Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

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.

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.

Design and theoretical investigation of a digital x-ray detector with large area and high spatial resolution

NASA Astrophysics Data System (ADS)

Gui, Jianbao; Guo, Jinchuan; Yang, Qinlao; Liu, Xin; Niu, Hanben

2007-05-01

X-ray phase contrast imaging is a promising new technology today, but the requirements of a digital detector with large area, high spatial resolution and high sensitivity bring forward a large challenge to researchers. This paper is related to the design and theoretical investigation of an x-ray direct conversion digital detector based on mercuric iodide photoconductive layer with the latent charge image readout by photoinduced discharge (PID). Mercuric iodide has been verified having a good imaging performance (high sensitivity, low dark current, low voltage operation and good lag characteristics) compared with the other competitive materials (α-Se,PbI II,CdTe,CdZnTe) and can be easily deposited on large substrates in the manner of polycrystalline. By use of line scanning laser beam and parallel multi-electrode readout make the system have high spatial resolution and fast readout speed suitable for instant general radiography and even rapid sequence radiography.

Objectives and Layout of a High-Resolution X-ray Imaging Crystal Spectrometer for the Large Helical Device (LHD)

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

Bitter, M; Gates, D; Monticello, D

A high-resolution X-ray imaging crystal spectrometer, whose concept was tested on NSTX and Alcator C-Mod, is being designed for LHD. This instrument will record spatially resolved spectra of helium-like Ar16+ and provide ion temperature profiles with spatial and temporal resolutions of < 2 cm and ≥ 10 ms. The stellarator equilibrium reconstruction codes, STELLOPT and PIES, will be used for the tomographic inversion of the spectral data. The spectrometer layout and instrumental features are largely determined by the magnetic field structure of LHD.

Light-sheet enhanced resolution of light field microscopy for rapid imaging of large volumes

NASA Astrophysics Data System (ADS)

Madrid Wolff, Jorge; Castro, Diego; Arbeláez, Pablo; Forero-Shelton, Manu

2018-02-01

Whole-brain imaging is challenging because it demands microscopes with high temporal and spatial resolution, which are often at odds, especially in the context of large fields of view. We have designed and built a light-sheet microscope with digital micromirror illumination and light-field detection. On the one hand, light sheets provide high resolution optical sectioning on live samples without compromising their viability. On the other hand, light field imaging makes it possible to reconstruct full volumes of relatively large fields of view from a single camera exposure; however, its enhanced temporal resolution comes at the expense of spatial resolution, limiting its applicability. We present an approach to increase the resolution of light field images using DMD-based light sheet illumination. To that end, we develop a method to produce synthetic resolution targets for light field microscopy and a procedure to correct the depth at which planes are refocused with rendering software. We measured the axial resolution as a function of depth and show a three-fold potential improvement with structured illumination, albeit by sacrificing some temporal resolution, also three-fold. This results in an imaging system that may be adjusted to specific needs without having to reassemble and realign it. This approach could be used to image relatively large samples at high rates.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

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

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

NASA Astrophysics Data System (ADS)

Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

2017-11-01

Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

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.

Scanning digital lithography providing high speed large area patterning with diffraction limited sub-micron resolution

NASA Astrophysics Data System (ADS)

Wen, Sy-Bor; Bhaskar, Arun; Zhang, Hongjie

2018-07-01

A scanning digital lithography system using computer controlled digital spatial light modulator, spatial filter, infinity correct optical microscope and high precision translation stage is proposed and examined. Through utilizing the spatial filter to limit orders of diffraction modes for light delivered from the spatial light modulator, we are able to achieve diffraction limited deep submicron spatial resolution with the scanning digital lithography system by using standard one inch level optical components with reasonable prices. Raster scanning of this scanning digital lithography system using a high speed high precision x-y translation stage and piezo mount to real time adjust the focal position of objective lens allows us to achieve large area sub-micron resolved patterning with high speed (compared with e-beam lithography). It is determined in this study that to achieve high quality stitching of lithography patterns with raster scanning, a high-resolution rotation stage will be required to ensure the x and y directions of the projected pattern are in the same x and y translation directions of the nanometer precision x-y translation stage.

Ultrafast, large-field multiphoton microscopy based on an acousto-optic deflector and a spatial light modulator.

PubMed

Shao, Yonghong; Qin, Wan; Liu, Honghai; Qu, Junle; Peng, Xiang; Niu, Hanben; Gao, Bruce Z

2012-07-01

We present an ultrafast, large-field multiphoton excitation fluorescence microscope with high lateral and axial resolutions based on a two-dimensional (2-D) acousto-optical deflector (AOD) scanner and spatial light modulator (SLM). When a phase-only SLM is used to shape the near-infrared light from a mode-locked titanium:sapphire laser into a multifocus array including the 0-order beam, a 136 μm × 136 μm field of view is achieved with a 60× objective using a 2-D AOD scanner without any mechanical scan element. The two-photon fluorescence image of a neuronal network that was obtained using this system demonstrates that our microscopy permits observation of dynamic biological events in a large field with high-temporal and -spatial resolution.

Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

NASA Astrophysics Data System (ADS)

Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

2016-04-01

We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

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

Adams, B.W.; et al.

The Large Area Picosecond PhotoDetector (LAPPD) Collaboration was formed in 2009 to develop large-area photodetectors capable of time resolutions measured in pico-seconds, with accompanying sub-millimeter spatial resolution. During the next three and one-half years the Collaboration developed the LAPPD design of 20 x 20 cm modules with gains greater thanmore » $10^7$ and non-uniformity less than $$15\\%$$, time resolution less than 50 psec for single photons and spatial resolution of 700~microns in both lateral dimensions. We describe the R\\&D performed to develop large-area micro-channel plate glass substrates, resistive and secondary-emitting coatings, large-area bialkali photocathodes, and RF-capable hermetic packaging. In addition, the Collaboration developed the necessary electronics for large systems capable of precise timing, built up from a custom low-power 15-GigaSample/sec waveform sampling 6-channel integrated circuit and supported by a two-level modular data acquisition system based on Field-Programmable Gate Arrays for local control, data-sparcification, and triggering. We discuss the formation, organization, and technical successes and short-comings of the Collaboration. The Collaboration ended in December 2012 with a transition from R\\&D to commercialization.« less

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

Interferometric temporal focusing microscopy using three-photon excitation fluorescence.

PubMed

Toda, Keisuke; Isobe, Keisuke; Namiki, Kana; Kawano, Hiroyuki; Miyawaki, Atsushi; Midorikawa, Katsumi

2018-04-01

Super-resolution microscopy has become a powerful tool for biological research. However, its spatial resolution and imaging depth are limited, largely due to background light. Interferometric temporal focusing (ITF) microscopy, which combines structured illumination microscopy and three-photon excitation fluorescence microscopy, can overcome these limitations. Here, we demonstrate ITF microscopy using three-photon excitation fluorescence, which has a spatial resolution of 106 nm at an imaging depth of 100 µm with an excitation wavelength of 1060 nm.

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.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Unleashing spatially distributed ecohydrology modeling using Big Data tools

NASA Astrophysics Data System (ADS)

Miles, B.; Idaszak, R.

2015-12-01

Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well as point time series of arbitrary variables at arbitrary points in space within a watershed or river basin. By treating ecohydrology modeling as a Big Data problem, we hope to provide a platform for answering transformative science and management questions related to water quantity and quality in a world of non-stationary climate.

Integration of airborne Thematic Mapper Simulator (TMS) data and digitized aerial photography via an ISH transformation. [Intensity Saturation Hue

NASA Technical Reports Server (NTRS)

Ambrosia, Vincent G.; Myers, Jeffrey S.; Ekstrand, Robert E.; Fitzgerald, Michael T.

1991-01-01

A simple method for enhancing the spatial and spectral resolution of disparate data sets is presented. Two data sets, digitized aerial photography at a nominal spatial resolution 3,7 meters and TMS digital data at 24.6 meters, were coregistered through a bilinear interpolation to solve the problem of blocky pixel groups resulting from rectification expansion. The two data sets were then subjected to intensity-saturation-hue (ISH) transformations in order to 'blend' the high-spatial-resolution (3.7 m) digitized RC-10 photography with the high spectral (12-bands) and lower spatial (24.6 m) resolution TMS digital data. The resultant merged products make it possible to perform large-scale mapping, ease photointerpretation, and can be derived for any of the 12 available TMS spectral bands.

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

Smith, Donald F.; Schulz, Carl; Konijnenburg, Marco

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, butmore » requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.« less

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

Pulsed-neutron imaging by a high-speed camera and center-of-gravity processing

NASA Astrophysics Data System (ADS)

Mochiki, K.; Uragaki, T.; Koide, J.; Kushima, Y.; Kawarabayashi, J.; Taketani, A.; Otake, Y.; Matsumoto, Y.; Su, Y.; Hiroi, K.; Shinohara, T.; Kai, T.

2018-01-01

Pulsed-neutron imaging is attractive technique in the research fields of energy-resolved neutron radiography and RANS (RIKEN) and RADEN (J-PARC/JAEA) are small and large accelerator-driven pulsed-neutron facilities for its imaging, respectively. To overcome the insuficient spatial resolution of the conunting type imaging detectors like μ NID, nGEM and pixelated detectors, camera detectors combined with a neutron color image intensifier were investigated. At RANS center-of-gravity technique was applied to spots image obtained by a CCD camera and the technique was confirmed to be effective for improving spatial resolution. At RADEN a high-frame-rate CMOS camera was used and super resolution technique was applied and it was recognized that the spatial resolution was futhermore improved.

