reseei (QM6a) in 7 day incubations. The soluble C in finer pores was more complex than the soluble C in coarser pores, and the incubations revealed that the more complex C in these fine pores is not recalcitrant. The decomposition of this complex C led to greater losses of C through respiration than the simpler C from coarser pore waters. Our research suggests that soils that experience repeated cycles of drying and wetting may be accompanied by repeated cycles of increased CO 2 fluxes that are driven by i) the transport of C from protected pools into active, ii) the chemical quality of the potentially soluble C, and iii) the type of microorganisms most likely to metabolize this C.« less

Differences in soluble organic carbon chemistry in pore waters sampled from different pore size domains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Vanessa L.; Smith, A. P.; Tfaily, Malak

Spatial isolation of soil organic carbon (SOC) in different sized pores may be a mechanism by which otherwise labile carbon (C) could be protected in soils. When soil water content increases, the hydrologic connectivity of soil pores also increases, allowing greater transport of SOC and other resources from protected locations, to microbially colonized locations more favorable to decomposition. The heterogeneous distribution of specialized decomposers, C, and other resources throughout the soil indicates that the metabolism or persistence of soil C compounds is highly dependent on short-distance transport processes. The objective of this research was to characterize the complexity of Cmore » in pore waters held at weak and strong water tensions (effectively soil solution held behind coarse- and fine-pore throats, respectively) and evaluate the microbial decomposability of these pore waters. We saturated intact soil cores and extracted pore waters with increasing suction pressures to sequentially sample pore waters from increasingly fine pore domains. Ultrahigh resolution mass spectrometry of the SOC was used to profile the major biochemical classes (i.e., lipids, proteins, lignin, carbohydrates, and condensed aromatics) of compounds present in the pore waters; some of these samples were then used as substrates for growth of Cellvibrio japonicus (DSMZ 16018), Streptomyces cellulosae (ATCC ® 25439™), and Trichoderma reseei (QM6a) in 7 day incubations. The soluble C in finer pores was more complex than the soluble C in coarser pores, and the incubations revealed that the more complex C in these fine pores is not recalcitrant. The decomposition of this complex C led to greater losses of C through respiration than the simpler C from coarser pore waters. Our research suggests that soils that experience repeated cycles of drying and wetting may be accompanied by repeated cycles of increased CO 2 fluxes that are driven by i) the transport of C from protected pools into active, ii) the chemical quality of the potentially soluble C, and iii) the type of microorganisms most likely to metabolize this C.« less

Effect of flour particle size on microstructural, rheological and physico-sensory characteristics of bread and south Indian parotta.

PubMed

Sakhare, Suresh D; Inamdar, Aashitosh A; Soumya, C; Indrani, D; Rao, G Venkateswara

2014-12-01

Wheat flour fractioned by sieving into four different particle size fractions namely finer fractions (<75 and 75-118 μm), coarser fractions (118-150 and >150 μm) were analyzed for their chemical, rheological, bread & parotta making characteristics. The finer fractions had lower ash, higher dry gluten, damaged starch and sodium dodecysulphate (SDS)-sedimentation value than the coarser fractions. The flour from finer fractions gave bread with best sensory and textural attributes. The parottas from finer fractions showed significantly higher sensory scores for colour, texture, layers, mouthfeel and overall quality score than the coarser fractions. In the micrograph of finer flour fractions, higher number of loosened single starch granules than the aggregates of starch and protein matrix were seen as compared to coarser fractions. These studies indicate that the flour from the finer fractions produce higher quality bread, parotta owing to the presence of higher damaged starch content, quantity and quality of protein in these fractions than coarser fractions.

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

PALS (Passive Active L-band System) Radiometer-Based Soil Moisture Retrieval for the SMAP Validation Experiment 2012 (SMAPVEX12)

NASA Astrophysics Data System (ADS)

Colliander, A.; Jackson, T. J.; Chan, S.; Bindlish, R.; O'Neill, P. E.; Chazanoff, S. L.; McNairn, H.; Bullock, P.; Powers, J.; Wiseman, G.; Berg, A. A.; Magagi, R.; Njoku, E. G.

2014-12-01

NASA's (National Aeronautics and Space Administration) Soil Moisture Active Passive (SMAP) mission is scheduled for launch in early January 2015. For pre-launch soil moisture algorithm development and validation, the SMAP project and NASA coordinated a SMAP Validation Experiment 2012 (SMAPVEX12) together with Agriculture and Agri-Food Canada in the vicinity of Winnipeg, Canada in June 7-July 19, 2012. Coincident active and passive airborne L-band data were acquired using the Passive Active L-band System (PALS) on 17 days during the experiment. Simultaneously with the PALS measurements, soil moisture ground truth data were collected manually. The vegetation and surface roughness were sampled on non-flight days. The SMAP mission will produce surface (top 5 cm) soil moisture products a) using a combination of its L-band radiometer and SAR (Synthetic Aperture Radar) measurements, b) using the radiometer measurement only, and c) using the SAR measurements only. The SMAPVEX12 data are being utilized for the development and testing of the algorithms applied for generating these soil moisture products. This talk will focus on presenting results of retrieving surface soil moisture using the PALS radiometer. The issues that this retrieval faces are very similar to those faced by the global algorithm using the SMAP radiometer. However, the different spatial resolution of the two observations has to be accounted for in the analysis. The PALS 3 dB footprint in the experiment was on the order of 1 km, whereas the SMAP radiometer has a footprint of about 40 km. In this talk forward modeled brightness temperature over the manually sampled fields and the retrieved soil moisture over the entire experiment domain are presented and discussed. In order to provide a retrieval product similar to that of the SMAP passive algorithm, various ancillary information had to be obtained for the SMAPVEX12 domain. In many cases there are multiple options on how to choose and reprocess these data. The derivation of these data elements and their impact on the retrieval and the spatial scales of the different observations are also discussed. In particular, land cover and soil type heterogeneity have a dramatic impact on parameterization of the algorithm when going from finer to coarser spatial resolutions.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Multiscale Bayesian neural networks for soil water content estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.; Springer, Everett P.

2008-08-01

Artificial neural networks (ANN) have been used for some time now to estimate soil hydraulic parameters from other available or more easily measurable soil properties. However, most such uses of ANNs as pedotransfer functions (PTFs) have been at matching spatial scales (1:1) of inputs and outputs. This approach assumes that the outputs are only required at the same scale as the input data. Unfortunately, this is rarely true. Different hydrologic, hydroclimatic, and contaminant transport models require soil hydraulic parameter data at different spatial scales, depending upon their grid sizes. While conventional (deterministic) ANNs have been traditionally used in these studies, the use of Bayesian training of ANNs is a more recent development. In this paper, we develop a Bayesian framework to derive soil water retention function including its uncertainty at the point or local scale using PTFs trained with coarser-scale Soil Survey Geographic (SSURGO)-based soil data. The approach includes an ANN trained with Bayesian techniques as a PTF tool with training and validation data collected across spatial extents (scales) in two different regions in the United States. The two study areas include the Las Cruces Trench site in the Rio Grande basin of New Mexico, and the Southern Great Plains 1997 (SGP97) hydrology experimental region in Oklahoma. Each region-specific Bayesian ANN is trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000), and predictions of the soil water contents at different pressure heads with point scale data (1:1) inputs are made. The resulting outputs are corrected for bias using both linear and nonlinear correction techniques. The results show good agreement between the soil water content values measured at the point scale and those predicted by the Bayesian ANN-based PTFs for both the study sites. Overall, Bayesian ANNs coupled with nonlinear bias correction are found to be very suitable tools for deriving soil hydraulic parameters at the local/fine scale from soil physical properties at coarser-scale and across different spatial extents. This approach could potentially be used for soil hydraulic properties estimation and downscaling.

Probabilistic #D data fusion for multiresolution surface generation

NASA Technical Reports Server (NTRS)

Manduchi, R.; Johnson, A. E.

2002-01-01

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

Reference evapotranspiration from coarse-scale and dynamically downscaled data in complex terrain: Sensitivity to interpolation and resolution

NASA Astrophysics Data System (ADS)

Strong, Courtenay; Khatri, Krishna B.; Kochanski, Adam K.; Lewis, Clayton S.; Allen, L. Niel

2017-05-01

The main objective of this study was to investigate whether dynamically downscaled high resolution (4-km) climate data from the Weather Research and Forecasting (WRF) model provide physically meaningful additional information for reference evapotranspiration (E) calculation compared to the recently published GridET framework that uses interpolation from coarser-scale simulations run at 32-km resolution. The analysis focuses on complex terrain of Utah in the western United States for years 1985-2010, and comparisons were made statewide with supplemental analyses specifically for regions with irrigated agriculture. E was calculated using the standardized equation and procedures proposed by the American Society of Civil Engineers from hourly data, and climate inputs from WRF and GridET were debiased relative to the same set of observations. For annual mean values, E from WRF (EW) and E from GridET (EG) both agreed well with E derived from observations (r2 = 0.95, bias < 2 mm). Domain-wide, EW and EG were well correlated spatially (r2 = 0.89), however local differences ΔE =EW -EG were as large as +439 mm year-1 (+26%) in some locations, and ΔE averaged +36 mm year-1. After linearly removing the effects of contrasts in solar radiation and wind speed, which are characteristically less reliable under downscaling in complex terrain, approximately half the residual variance was accounted for by contrasts in temperature and humidity between GridET and WRF. These contrasts stemmed from GridET interpolating using an assumed lapse rate of Γ = 6.5 K km-1, whereas WRF produced a thermodynamically-driven lapse rate closer to 5 K km-1 as observed in mountainous terrain. The primary conclusions are that observed lapse rates in complex terrain differ markedly from the commonly assumed Γ = 6.5 K km-1, these lapse rates can be realistically resolved via dynamical downscaling, and use of constant Γ produces differences in E of order as large as 102 mm year-1.

Spatial Distribution of Coffee Wilt Disease Under Roguing and Replanting Conditions: A Case Study from Kaweri Estate in Uganda.

PubMed

Pinard, F; Makune, S E; Campagne, P; Mwangi, J

2016-11-01

Based on time and spatial dynamic considerations, this study evaluates the potential role of short- and long-distance dispersal in the spread of coffee wilt disease (CWD) in a large commercial Robusta coffee estate in Uganda (Kaweri, 1,755 ha) over a 4-year period (2008 to 2012). In monthly surveys, total disease incidence, expansion of infection foci, and the occurrence of isolated infected trees were recorded and submitted to spatial analysis. Incidence was higher and disease progression faster in old coffee plantings compared with young plantings, indicating a lack of efficiency of roguing for reducing disease development in old plantings. At large spatial scale (approximately 1 km), Moran indices (both global and local) revealed the existence of clusters characterized by contrasting disease incidences. This suggested that local environmental conditions were heterogeneous or there were spatial interactions among blocks. At finer spatial scale (approximately 200 m), O-ring statistics revealed positive correlation between distant infection sites across distances as great as 60 m. Although these observations indicate the role of short-distance dispersal in foci expansion, dispersal at greater distances (>20 m) appeared to also contribute to both initiation of new foci and disease progression at coarser spatial scales. Therefore, our results suggested the role of aerial dispersal in CWD progression.

Ecoregions of the conterminous United States: evolution of a hierarchical spatial framework

USGS Publications Warehouse

Omernik, James M.; Griffith, Glenn E.

2014-01-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Ecoregions of the Conterminous United States: Evolution of a Hierarchical Spatial Framework

NASA Astrophysics Data System (ADS)

Omernik, James M.; Griffith, Glenn E.

2014-12-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Orientation decoding depends on maps, not columns

PubMed Central

Freeman, Jeremy; Brouwer, Gijs Joost; Heeger, David J.; Merriam, Elisha P.

2011-01-01

The representation of orientation in primary visual cortex (V1) has been examined at a fine spatial scale corresponding to the columnar architecture. We present functional magnetic resonance imaging (fMRI) measurements providing evidence for a topographic map of orientation preference in human V1 at a much coarser scale, in register with the angular-position component of the retinotopic map of V1. This coarse-scale orientation map provides a parsimonious explanation for why multivariate pattern analysis methods succeed in decoding stimulus orientation from fMRI measurements, challenging the widely-held assumption that decoding results reflect sampling of spatial irregularities in the fine-scale columnar architecture. Decoding stimulus attributes and cognitive states from fMRI measurements has proven useful for a number of applications, but our results demonstrate that the interpretation cannot assume decoding reflects or exploits columnar organization. PMID:21451017

Intercomparison of Satellite-Derived Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Tait, Andrew B.; Foster, James L.; Chang, Alfred T. C.; Allen, Milan

1999-01-01

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Intercomparison of AIRS and HIRDLS stratospheric gravity wave observations

NASA Astrophysics Data System (ADS)

Meyer, Catrin I.; Ern, Manfred; Hoffmann, Lars; Trinh, Quang Thai; Alexander, M. Joan

2018-01-01

We investigate stratospheric gravity wave observations by the Atmospheric InfraRed Sounder (AIRS) aboard NASA's Aqua satellite and the High Resolution Dynamics Limb Sounder (HIRDLS) aboard NASA's Aura satellite. AIRS operational temperature retrievals are typically not used for studies of gravity waves, because their vertical and horizontal resolution is rather limited. This study uses data of a high-resolution retrieval which provides stratospheric temperature profiles for each individual satellite footprint. Therefore the horizontal sampling of the high-resolution retrieval is 9 times better than that of the operational retrieval. HIRDLS provides 2-D spectral information of observed gravity waves in terms of along-track and vertical wavelengths. AIRS as a nadir sounder is more sensitive to short-horizontal-wavelength gravity waves, and HIRDLS as a limb sounder is more sensitive to short-vertical-wavelength gravity waves. Therefore HIRDLS is ideally suited to complement AIRS observations. A calculated momentum flux factor indicates that the waves seen by AIRS contribute significantly to momentum flux, even if the AIRS temperature variance may be small compared to HIRDLS. The stratospheric wave structures observed by AIRS and HIRDLS often agree very well. Case studies of a mountain wave event and a non-orographic wave event demonstrate that the observed phase structures of AIRS and HIRDLS are also similar. AIRS has a coarser vertical resolution, which results in an attenuation of the amplitude and coarser vertical wavelengths than for HIRDLS. However, AIRS has a much higher horizontal resolution, and the propagation direction of the waves can be clearly identified in geographical maps. The horizontal orientation of the phase fronts can be deduced from AIRS 3-D temperature fields. This is a restricting factor for gravity wave analyses of limb measurements. Additionally, temperature variances with respect to stratospheric gravity wave activity are compared on a statistical basis. The complete HIRDLS measurement period from January 2005 to March 2008 is covered. The seasonal and latitudinal distributions of gravity wave activity as observed by AIRS and HIRDLS agree well. A strong annual cycle at mid- and high latitudes is found in time series of gravity wave variances at 42 km, which has its maxima during wintertime and its minima during summertime. The variability is largest during austral wintertime at 60° S. Variations in the zonal winds at 2.5 hPa are associated with large variability in gravity wave variances. Altogether, gravity wave variances of AIRS and HIRDLS are complementary to each other. Large parts of the gravity wave spectrum are covered by joint observations. This opens up fascinating vistas for future gravity wave research.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

PubMed

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.

Preliminary study of a new gamma imager for on-line proton range monitoring during proton radiotherapy

NASA Astrophysics Data System (ADS)

Bennati, P.; Dasu, A.; Colarieti-Tosti, M.; Lönn, G.; Larsson, D.; Fabbri, A.; Galasso, M.; Cinti, M. N.; Pellegrini, R.; Pani, R.

2017-05-01

We designed and tested new concept imaging devices, based on a thin scintillating crystal, aimed at the online monitoring of the range of protons in tissue during proton radiotherapy. The proposed crystal can guarantee better spatial resolution and lower sensitivity with respect to a thicker one, at the cost of a coarser energy resolution. Two different samples of thin crystals were coupled to a position sensitive photo multiplier tube read out by 64 independent channels electronics. The detector was equipped with a knife-edge Lead collimator that defined a reasonable field of view of about 10 cm in the target. Geant4 Monte Carlo simulations were used to optimize the design of the experimental setup and assess the accuracy of the results. Experimental measurements were carried out at the Skandion Clinic, the recently opened proton beam facility in Uppsala, Sweden. PMMA and water phantoms studies were performed with a first prototype based on a round 6.0 mm thick Cry019 crystal and with a second detector based on a thinner 5 × 5 cm2, 2.0 mm thick LFS crystal. Phantoms were irradiated with mono-energetic proton beams whose energy was in the range between 110 and 160 MeV. According with the simulations and the experimental data, the detector based on LFS crystal seems able to identify the peak of prompt-gamma radiation and its results are in fair agreement with the expected shift of the proton range as a function of energy. The count rate remains one of the most critical limitations of our system, which was able to cope with only about 20% of the clinical dose rate. Nevertheless, we are confident that our study might provide the basis for developing a new full-functional system.

Characterizing the primary material sources and dominant erosional processes for post-fire debris-flow initiation in a headwater basin using multi-temporal terrestrial laser scanning data

USGS Publications Warehouse

Staley, Dennis M.; Waslewicz, Thad A.; Kean, Jason W.

2014-01-01

Wildfire dramatically alters the hydrologic response of a watershed such that even modest rainstorms can produce hazardous debris flows. Relative to shallow landslides, the primary sources of material and dominant erosional processes that contribute to post-fire debris-flow initiation are poorly constrained. Improving our understanding of how and where material is eroded from a watershed during a post-fire debris-flow requires (1) precise measurements of topographic change to calculate volumetric measurements of erosion and deposition, and (2) the identification of relevant morphometrically defined process domains to spatially constrain these measurements of erosion and deposition. In this study, we combine the morphometric analysis of a steep, small (0.01 km2) headwater drainage basin with measurements of topographic change using high-resolution (2.5 cm) multi-temporal terrestrial laser scanning data made before and after a post-fire debris flow. The results of the morphometric analysis are used to define four process domains: hillslope-divergent, hillslope-convergent, transitional, and channelized incision. We determine that hillslope-divergent and hillslope-convergent process domains represent the primary sources of material over the period of analysis in the study basin. From these results we conclude that raindrop-impact induced erosion, ravel, surface wash, and rilling are the primary erosional processes contributing to post-fire debris-flow initiation in the small, steep headwater basin. Further work is needed to determine (1) how these results vary with increasing drainage basin size, (2) how these data might scale upward for use with coarser resolution measurements of topography, and (3) how these results change with evolving sediment supply conditions and vegetation recovery.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

PubMed Central

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2> 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2> 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed. PMID:29230229

Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

NASA Astrophysics Data System (ADS)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

Pathways of geomorphic evolution of sandstone escarpments in the Góry Stołowe tableland (SW Poland) - Insights from LiDAR-based high-resolution DEM

NASA Astrophysics Data System (ADS)

Migoń, Piotr; Kasprzak, Marek

2016-05-01

The tableland of the Stołowe Mountains (SW Poland), with its prominent mesas and sandstone-capped escarpments, belongs to the most spectacular geomorphic landscapes of Central Europe. While the gross morphological features of the area have long been recognized, the evolutionary pathways of densely forested and poorly accessible escarpment slopes remained poorly understood. In this paper we use LiDAR data to shed a new light on landform inventories within the escarpments, their spatial patterns and, using process-from-form reasoning, on the longer-term evolution of the escarpments. Four sites, two on each major escarpment, have been subject to detailed analysis which involved examination of shaded relief, slope, plan and profile curvature and topographic wetness index. In each case, the 1 × 1 m model was used, while for the most complex site at Mt. Szczeliniec Wielki the results were compared with the 5 × 5 m model to check the impact of model resolution on geomorphic interpretation. Despite some loss of information involved in model re-interpolation to the coarser scale, the main features of escarpment morphology could still be recognized. On the other hand, automatic landform classification based on the calculation of Topographic Position Index from the 10 × 10 m model and performed for the entire tableland failed to reveal differences between various sections of the escarpments, detectable on finer models. The analysis of spatial patterns of minor landforms within the escarpments, identified on LiDAR-derived models shows that no single pathway of escarpment evolution exists. Both the upper slopes (in sandstone caprock) and the mid-slopes (in weaker rocks) show signs of instability and these are not necessarily coupled. Large-scale caprock failures do occur but seem rare and localized. Sandstone free faces are rather subject to continuous slow retreat by detachment of individual joint-bound blocks. Another zone of instability occurs well below the caprock and the dominant processes are shallow landslips initiated within weak, deformable rocks.

Surface-water radon-222 distribution along the west-central Florida shelf

USGS Publications Warehouse

Smith, C.G.; Robbins, L.L.

2012-01-01

In February 2009 and August 2009, the spatial distribution of radon-222 in surface water was mapped along the west-central Florida shelf as collaboration between the Response of Florida Shelf Ecosystems to Climate Change project and a U.S. Geological Survey Mendenhall Research Fellowship project. This report summarizes the surface distribution of radon-222 from two cruises and evaluates potential physical controls on radon-222 fluxes. Radon-222 is an inert gas produced overwhelmingly in sediment and has a short half-life of 3.8 days; activities in surface water ranged between 30 and 170 becquerels per cubic meter. Overall, radon-222 activities were enriched in nearshore surface waters relative to offshore waters. Dilution in offshore waters is expected to be the cause of the low offshore activities. While thermal stratification of the water column during the August survey may explain higher radon-222 activities relative to the February survey, radon-222 activity and integrated surface-water inventories decreased exponentially from the shoreline during both cruises. By estimating radon-222 evasion by wind from nearby buoy data and accounting for internal production from dissolved radium-226, its radiogenic long-lived parent, a simple one-dimensional model was implemented to determine the role that offshore mixing, benthic influx, and decay have on the distribution of excess radon-222 inventories along the west Florida shelf. For multiple statistically based boundary condition scenarios (first quartile, median, third quartile, and maximum radon-222 inshore of 5 kilometers), the cross-shelf mixing rates and average nearshore submarine groundwater discharge (SGD) rates varied from 100.38 to 10-3.4 square kilometers per day and 0.00 to 1.70 centimeters per day, respectively. This dataset and modeling provide the first attempt to assess cross-shelf mixing and SGD on such a large spatial scale. Such estimates help scale up SGD rates that are often made at 1- to 10-meter resolution to a coarser but more regionally applicable scale of 1- to 10-kilometer resolution. More stringent analyses and model evaluation are required, but results and analyses presented in this report provide the foundation for conducting a more rigorous statistical assessment.

Influence of grid resolution in fluid-model simulation of nanosecond dielectric barrier discharge plasma actuator

NASA Astrophysics Data System (ADS)

Hua, Weizhuo; Fukagata, Koji

2018-04-01

Two-dimensional numerical simulation of a surface dielectric barrier discharge (SDBD) plasma actuator, driven by a nanosecond voltage pulse, is conducted. A special focus is laid upon the influence of grid resolution on the computational result. It is found that the computational result is not very sensitive to the streamwise grid spacing, whereas the wall-normal grid spacing has a critical influence. In particular, the computed propagation velocity changes discontinuously around the wall-normal grid spacing about 2 μm due to a qualitative change of discharge structure. The present result suggests that a computational grid finer than that was used in most of previous studies is required to correctly capture the structure and dynamics of streamer: when a positive nanosecond voltage pulse is applied to the upper electrode, a streamer forms in the vicinity of upper electrode and propagates along the dielectric surface with a maximum propagation velocity of 2 × 108 cm/s, and a gap with low electron and ion density (i.e., plasma sheath) exists between the streamer and dielectric surface. Difference between the results obtained using the finer and the coarser grid is discussed in detail in terms of the electron transport at a position near the surface. When the finer grid is used, the low electron density near the surface is caused by the absence of ionization avalanche: in that region, the electrons generated by ionization is compensated by drift-diffusion flux. In contrast, when the coarser grid is used, underestimated drift-diffusion flux cannot compensate the electrons generated by ionization, and it leads to an incorrect increase of electron density.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

Quantifying the linear and nonlinear relations between the urban form fragmentation and the carbon emission distribution

NASA Astrophysics Data System (ADS)

Zuo, S.; Dai, S.; Ren, Y.; Yu, Z.

2017-12-01

Scientifically revealing the spatial heterogeneity and the relationship between the fragmentation of urban landscape and the direct carbon emissions are of great significance to land management and urban planning. In fact, the linear and nonlinear effects among the various factors resulted in the carbon emission spatial map. However, there is lack of the studies on the direct and indirect relations between the carbon emission and the city functional spatial form changes, which could not be reflected by the land use change. The linear strength and direction of the single factor could be calculated through the correlation and Geographically Weighted Regression (GWR) analysis, the nonlinear power of one factor and the interaction power of each two factors could be quantified by the Geodetector analysis. Therefore, we compared the landscape fragmentation metrics of the urban land cover and functional district patches to characterize the landscape form and then revealed the relations between the landscape fragmentation level and the direct the carbon emissions based on the three methods. The results showed that fragmentation decreased and the fragmented patches clustered at the coarser resolution. The direct CO2 emission density and the population density increased when the fragmentation level aggregated. The correlation analysis indicated the weak linear relation between them. The spatial variation of GWR output indicated the fragmentation indicator (MESH) had the positive influence on the carbon emission located in the relatively high emission region, and the negative effects regions accounted for the small part of the area. The Geodetector which explores the nonlinear relation identified the DIVISION and MESH as the most powerful direct factor for the land cover patches, NP and PD for the functional district patches, and the interactions between fragmentation indicator (MESH) and urban sprawl metrics (PUA and DIS) had the greatly increased explanation powers on the urban carbon emission. Overall, this study provides a framework to understand the relation between the urban landscape fragmentation and the carbon emission for the low carbon city construction planning in the other cities.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2004-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1'(approximately 10 km) and coarser resolution equal-angle grids, and are computed for the first seven MODIS wavelengths, ranging from 0.47 through 2.1 microns, and for three broadband wavelengths, 0.3-0.7,0.3-5.0 and 0.7-5.0 microns.

Mapping Surface Temperatures on a Debris-Covered Glacier with an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip D. A.; Shea, Joseph M.; Litt, Maxime; Steiner, Jakob F.; Treichler, Désirée; Koch, Inka; Immerzeel, Walter W.

2018-05-01

A mantel of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with -1.4±1.8, 11.0 ±5.2 and 15.3±4.7 °C for the three flights (mean±sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 °C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

NASA Technical Reports Server (NTRS)

Xiong, Jun; Thenkabail, Prasad S.; Tilton, James C.; Gumma, Murali K.; Teluguntla, Pardhasaradhi; Oliphant, Adam; Congalton, Russell G.; Yadav, Kamini; Gorelick, Noel

2017-01-01

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

UAV-based remote sensing surveys of lava flow fields: a case study from Etna's 1974 channel-fed lava flows

NASA Astrophysics Data System (ADS)

Favalli, Massimiliano; Fornaciai, Alessandro; Nannipieri, Luca; Harris, Andrew; Calvari, Sonia; Lormand, Charline

2018-03-01

During an eruption, time scales of topographic change are fast and involve vertical and planimetric evolution of millimeters to meters as the event progresses. Repeat production of high spatial resolution terrain models of lava flow fields over time scales of a few hours is thus a high-value capability in tracking the buildup of the deposit. Among the wide range of terrestrial and aerial methods available to collect such topographic data, the use of an unmanned aerial vehicle (UAV) as an acquisition platform, together with structure from motion (SfM) photogrammetry, has become especially useful. This approach allows high-frequency production of centimeter-scale terrain models over kilometer-scale areas, including dangerous and inaccessible zones, with low cost and minimal hazard to personnel. This study presents the application of such an integrated UAV-SfM method to generate a high spatial resolution digital terrain model and orthomosaic of Mount Etna's January-February 1974 lava flow field. The SfM method, applied to images acquired using a UAV platform, enabled the extraction of a very high spatial resolution (20 cm) digital elevation model and the generation of a 3-cm orthomosaic covering an area of 1.35 km2. This spatial resolution enabled us to analyze the morphology of sub-meter-scale features, such as folds, blocks, and cracks, over kilometer-scale areas. The 3-cm orthomosaic allowed us to further push the analysis to centimeter-scale grain size distribution of the lava surface. Using these data, we define three types of crust structure and relate them to positions within a channel-fed ´áā flow system. These crust structures are (i) flow parallel shear lines, (ii) raft zones, and (iii) folded zones. Flow parallel shear lines are found at the channel edges, and are 2-m-wide and 0.25-m-deep zones running along the levee base and in which cracking is intense. They result from intense shearing between the moving channel lava and the static levee lava. In zones where initial levees are just beginning to form, these subtle features are the only marker that delimits the moving lava from the stagnant marginal lava. Rafts generally form as the system changes from a stable to a transitional channel regime. Over this 170-m-long zone, the channel broadens from 8 to 70 m and rafts are characterized by topographically higher and poorly cracked areas, surrounded by lower, heavily cracked areas. We interpret the rafts as forming due to breakup of crust zones, previously moving in a coherent manner in the narrow proximal channel reach. Folded zones involve arcuate, cross-flow ridges with their apexes pointing down-flow, where ridges have relatively small clasts and depressions are of coarser-grained breccia. Our folds have wavelengths of 10 m and amplitudes of 1 m; are found towards the flow front, down-flow of the raft zones; and are associated with piling up of lava behind a static or slowly moving flow front. The very high spatial resolution topographic data available from UAV-SfM allow us to resolve surfaces where roughness has a vertical and horizontal scale of variation that is less than 1 m. This is the case over pāhoehoe and ´áā flow surfaces, and thus allows us to explore those new structures that are only apparent in the sub-metric data. Moreover, during future eruptions, the possibility to acquire such information in near-real time will allow a prompt analysis of developing lava flow fields and structures therein, such as developing lava channel systems, so as to contribute to timely hazard assessment, modeling, and projections.

A multigrid method for steady Euler equations on unstructured adaptive grids

NASA Technical Reports Server (NTRS)

Riemslagh, Kris; Dick, Erik

1993-01-01

A flux-difference splitting type algorithm is formulated for the steady Euler equations on unstructured grids. The polynomial flux-difference splitting technique is used. A vertex-centered finite volume method is employed on a triangular mesh. The multigrid method is in defect-correction form. A relaxation procedure with a first order accurate inner iteration and a second-order correction performed only on the finest grid, is used. A multi-stage Jacobi relaxation method is employed as a smoother. Since the grid is unstructured a Jacobi type is chosen. The multi-staging is necessary to provide sufficient smoothing properties. The domain is discretized using a Delaunay triangular mesh generator. Three grids with more or less uniform distribution of nodes but with different resolution are generated by successive refinement of the coarsest grid. Nodes of coarser grids appear in the finer grids. The multigrid method is started on these grids. As soon as the residual drops below a threshold value, an adaptive refinement is started. The solution on the adaptively refined grid is accelerated by a multigrid procedure. The coarser multigrid grids are generated by successive coarsening through point removement. The adaption cycle is repeated a few times. Results are given for the transonic flow over a NACA-0012 airfoil.

Research on regional numerical weather prediction

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1976-01-01

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

Mapping and detecting bark beetle-caused tree mortality in the western United States

NASA Astrophysics Data System (ADS)

Meddens, Arjan J. H.

Recently, insect outbreaks across North America have dramatically increased and the forest area affected by bark beetles is similar to that affected by fire. Remote sensing offers the potential to detect insect outbreaks with high accuracy. Chapter one involved detection of insect-caused tree mortality on the tree level for a 90km2 area in northcentral Colorado. Classes of interest included green trees, multiple stages of post-insect attack tree mortality including dead trees with red needles ("red-attack") and dead trees without needles ("gray-attack"), and non-forest. The results illustrated that classification of an image with a spatial resolution similar to the area of a tree crown outperformed that from finer and coarser resolution imagery for mapping tree mortality and non-forest classes. I also demonstrated that multispectral imagery could be used to separate multiple postoutbreak attack stages (i.e., red-attack and gray-attack) from other classes in the image. In Chapter 2, I compared and improved methods for detecting bark beetle-caused tree mortality using medium-resolution satellite data. I found that overall classification accuracy was similar between single-date and multi-date classification methods. I developed regression models to predict percent red attack within a 30-m grid cell and these models explained >75% of the variance using three Landsat spectral explanatory variables. Results of the final product showed that approximately 24% of the forest within the Landsat scene was comprised of tree mortality caused by bark beetles. In Chapter 3, I developed a gridded data set with 1-km2 resolution using aerial survey data and improved estimates of tree mortality across the western US and British Columbia. In the US, I also produced an upper estimate by forcing the mortality area to match that from high-resolution imagery in Idaho, Colorado, and New Mexico. Cumulative mortality area from all bark beetles was 5.46 Mha in British Columbia in 2001-2010 and 0.47-5.37 Mha (lower and upper estimate) in the western conterminous US during 1997-2010. Improved methods for detection and mapping of insect outbreak areas will lead to improved assessments of the effects of these forest disturbances on the economy, carbon cycle (and feedback to climate change), fuel loads, hydrology and forest ecology.

Hydrological regime as key to the morpho-texture and activity of braided streams

NASA Astrophysics Data System (ADS)

Storz-Peretz, Y.; Laronne, J. B.

2012-04-01

Braided streams are a common fluvial pattern in different climates. However, studies of gravel braided streams have mainly been conducted in humid braided systems or in flume simulations thereof, leaving arid braided streams scarcely investigated. Dryland rivers have bare catchments, rapid flow recession and unarmoured channel beds which are responsible for very high bedload discharges, thereby increasing the likelihood for braiding. Our main objective is to characterize the morpho-texture of the main morphological elements - mid-channel bars, chutes and anabranches (braid-cells) in the dryland braided system and compare them to their humid counterparts. Selected areas of the dryland braided Wadis Ze'elim, Rahaf and Roded in the SE hyper-arid Israel were measured, as were La-Bleone river in the French pre-alps along with the Saisera and Cimoliana rivers in NE Italy representing humid braided systems. Terrestrial Laser Scanning (TLS) of morphological units produced point clouds from which high resolution accurate Digital Elevation Models (DEMs) were extracted. Active braid cells in humid environments were also surveyed by electronic theodolite. Roughness and upper tail Grain Size Distribution (GSD) quantiles were derived from the scanned point clouds or from Wolman sampling. Results indicate that dryland anabranches tend to be finer-grained and less armoured than the bars, contrary to the humid braided systems, where the main or larger anabranches are coarser-grained and more armoured than the bars. Chutes are commonly similar or coarser-grained than the bars they dissect, in accordance with their steeper gradients due to the considerable relief of the bar-anabranch. The morpho-texture displayed in the steep braided Saisera River, located in the Italian Dolomites having the highest annual precipitation, has similarity to that of the dryland braided channels. In drylands coarse gravel is deposited mainly as bars due to the high flux of bedload, whereas the rapid flow recession is responsible for deposition of finer sediment with minimal winnowing in the branch channels. Therefore, channels are finer-grained than the bars. This process is associated with the mid-channel deposition of central bars. However, the steeper chutes and coarser anabranches are associated with erosive braiding processes, such as chute cutoffs and multiple bar dissection, allowing winnowing to occur also during rapid recession. Hence coarser-grained anabranches in drylands are essentially chutes. Lengthy flow recession in humid braided channels allows winnowing of fines, thereby generating armored channels, the finer sedimentary particles often deposited downstream as unit bars. Therefore, channels are coarser-grained than the bars they surround. Even though the steep Saisera is in a humid region, its hydrological regime is ephemeral with rapid and short recessions, responsible for a morpho-texture similar to that of dryland braided streams. Hence, the hydrologic regimen is a key to understanding the morpho-textural character of braided channels and for the higher activity of the ephemeral unarmoured channels in sub-barful events compared to their humid counterparts.

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Kang, In-Sik; Reale, Oreste

2009-01-01

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

NASA Astrophysics Data System (ADS)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

Restoring the spatial resolution of refocus images on 4D light field

NASA Astrophysics Data System (ADS)

Lim, JaeGuyn; Park, ByungKwan; Kang, JooYoung; Lee, SeongDeok

2010-01-01

This paper presents the method for generating a refocus image with restored spatial resolution on a plenoptic camera, which functions controlling the depth of field after capturing one image unlike a traditional camera. It is generally known that the camera captures 4D light field (angular and spatial information of light) within a limited 2D sensor and results in reducing 2D spatial resolution due to inevitable 2D angular data. That's the reason why a refocus image is composed of a low spatial resolution compared with 2D sensor. However, it has recently been known that angular data contain sub-pixel spatial information such that the spatial resolution of 4D light field can be increased. We exploit the fact for improving the spatial resolution of a refocus image. We have experimentally scrutinized that the spatial information is different according to the depth of objects from a camera. So, from the selection of refocused regions (corresponding depth), we use corresponding pre-estimated sub-pixel spatial information for reconstructing spatial resolution of the regions. Meanwhile other regions maintain out-of-focus. Our experimental results show the effect of this proposed method compared to existing method.

Ray Casting of Large Multi-Resolution Volume Datasets

NASA Astrophysics Data System (ADS)

Lux, C.; Fröhlich, B.

2009-04-01

High quality volume visualization through ray casting on graphics processing units (GPU) has become an important approach for many application domains. We present a GPU-based, multi-resolution ray casting technique for the interactive visualization of massive volume data sets commonly found in the oil and gas industry. Large volume data sets are represented as a multi-resolution hierarchy based on an octree data structure. The original volume data is decomposed into small bricks of a fixed size acting as the leaf nodes of the octree. These nodes are the highest resolution of the volume. Coarser resolutions are represented through inner nodes of the hierarchy which are generated by down sampling eight neighboring nodes on a finer level. Due to limited memory resources of current desktop workstations and graphics hardware only a limited working set of bricks can be locally maintained for a frame to be displayed. This working set is chosen to represent the whole volume at different local resolution levels depending on the current viewer position, transfer function and distinct areas of interest. During runtime the working set of bricks is maintained in CPU- and GPU memory and is adaptively updated by asynchronously fetching data from external sources like hard drives or a network. The CPU memory hereby acts as a secondary level cache for these sources from which the GPU representation is updated. Our volume ray casting algorithm is based on a 3D texture-atlas in GPU memory. This texture-atlas contains the complete working set of bricks of the current multi-resolution representation of the volume. This enables the volume ray casting algorithm to access the whole working set of bricks through only a single 3D texture. For traversing rays through the volume, information about the locations and resolution levels of visited bricks are required for correct compositing computations. We encode this information into a small 3D index texture which represents the current octree subdivision on its finest level and spatially organizes the bricked data. This approach allows us to render a bricked multi-resolution volume data set utilizing only a single rendering pass with no loss of compositing precision. In contrast most state-of-the art volume rendering systems handle the bricked data as individual 3D textures, which are rendered one at a time while the results are composited into a lower precision frame buffer. Furthermore, our method enables us to integrate advanced volume rendering techniques like empty-space skipping, adaptive sampling and preintegrated transfer functions in a very straightforward manner with virtually no extra costs. Our interactive volume ray tracing implementation allows high quality visualizations of massive volume data sets of tens of Gigabytes in size on standard desktop workstations.

A multi-resolution approach to electromagnetic modelling

NASA Astrophysics Data System (ADS)

Cherevatova, M.; Egbert, G. D.; Smirnov, M. Yu

2018-07-01

We present a multi-resolution approach for 3-D magnetotelluric forward modelling. Our approach is motivated by the fact that fine-grid resolution is typically required at shallow levels to adequately represent near surface inhomogeneities, topography and bathymetry, while a much coarser grid may be adequate at depth where the diffusively propagating electromagnetic fields are much smoother. With a conventional structured finite difference grid, the fine discretization required to adequately represent rapid variations near the surface is continued to all depths, resulting in higher computational costs. Increasing the computational efficiency of the forward modelling is especially important for solving regularized inversion problems. We implement a multi-resolution finite difference scheme that allows us to decrease the horizontal grid resolution with depth, as is done with vertical discretization. In our implementation, the multi-resolution grid is represented as a vertical stack of subgrids, with each subgrid being a standard Cartesian tensor product staggered grid. Thus, our approach is similar to the octree discretization previously used for electromagnetic modelling, but simpler in that we allow refinement only with depth. The major difficulty arose in deriving the forward modelling operators on interfaces between adjacent subgrids. We considered three ways of handling the interface layers and suggest a preferable one, which results in similar accuracy as the staggered grid solution, while retaining the symmetry of coefficient matrix. A comparison between multi-resolution and staggered solvers for various models shows that multi-resolution approach improves on computational efficiency without compromising the accuracy of the solution.

High Spatial Resolution Commercial Satellite Imaging Product Characterization

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Pagnutti, Mary; Blonski, Slawomir; Ross, Kenton W.; Stnaley, Thomas

2005-01-01

NASA Stennis Space Center's Remote Sensing group has been characterizing privately owned high spatial resolution multispectral imaging systems, such as IKONOS, QuickBird, and OrbView-3. Natural and man made targets were used for spatial resolution, radiometric, and geopositional characterizations. Higher spatial resolution also presents significant adjacency effects for accurate reliable radiometry.

Investigation of microwave hologram techniques for application to earth resources

NASA Technical Reports Server (NTRS)

Larson, R. W.; Bayma, R. W.; Evans, M. B.; Zelenka, J. S.; Doss, H. W.; Ferris, J. E.

1974-01-01

An investigation of microwave hologram techniques for application to earth resources was conducted during the period from June 1971 to November 1972. The objective of this investigation has been to verify the feasibility of an orbital microwave holographic radar experiment. The primary advantage of microwave hologram radar (MHR) over the side-looking airborne radar (SLAR) is that of aspect or viewing angle; the MHR has a viewing angle identical with that of photography and IR systems. The combination of these systems can thus extend the multispectral analysis concept to span optical through microwave wavelengths. Another advantage is the capacity of the MHR system to generate range contours by operating in a two-frequency mode. It should be clear that along-track resolution of an MHR can be comparable with SLAR systems, but cross-track resolution will be approximately an order of magnitude coarser than the range resolution achievable with an arbitrary SLAR system. An advantage of the MHR over the SLAR is that less average transmitter power is required. This reduction in power results from the much larger receiving apertures associated with MHR systems.

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

Davis, Bruce; Ryan, Robert; Holekamp, Kara; Vaughn, Ronald

2011-01-01

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Forest Biomass Mapping from Stereo Imagery and Radar Data

NASA Astrophysics Data System (ADS)

Sun, G.; Ni, W.; Zhang, Z.

2013-12-01

Both InSAR and lidar data provide critical information on forest vertical structure, which are critical for regional mapping of biomass. However, the regional application of these data is limited by the availability and acquisition costs. Some researchers have demonstrated potentials of stereo imagery in the estimation of forest height. Most of these researches were conducted on aerial images or spaceborne images with very high resolutions (~0.5m). Space-born stereo imagers with global coverage such as ALOS/PRISM have coarser spatial resolutions (2-3m) to achieve wider swath. The features of stereo images are directly affected by resolutions and the approaches use by most of researchers need to be adjusted for stereo imagery with lower resolutions. This study concentrated on analyzing the features of point clouds synthesized from multi-view stereo imagery over forested areas. The small footprint lidar and lidar waveform data were used as references. The triplets of ALOS/PRISM data form three pairs (forward/nadir, backward/nadir and forward/backward) of stereo images. Each pair of the stereo images can be used to generate points (pixels) with 3D coordinates. By carefully co-register these points from three pairs of stereo images, a point cloud data was generated. The height of each point above ground surface was then calculated using DEM from National Elevation Dataset, USGS as the ground surface elevation. The height data were gridded into pixel of different sizes and the histograms of the points within a pixel were analyzed. The average height of the points within a pixel was used as the height of the pixel to generate a canopy height map. The results showed that the synergy of point clouds from different views were necessary, which increased the point density so the point cloud could detect the vertical structure of sparse and unclosed forests. The top layer of multi-layered forest could be captured but the dense forest prevented the stereo imagery to see through. The canopy height map exhibited spatial patterns of roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlation with RH50 of LVIS data at 30m pixel size with a gain of 1.04, bias of 4.3m and R2 of 0.74 (Fig. 1). The canopy height map from PRISM and dual-pol PALSAR data were used together to map biomass in our study area near Howland, Maine, and the results were evaluated using biomass map generated from LVIS waveform data independently. The results showed that adding CHM from PRISM significantly improved biomass accuracy and raised the biomass saturation level of L-band SAR data in forest biomass mapping.

Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

DTIC Science & Technology

2007-09-01

spatial - resolution hyperspectral image to produce a sharpened product. The result is a product that has the spectral properties of the ...multispectral sensors. In this work, we examine the benefits of combining data from high- spatial - resolution , low- spectral - resolution spectral imaging...sensors with data obtained from high- spectral - resolution , low- spatial - resolution spectral imaging sensors.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

PubMed

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

PubMed Central

Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828

Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC4RS and DISCOVER-AQ airborne campaigns

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Crawford, James H.; Wisthaler, Armin; Zhan, Xiwu; Hain, Christopher R.; Lee, Pius; Guenther, Alex B.

2017-08-01

Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ˜ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

Assessing changes to South African maize production areas in 2055 using empirical and process-based crop models

NASA Astrophysics Data System (ADS)

Estes, L.; Bradley, B.; Oppenheimer, M.; Beukes, H.; Schulze, R. E.; Tadross, M.

2010-12-01

Rising temperatures and altered precipitation patterns associated with climate change pose a significant threat to crop production, particularly in developing countries. In South Africa, a semi-arid country with a diverse agricultural sector, anthropogenic climate change is likely to affect staple crops and decrease food security. Here, we focus on maize production, South Africa’s most widely grown crop and one with high socio-economic value. We build on previous coarser-scaled studies by working at a finer spatial resolution and by employing two different modeling approaches: the process-based DSSAT Cropping System Model (CSM, version 4.5), and an empirical distribution model (Maxent). For climate projections, we use an ensemble of 10 general circulation models (GCMs) run under both high and low CO2 emissions scenarios (SRES A2 and B1). The models were down-scaled to historical climate records for 5838 quinary-scale catchments covering South Africa (mean area = 164.8 km2), using a technique based on self-organizing maps (SOMs) that generates precipitation patterns more consistent with observed gradients than those produced by the parent GCMs. Soil hydrological and mechanical properties were derived from textural and compositional data linked to a map of 26422 land forms (mean area = 46 km2), while organic carbon from 3377 soil profiles was mapped using regression kriging with 8 spatial predictors. CSM was run using typical management parameters for the several major dryland maize production regions, and with projected CO2 values. The Maxent distribution model was trained using maize locations identified using annual phenology derived from satellite images coupled with airborne crop sampling observations. Temperature and precipitation projections were based on GCM output, with an additional 10% increase in precipitation to simulate higher water-use efficiency under future CO2 concentrations. The two modeling approaches provide spatially explicit projections of gains and losses in maize productivity. We identify several areas-particularly along the southern and eastern boundaries of current production-with potential for increased productivity. However, larger areas, primarily in the more arid western and northern production regions, are likely to experience diminished productivity. The combination of process-based and distribution models for agricultural impacts assessments provides a useful comparison of two different crop modeling frameworks, as well as the finest scale investigation using a spatially-explicit implementation of a process-based model for South Africa. The large GCM ensemble and multiple emissions scenarios provide a broad climate risk assessment for current maize production. SOM downscaling can help improve climate impacts assessments by increasing their resolution, and by circumventing GCM precipitation schemes whose outcomes are highly divergent.

Assessment of the effects of horizontal grid resolution on long ...

EPA Pesticide Factsheets

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment.

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena; Blaisdell, John

2015-01-01

Demonstrate via Observing System Simulation Experiments (OSSEs) the potential utility of flying high spatial resolution AIRS class IR sounders on future LEO and GEO missions.The study simulates and analyzes radiances for 3 sounders with AIRS spectral and radiometric properties on different orbits with different spatial resolutions: 1) Control run 13 kilometers AIRS spatial resolution at nadir on LEO in Aqua orbit; 2) 2 kilometer spatial resolution LEO sounder at nadir ARIES; 3) 5 kilometers spatial resolution sounder on a GEO orbit, radiances simulated every 72 minutes.

Detector motion method to increase spatial resolution in photon-counting detectors

NASA Astrophysics Data System (ADS)

Lee, Daehee; Park, Kyeongjin; Lim, Kyung Taek; Cho, Gyuseong

2017-03-01

Medical imaging requires high spatial resolution of an image to identify fine lesions. Photon-counting detectors in medical imaging have recently been rapidly replacing energy-integrating detectors due to the former`s high spatial resolution, high efficiency and low noise. Spatial resolution in a photon counting image is determined by the pixel size. Therefore, the smaller the pixel size, the higher the spatial resolution that can be obtained in an image. However, detector redesigning is required to reduce pixel size, and an expensive fine process is required to integrate a signal processing unit with reduced pixel size. Furthermore, as the pixel size decreases, charge sharing severely deteriorates spatial resolution. To increase spatial resolution, we propose a detector motion method using a large pixel detector that is less affected by charge sharing. To verify the proposed method, we utilized a UNO-XRI photon-counting detector (1-mm CdTe, Timepix chip) at the maximum X-ray tube voltage of 80 kVp. A similar spatial resolution of a 55- μm-pixel image was achieved by application of the proposed method to a 110- μm-pixel detector with a higher signal-to-noise ratio. The proposed method could be a way to increase spatial resolution without a pixel redesign when pixels severely suffer from charge sharing as pixel size is reduced.