Solar Confocal Interferometers for Sub-Picometer-Resolution Spectral Filters

NASA Technical Reports Server (NTRS)

Gary, G. Allen; Pietraszewski, Chris; West, Edward A.; Dines, Terence C.

2006-01-01

The confocal Fabry-Perot interferometer allows sub-picometer spectral resolution of Fraunhofer line profiles. Such high spectral resolution is needed to keep pace with the higher spatial resolution of the new set of large-aperture solar telescopes. The line-of-sight spatial resolution derived for line profile inversions would then track the improvements of the transverse spatial scale provided by the larger apertures. The confocal interferometer's unique properties allow a simultaneous increase in both etendue and spectral power. Methods: We have constructed and tested two confocal interferometers. Conclusions: In this paper we compare the confocal interferometer with other spectral imaging filters, provide initial design parameters, show construction details for two designs, and report on the laboratory test results for these interferometers, and propose a multiple etalon system for future testing of these units and to obtain sub-picometer spectral resolution information on the photosphere in both the visible and near-infrared.

A compact large-format streak tube for imaging lidar

NASA Astrophysics Data System (ADS)

Hui, Dandan; Luo, Duan; Tian, Liping; Lu, Yu; Chen, Ping; Wang, Junfeng; Sai, Xiaofeng; Wen, Wenlong; Wang, Xing; Xin, Liwei; Zhao, Wei; Tian, Jinshou

2018-04-01

The streak tubes with a large effective photocathode area, large effective phosphor screen area, and high photocathode radiant sensitivity are essential for improving the field of view, depth of field, and detectable range of the multiple-slit streak tube imaging lidar. In this paper, a high spatial resolution, large photocathode area, and compact meshless streak tube with a spherically curved cathode and screen is designed and tested. Its spatial resolution reaches 20 lp/mm over the entire Φ28 mm photocathode working area, and the simulated physical temporal resolution is better than 30 ps. The temporal distortion in our large-format streak tube, which is shown to be a non-negligible factor, has a minimum value as the radius of curvature of the photocathode varies. Furthermore, the photocathode radiant sensitivity and radiant power gain reach 41 mA/W and 18.4 at the wavelength of 550 nm, respectively. Most importantly, the external dimensions of our streak tube are no more than Φ60 mm × 110 mm.

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.

Spatial resolution requirements for automated cartographic road extraction

USGS Publications Warehouse

Benjamin, S.; Gaydos, L.

1990-01-01

Ground resolution requirements for detection and extraction of road locations in a digitized large-scale photographic database were investigated. A color infrared photograph of Sunnyvale, California was scanned, registered to a map grid, and spatially degraded to 1- to 5-metre resolution pixels. Road locations in each data set were extracted using a combination of image processing and CAD programs. These locations were compared to a photointerpretation of road locations to determine a preferred pixel size for the extraction method. Based on road pixel omission error computations, a 3-metre pixel resolution appears to be the best choice for this extraction method. -Authors

Extracting spatial information from large aperture exposures of diffuse sources

NASA Technical Reports Server (NTRS)

Clarke, J. T.; Moos, H. W.

1981-01-01

The spatial properties of large aperture exposures of diffuse emission can be used both to investigate spatial variations in the emission and to filter out camera noise in exposures of weak emission sources. Spatial imaging can be accomplished both parallel and perpendicular to dispersion with a resolution of 5-6 arc sec, and a narrow median filter running perpendicular to dispersion across a diffuse image selectively filters out point source features, such as reseaux marks and fast particle hits. Spatial information derived from observations of solar system objects is presented.

Modeling streams and hydrogeomorphic attributes in Oregon from digital and field data

Treesearch

Sharon E. Clarke; Kelly M. Burnett; Daniel J. Miller

2008-01-01

Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo-referenced attributes are uncommon over relevant spatial extents. Field inventories provide high-quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so...