The Effect of Remote Sensor Spatial Resolution in Monitoring U.S. Army Training Maneuver Sites

DTIC Science & Technology

1990-12-01

THE EFFECT OF REMOTE SENSOR SPATIAL RESOLUTION IN MONITORING U.S. ARMY...Multispectral Scanner with 6.5 meter spatial resolution provided the most effective digital data set for enhancing tank trails. However, this Airborne Scanner...primary objective of this research was to determine the capabilities and limitations of remote sensor systems having different spatial resolutions to

Uav Photogrammetry for Mapping and Monitoring of Northern Permafrost Landscapes

NASA Astrophysics Data System (ADS)

Fraser, R. H.; Olthof, I.; Maloley, M.; Fernandes, R.; Prevost, C.; van der Sluijs, J.

2015-08-01

Northern environments are changing in response to recent climate warming, resource development, and natural disturbances. The Arctic climate has warmed by 2-3°C since the 1950's, causing a range of cryospheric changes including declines in sea ice extent, snow cover duration, and glacier mass, and warming permafrost. The terrestrial Arctic has also undergone significant temperature-driven changes in the form of increased thermokarst, larger tundra fires, and enhanced shrub growth. Monitoring these changes to inform land managers and decision makers is challenging due to the vast spatial extents involved and difficult access. Environmental monitoring in Canada's North is often based on local-scale measurements derived from aerial reconnaissance and photography, and ecological, hydrologic, and geologic sampling and surveying. Satellite remote sensing can provide a complementary tool for more spatially comprehensive monitoring but at coarser spatial resolutions. Satellite remote sensing has been used to map Arctic landscape changes related to vegetation productivity, lake expansion and drainage, glacier retreat, thermokarst, and wildfire activity. However, a current limitation with existing satellite-based techniques is the measurement gap between field measurements and high resolution satellite imagery. Bridging this gap is important for scaling up field measurements to landscape levels, and validating and calibrating satellite-based analyses. This gap can be filled to a certain extent using helicopter or fixed-wing aerial surveys, but at a cost that is often prohibitive. Unmanned aerial vehicle (UAV) technology has only recently progressed to the point where it can provide an inexpensive and efficient means of capturing imagery at this middle scale of measurement with detail that is adequate to interpret Arctic vegetation (i.e. 1-5 cm) and coverage that can be directly related to satellite imagery (1-10 km2). Unlike satellite measurements, UAVs permit frequent surveys (e.g. for monitoring vegetation phenology, fires, and hydrology), are not constrained by repeat cycle or cloud cover, can be rapidly deployed following a significant event, and are better suited than manned aircraft for mapping small areas. UAVs are becoming more common for agriculture, law enforcement, and marketing, but their use in the Arctic is still rare and represents untapped technology for northern mapping, monitoring, and environmental research. We are conducting surveys over a range of sensitive or changing northern landscapes using a variety of UAV multicopter platforms and small sensors. Survey targets include retrogressive thaw slumps, tundra shrub vegetation, recently burned vegetation, road infrastructure, and snow. Working with scientific partners involved in northern monitoring programs (NWT CIMP, CHARS, NASA ABOVE, NRCan-GSC) we are investigating the advantages, challenges, and best practices for acquiring high resolution imagery from multicopters to create detailed orthomosaics and co-registered 3D terrain models. Colour and multispectral orthomosaics are being integrated with field measurements and satellite imagery to conduct spatial scaling of environmental parameters. Highly detailed digital terrain models derived using structure from motion (SfM) photogrammetry are being applied to measure thaw slump morphology and change, snow depth, tundra vegetation structure, and surface condition of road infrastructure. These surveys and monitoring applications demonstrate that UAV-based photogrammetry is poised to make a rapid contribution to a wide range of northern monitoring and research applications.

The effects of transient attention on spatial resolution and the size of the attentional cue.

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

It has been shown that transient attention enhances spatial resolution, but is the effect of transient attention on spatial resolution modulated by the size of the attentional cue? Would a gradual increase in the size of the cue lead to a gradual decrement in spatial resolution? To test these hypotheses, we used a texture segmentation task in which performance depends on spatial resolution, and systematically manipulated the size of the attentional cue: A bar of different lengths (Experiment 1) or a frame of different sizes (Experiments 2-3) indicated the target region in a texture segmentation display. Observers indicated whether a target patch region (oriented line elements in a background of an orthogonal orientation), appearing at a range of eccentricities, was present in the first or the second interval. We replicated the attentional enhancement of spatial resolution found with small cues; attention improved performance at peripheral locations but impaired performance at central locations. However, there was no evidence of gradual resolution decrement with large cues. Transient attention enhanced spatial resolution at the attended location when it was attracted to that location by a small cue but did not affect resolution when it was attracted by a large cue. These results indicate that transient attention cannot adapt its operation on spatial resolution on the basis of the size of the attentional cue.

Selecting a spatial resolution for estimation of per-field green leaf area index

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Williamson, H. Dawn

1988-01-01

For any application of multispectral scanner (MSS) data, a user is faced with a number of choices concerning the characteristics of the data; one of these is their spatial resolution. A pilot study was undertaken to determine the spatial resolution that would be optimal for the per-field estimation of green leaf area index (GLAI) in grassland. By reference to empirically-derived data from three areas of grassland, the suitable spatial resolution was hypothesized to lie in the lower portion of a 2-18 m range. To estimate per-field GLAI, airborne MSS data were collected at spatial resolutions of 2 m, 5 m and 10 m. The highest accuracies of per-field GLAI estimation were achieved using MSS data with spatial resolutions of 2 m and 5 m.

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution. [Sam Houston National Forest, Texas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.

1976-01-01

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

High Resolution Mesoscale Weather Data Improvement to Spatial Effects for Dose-Rate Contour Plot Predictions

DTIC Science & Technology

2007-03-01

time. This is a very powerful tool in determining fine spatial resolution , as boundary conditions are not only updated at every timestep, but the ...HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT PREDICTIONS THESIS Christopher P...11 1 HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT

Attention Modifies Spatial Resolution According to Task Demands.

PubMed

Barbot, Antoine; Carrasco, Marisa

2017-03-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands.

Attention Modifies Spatial Resolution According to Task Demands

PubMed Central

Barbot, Antoine; Carrasco, Marisa

2017-01-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands. PMID:28118103

Effects of spatial resolution

NASA Technical Reports Server (NTRS)

Abrams, M.

1982-01-01

Studies of the effects of spatial resolution on extraction of geologic information are woefully lacking but spatial resolution effects can be examined as they influence two general categories: detection of spatial features per se; and the effects of IFOV on the definition of spectral signatures and on general mapping abilities.

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

NASA Astrophysics Data System (ADS)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat-MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral resolution and abbreviated as HSLS, this method aims to generate the fused data with both high spatial and high spectral resolutions. Motivated by the observation that each hyperspectral pixel can be represented by a linear combination of a few endmembers, this method first extracts the spectral bases of LSHS and HSLS images by making full use of the rich spectral information in LSHS data. The spectral bases of these two categories data then formulate a dictionary-pair due to their correspondence in representing each pixel spectra of LSHS data and HSLS data, respectively. Subsequently, the LSHS image is spatially unmixed by representing the HSLS image with respect to the corresponding learned dictionary to derive its representation coefficients. Combining the spectral bases of LSHS data and the representation coefficients of HSLS data, we finally derive the fused data characterized by the spectral resolution of LSHS data and the spatial resolution of HSLS data.

Results of the spatial resolution simulation for multispectral data (resolution brochures)

NASA Technical Reports Server (NTRS)

1982-01-01

The variable information content of Earth Resource products at different levels of spatial resolution and in different spectral bands is addressed. A low-cost brochure that scientists and laymen could use to visualize the effects of increasing the spatial resolution of multispectral scanner images was produced.

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Spatial Resolution Requirements for Accurate Identification of Drivers of Atrial Fibrillation

PubMed Central

Roney, Caroline H.; Cantwell, Chris D.; Bayer, Jason D.; Qureshi, Norman A.; Lim, Phang Boon; Tweedy, Jennifer H.; Kanagaratnam, Prapa; Vigmond, Edward J.; Ng, Fu Siong

2017-01-01

Background— Recent studies have demonstrated conflicting mechanisms underlying atrial fibrillation (AF), with the spatial resolution of data often cited as a potential reason for the disagreement. The purpose of this study was to investigate whether the variation in spatial resolution of mapping may lead to misinterpretation of the underlying mechanism in persistent AF. Methods and Results— Simulations of rotors and focal sources were performed to estimate the minimum number of recording points required to correctly identify the underlying AF mechanism. The effects of different data types (action potentials and unipolar or bipolar electrograms) and rotor stability on resolution requirements were investigated. We also determined the ability of clinically used endocardial catheters to identify AF mechanisms using clinically recorded and simulated data. The spatial resolution required for correct identification of rotors and focal sources is a linear function of spatial wavelength (the distance between wavefronts) of the arrhythmia. Rotor localization errors are larger for electrogram data than for action potential data. Stationary rotors are more reliably identified compared with meandering trajectories, for any given spatial resolution. All clinical high-resolution multipolar catheters are of sufficient resolution to accurately detect and track rotors when placed over the rotor core although the low-resolution basket catheter is prone to false detections and may incorrectly identify rotors that are not present. Conclusions— The spatial resolution of AF data can significantly affect the interpretation of the underlying AF mechanism. Therefore, the interpretation of human AF data must be taken in the context of the spatial resolution of the recordings. PMID:28500175

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes themore » spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.« less

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

PubMed Central

Jansen, Michael; Li, Xiaobing; Lashgari, Reza; Kremkow, Jens; Bereshpolova, Yulia; Swadlow, Harvey A.; Zaidi, Qasim; Alonso, Jose-Manuel

2015-01-01

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color. PMID:25416722

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.

2014-10-07

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less

[An effective method for improving the imaging spatial resolution of terahertz time domain spectroscopy system].

PubMed

Zhang, Zeng-yan; Ji, Te; Zhu, Zhi-yong; Zhao, Hong-wei; Chen, Min; Xiao, Ti-qiao; Guo, Zhi

2015-01-01

Terahertz radiation is an electromagnetic radiation in the range between millimeter waves and far infrared. Due to its low energy and non-ionizing characters, THz pulse imaging emerges as a novel tool in many fields, such as material, chemical, biological medicine, and food safety. Limited spatial resolution is a significant restricting factor of terahertz imaging technology. Near field imaging method was proposed to improve the spatial resolution of terahertz system. Submillimeter scale's spauial resolution can be achieved if the income source size is smaller than the wawelength of the incoming source and the source is very close to the sample. But many changes were needed to the traditional terahertz time domain spectroscopy system, and it's very complex to analyze sample's physical parameters through the terahertz signal. A method of inserting a pinhole upstream to the sample was first proposed in this article to improve the spatial resolution of traditional terahertz time domain spectroscopy system. The measured spatial resolution of terahertz time domain spectroscopy system by knife edge method can achieve spatial resolution curves. The moving stage distance between 10 % and 90 Yo of the maximum signals respectively was defined as the, spatial resolution of the system. Imaging spatial resolution of traditional terahertz time domain spectroscopy system was improved dramatically after inserted a pinhole with diameter 0. 5 mm, 2 mm upstream to the sample. Experimental results show that the spatial resolution has been improved from 1. 276 mm to 0. 774 mm, with the increment about 39 %. Though this simple method, the spatial resolution of traditional terahertz time domain spectroscopy system was increased from millimeter scale to submillimeter scale. A pinhole with diameter 1 mm on a polyethylene plate was taken as sample, to terahertz imaging study. The traditional terahertz time domain spectroscopy system and pinhole inserted terahertz time domain spectroscopy system were applied in the imaging experiment respectively. The relative THz-power loss imaging of samples were use in this article. This method generally delivers the best signal to noise ratio in loss images, dispersion effects are cancelled. Terahertz imaging results show that the sample's boundary was more distinct after inserting the pinhole in front of, sample. The results also conform that inserting pinhole in front of sample can improve the imaging spatial resolution effectively. The theoretical analyses of the method which improve the spatial resolution by inserting a pinhole in front of sample were given in this article. The analyses also indicate that the smaller the pinhole size, the longer spatial coherence length of the system, the better spatial resolution of the system. At the same time the terahertz signal will be reduced accordingly. All the experimental results and theoretical analyses indicate that the method of inserting a pinhole in front of sample can improve the spatial resolution of traditional terahertz time domain spectroscopy system effectively, and it will further expand the application of terahertz imaging technology.

Multiscale study on stochastic reconstructions of shale samples

NASA Astrophysics Data System (ADS)

Lili, J.; Lin, M.; Jiang, W. B.

2016-12-01

Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared. The result indicates that the agreement between the original 3D sample and the generated stochastic realizations is excellent. This work is supported by "973" Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02) and the National Natural Science Foundation of China (Grant No. 41574129).

Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport

NASA Astrophysics Data System (ADS)

Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan

2015-10-01

Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.

Documenting Liquefaction Failures Using Satellite Remote Sensing and Artificial Intelligence Algorithms

NASA Astrophysics Data System (ADS)

Oommen, T.; Baise, L. G.; Gens, R.; Prakash, A.; Gupta, R. P.

2009-12-01

Historically, earthquake induced liquefaction is known to have caused extensive damage around the world. Therefore, there is a compelling need to characterize and map liquefaction after a seismic event. Currently, after an earthquake event, field-based mapping of liquefaction is sporadic and limited due to inaccessibility, short life of the failures, difficulties in mapping large aerial extents, and lack of resources. We hypothesize that as liquefaction occurs in saturated granular soils due to an increase in pore pressure, the liquefaction related terrain changes should have an associated increase in soil moisture with respect to the surrounding non-liquefied regions. The increase in soil moisture affects the thermal emittance and, hence, change detection using pre- and post-event thermal infrared (TIR) imagery is suitable for identifying areas that have undergone post-earthquake liquefaction. Though change detection using TIR images gives the first indication of areas of liquefaction, the spatial resolution of TIR images is typically coarser than the resolution of corresponding visible, near-infrared (NIR), and shortwave infrared (SWIR) images. We hypothesize that liquefaction induced changes in the soil and associated surface effects cause textural and spectral changes in images acquired in the visible, NIR, and SWIR. Although these changes can be from various factors, a synergistic approach taking advantage of the thermal signature variation due to changing soil moisture condition, together with the spectral information from high resolution visible, NIR, and SWIR bands can help to narrow down the locations of post-event liquefaction for regional documentation. In this study, we analyze the applicability of combining various spectral bands from different satellites (Landsat, Terra-MISR, IRS-1C, and IRS-1D) for documenting liquefaction failures associated with the magnitude 7.6 earthquake that occurred in Bhuj, India, in 2001. We combine the various spectral bands by neighborhood correlation image analysis using an artificial intelligence algorithm called support vector machine to remotely identify and document liquefaction failures across a region; and assess the reliability and accuracy of the thermal remote sensing approach in documenting regional liquefaction failures. Finally, we present the applicability of the satellite data analyzed and appropriateness of a multisensor and multispectral approach for documenting liquefaction related failures.

Tropical Cyclone Intensity in Global Models

NASA Astrophysics Data System (ADS)

Davis, C. A.; Wang, W.; Ahijevych, D.

2017-12-01

In recent years, global prediction and climate models have begun to depict intense tropical cyclones, even up to Category 5 on the Saffir-Simpson scale. In light of the limitation of horizontal resolution in such models, we examine the how well these models treat tropical cyclone intensity, measured from several different perspectives. The models evaluated include the operational Global Forecast System, with a grid spacing of about 13 km, and the Model for Prediction Across Scales, with a variable resolution of 15 km over the Northwest Pacific transitioning to 60 km elsewhere. We focus on the Northwest Pacific for the period July-October, 2016. Results indicate that discrimination of tropical cyclone intensity is reasonably good up to roughly category 3 storms. The models are able to capture storms of category 4 intensity, but still exhibit a negative intensity bias of 20-30 knots at lead times beyond 5 days. This is partly indicative of the large number of super-typhoons that occurred in 2016. The question arises of how well global models should represent intensity, given that it is unreasonable for them to depict the inner core of many intense tropical cyclones with a grid increment of 13-15 km. We compute an expected "best-case" prediction of intensity based on filtering the observed wind profiles of Atlantic tropical cyclones according to different hypothetical model resolutions. The Atlantic is used because of the significant number of reconnaissance missions and more reliable estimate of wind radii. Results indicate that, even under the most optimistic assumptions, models with horizontal grid spacing of 1/4 degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, models with a grid spacing of 1/4 degree or greater are unlikely to systematically discriminate hurricanes with differing intensity. Finally, for simple wind profiles, it is shown how an accurate representation of maximum wind on a coarse grid will lead to an overestimate of horizontally integrated kinetic energy by a factor of two or more.

Regional Estimates of Drought-Induced Tree Canopy Loss across Texas

NASA Astrophysics Data System (ADS)

Schwantes, A.; Swenson, J. J.; González-Roglich, M.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.

2015-12-01

The severe drought of 2011 killed millions of trees across the state of Texas. Drought-induced tree-mortality can have significant impacts to carbon cycling, regional biophysics, and community composition. We quantified canopy cover loss across the state using remotely sensed imagery from before and after the drought at multiple scales. First, we classified ~200 orthophotos (1-m spatial resolution) from the National Agriculture Imagery Program, using a supervised maximum likelihood classification. Area of canopy cover loss in these classifications was highly correlated (R2 = 0.8) with ground estimates of canopy cover loss, measured in 74 plots across 15 different sites in Texas. These 1-m orthophoto classifications were then used to calibrate and validate coarser scale (30-m) Landsat imagery to create wall-to-wall tree canopy cover loss maps across the state of Texas. We quantified percent dead and live canopy within each pixel of Landsat to create continuous maps of dead and live tree cover, using two approaches: (1) a zero-inflated beta distribution model and (2) a random forest algorithm. Widespread canopy loss occurred across all the major natural systems of Texas, with the Edwards Plateau region most affected. In this region, on average, 10% of the forested area was lost due to the 2011 drought. We also identified climatic thresholds that controlled the spatial distribution of tree canopy loss across the state. However, surprisingly, there were many local hot spots of canopy loss, suggesting that not only climatic factors could explain the spatial patterns of canopy loss, but rather other factors related to soil, landscape, management, and stand density also likely played a role. As increases in extreme droughts are predicted to occur with climate change, it will become important to define methods that can detect associated drought-induced tree mortality across large regions. These maps could then be used (1) to quantify impacts to carbon cycling and regional biophysics, (2) to better understand the spatiotemporal dynamics of tree mortality, and (3) to calibrate and/or validate mortality algorithms in regional models.

LANDSAT-D investigations in snow hydrology. [Sierra Nevada Mountains

NASA Technical Reports Server (NTRS)

Dozier, J.

1983-01-01

Thematic mapper data for the southern Sierra Nevada area were registered to digital topographic data and compared to LANDSAT MSS and NOAA-7 AVHRR data of snow covered areas in order to determine the errors associated with using coarser resolution and to qualify the information lost when high resolution data are not available. Both the zenith and the azimuth variations in the radiative field are considered in an atmospheric radiative transfer model which deals with a plane parallel structured atmosphere composed of different layers, each assumed to be homogeneous in composition and to have a linear in tau temperature profile. Astronomical parameters for each layer are Earth-Sun distance and solar flux at the top of the atmosphere. Atmospheric parameters include pressure temperature, chemical composition of the air molecules, and the composition and size of the aerosol, water droplets, and ice crystals. Outputs of the model are the monochromatic radiance and irradiance at each level. The use of the model in atmospheric correction of remotely sensed data is discussed.

Hazardous thunderstorm intensification over Lake Victoria

PubMed Central

Thiery, Wim; Davin, Edouard L.; Seneviratne, Sonia I.; Bedka, Kristopher; Lhermitte, Stef; van Lipzig, Nicole P. M.

2016-01-01

Weather extremes have harmful impacts on communities around Lake Victoria, where thousands of fishermen die every year because of intense night-time thunderstorms. Yet how these thunderstorms will evolve in a future warmer climate is still unknown. Here we show that Lake Victoria is projected to be a hotspot of future extreme precipitation intensification by using new satellite-based observations, a high-resolution climate projection for the African Great Lakes and coarser-scale ensemble projections. Land precipitation on the previous day exerts a control on night-time occurrence of extremes on the lake by enhancing atmospheric convergence (74%) and moisture availability (26%). The future increase in extremes over Lake Victoria is about twice as large relative to surrounding land under a high-emission scenario, as only over-lake moisture advection is high enough to sustain Clausius–Clapeyron scaling. Our results highlight a major hazard associated with climate change over East Africa and underline the need for high-resolution projections to assess local climate change. PMID:27658848

VizieR Online Data Catalog: LMC and Cen A 1.3-10GHz polarization behavior (Anderson+, 2016)

NASA Astrophysics Data System (ADS)

Anderson, C. S.; Gaensler, B. M.; Feain, I. J.

2016-08-01

The targets for our study were selected from among two archival polarization data sets, which were observed and processed by several independent groups. i.e. LMC observations spanning from 1994 Oct to 1996 Jan in 1.328-1.432GHz band; Cen A observations spanning from 2006 Dec to 2008 Feb in 1.296-1.480GHz band. We observed the 40 sample sources using the Australia Telescope Compact Array (ATCA) over 1.1-3.1GHz (16cm), 4.5-6.5GHz (6cm), and 8.0-10.0GHz (3cm) in full polarization with a nominal 1MHz channel resolution between 2012 Feb 10-12 and 2012 Aug 17-19. We imaged each source in Stokes I, Q, and U at 20MHz intervals through the 16 and 6cm bands, and at a substantially coarser resolution of 200MHz in the 3cm band. See sections 2 and 3 for further explanations. (2 data files).

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

PubMed

Piqueras, Sara; Bedia, Carmen; Beleites, Claudia; Krafft, Christoph; Popp, Jürgen; Maeder, Marcel; Tauler, Romà; de Juan, Anna

2018-06-05

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Polychaete Tubes, Turbulence, and Erosion of Fine-Grained Sediment

NASA Astrophysics Data System (ADS)

Kincke-Tootle, A.; Frank, D. P.; Briggs, K. B.; Calantoni, J.

2016-02-01

The role of polychaete tubes protruding through the benthic boundary layer in promoting or hindering erosion of fine-grained sediment was examined in laboratory experiments. Diver core samples of the top 10cm of sediment were collected west of Trinity Shoal off the Louisiana coast in 10-m depth. Diver cores were used in laboratory experiments conducted in a unidirectional flume. Tubes that were constructed by polychaetes, which comprised 70% of the species from the study area, were inserted into the core sediment surface. The sediment cores were then placed in the 2-m long test section of a small oscillatory flow tunnel and high-speed, stereo particle image velocimetry was used to determine the 2-dimensional, 3-component fluid velocity at high temporal (100 Hz) and spatial (< 1mm vector spacing) resolution. The tubes that protruded above the boundary layer allowed vortices to be initiated. Tubes are made up of shell fragments and fine-grained sediment, allowing for some rigidity and resistance to the flow. Rigidity determines the resistance causing small-scale eddies to form. The small-scale turbulence incited scour erosion, allowing fine-grained particles to be suspended into the water and in some cases coarser particles to be mobilized. Less-rigid tubes succumb to the shear stress, inhibit the formation of small-scale eddies, limit sediment erodibility, and increase the critical shear stress of the sediment. Discussion will focus on a modification to the critical Shields parameter to account for the effects of benthic biological activity.

Remote Sensing of Snow Cover. Section; Snow Extent

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Frei, Allan; Drey, Stephen J.

2012-01-01

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

NASA Astrophysics Data System (ADS)

Wiggins, B. B.; deSouza, Z. O.; Vadas, J.; Alexander, A.; Hudan, S.; deSouza, R. T.

2017-11-01

A second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gustafson, William I.; Ma, Po-Lun; Xiao, Heng

2013-08-29

The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependencemore » of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.« less

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance.

PubMed

Li, Ke; Garrett, John; Ge, Yongshuai; Chen, Guang-Hong

2014-07-01

Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDIvol =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo(®), GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d'. (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

Continuing global monitoring of anthropogenic and volcanic SO2 sources from Aura/OMI to SNPP/OMPS

NASA Astrophysics Data System (ADS)

Li, C.; Krotkov, N. A.; Carn, S. A.; Joiner, J.; McLinden, C. A.; Fioletov, V.

2017-12-01

Sulfur dioxide (SO2) is an important trace gas that has significant impacts on air quality, the climate, and stratospheric ozone. It is predominantly emitted from anthropogenic sources such as coal-fired power plants and smelters, but also has sizable sources from volcanic activity. The Ozone Monitoring Instrument (OMI) aboard NASA's Earth Observing System (EOS) Aura spacecraft has been providing global observations of both anthropogenic and volcanic SO2 since its launch in 2004. The Ozone Mapping and Profiler Suite (OMPS) nadir mapper, launched aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite in 2011, will continue the 13+ year OMI SO2 time series. However, it is a significant challenge to build a coherent data record between OMI and OMPS, as the SO2 signal is relatively weak and its retrieval is subject to a number of interferences such as ozone absorption. Additionally, the two instruments also have different spectral and spatial resolutions that result in different sensitivities to SO2. Even a relatively small error in retrievals, due to either algorithmic or instrumental factors, may lead to a large inter-instrument bias in SO2. In this presentation, we report on our latest effort and progress in developing EOS continuity SNPP/OMPS SO2 products. We have applied a consistent retrieval technique based on principal component analysis (PCA) of measured radiance data to both OMI and OMPS. We show that the PCA retrieval technique, which extracts principal components (PCs) from measured radiances and applies these PCs in spectral fitting to minimize the effects of various interfering processes, is capable of producing highly consistent OMI and OMPS SO2 data for both anthropogenic sources and large volcanic eruptions. To gain a quantitative understanding of the two instruments' capabilities of monitoring SO2 sources, we have also applied a new emission estimation technique that combines satellite SO2 and wind information to both of them. This method allows SO2 emissions from 500 sources worldwide to be detected and quantified from OMI data. The OMPS-based emission estimates using the same method agree well with OMI-based ones, although OMPS detects fewer of the smaller sources seen by OMI, owing to its coarser spatial resolution.

A dual resolution measurement based Monte Carlo simulation technique for detailed dose analysis of small volume organs in the skull base region

NASA Astrophysics Data System (ADS)

Yeh, Chi-Yuan; Tung, Chuan-Jung; Chao, Tsi-Chain; Lin, Mu-Han; Lee, Chung-Chi

2014-11-01

The purpose of this study was to examine dose distribution of a skull base tumor and surrounding critical structures in response to high dose intensity-modulated radiosurgery (IMRS) with Monte Carlo (MC) simulation using a dual resolution sandwich phantom. The measurement-based Monte Carlo (MBMC) method (Lin et al., 2009) was adopted for the study. The major components of the MBMC technique involve (1) the BEAMnrc code for beam transport through the treatment head of a Varian 21EX linear accelerator, (2) the DOSXYZnrc code for patient dose simulation and (3) an EPID-measured efficiency map which describes non-uniform fluence distribution of the IMRS treatment beam. For the simulated case, five isocentric 6 MV photon beams were designed to deliver a total dose of 1200 cGy in two fractions to the skull base tumor. A sandwich phantom for the MBMC simulation was created based on the patient's CT scan of a skull base tumor [gross tumor volume (GTV)=8.4 cm3] near the right 8th cranial nerve. The phantom, consisted of a 1.2-cm thick skull base region, had a voxel resolution of 0.05×0.05×0.1 cm3 and was sandwiched in between 0.05×0.05×0.3 cm3 slices of a head phantom. A coarser 0.2×0.2×0.3 cm3 single resolution (SR) phantom was also created for comparison with the sandwich phantom. A particle history of 3×108 for each beam was used for simulations of both the SR and the sandwich phantoms to achieve a statistical uncertainty of <2%. Our study showed that the planning target volume (PTV) receiving at least 95% of the prescribed dose (VPTV95) was 96.9%, 96.7% and 99.9% for the TPS, SR, and sandwich phantom, respectively. The maximum and mean doses to large organs such as the PTV, brain stem, and parotid gland for the TPS, SR and sandwich MC simulations did not show any significant difference; however, significant dose differences were observed for very small structures like the right 8th cranial nerve, right cochlea, right malleus and right semicircular canal. Dose volume histogram (DVH) analyses revealed much smoother DVH curves for the dual resolution sandwich phantom when compared to the SR phantom. In conclusion, MBMC simulations using a dual resolution sandwich phantom improved simulation spatial resolution for skull base IMRS therapy. More detailed dose analyses for small critical structures can be made available to help in clinical judgment.

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex.

PubMed

Jansen, Michael; Li, Xiaobing; Lashgari, Reza; Kremkow, Jens; Bereshpolova, Yulia; Swadlow, Harvey A; Zaidi, Qasim; Alonso, Jose-Manuel

2015-10-01

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color. © The Author 2014. Published by Oxford University Press.

The spatial resolution of silicon-based electron detectors in beta-autoradiography.

PubMed

Cabello, Jorge; Wells, Kevin

2010-03-21

Thin tissue autoradiography is an imaging modality where ex-vivo tissue sections are placed in direct contact with autoradiographic film. These tissue sections contain a radiolabelled ligand bound to a specific biomolecule under study. This radioligand emits beta - or beta+ particles ionizing silver halide crystals in the film. High spatial resolution autoradiograms are obtained using low energy radioisotopes, such as (3)H where an intrinsic 0.1-1 microm spatial resolution can be achieved. Several digital alternatives have been presented over the past few years to replace conventional film but their spatial resolution has yet to equal film, although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film. It will be shown in this work how pixel size is a critical parameter for achieving high spatial resolution for low energy uncollimated beta imaging. In this work we also examine the confounding factors impeding silicon-based technologies with respect to spatial resolution. The study considers charge diffusion in silicon and detector noise, and this is applied to a range of radioisotopes typically used in autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cornford, S. L.; Martin, D. F.; Lee, V.

At least in conventional hydrostatic ice-sheet models, the numerical error associated with grounding line dynamics can be reduced by modifications to the discretization scheme. These involve altering the integration formulae for the basal traction and/or driving stress close to the grounding line and exhibit lower – if still first-order – error in the MISMIP3d experiments. MISMIP3d may not represent the variety of real ice streams, in that it lacks strong lateral stresses, and imposes a large basal traction at the grounding line. We study resolution sensitivity in the context of extreme forcing simulations of the entire Antarctic ice sheet, using the BISICLES adaptive mesh ice-sheet model with two schemes: the original treatment, and a scheme, which modifies the discretization of the basal traction. The second scheme does indeed improve accuracy – by around a factor of two – for a given mesh spacing, butmore » $$\\lesssim 1$$ km resolution is still necessary. For example, in coarser resolution simulations Thwaites Glacier retreats so slowly that other ice streams divert its trunk. In contrast, with $$\\lesssim 1$$ km meshes, the same glacier retreats far more quickly and triggers the final phase of West Antarctic collapse a century before any such diversion can take place.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scaduto, DA; Hu, Y-H; Zhao, W

Purpose: Spatial resolution in digital breast tomosynthesis (DBT) is affected by inherent/binned detector resolution, oblique entry of x-rays, and focal spot size/motion; the limited angular range further limits spatial resolution in the depth-direction. While DBT is being widely adopted clinically, imaging performance metrics and quality control protocols have not been standardized. AAPM Task Group 245 on Tomosynthesis Quality Control has been formed to address this deficiency. Methods: Methods of measuring spatial resolution are evaluated using two prototype quality control phantoms for DBT. Spatial resolution in the detector plane is measured in projection and reconstruction domains using edge-spread function (ESF), point-spreadmore » function (PSF) and modulation transfer function (MTF). Spatial resolution in the depth-direction and effective slice thickness are measured in the reconstruction domain using slice sensitivity profile (SSP) and artifact spread function (ASF). An oversampled PSF in the depth-direction is measured using a 50 µm angulated tungsten wire, from which the MTF is computed. Object-dependent PSF is derived and compared with ASF. Sensitivity of these measurements to phantom positioning, imaging conditions and reconstruction algorithms is evaluated. Results are compared from systems of varying acquisition geometry (9–25 projections over 15–60°). Dependence of measurements on feature size is investigated. Results: Measurements of spatial resolution using PSF and LSF are shown to depend on feature size; depth-direction spatial resolution measurements are shown to similarly depend on feature size for ASF, though deconvolution with an object function removes feature size-dependence. A slanted wire may be used to measure oversampled PSFs, from which MTFs may be computed for both in-plane and depth-direction resolution. Conclusion: Spatial resolution measured using PSF is object-independent with sufficiently small object; MTF is object-independent. Depth-direction spatial resolution may be measured directly using MTF or indirectly using ASF or SSP as surrogate measurements. While MTF is object-independent, it is invalid for nonlinear reconstructions.« less

Spatial and temporal remote sensing data fusion for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

The suite of available remote sensing instruments varies widely in terms of sensor characteristics, spatial resolution and acquisition frequency. For example, the Moderate-resolution Imaging Spectroradiometer (MODIS) provides daily global observations at 250m to 1km spatial resolution. While imagery...

Development of a large-area Multigap RPC with adequate spatial resolution for muon tomography

NASA Astrophysics Data System (ADS)

Wang, J.; Wang, Y.; Wang, X.; Zeng, M.; Xie, B.; Han, D.; Lyu, P.; Wang, F.; Li, Y.

2016-11-01

We study the performance of a large-area 2-D Multigap Resistive Plate Chamber (MRPC) designed for muon tomography with high spatial resolution. An efficiency up to 98% and a spatial resolution of around 270 μ m are obtained in cosmic ray and X-ray tests. The performance of the MRPC is also investigated for two working gases: standard gas and pure Freon. The result shows that the MRPC working in pure Freon can provide higher efficiency and better spatial resolution.

Spatially extended hybrid methods: a review

PubMed Central

2018-01-01

Many biological and physical systems exhibit behaviour at multiple spatial, temporal or population scales. Multiscale processes provide challenges when they are to be simulated using numerical techniques. While coarser methods such as partial differential equations are typically fast to simulate, they lack the individual-level detail that may be required in regions of low concentration or small spatial scale. However, to simulate at such an individual level throughout a domain and in regions where concentrations are high can be computationally expensive. Spatially coupled hybrid methods provide a bridge, allowing for multiple representations of the same species in one spatial domain by partitioning space into distinct modelling subdomains. Over the past 20 years, such hybrid methods have risen to prominence, leading to what is now a very active research area across multiple disciplines including chemistry, physics and mathematics. There are three main motivations for undertaking this review. Firstly, we have collated a large number of spatially extended hybrid methods and presented them in a single coherent document, while comparing and contrasting them, so that anyone who requires a multiscale hybrid method will be able to find the most appropriate one for their need. Secondly, we have provided canonical examples with algorithms and accompanying code, serving to demonstrate how these types of methods work in practice. Finally, we have presented papers that employ these methods on real biological and physical problems, demonstrating their utility. We also consider some open research questions in the area of hybrid method development and the future directions for the field. PMID:29491179

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

2012-01-01

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

Some effects of finite spatial resolution on skin friction measurements in turbulent boundary layers

NASA Technical Reports Server (NTRS)

Westphal, Russell V.

1988-01-01

The effects of finite spatial resolution often cause serious errors in measurements in turbulent boundary layers, with particularly large effects for measurements of fluctuating skin friction and velocities within the sublayer. However, classical analyses of finite spatial resolution effects have generally not accounted for the substantial inhomogeneity and anisotropy of near-wall turbulence. The present study has made use of results from recent computational simulations of wall-bounded turbulent flows to examine spatial resolution effects for measurements made at a wall using both single-sensor probes and those employing two sensing volumes in a V shape. Results are presented to show the effects of finite spatial resolution on a variety of quantitites deduced from the skin friction field.

Running GCM physics and dynamics on different grids: Algorithm and tests

NASA Astrophysics Data System (ADS)

Molod, A.

2006-12-01

The major drawback in the use of sigma coordinates in atmospheric GCMs, namely the error in the pressure gradient term near sloping terrain, leaves the use of eta coordinates an important alternative. A central disadvantage of an eta coordinate, the inability to retain fine resolution in the vertical as the surface rises above sea level, is addressed here. An `alternate grid' technique is presented which allows the tendencies of state variables due to the physical parameterizations to be computed on a vertical grid (the `physics grid') which retains fine resolution near the surface, while the remaining terms in the equations of motion are computed using an eta coordinate (the `dynamics grid') with coarser vertical resolution. As a simple test of the technique a set of perpetual equinox experiments using a simplified lower boundary condition with no land and no topography were performed. The results show that for both low and high resolution alternate grid experiments, much of the benefit of increased vertical resolution for the near surface meridional wind (and mass streamfield) can be realized by enhancing the vertical resolution of the `physics grid' in the manner described here. In addition, approximately half of the increase in zonal jet strength seen with increased vertical resolution can be realized using the `alternate grid' technique. A pair of full GCM experiments with realistic lower boundary conditions and topography were also performed. It is concluded that the use of the `alternate grid' approach offers a promising way forward to alleviate a central problem associated with the use of the eta coordinate in atmospheric GCMs.

Characterization and modelling of the spatially- and spectrally-varying point-spread function in hyperspectral imaging systems for computational correction of axial optical aberrations

NASA Astrophysics Data System (ADS)

Špiclin, Žiga; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2012-03-01

Spatial resolution of hyperspectral imaging systems can vary significantly due to axial optical aberrations that originate from wavelength-induced index-of-refraction variations of the imaging optics. For systems that have a broad spectral range, the spatial resolution will vary significantly both with respect to the acquisition wavelength and with respect to the spatial position within each spectral image. Variations of the spatial resolution can be effectively characterized as part of the calibration procedure by a local image-based estimation of the pointspread function (PSF) of the hyperspectral imaging system. The estimated PSF can then be used in the image deconvolution methods to improve the spatial resolution of the spectral images. We estimated the PSFs from the spectral images of a line grid geometric caliber. From individual line segments of the line grid, the PSF was obtained by a non-parametric estimation procedure that used an orthogonal series representation of the PSF. By using the non-parametric estimation procedure, the PSFs were estimated at different spatial positions and at different wavelengths. The variations of the spatial resolution were characterized by the radius and the fullwidth half-maximum of each PSF and by the modulation transfer function, computed from images of USAF1951 resolution target. The estimation and characterization of the PSFs and the image deconvolution based spatial resolution enhancement were tested on images obtained by a hyperspectral imaging system with an acousto-optic tunable filter in the visible spectral range. The results demonstrate that the spatial resolution of the acquired spectral images can be significantly improved using the estimated PSFs and image deconvolution methods.

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Cole, Wesley

2016-11-14

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution

NASA Astrophysics Data System (ADS)

van Wessem, J. M.; Ligtenberg, S. R. M.; Reijmer, C. H.; van de Berg, W. J.; van den Broeke, M. R.; Barrand, N. E.; Thomas, E. R.; Turner, J.; Wuite, J.; Scambos, T. A.; van Meijgaard, E.

2016-02-01

This study presents a high-resolution (˜ 5.5 km) estimate of surface mass balance (SMB) over the period 1979-2014 for the Antarctic Peninsula (AP), generated by the regional atmospheric climate model RACMO2.3 and a firn densification model (FDM). RACMO2.3 is used to force the FDM, which calculates processes in the snowpack, such as meltwater percolation, refreezing and runoff. We evaluate model output with 132 in situ SMB observations and discharge rates from six glacier drainage basins, and find that the model realistically simulates the strong spatial variability in precipitation, but that significant biases remain as a result of the highly complex topography of the AP. It is also clear that the observations significantly underrepresent the high-accumulation regimes, complicating a full model evaluation. The SMB map reveals large accumulation gradients, with precipitation values above 3000 mm we yr-1 in the western AP (WAP) and below 500 mm we yr-1 in the eastern AP (EAP), not resolved by coarser data sets such as ERA-Interim. The average AP ice-sheet-integrated SMB, including ice shelves (an area of 4.1 × 105 km2), is estimated at 351 Gt yr-1 with an interannual variability of 58 Gt yr-1, which is dominated by precipitation (PR) (365 ± 57 Gt yr-1). The WAP (2.4 × 105 km2) SMB (276 ± 47 Gt yr-1), where PR is large (276 ± 47 Gt yr-1), dominates over the EAP (1.7 × 105 km2) SMB (75 ± 11 Gt yr-1) and PR (84 ± 11 Gt yr-1). Total sublimation is 11 ± 2 Gt yr-1 and meltwater runoff into the ocean is 4 ± 4 Gt yr-1. There are no significant trends in any of the modelled AP SMB components, except for snowmelt that shows a significant decrease over the last 36 years (-0.36 Gt yr-2).

Comparison of Measured and WRF-LES Turbulence Statistics in a Real Convective Boundary Layer over Complex Terrain

NASA Astrophysics Data System (ADS)

Rai, R. K.; Berg, L. K.; Kosovic, B.; Mirocha, J. D.; Pekour, M. S.; Shaw, W. J.

2015-12-01

Resolving the finest turbulent scales present in the lower atmosphere using numerical simulations helps to study the processes that occur in the atmospheric boundary layer, such as the turbulent inflow condition to the wind plant and the generation of the wake behind wind turbines. This work employs several nested domains in the WRF-LES framework to simulate conditions in a convectively driven cloud free boundary layer at an instrumented field site in complex terrain. The innermost LES domain (30 m spatial resolution) receives the boundary forcing from two other coarser resolution LES outer domains, which in turn receive boundary conditions from two WRF-mesoscale domains. Wind and temperature records from sonic anemometers mounted at two vertical levels (30 m and 60 m) are compared with the LES results in term of first and second statistical moments as well as power spectra and distributions of wind velocity. For the two mostly used boundary layer parameterizations (MYNN and YSU) tested in the WRF mesoscale domains, the MYNN scheme shows slightly better agreement with the observations for some quantities, such as time averaged velocity and Turbulent Kinetic Energy (TKE). However, LES driven by WRF-mesoscale simulations using either parameterization have similar velocity spectra and distributions of velocity. For each component of the wind velocity, WRF-LES power spectra are found to be comparable to the spectra derived from the measured data (for the frequencies that are accurately represented by WRF-LES). Furthermore, the analysis of LES results shows a noticeable variability of the mean and variance even over small horizontal distances that would be considered sub-grid scale in mesoscale simulations. This observed statistical variability in space and time can be utilized to further analyze the turbulence quantities over a heterogeneous surface and to improve the turbulence parameterization in the mesoscale model.

The Analysis of Burrows Recognition Accuracy in XINJIANG'S Pasture Area Based on Uav Visible Images with Different Spatial Resolution

NASA Astrophysics Data System (ADS)

Sun, D.; Zheng, J. H.; Ma, T.; Chen, J. J.; Li, X.

2018-04-01

The rodent disaster is one of the main biological disasters in grassland in northern Xinjiang. The eating and digging behaviors will cause the destruction of ground vegetation, which seriously affected the development of animal husbandry and grassland ecological security. UAV low altitude remote sensing, as an emerging technique with high spatial resolution, can effectively recognize the burrows. However, how to select the appropriate spatial resolution to monitor the calamity of the rodent disaster is the first problem we need to pay attention to. The purpose of this study is to explore the optimal spatial scale on identification of the burrows by evaluating the impact of different spatial resolution for the burrows identification accuracy. In this study, we shoot burrows from different flight heights to obtain visible images of different spatial resolution. Then an object-oriented method is used to identify the caves, and we also evaluate the accuracy of the classification. We found that the highest classification accuracy of holes, the average has reached more than 80 %. At the altitude of 24 m and the spatial resolution of 1cm, the accuracy of the classification is the highest We have created a unique and effective way to identify burrows by using UAVs visible images. We draw the following conclusion: the best spatial resolution of burrows recognition is 1 cm using DJI PHANTOM-3 UAV, and the improvement of spatial resolution does not necessarily lead to the improvement of classification accuracy. This study lays the foundation for future research and can be extended to similar studies elsewhere.

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch; Zaidi, Habib; Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailedmore » investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.« less

Remote sensing of ambient particles in Delhi and its environs: estimation and validation

PubMed Central

KUMAR, N.; CHU, A.; FOSTER, A.

2011-01-01

Recent advances in atmospheric remote sensing offer a unique opportunity to compute indirect estimates of air quality, particularly for developing countries that lack adequate spatial–temporal coverage of air pollution monitoring. The present research establishes an empirical relationship between satellite-based aerosol optical depth (AOD) and ambient particulate matter (PM) in Delhi and its environs. The PM data come from two different sources. Firstly, a field campaign was conducted to monitor airborne particles ≤ 2.5 μm and ≤10 μm in aerodynamic diameter (PM2.5 and PM10 respectively) at 113 spatially dispersed sites from July to December 2003 using photometric samplers. Secondly, data on eight hourly PM10 and total suspended particulate (TSP) matter, collected using gravimetric samplers, from 2000 to 2005 were acquired from the Central Pollution Control Board (CPCB). The aerosol optical depths were estimated from MODIS data, acquired from NASA’s Goddard Space Flight Center Earth Sciences Distributed Active Archive Center from 2000 to 2005. Both the PM and AOD data were collocated by time and space: PM mass ± 150 min of AOD time, and ± 2.5 and 5 km radius (separately) of the centroid of the AOD pixel for the 5 and 10 km AOD, respectively. The analysis here shows that PM correlates positively with the 5 km AOD; a 1% change in the AOD explains 0.52% ± 0.20% and 0.39% ± 0.15% changes in PM2.5 within 45 and 150 min intervals (of AOD data) respectively. At a coarser spatial resolution, however, the relationship between AOD and PM is relatively weak. But, the relationship turns significantly stronger when monthly estimates are analysed over a span of six years (2000 to 2005), especially for the winter months, which have relatively stable meteorological conditions. PMID:22162895

Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas.

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

An evaluation of spatial resolution of a prototype proton CT scanner.

PubMed

Plautz, Tia E; Bashkirov, V; Giacometti, V; Hurley, R F; Johnson, R P; Piersimoni, P; Sadrozinski, H F-W; Schulte, R W; Zatserklyaniy, A

2016-12-01

To evaluate the spatial resolution of proton CT using both a prototype proton CT scanner and Monte Carlo simulations. A custom cylindrical edge phantom containing twelve tissue-equivalent inserts with four different compositions at varying radial displacements from the axis of rotation was developed for measuring the modulation transfer function (MTF) of a prototype proton CT scanner. Two scans of the phantom, centered on the axis of rotation, were obtained with a 200 MeV, low-intensity proton beam: one scan with steps of 4°, and one scan with the phantom continuously rotating. In addition, Monte Carlo simulations of the phantom scan were performed using scanners idealized to various degrees. The data were reconstructed using an iterative projection method with added total variation superiorization based on individual proton histories. Edge spread functions in the radial and azimuthal directions were obtained using the oversampling technique. These were then used to obtain the modulation transfer functions. The spatial resolution was defined by the 10% value of the modulation transfer function (MTF 10% ) in units of line pairs per centimeter (lp/cm). Data from the simulations were used to better understand the contributions of multiple Coulomb scattering in the phantom and the scanner hardware, as well as the effect of discretization of proton location. The radial spatial resolution of the prototype proton CT scanner depends on the total path length, W, of the proton in the phantom, whereas the azimuthal spatial resolution depends both on W and the position, u - , at which the most-likely path uncertainty is evaluated along the path. For protons contributing to radial spatial resolution, W varies with the radial position of the edge, whereas for protons contributing to azimuthal spatial resolution, W is approximately constant. For a pixel size of 0.625 mm, the radial spatial resolution of the image reconstructed from the fully idealized simulation data ranged between 6.31 ± 0.36 lp/cm for W = 197 mm i.e., close to the center of the phantom, and 13.79 ± 0.36 lp/cm for W = 97 mm, near the periphery of the phantom. The azimuthal spatial resolution ranged from 6.99 ± 0.23 lp/cm at u - = 75 mm (near the center) to 11.20 ± 0.26 lp/cm at u - = 20 mm (near the periphery). Multiple Coulomb scattering limits the radial spatial resolution for path lengths greater than approximately 130 mm, and the azimuthal spatial resolution for positions of evaluation greater than approximately 40 mm for W = 199 mm. The radial spatial resolution of the image reconstructed from data from the 4° stepped experimental scan ranged from 5.11 ± 0.61 lp/cm for W = 197 mm to 8.58 ± 0.50 lp/cm for W = 97 mm. In the azimuthal direction, the spatial resolution ranged from 5.37 ± 0.40 lp/cm at u - = 75 mm to 7.27 ± 0.39 lp/cm at u - = 20 mm. The continuous scan achieved the same spatial resolution as that of the stepped scan. Multiple Coulomb scattering in the phantom is the limiting physical factor of the achievable spatial resolution of proton CT; additional loss of spatial resolution in the prototype system is associated with scattering in the proton tracking system and inadequacies of the proton path estimate used in the iterative reconstruction algorithm. Improvement in spatial resolution may be achievable by improving the most likely path estimate by incorporating information about high and low density materials, and by minimizing multiple Coulomb scattering in the proton tracking system.

An evaluation of spatial resolution of a prototype proton CT scanner

PubMed Central

Plautz, Tia E.; Bashkirov, V.; Giacometti, V.; Hurley, R. F.; Piersimoni, P.; Sadrozinski, H. F.-W.; Schulte, R. W.; Zatserklyaniy, A.

2016-01-01

Purpose: To evaluate the spatial resolution of proton CT using both a prototype proton CT scanner and Monte Carlo simulations. Methods: A custom cylindrical edge phantom containing twelve tissue-equivalent inserts with four different compositions at varying radial displacements from the axis of rotation was developed for measuring the modulation transfer function (MTF) of a prototype proton CT scanner. Two scans of the phantom, centered on the axis of rotation, were obtained with a 200 MeV, low-intensity proton beam: one scan with steps of 4°, and one scan with the phantom continuously rotating. In addition, Monte Carlo simulations of the phantom scan were performed using scanners idealized to various degrees. The data were reconstructed using an iterative projection method with added total variation superiorization based on individual proton histories. Edge spread functions in the radial and azimuthal directions were obtained using the oversampling technique. These were then used to obtain the modulation transfer functions. The spatial resolution was defined by the 10% value of the modulation transfer function (MTF10%) in units of line pairs per centimeter (lp/cm). Data from the simulations were used to better understand the contributions of multiple Coulomb scattering in the phantom and the scanner hardware, as well as the effect of discretization of proton location. Results: The radial spatial resolution of the prototype proton CT scanner depends on the total path length, W, of the proton in the phantom, whereas the azimuthal spatial resolution depends both on W and the position, u−, at which the most-likely path uncertainty is evaluated along the path. For protons contributing to radial spatial resolution, W varies with the radial position of the edge, whereas for protons contributing to azimuthal spatial resolution, W is approximately constant. For a pixel size of 0.625 mm, the radial spatial resolution of the image reconstructed from the fully idealized simulation data ranged between 6.31 ± 0.36 lp/cm for W = 197 mm i.e., close to the center of the phantom, and 13.79 ± 0.36 lp/cm for W = 97 mm, near the periphery of the phantom. The azimuthal spatial resolution ranged from 6.99 ± 0.23 lp/cm at u− = 75 mm (near the center) to 11.20 ± 0.26 lp/cm at u− = 20 mm (near the periphery). Multiple Coulomb scattering limits the radial spatial resolution for path lengths greater than approximately 130 mm, and the azimuthal spatial resolution for positions of evaluation greater than approximately 40 mm for W = 199 mm. The radial spatial resolution of the image reconstructed from data from the 4° stepped experimental scan ranged from 5.11 ± 0.61 lp/cm for W = 197 mm to 8.58 ± 0.50 lp/cm for W = 97 mm. In the azimuthal direction, the spatial resolution ranged from 5.37 ± 0.40 lp/cm at u− = 75 mm to 7.27 ± 0.39 lp/cm at u− = 20 mm. The continuous scan achieved the same spatial resolution as that of the stepped scan. Conclusions: Multiple Coulomb scattering in the phantom is the limiting physical factor of the achievable spatial resolution of proton CT; additional loss of spatial resolution in the prototype system is associated with scattering in the proton tracking system and inadequacies of the proton path estimate used in the iterative reconstruction algorithm. Improvement in spatial resolution may be achievable by improving the most likely path estimate by incorporating information about high and low density materials, and by minimizing multiple Coulomb scattering in the proton tracking system. PMID:27908179

Dependence of chromatic responses in V1 on visual field eccentricity and spatial frequency: an fMRI study.

PubMed

D'Souza, Dany V; Auer, Tibor; Frahm, Jens; Strasburger, Hans; Lee, Barry B

2016-03-01

Psychophysical sensitivity to red-green chromatic modulation decreases with visual eccentricity, compared to sensitivity to luminance modulation, even after appropriate stimulus scaling. This is likely to occur at a central, rather than a retinal, site. Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) responses to stimuli designed to separately stimulate different afferent channels' [red-green, luminance, and short-wavelength (S)-cone] circular gratings were recorded as a function of visual eccentricity (±10  deg) and spatial frequency (SF) in human primary visual cortex (V1) and further visual areas (V2v, V3v). In V1, the SF tuning of BOLD fMRI responses became coarser with eccentricity. For red-green and luminance gratings, similar SF tuning curves were found at all eccentricities. The pattern for S-cone modulation differed, with SF tuning changing more slowly with eccentricity than for the other two modalities. This may be due to the different retinal distribution with eccentricity of this receptor type. A similar pattern held in V2v and V3v. This would suggest that transformation or spatial filtering of the chromatic (red-green) signal occurs beyond these areas.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-03-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-07-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu; Garrett, John

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIRmore » (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.« less

High-resolution scanning precession electron diffraction: Alignment and spatial resolution.

PubMed

Barnard, Jonathan S; Johnstone, Duncan N; Midgley, Paul A

2017-03-01

Methods are presented for aligning the pivot point of a precessing electron probe in the scanning transmission electron microscope (STEM) and for assessing the spatial resolution in scanning precession electron diffraction (SPED) experiments. The alignment procedure is performed entirely in diffraction mode, minimising probe wander within the bright-field (BF) convergent beam electron diffraction (CBED) disk and is used to obtain high spatial resolution SPED maps. Through analysis of the power spectra of virtual bright-field images extracted from the SPED data, the precession-induced blur was measured as a function of precession angle. At low precession angles, SPED spatial resolution was limited by electronic noise in the scan coils; whereas at high precession angles SPED spatial resolution was limited by tilt-induced two-fold astigmatism caused by the positive spherical aberration of the probe-forming lens. Copyright © 2016 Elsevier B.V. All rights reserved.

Effect of Electric Field Gradient on Sub-nanometer Spatial Resolution of Tip-enhanced Raman Spectroscopy

PubMed Central

Meng, Lingyan; Yang, Zhilin; Chen, Jianing; Sun, Mengtao

2015-01-01

Tip-enhanced Raman spectroscopy (TERS) with sub-nanometer spatial resolution has been recently demonstrated experimentally. However, the physical mechanism underlying is still under discussion. Here we theoretically investigate the electric field gradient of a coupled tip-substrate system. Our calculations suggest that the ultra-high spatial resolution of TERS can be partially attributed to the electric field gradient effect owning to its tighter spatial confinement and sensitivity to the infrared (IR)-active of molecules. Particularly, in the case of TERS of flat-lying H2TBPP molecules,we find the electric field gradient enhancement is the dominating factor for the high spatial resolution, which qualitatively coincides with previous experimental report. Our theoretical study offers a new paradigm for understanding the mechanisms of the ultra-high spatial resolution demonstrated in tip-enhanced spectroscopy which is of importance but neglected. PMID:25784161

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

How Attention Affects Spatial Resolution

PubMed Central

Carrasco, Marisa; Barbot, Antoine

2015-01-01

We summarize and discuss a series of psychophysical studies on the effects of spatial covert attention on spatial resolution, our ability to discriminate fine patterns. Heightened resolution is beneficial in most, but not all, visual tasks. We show how endogenous attention (voluntary, goal driven) and exogenous attention (involuntary, stimulus driven) affect performance on a variety of tasks mediated by spatial resolution, such as visual search, crowding, acuity, and texture segmentation. Exogenous attention is an automatic mechanism that increases resolution regardless of whether it helps or hinders performance. In contrast, endogenous attention flexibly adjusts resolution to optimize performance according to task demands. We illustrate how psychophysical studies can reveal the underlying mechanisms of these effects and allow us to draw linking hypotheses with known neurophysiological effects of attention. PMID:25948640

Super-resolution optical microscopy for studying membrane structure and dynamics.

PubMed

Sezgin, Erdinc

2017-07-12

Investigation of cell membrane structure and dynamics requires high spatial and temporal resolution. The spatial resolution of conventional light microscopy is limited due to the diffraction of light. However, recent developments in microscopy enabled us to access the nano-scale regime spatially, thus to elucidate the nanoscopic structures in the cellular membranes. In this review, we will explain the resolution limit, address the working principles of the most commonly used super-resolution microscopy techniques and summarise their recent applications in the biomembrane field.

A multi-resolution approach to electromagnetic modeling.

NASA Astrophysics Data System (ADS)

Cherevatova, M.; Egbert, G. D.; Smirnov, M. Yu

2018-04-01

We present a multi-resolution approach for three-dimensional magnetotelluric forward modeling. Our approach is motivated by the fact that fine grid resolution is typically required at shallow levels to adequately represent near surface inhomogeneities, topography, and bathymetry, while a much coarser grid may be adequate at depth where the diffusively propagating electromagnetic fields are much smoother. This is especially true for forward modeling required in regularized inversion, where conductivity variations at depth are generally very smooth. With a conventional structured finite-difference grid the fine discretization required to adequately represent rapid variations near the surface are continued to all depths, resulting in higher computational costs. Increasing the computational efficiency of the forward modeling is especially important for solving regularized inversion problems. We implement a multi-resolution finite-difference scheme that allows us to decrease the horizontal grid resolution with depth, as is done with vertical discretization. In our implementation, the multi-resolution grid is represented as a vertical stack of sub-grids, with each sub-grid being a standard Cartesian tensor product staggered grid. Thus, our approach is similar to the octree discretization previously used for electromagnetic modeling, but simpler in that we allow refinement only with depth. The major difficulty arose in deriving the forward modeling operators on interfaces between adjacent sub-grids. We considered three ways of handling the interface layers and suggest a preferable one, which results in similar accuracy as the staggered grid solution, while retaining the symmetry of coefficient matrix. A comparison between multi-resolution and staggered solvers for various models show that multi-resolution approach improves on computational efficiency without compromising the accuracy of the solution.

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

USGS Publications Warehouse

Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

2014-01-01

Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE PAGES

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei; ...

2017-05-11

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method

NASA Astrophysics Data System (ADS)

Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.

2017-02-01

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

Coarsening of physics for biogeochemical model in NEMO

NASA Astrophysics Data System (ADS)

Bricaud, Clement; Le Sommer, Julien; Madec, Gurvan; Deshayes, Julie; Chanut, Jerome; Perruche, Coralie

2017-04-01

Ocean mesoscale and submesoscale turbulence contribute to ocean tracer transport and to shaping ocean biogeochemical tracers distribution. Representing adequately tracer transport in ocean models therefore requires to increase model resolution so that the impact of ocean turbulence is adequately accounted for. But due to supercomputers power and storage limitations, global biogeochemical models are not yet run routinely at eddying resolution. Still, because the "effective resolution" of eddying ocean models is much coarser than the physical model grid resolution, tracer transport can be reconstructed to a large extent by computing tracer transport and diffusion with a model grid resolution close to the effective resolution of the physical model. This observation has motivated the implementation of a new capability in NEMO ocean model (http://www.nemo-ocean.eu/) that allows to run the physical model and the tracer transport model at different grid resolutions. In a first time, we present results obtained with this new capability applied to a synthetic age tracer in a global eddying model configuration. In this model configuration, ocean dynamic is computed at ¼° resolution but tracer transport is computed at 3/4° resolution. The solution obtained is compared to 2 reference setup ,one at ¼° resolution for both physics and passive tracer models and one at 3/4° resolution for both physics and passive tracer model. We discuss possible options for defining the vertical diffusivity coefficient for the tracer transport model based on information from the high resolution grid. We describe the impact of this choice on the distribution and one the penetration of the age tracer. In a second time we present results obtained by coupling the physics with the biogeochemical model PISCES. We look at the impact of this methodology on some tracers distribution and dynamic. The method described here can found applications in ocean forecasting, such as the Copernicus Marine service operated by Mercator-Ocean, and in Earth System Models for climate applications.

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

NASA Technical Reports Server (NTRS)

Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.

1992-01-01

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Spatial resolution of a spherical x-ray crystal spectrometer at various magnifications

DOE PAGES

Gao, Lan; Hill, K. W.; Bitter, M.; ...

2016-08-23

Here, a high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ 2 rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystalmore » (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications ( M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Emotional cues enhance the attentional effects on spatial and temporal resolution.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-12-01

In the present study, we demonstrated that the emotional significance of a spatial cue enhances the effect of covert attention on spatial and temporal resolution (i.e., our ability to discriminate small spatial details and fast temporal flicker). Our results indicated that fearful face cues, as compared with neutral face cues, enhanced the attentional benefits in spatial resolution but also enhanced the attentional deficits in temporal resolution. Furthermore, we observed that the overall magnitudes of individuals' attentional effects correlated strongly with the magnitude of the emotion × attention interaction effect. Combined, these findings provide strong support for the idea that emotion enhances the strength of a cue's attentional response.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Teuling, Adriaan J.; Torfs, Paul J. J. F.; Uijlenhoet, Remko; Mizukami, Naoki; Clark, Martyn P.

2016-03-01

A meta-analysis on 192 peer-reviewed articles reporting on applications of the variable infiltration capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, L. A.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.; Mizukami, N.; Clark, M. P.

2015-12-01

A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Spatial resolution limits for the isotropic-3D PET detector X’tal cube

NASA Astrophysics Data System (ADS)

Yoshida, Eiji; Tashima, Hideaki; Hirano, Yoshiyuki; Inadama, Naoko; Nishikido, Fumihiko; Murayama, Hideo; Yamaya, Taiga

2013-11-01

Positron emission tomography (PET) has become a popular imaging method in metabolism, neuroscience, and molecular imaging. For dedicated human brain and small animal PET scanners, high spatial resolution is needed to visualize small objects. To improve the spatial resolution, we are developing the X’tal cube, which is our new PET detector to achieve isotropic 3D positioning detectability. We have shown that the X’tal cube can achieve 1 mm3 uniform crystal identification performance with the Anger-type calculation even at the block edges. We plan to develop the X’tal cube with even smaller 3D grids for sub-millimeter crystal identification. In this work, we investigate spatial resolution of a PET scanner based on the X’tal cube using Monte Carlo simulations for predicting resolution performance in smaller 3D grids. For spatial resolution evaluation, a point source emitting 511 keV photons was simulated by GATE for all physical processes involved in emission and interaction of positrons. We simulated two types of animal PET scanners. The first PET scanner had a detector ring 14.6 cm in diameter composed of 18 detectors. The second PET scanner had a detector ring 7.8 cm in diameter composed of 12 detectors. After the GATE simulations, we converted the interacting 3D position information to digitalized positions for realistic segmented crystals. We simulated several X’tal cubes with cubic crystals from (0.5 mm)3 to (2 mm)3 in size. Also, for evaluating the effect of DOI resolution, we simulated several X’tal cubes with crystal thickness from (0.5 mm)3 to (9 mm)3. We showed that sub-millimeter spatial resolution was possible using cubic crystals smaller than (1.0 mm)3 even with the assumed physical processes. Also, the weighted average spatial resolutions of both PET scanners with (0.5 mm)3 cubic crystals were 0.53 mm (14.6 cm ring diameter) and 0.48 mm (7.8 cm ring diameter). For the 7.8 cm ring diameter, spatial resolution with 0.5×0.5×1.0 mm3 crystals was improved 39% relative to the (1 mm)3 cubic crystals. On the other hand, spatial resolution with (0.5 mm)3 cubic crystals was improved 47% relative to the (1 mm)3 cubic crystals. The X’tal cube promises better spatial resolution for the 3D crystal block with isotropic resolution.

Toward Characterizing the 4D Structure of Precipitation at the Headwater Catchment Scale in Mountainous Regions

NASA Astrophysics Data System (ADS)

Barros, A. P.; Prat, O. P.; Sun, X.; Shrestha, P.; Miller, D.

2009-04-01

The classic conceptual model of orographic rainfall depicts strong stationary horizontal gradients in rainfall accumulations and landcover contrasts across topographic divides (i.e. the rainshadow) at the broad scale of mountain ranges, or isolated orographic features. Whereas this model is sufficient to fingerprint the land-modulation of precipitation at the macroscale in climate studies, and can be useful to force geological models of land evolution for example, it fails to describe the active 4D space-time gradients that are critical at the fundamental scale of mountain hydrometeorology and hydrology, that is the headwater catchment. That is, the scale at which flash-floods are generated and landslides are triggered. Our work surveying the spatial and temporal habits of clouds and rainfall for some of the world's major mountain ranges from remotely-sensed data shows a close alignment of spatial scaling behavior with landform down to the mountain fold scale, that is the ridge-valley. Likewise, we find that diurnal and seasonal cycles are organized and constrained by topography from the macro- to the meso- to the alpha-scale of individual basins varying with synoptic weather conditions. At the catchment scale, the diurnal cycle exhibits an oscillatory behavior with storm features moving up and down from the ridge crests to the valley floor and back and forth from head to mouth along the valley with strong variations in rainfall intensity and duration. Direct observations to provide quantitative estimates of precipitation at this scale are beyond the capability of satellite-based observations present and anticipated in the next 10-20 years. This limitation can be addressed by assimilating the space-time modes of variability of rainfall into satellite-observations at coarser scale using multiscale blending algorithms. The challenge is to characterize the modes of space-time variability of precipitation in a systematic, and quantitative fashion that can be generalized. It requires understanding the physical controls that govern the diurnal cycle and how these physical controls translate into spatial and temporal variability of dynamics and microphysics of precipitation in headwater catchments, and especially in the context of extreme events for natural hazards assessments. Toward this goal, we have initiated a sequence of number of intense observing period (IOP) campaigns in the Great Smoky Mountains National Park using radiosondes, tethersondes, microrain radars, and a high resolution raingauge network that for the first time monitors rainfall systematically along ridges in the Appalachians. Along with field observations, a high-resolution coupled model has been implemented to diagnose the evolution of the 4D structure of regional circulations and associated precipitation for IOP conditions and for reconstructing historical extremes associated with the interaction of tropical cyclones with the mountains. A synthesis of data analysis and model simulations will be presented.

Ocean Color Products Supporting the Assessment of Good Environmental Status: Development of a Spatial Distribution Model for the Seagrass Posidonia Oceanica (L.) Delille, 1813

NASA Astrophysics Data System (ADS)

Zucchetta, M.; Taji, M. A.; Mangin, A.; Pastres, R.

2015-12-01

Posidonia oceanica (L.) Delile, 1813 is a seagrass species endemic to the Mediterranean Sea, which is considered as one of the key habitats of the coastal areas. This species forms large meadows sensitive to several anthropogenic pressures, that can be regarded as indicators of environment quality in coastal environments and its distributional patterns should be take into account when evaluating the Environmental Status following the Ecosystem approach promoted by the Mediterranean Action Plan of UNEP and the EU Marine Strategy Framework Directive (2008/56/EC). The aim of this study was to develop a Species Distribution Model for P. oceanica, to be applied to the whole Mediterranean North African coast, in order to obtain an estimation of the potential distribution of this species in the region to be considered as an indicator for the assessment of good Environmental Status. As the study area is a data-poor zone with regard to seagrass distribution (i.e. only for some areas detailed distribution maps are available), the Species Distribution Model (SDM) was calibrated using high resolution data from 5 Mediterranean sites, located in Italy and Spain and validated using available data from the North African coast. Usually, when developing SDMs species occupancy data is available at coarser resolution than the information of environmental variables, and thus has to be downscaled at the appropriate grain to be coupled to the environmental conditions. Tackling the case of P. oceanica we had to face the opposite problem: the quality (in terms of resolution) of the information on seagrass distribution is generally very high compared to the environmental data available over large scale in marine domains (e.g. global bathymetry data). The high resolution application and the model transfer (from calibration areas to North African coast) was possible taking advantage of Ocean Color products: the probability of presence of the species in a given area was modelled using a binomial generalized linear model as a function of the bathymetry and some water characteristics mainly obtained from satellite data. Full resolution (c.a. 300m) Medium Resolution Imaging Spectrometer (MERIS) sensor imagery have been processed in order to extract a set of environmental variables to be coupled to seagrass distribution in the areas used to calibrate the model and for the whole North Africa coast (i.e. model application area). For the period 2003-2011 we processed data of: 1) the diffuse attenuation coefficient 2) coloured dissolved organic matter 3) Particle backscatter at 443nm; 4) Euphotic depth, estimated considering the coefficient of extinction of light; 5) Euphotic depth/ depth ratio, combining the estimation of euphotic depth with the bathymetry. Other variables have been resampled at MERIS full resolution, like data obtained from Moderate Resolution Imaging Spectroradiometer (MODIS; Sea Surface Temperature and Photosynthetically Available Radiation) or by model simulation (e.g. water salinity). The fitted model suggests that water transparency plays a major role, but also other variables, such as salinity and photosynthetically available radiation at surface, are important at larger spatial scales in explaining meadows distribution. The availability of high resolution time-series of input data allowed us to apply the validated model to the whole NA coast. Using model predictions to identify areas with suitable conditions for P. oceanica, it was possible to develop an indicator of potential habitat use and to define baseline reference conditions, necessary for the assessment of Good Environmental Status in Mediterranean coastal waters. This work shows how the Ocean and Land Colour Instrument (OLCI) within the Sentinel-3 mission can be exploited - thanks to the way opened by MERIS - to carry out the operational monitoring needed for the implementation of the UNEP MAP and EU MSFD Ecosystem Approach to the integrated management of land, water and living resources.

Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

NASA Astrophysics Data System (ADS)

Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

2017-12-01

Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.

Highly Coarse-Grained Representations of Transmembrane Proteins

PubMed Central

2017-01-01

Numerous biomolecules and biomolecular complexes, including transmembrane proteins (TMPs), are symmetric or at least have approximate symmetries. Highly coarse-grained models of such biomolecules, aiming at capturing the essential structural and dynamical properties on resolution levels coarser than the residue scale, must preserve the underlying symmetry. However, making these models obey the correct physics is in general not straightforward, especially at the highly coarse-grained resolution where multiple (∼3–30 in the current study) amino acid residues are represented by a single coarse-grained site. In this paper, we propose a simple and fast method of coarse-graining TMPs obeying this condition. The procedure involves partitioning transmembrane domains into contiguous segments of equal length along the primary sequence. For the coarsest (lowest-resolution) mappings, it turns out to be most important to satisfy the symmetry in a coarse-grained model. As the resolution is increased to capture more detail, however, it becomes gradually more important to match modular repeats in the secondary structure (such as helix-loop repeats) instead. A set of eight TMPs of various complexity, functionality, structural topology, and internal symmetry, representing different classes of TMPs (ion channels, transporters, receptors, adhesion, and invasion proteins), has been examined. The present approach can be generalized to other systems possessing exact or approximate symmetry, allowing for reliable and fast creation of multiscale, highly coarse-grained mappings of large biomolecular assemblies. PMID:28043122

Spatial resolution limitation of liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Wang, Xinghua; Wang, Bin; McManamon, Paul F., III; Pouch, John J.; Miranda, Felix A.; Anderson, James E.; Bos, Philip J.

2004-10-01

The effect of fringing electric fields in a liquid crystal (LC) Optical Phased Array (OPA), also referred to as a spatial light modulator (SLM), is a governing factor that determines the diffraction efficiency (DE) of the LC OPA for high resolution spatial phase modulation. In this article, the fringing field effect in a high resolution LC OPA is studied by accurate modeling the DE of the LC blazed gratings by LC director simulation and Finite Difference Time Domain (FDTD) simulation. Influence factors that contribute significantly to the DE are discussed. Such results provide fundamental understanding for high resolution LC devices.

Data for Figures and Tables in Journal Article Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations, doi:10.1016/j.atmosenv.2016.02.036

EPA Pesticide Factsheets

The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.This dataset is associated with the following publication

Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Fewtrell, Timothy J.; Duncan, Alastair; Sampson, Christopher C.; Neal, Jeffrey C.; Bates, Paul D.

2011-01-01

This paper describes benchmark testing of a diffusive and an inertial formulation of the de St. Venant equations implemented within the LISFLOOD-FP hydraulic model using high resolution terrestrial LiDAR data. The models are applied to a hypothetical flooding scenario in a section of Alcester, UK which experienced significant surface water flooding in the June and July floods of 2007 in the UK. The sensitivity of water elevation and velocity simulations to model formulation and grid resolution are analyzed. The differences in depth and velocity estimates between the diffusive and inertial approximations are within 10% of the simulated value but inertial effects persist at the wetting front in steep catchments. Both models portray a similar scale dependency between 50 cm and 5 m resolution which reiterates previous findings that errors in coarse scale topographic data sets are significantly larger than differences between numerical approximations. In particular, these results confirm the need to distinctly represent the camber and curbs of roads in the numerical grid when simulating surface water flooding events. Furthermore, although water depth estimates at grid scales coarser than 1 m appear robust, velocity estimates at these scales seem to be inconsistent compared to the 50 cm benchmark. The inertial formulation is shown to reduce computational cost by up to three orders of magnitude at high resolutions thus making simulations at this scale viable in practice compared to diffusive models. For the first time, this paper highlights the utility of high resolution terrestrial LiDAR data to inform small-scale flood risk management studies.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Generation of Accurate Lateral Boundary Conditions for a Surface-Water Groundwater Interaction Model

NASA Astrophysics Data System (ADS)

Khambhammettu, P.; Tsou, M.; Panday, S. M.; Kool, J.; Wei, X.

2010-12-01

The 106 mile long Peace River in Florida flows south from Lakeland to Charlotte Harbor and has a drainage basin of approximately 2,350 square miles. A long-term decline in stream flows and groundwater potentiometric levels has been observed in the region. Long-term trends in rainfall, along with effects of land use changes on runoff, surface-water storage, recharge and evapotranspiration patterns, and increased groundwater and surface-water withdrawals have contributed to this decline. The South West Florida Water Management District (SWFWMD) has funded the development of the Peace River Integrated Model (PRIM) to assess the effects of land use, water use, and climatic changes on stream flows and to evaluate the effectiveness of various management alternatives for restoring stream flows. The PRIM was developed using MODHMS, a fully integrated surface-water groundwater flow and transport simulator developed by HydroGeoLogic, Inc. The development of the lateral boundary conditions (groundwater inflow and outflow) for the PRIM in both historical and predictive contexts is discussed in this presentation. Monthly-varying specified heads were used to define the lateral boundary conditions for the PRIM. These head values were derived from the coarser Southern District Groundwater Model (SDM). However, there were discrepancies between the simulated SDM heads and measured heads: the likely causes being spatial (use of a coarser grid) and temporal (monthly average pumping rates and recharge rates) approximations in the regional SDM. Finer re-calibration of the SDM was not feasible, therefore, an innovative approach was adopted to remove the discrepancies. In this approach, point discrepancies/residuals between the observed and simulated heads were kriged with an appropriate variogram to generate a residual surface. This surface was then added to the simulated head surface of the SDM to generate a corrected head surface. This approach preserves the trends associated with groundwater pumping / recharge in the SDM and adds the kriged residual surface as variations back to the trend. The variations could be from the scale effects of grid resolution and from the temporal averaging of stresses (pumping, recharge, etc.,). The validity of the approach is demonstrated by visual and statistical comparison of the observed and simulated heads before and after correction. For predictive simulations, an Artificial Neural Network was trained to predict heads at monitoring wells based on precipitation and pumping. These predicted head values could then be used as surrogate observations for correcting the results of the regional SDM. In summary, an appropriate approach to link a regional groundwater model to a detailed surface-water groundwater interaction model is demonstrated with an example.

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

The spatial resolution of a rotating gamma camera tomographic facility.

PubMed

Webb, S; Flower, M A; Ott, R J; Leach, M O; Inamdar, R

1983-12-01

An important feature determining the spatial resolution in transverse sections reconstructed by convolution and back-projection is the frequency filter corresponding to the convolution kernel. Equations have been derived giving the theoretical spatial resolution, for a perfect detector and noise-free data, using four filter functions. Experiments have shown that physical constraints will always limit the resolution that can be achieved with a given system. The experiments indicate that the region of the frequency spectrum between KN/2 and KN where KN is the Nyquist frequency does not contribute significantly to resolution. In order to investigate the physical effect of these filter functions, the spatial resolution of reconstructed images obtained with a GE 400T rotating gamma camera has been measured. The results obtained serve as an aid to choosing appropriate reconstruction filters for use with a rotating gamma camera system.

A high time and spatial resolution MRPC designed for muon tomography

NASA Astrophysics Data System (ADS)

Shi, L.; Wang, Y.; Huang, X.; Wang, X.; Zhu, W.; Li, Y.; Cheng, J.

2014-12-01

A prototype of cosmic muon scattering tomography system has been set up in Tsinghua University in Beijing. Multi-gap Resistive Plate Chamber (MRPC) is used in the system to get the muon tracks. Compared with other detectors, MRPC can not only provide the track but also the Time of Flight (ToF) between two detectors which can estimate the energy of particles. To get a more accurate track and higher efficiency of the tomography system, a new type of high time and two-dimensional spatial resolution MRPC has been developed. A series of experiments have been done to measure the efficiency, time resolution and spatial resolution. The results show that the efficiency can reach 95% and its time resolution is around 65 ps. The cluster size is around 4 and the spatial resolution can reach 200 μ m.

150-μm Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images.

PubMed

Leng, Shuai; Rajendran, Kishore; Gong, Hao; Zhou, Wei; Halaweish, Ahmed F; Henning, Andre; Kappler, Steffen; Baer, Matthias; Fletcher, Joel G; McCollough, Cynthia H

2018-05-28

The aims of this study were to quantitatively assess two new scan modes on a photon-counting detector computed tomography system, each designed to maximize spatial resolution, and to qualitatively demonstrate potential clinical impact using patient data. This Health Insurance Portability Act-compliant study was approved by our institutional review board. Two high-spatial-resolution scan modes (Sharp and UHR) were evaluated using phantoms to quantify spatial resolution and image noise, and results were compared with the standard mode (Macro). Patients were scanned using a conventional energy-integrating detector scanner and the photon-counting detector scanner using the same radiation dose. In first patient images, anatomic details were qualitatively evaluated to demonstrate potential clinical impact. Sharp and UHR modes had a 69% and 87% improvement in in-plane spatial resolution, respectively, compared with Macro mode (10% modulation-translation-function values of 16.05, 17.69, and 9.48 lp/cm, respectively). The cutoff spatial frequency of the UHR mode (32.4 lp/cm) corresponded to a limiting spatial resolution of 150 μm. The full-width-at-half-maximum values of the section sensitivity profiles were 0.41, 0.44, and 0.67 mm for the thinnest image thickness for each mode (0.25, 0.25, and 0.5 mm, respectively). At the same in-plane spatial resolution, Sharp and UHR images had up to 15% lower noise than Macro images. Patient images acquired in Sharp mode demonstrated better delineation of fine anatomic structures compared with Macro mode images. Phantom studies demonstrated superior resolution and noise properties for the Sharp and UHR modes relative to the standard Macro mode and patient images demonstrated the potential benefit of these scan modes for clinical practice.

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Multi-Resolution Analysis of MODIS and ASTER Satellite Data for Water Classification

DTIC Science & Technology

2006-09-01

spectral bands, but also with different pixel resolutions . The overall goal... the total water surface. Due to the constraint that high spatial resolution satellite images are low temporal resolution , one needs a reliable method...at 15 m resolution , were processed. We used MODIS reflectance data from MOD02 Level 1B data. Even the spatial resolution of the 1240 nm

Definition of the Spatial Resolution of X-Ray Microanalysis in Thin Foils

NASA Technical Reports Server (NTRS)

Williams, D. B.; Michael, J. R.; Goldstein, J. I.; Romig, A. D., Jr.

1992-01-01

The spatial resolution of X-ray microanalysis in thin foils is defined in terms of the incident electron beam diameter and the average beam broadening. The beam diameter is defined as the full width tenth maximum of a Gaussian intensity distribution. The spatial resolution is calculated by a convolution of the beam diameter and the average beam broadening. This definition of the spatial resolution can be related simply to experimental measurements of composition profiles across interphase interfaces. Monte Carlo calculations using a high-speed parallel supercomputer show good agreement with this definition of the spatial resolution and calculations based on this definition. The agreement is good over a range of specimen thicknesses and atomic number, but is poor when excessive beam tailing distorts the assumed Gaussian electron intensity distributions. Beam tailing occurs in low-Z materials because of fast secondary electrons and in high-Z materials because of plural scattering.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Cole, Wesley

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

Moving towards Hyper-Resolution Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Rouf, T.; Maggioni, V.; Houser, P.; Mei, Y.

2017-12-01

Developing a predictive capability for terrestrial hydrology across landscapes, with water, energy and nutrients as the drivers of these dynamic systems, faces the challenge of scaling meter-scale process understanding to practical modeling scales. Hyper-resolution land surface modeling can provide a framework for addressing science questions that we are not able to answer with coarse modeling scales. In this study, we develop a hyper-resolution forcing dataset from coarser resolution products using a physically based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, roughness, and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. Hourly NLDAS (North America Land Data Assimilation System) forcing data (i.e., near-surface air temperature, pressure, and humidity) have been downscaled to 500m resolution over the study area for 2015-present. Results show that correlation coefficients between the downscaled temperature dataset and ground observations are consistently higher than the ones between the NLDAS temperature data at their native resolution and ground observations. Not only correlation coefficients are higher, but also the deviation around the 1:1 line in the density scatterplots is smaller for the downscaled dataset than the original one with respect to the ground observations. Results are therefore encouraging as they demonstrate that the 500m temperature dataset has a good agreement with the ground information and can be adopted to force the land surface model for soil moisture estimation. The study has been expanded to wind speed and direction, incident longwave and shortwave radiation, pressure, and precipitation. Precipitation is well known to vary dramatically with elevation and orography. Therefore, we are pursuing a downscaling technique based on both topographical and vegetation characteristics.

Effect of DEM resolution on rainfall-triggered landslide modeling within a triangulated network-based model. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Arnone, E.; Dialynas, Y. G.; Noto, L. V.; Bras, R. L.

2013-12-01

Catchment slope distribution is one of the topographic characteristics that significantly control rainfall-triggered landslide modeling, in both direct and indirect ways. Slope directly determines the soil volume associated with instability. Indirectly slope also affects the subsurface lateral redistribution of soil moisture across the basin, which in turn determines the water pore pressure conditions that impact slope stability. In this study, we investigate the influence of DEM resolution on slope stability and the slope stability analysis by using a distributed eco-hydrological and landslide model, the tRIBS-VEGGIE (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). The model implements a triangulated irregular network to describe the topography, and it is capable of evaluating vegetation dynamics and predicting shallow landslides triggered by rainfall. The impact of DEM resolution on the landslide prediction was studied using five TINs derived from five grid DEMs at different resolutions, i.e. 10, 20, 30, 50 and 70 m respectively. The analysis was carried out on the Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. Results showed that the use of the irregular mesh reduced the loss of accuracy in the derived slope distribution when coarser resolutions were used. The impact of the different resolutions on soil moisture patterns was important only when the lateral redistribution was considerable, depending on hydrological properties and rainfall forcing. In some cases, the use of different DEM resolutions did not significantly affect tRIBS-VEGGIE landslide output, in terms of landslide locations, and values of slope and soil moisture at failure.

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Use of UAS remote sensing data to estimate crop ET at high spatial resolution

USDA-ARS?s Scientific Manuscript database

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

Sub-millimetre DOI detector based on monolithic LYSO and digital SiPM for a dedicated small-animal PET system.

PubMed

Marcinkowski, Radosław; Mollet, Pieter; Van Holen, Roel; Vandenberghe, Stefaan

2016-03-07

The mouse model is widely used in a vast range of biomedical and preclinical studies. Thanks to the ability to detect and quantify biological processes at the molecular level in vivo, PET has become a well-established tool in these investigations. However, the need to visualize and quantify radiopharmaceuticals in anatomic structures of millimetre or less requires good spatial resolution and sensitivity from small-animal PET imaging systems.In previous work we have presented a proof-of-concept of a dedicated high-resolution small-animal PET scanner based on thin monolithic scintillator crystals and Digital Photon Counter photosensor. The combination of thin monolithic crystals and MLE positioning algorithm resulted in an excellent spatial resolution of 0.7 mm uniform in the entire field of view (FOV). However, the limitation of the scanner was its low sensitivity due to small thickness of the lutetium-yttrium oxyorthosilicate (LYSO) crystals (2 mm).Here we present an improved detector design for a small-animal PET system that simultaneously achieves higher sensitivity and sustains a sub-millimetre spatial resolution. The proposed detector consists of a 5 mm thick monolithic LYSO crystal optically coupled to a Digital Photon Counter. Mean nearest neighbour (MNN) positioning combined with depth of interaction (DOI) decoding was employed to achieve sub-millimetre spatial resolution. To evaluate detector performance the intrinsic spatial resolution, energy resolution and coincidence resolving time (CRT) were measured. The average intrinsic spatial resolution of the detector was 0.60 mm full-width-at-half-maximum (FWHM). A DOI resolution of 1.66 mm was achieved. The energy resolution was 23% FWHM at 511 keV and CRT of 529 ps were measured. The improved detector design overcomes the sensitivity limitation of the previous design by increasing the nominal sensitivity of the detector block and retains an excellent intrinsic spatial resolution.

The robustness of T2 value as a trabecular structural index at multiple spatial resolutions of 7 Tesla MRI.

PubMed

Lee, D K; Song, Y K; Park, B W; Cho, H P; Yeom, J S; Cho, G; Cho, H

2018-04-15

To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. The effects of MRI resolutions to T 2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T 2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T 2 and T2* were measured by degrading spatial resolutions on a 7 T system. In the defatted trabecular experiment, both T 2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm 3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| < 0.50) at spatial resolutions of 250 and 500 µm 3 . The correlations for T2* rapidly dropped ( |r| < 0.50) at a spatial resolution of 500 µm 3 , whereas those for T 2 remained consistently high ( |r| > 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm 3 , 2 minutes) T 2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm 3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). T 2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain. © 2018 International Society for Magnetic Resonance in Medicine.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

NASA Astrophysics Data System (ADS)

Gong, Kuang; Cherry, Simon R.; Qi, Jinyi

2016-03-01

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

High Efficiency Multi-shot Interleaved Spiral-In/Out Acquisition for High Resolution BOLD fMRI

PubMed Central

Jung, Youngkyoo; Samsonov, Alexey A.; Liu, Thomas T.; Buracas, Giedrius T.

2012-01-01

Growing demand for high spatial resolution BOLD functional MRI faces a challenge of the spatial resolution vs. coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in-out trajectory is preferred over spiral-in due to increased BOLD signal CNR and higher acquisition efficiency than that of spiral-out or non-interleaved spiral in/out trajectories (1), but to date applicability of the multi-shot interleaved spiral in-out for high spatial resolution imaging has not been studied. Herein we propose multi-shot interleaved spiral in-out acquisition and investigate its applicability for high spatial resolution BOLD fMRI. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2* decay, off-resonance and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in-out pulse sequence yields high BOLD CNR images at in-plane resolution below 1x1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multi-shot interleaved spiral in-out acquisition is a promising technique for high spatial resolution BOLD fMRI applications. PMID:23023395

The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI.

PubMed

Molloy, Erin K; Meyerand, Mary E; Birn, Rasmus M

2014-02-01

Functional MRI blood oxygen level-dependent (BOLD) signal changes can be subtle, motivating the use of imaging parameters and processing strategies that maximize the temporal signal-to-noise ratio (tSNR) and thus the detection power of neuronal activity-induced fluctuations. Previous studies have shown that acquiring data at higher spatial resolutions results in greater percent BOLD signal changes, and furthermore that spatially smoothing higher resolution fMRI data improves tSNR beyond that of data originally acquired at a lower resolution. However, higher resolution images come at the cost of increased acquisition time, and the number of image volumes also influences detectability. The goal of our study is to determine how the detection power of neuronally induced BOLD fluctuations acquired at higher spatial resolutions and then spatially smoothed compares to data acquired at the lower resolutions with the same imaging duration. The number of time points acquired during a given amount of imaging time is a practical consideration given the limited ability of certain populations to lie still in the MRI scanner. We compare acquisitions at three different in-plane spatial resolutions (3.50×3.50mm(2), 2.33×2.33mm(2), 1.75×1.75mm(2)) in terms of their tSNR, contrast-to-noise ratio, and the power to detect both task-related activation and resting-state functional connectivity. The impact of SENSE acceleration, which speeds up acquisition time increasing the number of images collected, is also evaluated. Our results show that after spatially smoothing the data to the same intrinsic resolution, lower resolution acquisitions have a slightly higher detection power of task-activation in some, but not all, brain areas. There were no significant differences in functional connectivity as a function of resolution after smoothing. Similarly, the reduced tSNR of fMRI data acquired with a SENSE factor of 2 is offset by the greater number of images acquired, resulting in few significant differences in detection power of either functional activation or connectivity after spatial smoothing. © 2013.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

A Comparison of Spatial and Spectral Image Resolution for Mapping Invasive Plants in Coastal California

NASA Astrophysics Data System (ADS)

Underwood, Emma C.; Ustin, Susan L.; Ramirez, Carlos M.

2007-01-01

We explored the potential of detecting three target invasive species: iceplant ( Carpobrotus edulis), jubata grass ( Cortaderia jubata), and blue gum ( Eucalyptus globulus) at Vandenberg Air Force Base, California. We compared the accuracy of mapping six communities (intact coastal scrub, iceplant invaded coastal scrub, iceplant invaded chaparral, jubata grass invaded chaparral, blue gum invaded chaparral, and intact chaparral) using four images with different combinations of spatial and spectral resolution: hyperspectral AVIRIS imagery (174 wavebands, 4 m spatial resolution), spatially degraded AVIRIS (174 bands, 30 m), spectrally degraded AVIRIS (6 bands, 4 m), and both spatially and spectrally degraded AVIRIS (6 bands, 30 m, i.e., simulated Landsat ETM data). Overall success rates for classifying the six classes was 75% (kappa 0.7) using full resolution AVIRIS, 58% (kappa 0.5) for the spatially degraded AVIRIS, 42% (kappa 0.3) for the spectrally degraded AVIRIS, and 37% (kappa 0.3) for the spatially and spectrally degraded AVIRIS. A true Landsat ETM image was also classified to illustrate that the results from the simulated ETM data were representative, which provided an accuracy of 50% (kappa 0.4). Mapping accuracies using different resolution images are evaluated in the context of community heterogeneity (species richness, diversity, and percent species cover). Findings illustrate that higher mapping accuracies are achieved with images possessing high spectral resolution, thus capturing information across the visible and reflected infrared solar spectrum. Understanding the tradeoffs in spectral and spatial resolution can assist land managers in deciding the most appropriate imagery with respect to target invasives and community characteristics.

Effects of Nonsphericity on the Behavior of Lorenz-Mie Resonances in Scattering Characteristics of Liquid-Cloud Droplets

NASA Technical Reports Server (NTRS)

Dlugach, Janna M.; Mishchenko, Michael I.

2014-01-01

By using the results of highly accurate T-matrix computations for randomly oriented oblate and prolate spheroids and Chebyshev particles with varying degrees of asphericity, we analyze the effects of a deviation of water-droplet shapes from that of a perfect sphere on the behavior of Lorenz-Mie morphology-dependent resonances of various widths. We demonstrate that the positions and profiles of the resonances can change significantly with increasing asphericity. The absolute degree of asphericity required to suppress a Lorenz-Mie resonance is approximately proportional to the resonance width. Our results imply that numerical averaging of scattering characteristics of real cloud droplets over sizes may rely on a significantly coarser size-parameter resolution than that required for ideal, perfectly spherical particles.

Error Estimation in an Optimal Interpolation Scheme for High Spatial and Temporal Resolution SST Analyses

NASA Technical Reports Server (NTRS)

Rigney, Matt; Jedlovec, Gary; LaFontaine, Frank; Shafer, Jaclyn

2010-01-01

Heat and moisture exchange between ocean surface and atmosphere plays an integral role in short-term, regional NWP. Current SST products lack both spatial and temporal resolution to accurately capture small-scale features that affect heat and moisture flux. NASA satellite is used to produce high spatial and temporal resolution SST analysis using an OI technique.

Instrumentation in molecular imaging.

PubMed

Wells, R Glenn

2016-12-01

In vivo molecular imaging is a challenging task and no single type of imaging system provides an ideal solution. Nuclear medicine techniques like SPECT and PET provide excellent sensitivity but have poor spatial resolution. Optical imaging has excellent sensitivity and spatial resolution, but light photons interact strongly with tissues and so only small animals and targets near the surface can be accurately visualized. CT and MRI have exquisite spatial resolution, but greatly reduced sensitivity. To overcome the limitations of individual modalities, molecular imaging systems often combine individual cameras together, for example, merging nuclear medicine cameras with CT or MRI to allow the visualization of molecular processes with both high sensitivity and high spatial resolution.

Microdome-gooved Gd(2)O(2)S:Tb scintillator for flexible and high resolution digital radiography.

PubMed

Jung, Phill Gu; Lee, Chi Hoon; Bae, Kong Myeong; Lee, Jae Min; Lee, Sang Min; Lim, Chang Hwy; Yun, Seungman; Kim, Ho Kyung; Ko, Jong Soo

2010-07-05

A flexible microdome-grooved Gd(2)O(2)S:Tb scintillator is simulated, fabricated, and characterized for digital radiography applications. According to Monte Carlo simulation results, the dome-grooved structure has a high spatial resolution, which is verified by X-ray image performance of the scintillator. The proposed scintillator has lower X-ray sensitivity than a nonstructured scintillator but almost two times higher spatial resolution at high spatial frequency. Through evaluation of the X-ray performance of the fabricated scintillators, we confirm that the microdome-grooved scintillator can be applied to next-generation flexible digital radiography systems requiring high spatial resolution.

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

2016-05-01

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Impaired temporal, not just spatial, resolution in amblyopia.

PubMed

Spang, Karoline; Fahle, Manfred

2009-11-01

In amblyopia, neuronal deficits deteriorate spatial vision including visual acuity, possibly because of a lack of use-dependent fine-tuning of afferents to the visual cortex during infancy; but temporal processing may deteriorate as well. Temporal, rather than spatial, resolution was investigated in patients with amblyopia by means of a task based on time-defined figure-ground segregation. Patients had to indicate the quadrant of the visual field where a purely time-defined square appeared. The results showed a clear decrease in temporal resolution of patients' amblyopic eyes compared with the dominant eyes in this task. The extent of this decrease in figure-ground segregation based on time of motion onset only loosely correlated with the decrease in spatial resolution and spanned a smaller range than did the spatial loss. Control experiments with artificially induced blur in normal observers confirmed that the decrease in temporal resolution was not simply due to the acuity loss. Amblyopia not only decreases spatial resolution, but also temporal factors such as time-based figure-ground segregation, even at high stimulus contrasts. This finding suggests that the realm of neuronal processes that may be disturbed in amblyopia is larger than originally thought.

The influence of 14CO2 releases from regional nuclear facilities at the Heidelberg 14CO2 sampling site (1986-2014)

NASA Astrophysics Data System (ADS)

Kuderer, Matthias; Hammer, Samuel; Levin, Ingeborg

2018-06-01

Atmospheric Δ14CO2 measurements are a well-established tool to estimate the regional fossil-fuel-derived CO2 component. However, emissions from nuclear facilities can significantly alter the regional Δ14CO2 level. In order to accurately quantify the signal originating from fossil CO2 emissions, a correction term for anthropogenic 14CO2 sources has to be determined. In this study, the HYSPLIT atmospheric dispersion model has been applied to calculate this correction for the long-term Δ14CO2 monitoring site in Heidelberg. Wind fields with a spatial resolution of 2.5° × 2.5°, 1° × 1°, and 0.5° × 0.5° show systematic deviations, with coarser resolved wind fields leading to higher mean values for the correction. The finally applied mean Δ14CO2 correction for the period from 1986-2014 is 2.3 ‰ with a standard deviation of 2.1 ‰ and maximum values up to 15.2 ‰. These results are based on the 0.5° × 0.5° wind field simulations in years when these fields were available (2009, 2011-2014), and for the other years they are based on 2.5° × 2.5° wind field simulations, corrected with a factor of 0.43. After operations at the Philippsburg boiling water reactor ceased in 2011, the monthly nuclear correction terms decreased to less than 2 ‰, with a mean value of 0.44 ± 0.32 ‰ from 2012 to 2014.

Significance of floods in metal dynamics and export in a small agricultural catchment

NASA Astrophysics Data System (ADS)

Roussiez, Vincent; Probst, Anne; Probst, Jean-Luc

2013-08-01

High-resolution monitoring of water discharge and water sampling were performed between early October 2006 and late September 2007 in the Montoussé River, a permanent stream draining an experimental agricultural catchment in Gascogne region (SW France). Dissolved and particulate concentrations of major elements and trace metals (i.e. Al, Fe, Mn, As, Cd, Cr, Cu, Ni, Pb, Sc and Zn) were examined. Our results showed that contamination levels were deficient to moderate, as a result of sustainable agricultural practices. Regarding dynamics, metal partitioning between particulate and dissolved phases was altered during flood conditions: the particulate phase was diluted by coarser and less contaminated particles from river bottom and banks, whereas the liquid phase was rapidly enriched owing to desorption mechanisms. Soluble/reactive elements were washed-off from soils at the beginning of the rain episode. The contribution of the flood event of May 2007 (by far the most significant episode over the study period) to the annual metal export was considerable for particulate forms (72-82%) and moderate for dissolved elements (0-20%). The hydrological functioning of the Montoussé stream poses dual threat on ecosystems, the consequences of which differ from both temporal and spatial scales: (i) desorption processes at the beginning of floods induce locally a rapid enrichment (up to 3.4-fold the pre-flood signatures on average for the event of May 2007) of waters in bioavailable metals, and (ii) labile metals - enriched by anthropogenic sources - associated to particles (mainly via carbonates and Fe/Mn oxides), were predominantly transferred during floods into downstream-connected rivers.

An algorithm for calculating minimum Euclidean distance between two geographic features

NASA Astrophysics Data System (ADS)

Peuquet, Donna J.

1992-09-01

An efficient algorithm is presented for determining the shortest Euclidean distance between two features of arbitrary shape that are represented in quadtree form. These features may be disjoint point sets, lines, or polygons. It is assumed that the features do not overlap. Features also may be intertwined and polygons may be complex (i.e. have holes). Utilizing a spatial divide-and-conquer approach inherent in the quadtree data model, the basic rationale is to narrow-in on portions of each feature quickly that are on a facing edge relative to the other feature, and to minimize the number of point-to-point Euclidean distance calculations that must be performed. Besides offering an efficient, grid-based alternative solution, another unique and useful aspect of the current algorithm is that is can be used for rapidly calculating distance approximations at coarser levels of resolution. The overall process can be viewed as a top-down parallel search. Using one list of leafcode addresses for each of the two features as input, the algorithm is implemented by successively dividing these lists into four sublists for each descendant quadrant. The algorithm consists of two primary phases. The first determines facing adjacent quadrant pairs where part or all of the two features are separated between the two quadrants, respectively. The second phase then determines the closest pixel-level subquadrant pairs within each facing quadrant pair at the lowest level. The key element of the second phase is a quick estimate distance heuristic for further elimination of locations that are not as near as neighboring locations.

Performance of multi-physics ensembles in convective precipitation events over northeastern Spain

NASA Astrophysics Data System (ADS)

García-Ortega, E.; Lorenzana, J.; Merino, A.; Fernández-González, S.; López, L.; Sánchez, J. L.

2017-07-01

Convective precipitation with hail greatly affects southwestern Europe, causing major economic losses. The local character of this meteorological phenomenon is a serious obstacle to forecasting. Therefore, the development of reliable short-term forecasts constitutes an essential challenge to minimizing and managing risks. However, deterministic outcomes are affected by different uncertainty sources, such as physics parameterizations. This study examines the performance of different combinations of physics schemes of the Weather Research and Forecasting model to describe the spatial distribution of precipitation in convective environments with hail falls. Two 30-member multi-physics ensembles, with two and three domains of maximum resolution 9 and 3km each, were designed using various combinations of cumulus, microphysics and radiation schemes. The experiment was evaluated for 10 convective precipitation days with hail over 2005-2010 in northeastern Spain. Different indexes were used to evaluate the ability of each ensemble member to capture the precipitation patterns, which were compared with observations of a rain-gauge network. A standardized metric was constructed to identify optimal performers. Results show interesting differences between the two ensembles. In two domain simulations, the selection of cumulus parameterizations was crucial, with the Betts-Miller-Janjic scheme the best. In contrast, the Kain-Fristch cumulus scheme gave the poorest results, suggesting that it should not be used in the study area. Nevertheless, in three domain simulations, the cumulus schemes used in coarser domains were not critical and the best results depended mainly on microphysics schemes. The best performance was shown by Morrison, New Thomson and Goddard microphysics.

Spatial Resolution and Refractive Index Contrast of Resonant Photonic Crystal Surfaces for Biosensing

PubMed Central

Triggs, G. J.; Fischer, M.; Stellinga, D.; Scullion, M. G.; Evans, G. J. O.; Krauss, T. F.

2015-01-01

By depositing a resolution test pattern on top of a Si3N4 photonic crystal resonant surface, we have measured the dependence of spatial resolution on refractive index contrast Δn. Our experimental results and finite-difference time-domain (FDTD) simulations at different refractive index contrasts show that the spatial resolution of our device reduces with reduced contrast, which is an important consideration in biosensing, where the contrast may be of order 10−2. We also compare 1-D and 2-D gratings, taking into account different incidence polarizations, leading to a better understanding of the excitation and propagation of the resonant modes in these structures, as well as how this contributes to the spatial resolution. At Δn = 0.077, we observe resolutions of 2 and 6 μm parallel to and perpendicular to the grooves of a 1-D grating, respectively, and show that for polarized illumination of a 2-D grating, resolution remains asymmetrical. Illumination of a 2-D grating at 45° results in symmetric resolution. At very low index contrast, the resolution worsens dramatically, particularly for Δn < 0.01, where we observe a resolution exceeding 10 μm for our device. In addition, we measure a reduction in the resonance linewidth as the index contrast becomes lower, corresponding to a longer resonant mode propagation length in the structure and contributing to the change in spatial resolution. PMID:26356353

The impact of wind energy turbine piles on ocean dynamics

NASA Astrophysics Data System (ADS)

Grashorn, Sebastian; Stanev, Emil V.

2016-04-01

The small- and meso-scale ocean response to wind parks has not been investigated in the southern North Sea until now with the help of high-resolution numerical modelling. Obstacles such as e.g. wind turbine piles may influence the ocean current system and produce turbulent kinetic energy which could affect sediment dynamics in the surrounding area. Two setups of the unstructured-grid model SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) have been developed for an idealized channel including a surface piercing cylindrical obstacle representing the pile and a more realistic test case including four exemplary piles. Experiments using a constant flow around the obstacles and a rotating M2 tidal wave are carried out. The resulting current and turbulence patterns are investigated to estimate the influence of the obstacles on the surrounding ocean dynamics. We demonstrate that using an unstructured ocean model provides the opportunity to embed a high-resolution representation of a wind park turbine pile system into a coarser North Sea setup, which is needed in order to perform a seamless investigation of the resulting geophysical processes.

Grating-based X-ray Dark-field Computed Tomography of Living Mice.

PubMed

Velroyen, A; Yaroshenko, A; Hahn, D; Fehringer, A; Tapfer, A; Müller, M; Noël, P B; Pauwels, B; Sasov, A; Yildirim, A Ö; Eickelberg, O; Hellbach, K; Auweter, S D; Meinel, F G; Reiser, M F; Bech, M; Pfeiffer, F

2015-10-01

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural - and thus indirectly functional - changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue.

Grating-based X-ray Dark-field Computed Tomography of Living Mice

PubMed Central

Velroyen, A.; Yaroshenko, A.; Hahn, D.; Fehringer, A.; Tapfer, A.; Müller, M.; Noël, P.B.; Pauwels, B.; Sasov, A.; Yildirim, A.Ö.; Eickelberg, O.; Hellbach, K.; Auweter, S.D.; Meinel, F.G.; Reiser, M.F.; Bech, M.; Pfeiffer, F.

2015-01-01

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural – and thus indirectly functional – changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue. PMID:26629545

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Electric crosstalk impairs spatial resolution of multi-electrode arrays in retinal implants

NASA Astrophysics Data System (ADS)

Wilke, R. G. H.; Khalili Moghadam, G.; Lovell, N. H.; Suaning, G. J.; Dokos, S.

2011-08-01

Active multi-electrode arrays are used in vision prostheses, including optic nerve cuffs and cortical and retinal implants for stimulation of neural tissue. For retinal implants, arrays with up to 1500 electrodes are used in clinical trials. The ability to convey information with high spatial resolution is critical for these applications. To assess the extent to which spatial resolution is impaired by electric crosstalk, finite-element simulation of electric field distribution in a simplified passive tissue model of the retina is performed. The effects of electrode size, electrode spacing, distance to target cells, and electrode return configuration (monopolar, tripolar, hexagonal) on spatial resolution is investigated in the form of a mathematical model of electric field distribution. Results show that spatial resolution is impaired with increased distance from the electrode array to the target cells. This effect can be partly compensated by non-monopolar electrode configurations and larger electrode diameters, albeit at the expense of lower pixel densities due to larger covering areas by each stimulation electrode. In applications where multi-electrode arrays can be brought into close proximity to target cells, as presumably with epiretinal implants, smaller electrodes in monopolar configuration can provide the highest spatial resolution. However, if the implantation site is further from the target cells, as is the case in suprachoroidal approaches, hexagonally guarded electrode return configurations can convey higher spatial resolution. This paper was originally submitted for the special issue containing contributions from the Sixth Biennial Research Congress of The Eye and the Chip.

Adaptive mesh refinement versus subgrid friction interpolation in simulations of Antarctic ice dynamics

DOE PAGES

Cornford, S. L.; Martin, D. F.; Lee, V.; ...

2016-05-13

At least in conventional hydrostatic ice-sheet models, the numerical error associated with grounding line dynamics can be reduced by modifications to the discretization scheme. These involve altering the integration formulae for the basal traction and/or driving stress close to the grounding line and exhibit lower – if still first-order – error in the MISMIP3d experiments. MISMIP3d may not represent the variety of real ice streams, in that it lacks strong lateral stresses, and imposes a large basal traction at the grounding line. We study resolution sensitivity in the context of extreme forcing simulations of the entire Antarctic ice sheet, using the BISICLES adaptive mesh ice-sheet model with two schemes: the original treatment, and a scheme, which modifies the discretization of the basal traction. The second scheme does indeed improve accuracy – by around a factor of two – for a given mesh spacing, butmore » $$\\lesssim 1$$ km resolution is still necessary. For example, in coarser resolution simulations Thwaites Glacier retreats so slowly that other ice streams divert its trunk. In contrast, with $$\\lesssim 1$$ km meshes, the same glacier retreats far more quickly and triggers the final phase of West Antarctic collapse a century before any such diversion can take place.« less

High resolution simulations on the North Aegean Sea seasonal circulation

NASA Astrophysics Data System (ADS)

Kourafalou, V. H.; Barbopoulos, K.

2003-01-01

The seasonal characteristics of the circulation in the North Aegean Sea are examined with the aid of a climatological type simulation (three-year run with perpetual year forcing) on a fine resolution grid (2.5 km by 2.5 km). The model is based on the Princeton Ocean Model with a parameterisation of plume dynamics that is employed for the input of waters with hydrographic properties that are different than the properties of basin waters, as the Black Sea Water (BSW) outflow through the Dardanelles Strait and riverine sources. The model is nested with a sequence of coarser regional and basin-wide models that provide for the long-term interaction between the study area and the Eastern Mediterranean at large. The results are employed to discuss the response of the North Aegean to the important circulation forcing mechanisms in the region, namely wind stress, heat and salt fluxes, buoyancy due to rivers and the BSW outflow (which is low in salinity and occasionally low in temperature) and the interaction with the Southern Aegean. The high resolution allows for the detailed representation of the complicated topography that presides in the region. This helps produce a rich eddy field and it allows for variability in the pathways of BSW that has implications in the basin hydrography and circulation.

The impact of vertical resolution in mesoscale model AROME forecasting of radiation fog

NASA Astrophysics Data System (ADS)

Philip, Alexandre; Bergot, Thierry; Bouteloup, Yves; Bouyssel, François

2015-04-01

Airports short-term forecasting of fog has a security and economic impact. Numerical simulations have been performed with the mesoscale model AROME (Application of Research to Operations at Mesoscale) (Seity et al. 2011). Three vertical resolutions (60, 90 and 156 levels) are used to show the impact of radiation fog on numerical forecasting. Observations at Roissy Charles De Gaulle airport are compared to simulations. Significant differences in the onset, evolution and dissipation of fog were found. The high resolution simulation is in better agreement with observations than a coarser one. The surface boundary layer and incoming long-wave radiations are better represented. A more realistic behaviour of liquid water content evolution allows a better anticipation of low visibility procedures (ceiling < 60m and/or visibility < 600m). The case study of radiation fog shows that it is necessary to have a well defined vertical grid to better represent local phenomena. A statistical study over 6 months (October 2011 - March 2012 ) using different configurations was carried out. Statistically, results were the same as in the case study of radiation fog. Seity Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, V. Masson, 2011: The AROME-France convective scale operational model. Mon.Wea.Rev., 139, 976-991.

The accuracy of temperature distributions used to derive the net transport for a zonally averaged model

NASA Technical Reports Server (NTRS)

Remsberg, Ellis E.; Bhatt, Praful P.

1994-01-01

Comparisons of satellite-derived temperatures with correlative temperatures indicate that the LIMS temperatures are accurate and contain more of the needed vertical resolution for calculating a residual mean circulation for transporting tracer-like species. Generally, the LIMS temperatures are accurate to at least 2 K. Other satellite data sets are comprised of temperatures with coarser vertical resolution, leading to biases that occur with an error pattern that is characteristic of their resolution. Their biases exceed 2 K at some altitudes. Retrievals of species using an infrared limb emission technique are sensitive to any temperature bias. Generally, the IMS comparisons with other data sets for ozone and water vapor are good to better than 20 percent; this represents an independent confirmation of the quality of LIMS and temperatures. Zonal mean comparisons between LIMS and SAMS temperatures also indicate agreement to better than 2 K from about 7 to 2hPa. Therefore, we are confident that SAMS N2O and CH4 are relatively free of temperature bias in that region. These factors support the generally good agreement in G90 between model N2O transported using a LIMS-derived RMC and the N2O contours from SAMS.

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe370mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Broadband Heating Rate Profile Project (BBHRP) - SGP 1bbhrpripbe1mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe1mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Visible AO Observations at Halpha for Accreting Young Planets

NASA Astrophysics Data System (ADS)

Close, L. M.; Follette, K.; Males, J. R.; Morzinski, K.; Rodigas, T. J.; Hinz, P.; Wu, Y.-L.; Apai, D.; Najita, J.; Puglisi, A.; Esposito, S.; Riccardi, A.; Bailey, V.; Xompero, M.; Briguglio, R.; Weinberger, A.

2014-01-01

We utilized the new high-order (250-378 mode) Magellan Adaptive Optics system (MagAO) to obtain very high-resolution science in the visible with MagAO's VisAO CCD camera. In the good-median seeing conditions of Magellan (0.5-0.7'') we find MagAO delivers individual short exposure images as good as 19 mas optical resolution. Due to telescope vibrations, long exposure (60s) r' (0.63μm) images are slightly coarser at FWHM = 23-29 mas (Strehl ~ 28%) with bright (R < 9 mag) guide stars. These are the highest resolution filled-aperture images published to date. Images of the young (~ 1 Myr) Orion Trapezium θ1 Ori A, B, and C cluster members were obtained with VisAO. In particular, the 32 mas binary θ1 Ori C 1 C 2 was easily resolved in non-interferometric images for the first time. Relative positions of the bright trapezium binary stars were measured with ~ 0.6-5 mas accuracy. In the second commissioning run we were able to correct 378 modes and achieved good contrasts (Strehl>20% on young transition disks at Hα). We discuss the contrasts achieved at Hα and the possibility of detecting low mass (~ 1-5 Mjup) planets (past 5AU) with our new SAPPHIRES survey with MagAO at Hα.

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

Sadowski, F. G.; Malila, W. A.; Sarno, J. E.; Nalepka, R. F.

1977-01-01

Inappropriate spatial resolution and corresponding data processing techniques may be major causes for non-optimal forest classification results frequently achieved from multispectral scanner (MSS) data. Procedures and results of empirical investigations are studied to determine the influence of MSS spatial resolution on the classification of forest features into levels of detail or hierarchies of information that might be appropriate for nationwide forest surveys and detailed in-place inventories. Two somewhat different, but related studies are presented. The first consisted of establishing classification accuracies for several hierarchies of features as spatial resolution was progressively coarsened from (2 meters) squared to (64 meters) squared. The second investigated the capabilities for specialized processing techniques to improve upon the results of conventional processing procedures for both coarse and fine resolution data.

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Dielectric Constant products: (the dielectric constant products are delivered together with soil moisture products, with the same averaging periods and generation frequency): maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation.

System and method for the detection of anomalies in an image

DOEpatents

Prasad, Lakshman; Swaminarayan, Sriram

2013-09-03

Preferred aspects of the present invention can include receiving a digital image at a processor; segmenting the digital image into a hierarchy of feature layers comprising one or more fine-scale features defining a foreground object embedded in one or more coarser-scale features defining a background to the one or more fine-scale features in the segmentation hierarchy; detecting a first fine-scale foreground feature as an anomaly with respect to a first background feature within which it is embedded; and constructing an anomalous feature layer by synthesizing spatially contiguous anomalous fine-scale features. Additional preferred aspects of the present invention can include detecting non-pervasive changes between sets of images in response at least in part to one or more difference images between the sets of images.

Simultaneous multiview capture and fusion improves spatial resolution in wide-field and light-sheet microscopy

PubMed Central

Wu, Yicong; Chandris, Panagiotis; Winter, Peter W.; Kim, Edward Y.; Jaumouillé, Valentin; Kumar, Abhishek; Guo, Min; Leung, Jacqueline M.; Smith, Corey; Rey-Suarez, Ivan; Liu, Huafeng; Waterman, Clare M.; Ramamurthi, Kumaran S.; La Riviere, Patrick J.; Shroff, Hari

2016-01-01

Most fluorescence microscopes are inefficient, collecting only a small fraction of the emitted light at any instant. Besides wasting valuable signal, this inefficiency also reduces spatial resolution and causes imaging volumes to exhibit significant resolution anisotropy. We describe microscopic and computational techniques that address these problems by simultaneously capturing and subsequently fusing and deconvolving multiple specimen views. Unlike previous methods that serially capture multiple views, our approach improves spatial resolution without introducing any additional illumination dose or compromising temporal resolution relative to conventional imaging. When applying our methods to single-view wide-field or dual-view light-sheet microscopy, we achieve a twofold improvement in volumetric resolution (~235 nm × 235 nm × 340 nm) as demonstrated on a variety of samples including microtubules in Toxoplasma gondii, SpoVM in sporulating Bacillus subtilis, and multiple protein distributions and organelles in eukaryotic cells. In every case, spatial resolution is improved with no drawback by harnessing previously unused fluorescence. PMID:27761486

The Effect of Spatial and Temporal Resolution of Cine Phase Contrast MRI on Wall Shear Stress and Oscillatory Shear Index Assessment

PubMed Central

Gijsen, Frank J.; Marquering, Henk; van Ooij, Pim; vanBavel, Ed; Wentzel, Jolanda J.; Nederveen, Aart J.

2016-01-01

Introduction Wall shear stress (WSS) and oscillatory shear index (OSI) are associated with atherosclerotic disease. Both parameters are derived from blood velocities, which can be measured with phase-contrast MRI (PC-MRI). Limitations in spatiotemporal resolution of PC-MRI are known to affect these measurements. Our aim was to investigate the effect of spatiotemporal resolution using a carotid artery phantom. Methods A carotid artery phantom was connected to a flow set-up supplying pulsatile flow. MRI measurement planes were placed at the common carotid artery (CCA) and internal carotid artery (ICA). Two-dimensional PC-MRI measurements were performed with thirty different spatiotemporal resolution settings. The MRI flow measurement was validated with ultrasound probe measurements. Mean flow, peak flow, flow waveform, WSS and OSI were compared for these spatiotemporal resolutions using regression analysis. The slopes of the regression lines were reported in %/mm and %/100ms. The distribution of low and high WSS and OSI was compared between different spatiotemporal resolutions. Results The mean PC-MRI CCA flow (2.5±0.2mL/s) agreed with the ultrasound probe measurements (2.7±0.02mL/s). Mean flow (mL/s) depended only on spatial resolution (CCA:-13%/mm, ICA:-49%/mm). Peak flow (mL/s) depended on both spatial (CCA:-13%/mm, ICA:-17%/mm) and temporal resolution (CCA:-19%/100ms, ICA:-24%/100ms). Mean WSS (Pa) was in inverse relationship only with spatial resolution (CCA:-19%/mm, ICA:-33%/mm). OSI was dependent on spatial resolution for CCA (-26%/mm) and temporal resolution for ICA (-16%/100ms). The regions of low and high WSS and OSI matched for most of the spatiotemporal resolutions (CCA:30/30, ICA:28/30 cases for WSS; CCA:23/30, ICA:29/30 cases for OSI). Conclusion We show that both mean flow and mean WSS are independent of temporal resolution. Peak flow and OSI are dependent on both spatial and temporal resolution. However, the magnitude of mean and peak flow, WSS and OSI, and the spatial distribution of OSI and WSS did not exhibit a strong dependency on spatiotemporal resolution. PMID:27669568

Zonal wavefront sensing with enhanced spatial resolution.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2016-12-01

In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Generating High-Temporal and Spatial Resolution TIR Image Data

NASA Astrophysics Data System (ADS)

Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

2017-09-01

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture.

PubMed

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M; Torres-Rua, Alfonso; McKee, Mac

2017-09-14

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from "AggieAir", an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture

PubMed Central

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M.; McKee, Mac

2017-01-01

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products. PMID:28906428

Calibration of Fuji BAS-SR type imaging plate as high spatial resolution x-ray radiography recorder

NASA Astrophysics Data System (ADS)

Yan, Ji; Zheng, Jianhua; Zhang, Xing; Chen, Li; Wei, Minxi

2017-05-01

Image Plates as x-ray recorder have advantages including reusable, high dynamic range, large active area, and so on. In this work, Fuji BAS-SR type image plate combined with BAS-5000 scanner is calibrated. The fade rates of Image Plates has been measured using x-ray diffractometric in different room temperature; the spectral response of Image Plates has been measured using 241Am radioactive sealed source and fitting with linear model; the spatial resolution of Image Plates has been measured using micro-focus x-ray tube. The results show that Image Plates has an exponent decade curve and double absorption edge response curve. The spatial resolution of Image Plates with 25μ/50μ scanner resolution is 6.5lp/mm, 11.9lp/mm respectively and gold grid radiography is collected with 80lp/mm spatial resolution using SR-type Image Plates. BAS-SR type Image Plates can do high spatial resolution and quantitative radiographic works. It can be widely used in High energy density physics (HEDP), inertial confinement fusion (ICF) and laboratory astronomy physics.

Simulations of the temporal and spatial resolution for a compact time-resolved electron diffractometer

NASA Astrophysics Data System (ADS)

Robinson, Matthew S.; Lane, Paul D.; Wann, Derek A.

2016-02-01

A novel compact electron gun for use in time-resolved gas electron diffraction experiments has recently been designed and commissioned. In this paper we present and discuss the extensive simulations that were performed to underpin the design in terms of the spatial and temporal qualities of the pulsed electron beam created by the ionisation of a gold photocathode using a femtosecond laser. The response of the electron pulses to a solenoid lens used to focus the electron beam has also been studied. The simulated results show that focussing the electron beam affects the overall spatial and temporal resolution of the experiment in a variety of ways, and that factors that improve the resolution of one parameter can often have a negative effect on the other. A balance must, therefore, be achieved between spatial and temporal resolution. The optimal experimental time resolution for the apparatus is predicted to be 416 fs for studies of gas-phase species, while the predicted spatial resolution of better than 2 nm-1 compares well with traditional time-averaged electron diffraction set-ups.

Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

PubMed Central

Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

2018-01-01

Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

NASA Astrophysics Data System (ADS)

Lin, S.; Li, J.; Liu, Q.

2018-04-01

Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

Fabrication and characterization of a 0.5-mm lutetium oxyorthosilicate detector array for high-resolution PET applications.

PubMed

Stickel, Jennifer R; Qi, Jinyi; Cherry, Simon R

2007-01-01

With the increasing use of in vivo imaging in mouse models of disease, there are many interesting applications that demand imaging of organs and tissues with submillimeter resolution. Though there are other contributing factors, the spatial resolution in small-animal PET is still largely determined by the detector pixel dimensions. In this work, a pair of lutetium oxyorthosilicate (LSO) arrays with 0.5-mm pixels was coupled to multichannel photomultiplier tubes and evaluated for use as high-resolution PET detectors. Flood histograms demonstrated that most crystals were clearly identifiable. Energy resolution varied from 22% to 38%. The coincidence timing resolution was 1.42-ns full width at half maximum (FWHM). The intrinsic spatial resolution was 0.68-mm FWHM as measured with a 30-gauge needle filled with (18)F. The improvement in spatial resolution in a tomographic setting is demonstrated using images of a line source phantom reconstructed with filtered backprojection and compared with images obtained from 2 dedicated small-animal PET scanners. Finally, a projection image of the mouse foot is shown to demonstrate the application of these 0.5-mm LSO detectors to a biologic task. A pair of highly pixelated LSO detections has been constructed and characterized for use as high-spatial-resolution PET detectors. It appears that small-animal PET systems capable of a FWHM spatial resolution of 600 microm or less are feasible and should be pursued.

Characterization of spatial and spectral resolution of a rotating prism chromotomographic hyperspectral imager

NASA Astrophysics Data System (ADS)

Bostick, Randall L.; Perram, Glen P.; Tuttle, Ronald

2009-05-01

The Air Force Institute of Technology (AFIT) has built a rotating prism chromotomographic hyperspectral imager (CTI) with the goal of extending the technology to exploit spatially extended sources with quickly varying (> 10 Hz) phenomenology, such as bomb detonations and muzzle flashes. This technology collects successive frames of 2-D data dispersed at different angles multiplexing spatial and spectral information which can then be used to reconstruct any arbitrary spectral plane(s). In this paper, the design of the AFIT instrument is described and then tested against a spectral target with near point source spatial characteristics to measure spectral and spatial resolution. It will be shown that, in theory, the spectral and spatial resolution in the 3-D spectral image cube is the nearly the same as a simple prism spectrograph with the same design. However, error in the knowledge of the prism linear dispersion at the detector array as a function of wavelength and projection angle will degrade resolution without further corrections. With minimal correction for error and use of a simple shift-and-add reconstruction algorithm, the CTI is able to produce a spatial resolution of about 2 mm in the object plane (234 μrad IFOV) and is limited by chromatic aberration. A spectral resolution of less than 1nm at shorter wavelengths is shown, limited primarily by prism dispersion.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

High Spatial Resolution Thermal Satellite Technologies

NASA Technical Reports Server (NTRS)

Ryan, Robert

2003-01-01

This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.

Improved spatial resolution in PET scanners using sampling techniques

PubMed Central

Surti, Suleman; Scheuermann, Ryan; Werner, Matthew E.; Karp, Joel S.

2009-01-01

Increased focus towards improved detector spatial resolution in PET has led to the use of smaller crystals in some form of light sharing detector design. In this work we evaluate two sampling techniques that can be applied during calibrations for pixelated detector designs in order to improve the reconstructed spatial resolution. The inter-crystal positioning technique utilizes sub-sampling in the crystal flood map to better sample the Compton scatter events in the detector. The Compton scatter rejection technique, on the other hand, rejects those events that are located further from individual crystal centers in the flood map. We performed Monte Carlo simulations followed by measurements on two whole-body scanners for point source data. The simulations and measurements were performed for scanners using scintillators with Zeff ranging from 46.9 to 63 for LaBr3 and LYSO, respectively. Our results show that near the center of the scanner, inter-crystal positioning technique leads to a gain of about 0.5-mm in reconstructed spatial resolution (FWHM) for both scanner designs. In a small animal LYSO scanner the resolution improves from 1.9-mm to 1.6-mm with the inter-crystal technique. The Compton scatter rejection technique shows higher gains in spatial resolution but at the cost of reduction in scanner sensitivity. The inter-crystal positioning technique represents a modest acquisition software modification for an improvement in spatial resolution, but at a cost of potentially longer data correction and reconstruction times. The Compton scatter rejection technique, while also requiring a modest acquisition software change with no increased data correction and reconstruction times, will be useful in applications where the scanner sensitivity is very high and larger improvements in spatial resolution are desirable. PMID:19779586

Regional climate simulations over complex topography using WRF: Andalusian present climate

NASA Astrophysics Data System (ADS)

Argüeso, D.; Hidalgo-Muñoz, J. M.; Calandria-Hernández, D.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

2010-09-01

In this study three WRF simulations were carried out and analyzed to assess its accuracy to describe the main climate features of Southern Spain in terms of maximum temperature, minimum temperature and precipitation. Present climate was represented by the last 30 year of the 20th Century (1970-1999). The model was evaluated using an observational network distributed throughout Andalusia that comprised both temperatures and precipitation. Since comparison between site-specific measurements and model grid points is definitely troublesome due to differences in spatial-scale, a multi-step regionalization strategy was adopted to upscale observational information. This is of particular importance when studying complex topography regions such as Andalusia, with a wide range of climate conditions in a relative small area. Additionally, WRF outputs were also compared with SPAIN02, a 20-km resolution gridded dataset of precipitation for further validation of the model performance. The model set up consisted in two domains with one-way nesting and spectral nudging. The target domain has a resolution of 10km with 136 by 136 points covering the whole Iberian Peninsula and nested in a coarser domain of 30-km resolution and 130 by 120 grid points. Both domains have 35 vertical levels. Three different driving data were used to provide the boundary conditions, one reanalysis (ERA-40) and two control runs from different General Circulation Models (ECHAM5 and CCSM 3.0). A conservative 7-month spin-up period was added to the 30-year simulation so that dependence on initial conditions can be completely removed. Physics options were chosen on the basis of previous parameterization sensitivity tests over Andalusia that led to a compromise configuration that adequately describes the different subclimates. Probability distributions of daily values as well as monthly statistics were examined to determine the uncertainties associated to each variable and take them into consideration for future regional high-resolution projections of climate change scenarios. These analyses permitted to conclude that WRF is an extremely useful tool due to the significant value-added information produced with respect to the driving data. Nonetheless, according to differences in performance between regions it has also been shown that results must be interpreted carefully depending on the region characteristics. Acknowledgements: The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2007-61151/CLI, and the Regional Government of Andalusia project P06-RNM-01622, have financed this study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Lan; Hill, K. W.; Bitter, M.

Here, a high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ 2 rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystalmore » (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications ( M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Evaluating Hyperspectral Imaging of Wetland Vegetation as a Tool for Detecting Estuarine Nutrient Enrichment

DTIC Science & Technology

2008-05-01

the vegetation’s uptake of water column nutrients produces a spectral response; and 3) the spectral and spatial resolutions ...analysis. This allowed us to evaluate these assumptions at the landscape level, by using the high spectral and spatial resolution of the hyperspectral... spatial resolution (2.5 m pixels) HyMap hyperspectral imagery of the entire wetland. After using a hand-held spectrometer to characterize

Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.

Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

NASA Astrophysics Data System (ADS)

Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

2014-11-01

Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.

Improving spectral resolution in spatial encoding dimension of single-scan nuclear magnetic resonance 2D spin echo correlated spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Liangjie; Wei, Zhiliang; Yang, Jian; Lin, Yanqin; Chen, Zhong

2014-11-01

The spatial encoding technique can be used to accelerate the acquisition of multi-dimensional nuclear magnetic resonance spectra. However, with this technique, we have to make trade-offs between the spectral width and the resolution in the spatial encoding dimension (F1 dimension), resulting in the difficulty of covering large spectral widths while preserving acceptable resolutions for spatial encoding spectra. In this study, a selective shifting method is proposed to overcome the aforementioned drawback. This method is capable of narrowing spectral widths and improving spectral resolutions in spatial encoding dimensions by selectively shifting certain peaks in spectra of the ultrafast version of spin echo correlated spectroscopy (UFSECSY). This method can also serve as a powerful tool to obtain high-resolution correlated spectra in inhomogeneous magnetic fields for its resistance to any inhomogeneity in the F1 dimension inherited from UFSECSY. Theoretical derivations and experiments have been carried out to demonstrate performances of the proposed method. Results show that the spectral width in spatial encoding dimension can be reduced by shortening distances between cross peaks and axial peaks with the proposed method and the expected resolution improvement can be achieved. Finally, the shifting-absent spectrum can be recovered readily by post-processing.

Soil moisture retrieval from Sentinel-1 satellite data

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo

2016-04-01

Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal resolution and the dual-polarized information of Sentinel-1 are utilized. Three candidate algorithms are presented at the conference, which are a data-driven algorithm, inversion of a radar scattering model and downscaling of coarser resolution soil moisture products. The research is part of the OWAS1S project (Optimizing Water Availability with Sentinel-1 Satellites), which stands for integration of the freely available global Sentinel-1 data and local knowledge on soil physical processes, to optimize water management of regional water systems and to develop value-added products for agriculture.

All-weather Land Surface Temperature Estimation from Satellite Data

NASA Astrophysics Data System (ADS)

Zhou, J.; Zhang, X.

2017-12-01

Satellite remote sensing, including the thermal infrared (TIR) and passive microwave (MW), provides the possibility to observe LST at large scales. For better modeling the land surface processes with high temporal resolutions, all-weather LST from satellite data is desirable. However, estimation of all-weather LST faces great challenges. On the one hand, TIR remote sensing is limited to clear-sky situations; this drawback reduces its usefulness under cloudy conditions considerably, especially in regions with frequent and/or permanent clouds. On the other hand, MW remote sensing suffers from much greater thermal sampling depth (TSD) and coarser spatial resolution than TIR; thus, MW LST is generally lower than TIR LST, especially at daytime. Two case studies addressing the challenges mentioned previously are presented here. The first study is for the development of a novel thermal sampling depth correction method (TSDC) to estimate the MW LST over barren land; this second study is for the development of a feasible method to merge the TIR and MW LSTs by addressing the coarse resolution of the latter one. In the first study, the core of the TSDC method is a new formulation of the passive microwave radiation balance equation, which allows linking bulk MW radiation to the soil temperature at a specific depth, i.e. the representative temperature: this temperature is then converted to LST through an adapted soil heat conduction equation. The TSDC method is applied to the 6.9 GHz channel in vertical polarization of AMSR-E. Evaluation shows that LST estimated by the TSDC method agrees well with the MODIS LST. Validation is based on in-situ LSTs measured at the Gobabeb site in western Namibia. The results demonstrate the high accuracy of the TSDC method: it yields a root-mean squared error (RMSE) of 2 K and ignorable systematic error over barren land. In the second study, the method consists of two core processes: (1) estimation of MW LST from MW brightness temperature and (2) three-time-scale decomposition of LST. The method is applied to two MW sensors (i.e. AMSR-E and AMSR2) and MODIS in northeast China and its surrounding area, with dominating land covers of forest and cropland. By comparing against the in-situ LST and surface air temperature, we find the merged LST has similar accuracy to the MODIS LST in version 6 and good image quality.

Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

USGS Publications Warehouse

Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

2017-01-01

Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.

Impact of buildings on surface solar radiation over urban Beijing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Bin; Liou, Kuo-Nan; Gu, Yu

The rugged surface of an urban area due to varying buildings can interact with solar beams and affect both the magnitude and spatiotemporal distribution of surface solar fluxes. Here we systematically examine the impact of buildings on downward surface solar fluxes over urban Beijing by using a 3-D radiation parameterization that accounts for 3-D building structures vs. the conventional plane-parallel scheme. We find that the resulting downward surface solar flux deviations between the 3-D and the plane-parallel schemes are generally ±1–10 W m -2 at 800 m grid resolution and within ±1 W m -2 at 4 km resolution. Pairsmore » of positive–negative flux deviations on different sides of buildings are resolved at 800 m resolution, while they offset each other at 4 km resolution. Flux deviations from the unobstructed horizontal surface at 4 km resolution are positive around noon but negative in the early morning and late afternoon. The corresponding deviations at 800 m resolution, in contrast, show diurnal variations that are strongly dependent on the location of the grids relative to the buildings. Both the magnitude and spatiotemporal variations of flux deviations are largely dominated by the direct flux. Furthermore, we find that flux deviations can potentially be an order of magnitude larger by using a finer grid resolution. Atmospheric aerosols can reduce the magnitude of downward surface solar flux deviations by 10–65 %, while the surface albedo generally has a rather moderate impact on flux deviations. The results imply that the effect of buildings on downward surface solar fluxes may not be critically significant in mesoscale atmospheric models with a grid resolution of 4 km or coarser. However, the effect can play a crucial role in meso-urban atmospheric models as well as microscale urban dispersion models with resolutions of 1 m to 1 km.« less

Outcomes and challenges of global high-resolution non-hydrostatic atmospheric simulations using the K computer

NASA Astrophysics Data System (ADS)

Satoh, Masaki; Tomita, Hirofumi; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Miyamoto, Yoshiaki; Yamaura, Tsuyoshi; Miyakawa, Tomoki; Nakano, Masuo; Kodama, Chihiro; Noda, Akira T.; Nasuno, Tomoe; Yamada, Yohei; Fukutomi, Yoshiki

2017-12-01

This article reviews the major outcomes of a 5-year (2011-2016) project using the K computer to perform global numerical atmospheric simulations based on the non-hydrostatic icosahedral atmospheric model (NICAM). The K computer was made available to the public in September 2012 and was used as a primary resource for Japan's Strategic Programs for Innovative Research (SPIRE), an initiative to investigate five strategic research areas; the NICAM project fell under the research area of climate and weather simulation sciences. Combining NICAM with high-performance computing has created new opportunities in three areas of research: (1) higher resolution global simulations that produce more realistic representations of convective systems, (2) multi-member ensemble simulations that are able to perform extended-range forecasts 10-30 days in advance, and (3) multi-decadal simulations for climatology and variability. Before the K computer era, NICAM was used to demonstrate realistic simulations of intra-seasonal oscillations including the Madden-Julian oscillation (MJO), merely as a case study approach. Thanks to the big leap in computational performance of the K computer, we could greatly increase the number of cases of MJO events for numerical simulations, in addition to integrating time and horizontal resolution. We conclude that the high-resolution global non-hydrostatic model, as used in this five-year project, improves the ability to forecast intra-seasonal oscillations and associated tropical cyclogenesis compared with that of the relatively coarser operational models currently in use. The impacts of the sub-kilometer resolution simulation and the multi-decadal simulations using NICAM are also reviewed.

Sympathy for the Devil: Detailing the Effects of Planning-Unit Size, Thematic Resolution of Reef Classes, and Socioeconomic Costs on Spatial Priorities for Marine Conservation

PubMed Central

Pressey, Robert L.; Weeks, Rebecca; Andréfouët, Serge; Moloney, James

2016-01-01

Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors—planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs—on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs. PMID:27829042

Sympathy for the Devil: Detailing the Effects of Planning-Unit Size, Thematic Resolution of Reef Classes, and Socioeconomic Costs on Spatial Priorities for Marine Conservation.

PubMed

Cheok, Jessica; Pressey, Robert L; Weeks, Rebecca; Andréfouët, Serge; Moloney, James

2016-01-01

Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors-planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs-on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs.

Investigation of spatial resolution improvement by use of a mouth-insert detector in the helmet PET scanner.

PubMed

Ahmed, Abdella M; Tashima, Hideaki; Yamaya, Taiga

2018-03-01

The dominant factor limiting the intrinsic spatial resolution of a positron emission tomography (PET) system is the size of the crystal elements in the detector. To increase sensitivity and achieve high spatial resolution, it is essential to use advanced depth-of-interaction (DOI) detectors and arrange them close to the subject. The DOI detectors help maintain high spatial resolution by mitigating the parallax error caused by the thickness of the scintillator near the peripheral regions of the field-of-view. As an optimal geometry for a brain PET scanner, with high sensitivity and spatial resolution, we proposed and developed the helmet-chin PET scanner using 54 four-layered DOI detectors consisting of a 16 × 16 × 4 array of GSOZ scintillator crystals with dimensions of 2.8 × 2.8 × 7.5 mm 3 . All the detectors used in the helmet-chin PET scanner had the same spatial resolution. In this study, we conducted a feasibility study of a new add-on detector arrangement for the helmet PET scanner by replacing the chin detector with a segmented crystal cube, having high spatial resolution in all directions, which can be placed inside the mouth. The crystal cube (which we have named the mouth-insert detector) has an array of 20 × 20 × 20 LYSO crystal segments with dimensions of 1 × 1 × 1 mm 3 . Thus, the scanner is formed by the combination of the helmet and mouth-insert detectors, and is referred to as the helmet-mouth-insert PET scanner. The results show that the helmet-mouth-insert PET scanner has comparable sensitivity and improved spatial resolution near the center of the hemisphere, compared to the helmet-chin PET scanner.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Developing a CCD camera with high spatial resolution for RIXS in the soft X-ray range

NASA Astrophysics Data System (ADS)

Soman, M. R.; Hall, D. J.; Tutt, J. H.; Murray, N. J.; Holland, A. D.; Schmitt, T.; Raabe, J.; Schmitt, B.

2013-12-01

The Super Advanced X-ray Emission Spectrometer (SAXES) at the Swiss Light Source contains a high resolution Charge-Coupled Device (CCD) camera used for Resonant Inelastic X-ray Scattering (RIXS). Using the current CCD-based camera system, the energy-dispersive spectrometer has an energy resolution (E/ΔE) of approximately 12,000 at 930 eV. A recent study predicted that through an upgrade to the grating and camera system, the energy resolution could be improved by a factor of 2. In order to achieve this goal in the spectral domain, the spatial resolution of the CCD must be improved to better than 5 μm from the current 24 μm spatial resolution (FWHM). The 400 eV-1600 eV energy X-rays detected by this spectrometer primarily interact within the field free region of the CCD, producing electron clouds which will diffuse isotropically until they reach the depleted region and buried channel. This diffusion of the charge leads to events which are split across several pixels. Through the analysis of the charge distribution across the pixels, various centroiding techniques can be used to pinpoint the spatial location of the X-ray interaction to the sub-pixel level, greatly improving the spatial resolution achieved. Using the PolLux soft X-ray microspectroscopy endstation at the Swiss Light Source, a beam of X-rays of energies from 200 eV to 1400 eV can be focused down to a spot size of approximately 20 nm. Scanning this spot across the 16 μm square pixels allows the sub-pixel response to be investigated. Previous work has demonstrated the potential improvement in spatial resolution achievable by centroiding events in a standard CCD. An Electron-Multiplying CCD (EM-CCD) has been used to improve the signal to effective readout noise ratio achieved resulting in a worst-case spatial resolution measurement of 4.5±0.2 μm and 3.9±0.1 μm at 530 eV and 680 eV respectively. A method is described that allows the contribution of the X-ray spot size to be deconvolved from these worst-case resolution measurements, estimating the spatial resolution to be approximately 3.5 μm and 3.0 μm at 530 eV and 680 eV, well below the resolution limit of 5 μm required to improve the spectral resolution by a factor of 2.

Coarse climate change projections for species living in a fine-scaled world.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-01-01

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change. © 2016 John Wiley & Sons Ltd.

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

WE-AB-202-07: Ventilation CT: Voxel-Level Comparison with Hyperpolarized Helium-3 & Xenon-129 MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tahir, B; Marshall, H; Hughes, P

Purpose: To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath-hold CT with hyperpolarized Helium-3 & Xenon-129 MRI in a cohort of lung cancer patients. Methods: 5 patients underwent expiration & inspiration breath-hold CT. Xenon-129 & {sup 1}H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium-3 & {sup 1}H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel-wise differences in Hounsfield units. Inspiration CTmore » and the Xenon-129’s corresponding anatomical {sup 1}H MRI were registered to Helium-3 MRI via the same-breath anatomical {sup 1}H MRI. This enabled direct comparison of CT ventilation with Helium-3 MRI & Xenon-129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in-plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same-breath {sup 1}H MRI lung mask. Spearman coefficients were used to assess voxel-level correlation. Results: The median Spearman’s coefficients of ventilation CT with Helium-3 & Xenon-129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively. Conclusion: This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium-3 & Xenon-129 MRI) in similar breath-holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non-ventilatory effects and registration errors at the voxel-level. Thus, it may be more beneficial to quantify ventilation at a more regional level.« less

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

An observationally-driven kinetic approach to coronal heating

NASA Astrophysics Data System (ADS)

Moraitis, K.; Toutountzi, A.; Isliker, H.; Georgoulis, M.; Vlahos, L.; Chintzoglou, G.

2016-11-01

Aims: Coronal heating through the explosive release of magnetic energy remains an open problem in solar physics. Recent hydrodynamical models attempt an investigation by placing swarms of "nanoflares" at random sites and times in modeled one-dimensional coronal loops. We investigate the problem in three dimensions, using extrapolated coronal magnetic fields of observed solar active regions. Methods: We applied a nonlinear force-free field extrapolation above an observed photospheric magnetogram of NOAA active region (AR) 11 158. We then determined the locations, energy contents, and volumes of "unstable" areas, namely areas prone to releasing magnetic energy due to locally accumulated electric current density. Statistical distributions of these volumes and their fractal dimension are inferred, investigating also their dependence on spatial resolution. Further adopting a simple resistivity model, we inferred the properties of the fractally distributed electric fields in these volumes. Next, we monitored the evolution of 105 particles (electrons and ions) obeying an initial Maxwellian distribution with a temperature of 10 eV, by following their trajectories and energization when subjected to the resulting electric fields. For computational convenience, the length element of the magnetic-field extrapolation is 1 arcsec, or 725 km, much coarser than the particles' collisional mean free path in the low corona (0.1-1 km). Results: The presence of collisions traps the bulk of the plasma around the unstable volumes, or current sheets (UCS), with only a tail of the distribution gaining substantial energy. Assuming that the distance between UCS is similar to the collisional mean free path we find that the low active-region corona is heated to 100-200 eV, corresponding to temperatures exceeding 2 MK, within tens of seconds for electrons and thousands of seconds for ions. Conclusions: Fractally distributed, nanoflare-triggening fragmented UCS in the active-region corona can heat electrons and ions with minor enhancements of the local resistivity. This statistical result is independent from the nature of the extrapolation and the spatial resolution of the modeled active-region corona. This finding should be coupled with a complete plasma treatment to determine whether a quasi-steady temperature similar to that of the ambient corona can be maintained, either via a kinetic or via a hybrid, kinetic and fluid, plasma treatment. The finding can also be extended to the quiet solar corona, provided that the currently undetected nanoflares are frequent enough to account for the lower (compared to active regions) energy losses in this case.

Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area

NASA Astrophysics Data System (ADS)

Pleniou, Magdalini; Koutsias, Nikos

2013-05-01

The aim of our study was to explore the spectral properties of fire-scorched (burned) and non fire-scorched (vegetation) areas, as well as areas with different burn/vegetation ratios, using a multisource multiresolution satellite data set. A case study was undertaken following a very destructive wildfire that occurred in Parnitha, Greece, July 2007, for which we acquired satellite images from LANDSAT, ASTER, and IKONOS. Additionally, we created spatially degraded satellite data over a range of coarser resolutions using resampling techniques. The panchromatic (1 m) and multispectral component (4 m) of IKONOS were merged using the Gram-Schmidt spectral sharpening method. This very high-resolution imagery served as the basis to estimate the cover percentage of burned areas, bare land and vegetation at pixel level, by applying the maximum likelihood classification algorithm. Finally, multiple linear regression models were fit to estimate each land-cover fraction as a function of surface reflectance values of the original and the spatially degraded satellite images. The main findings of our research were: (a) the Near Infrared (NIR) and Short-wave Infrared (SWIR) are the most important channels to estimate the percentage of burned area, whereas the NIR and red channels are the most important to estimate the percentage of vegetation in fire-affected areas; (b) when the bi-spectral space consists only of NIR and SWIR, then the NIR ground reflectance value plays a more significant role in estimating the percent of burned areas, and the SWIR appears to be more important in estimating the percent of vegetation; and (c) semi-burned areas comprising 45-55% burned area and 45-55% vegetation are spectrally closer to burned areas in the NIR channel, whereas those areas are spectrally closer to vegetation in the SWIR channel. These findings, at least partially, are attributed to the fact that: (i) completely burned pixels present low variance in the NIR and high variance in the SWIR, whereas the opposite is observed in completely vegetated areas where higher variance is observed in the NIR and lower variance in the SWIR, and (ii) bare land modifies the spectral signal of burned areas more than the spectral signal of vegetated areas in the NIR, while the opposite is observed in SWIR region of the spectrum where the bare land modifies the spectral signal of vegetation more than the burned areas because the bare land and the vegetation are spectrally more similar in the NIR, and the bare land and burned areas are spectrally more similar in the SWIR.

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T

2013-08-01

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.

LSA SAF Meteosat FRP Products: Part 2 - Evaluation and demonstration of use in the Copernicus Atmosphere Monitoring Service (CAMS)

NASA Astrophysics Data System (ADS)

Roberts, G.; Wooster, M. J.; Xu, W.; Freeborn, P. H.; Morcrette, J.-J.; Jones, L.; Benedetti, A.; Kaiser, J.

2015-06-01

Characterising the dynamics of landscape scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and northern and southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP dataset, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9-13 and 65-77% respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35% over the Northern Africa region to 89% over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America, and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 Peloponnese wildfires within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS), as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring System (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions datasets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET AOD indicates that the former is overestimated by ∼ 20-30%, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those currently implemented as part of the Monitoring Atmospheric Composition and Climate (MACC) programme within the CAMS.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.