Science and Technology Text Mining: Near-Earth Space

DTIC Science & Technology

2003-07-21

TRANSFER; 177SATELLITE IMAGES; 175 SPATIAL RESOLUTION ; 174 SEA ICE; 166 SYSTEM GPS; 166 TOPEX POSEIDON; 165 SATELLITE MEASUREMENTS; 163 RADIATION BUDGET...1073 ICE; 1065 SATELLITES; 1062 PAPER; 1009 EARTH; 1008 RESOLUTION ; 1000 MODELS; 962 RADIATION; 943 DERIVED; 938 OCEAN; 928 CURRENT; 925 SPATIAL ; 899...PARAMETERS; 729 TECHNIQUE; 714 OPTICAL; 714 SPACECRAFT; 711 DEGREE; 702 TRANSMISSION; 696 LARGE; 693 TEST; 686 NUMBER; 671 EFFECTS ; 662 SPECTRAL ; 661

Improved tracking and resolution of bacteria in holographic microscopy using dye and fluorescent protein labeling

NASA Astrophysics Data System (ADS)

Nadeau, Jay; Cho, YongBin; Kühn, Jonas; Liewer, Kurt

2016-04-01

Digital holographic microscopy (DHM) is an emerging imaging technique that permits instantaneous capture of a relatively large sample volume. However, large volumes usually come at the expense of lower spatial resolution, and the technique has rarely been used with prokaryotic cells due to their small size and low contrast. In this paper we demonstrate the use of a Mach-Zehnder dual-beam instrument for imaging of labeled and unlabeled bacteria and microalgae. Spatial resolution of 0.3 micrometers is achieved, providing a sampling of several pixels across a typical prokaryotic cell. Both cellular motility and morphology are readily recorded. The use of dyes provides both amplitude and phase contrast improvement and is of use to identify cells in dense samples.

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.

Three Dimensional High-Resolution Reconstruction of the Ionosphere Over the Very Large Array

DTIC Science & Technology

2010-12-15

Watts Progress Report, Dec 10; 1 Final Report: Three Dimensional High-Resolution Reconstruction of the Ionosphere over the Very Large Array...proposed research is reconstruct the three-dimensional regional electron density profile of Earth’s ionosphere with spatial resolution of better than 10 km...10x better sensitivity to total electron content (TEC, or chord integrated density) in the ionosphere that does GPS. The proposal funds the

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.

Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges.

PubMed

Fernández-Guisuraga, José Manuel; Sanz-Ablanedo, Enoc; Suárez-Seoane, Susana; Calvo, Leonor

2018-02-14

This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas.

Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges

PubMed Central

2018-01-01

This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas. PMID:29443914

Laser interferometry for the determination of thickness distributions of low absorbing films and their spatial and thickness resolutions.

PubMed

Mishima, T; Kao, K C

1982-03-15

New laser interferometry has been developed, based on the principle that a 2-D fringe pattern can be produced by interference of spatially coherent light beams. To avoid the effect of reflection from the back surface of the substrate, the Brewster angle of incidence is adopted; to suppress the effect of diffraction, a lens or a lens system is used. This laser interferometry is an efficient nondestructive technique for the determination of thickness distributions or uniformities of low absorbing films on transparent substrates over a large area without involving laborious computations. The limitation of spatial resolution, thickness resolution, and visibility of fringes is fully analyzed.

Pushing the limits of spatial resolution with the Kuiper Airborne observatory

NASA Technical Reports Server (NTRS)

Lester, Daniel

1994-01-01

The study of astronomical objects at high spatial resolution in the far-IR is one of the most serious limitations to our work at these wavelengths, which carry information about the luminosity of dusty and obscured sources. At IR wavelengths shorter than 30 microns, ground based telescopes with large apertures at superb sites achieve diffraction-limited performance close to the seeing limit in the optical. At millimeter wavelengths, ground based interferometers achieve resolution that is close to this. The inaccessibility of the far-IR from the ground makes it difficult, however, to achieve complementary resolution in the far-IR. The 1983 IRAS survey, while extraordinarily sensitive, provides us with a sky map at a spatial resolution that is limited by detector size on a spatial scale that is far larger than that available in other wavelengths on the ground. The survey resolution is of order 4 min in the 100 micron bandpass, and 2 min at 60 microns (IRAS Explanatory Supplement, 1988). Information on a scale of 1' is available on some sources from the CPC. Deconvolution and image resolution using this database is one of the subjects of this workshop.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

PubMed Central

Schubert, Walter

2013-01-01

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described—a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs. © 2013 The Authors. Journal of Molecular Recognition published by John Wiley & Sons, Ltd. PMID:24375580

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.

Example-Based Super-Resolution Fluorescence Microscopy.

PubMed

Jia, Shu; Han, Boran; Kutz, J Nathan

2018-04-23

Capturing biological dynamics with high spatiotemporal resolution demands the advancement in imaging technologies. Super-resolution fluorescence microscopy offers spatial resolution surpassing the diffraction limit to resolve near-molecular-level details. While various strategies have been reported to improve the temporal resolution of super-resolution imaging, all super-resolution techniques are still fundamentally limited by the trade-off associated with the longer image acquisition time that is needed to achieve higher spatial information. Here, we demonstrated an example-based, computational method that aims to obtain super-resolution images using conventional imaging without increasing the imaging time. With a low-resolution image input, the method provides an estimate of its super-resolution image based on an example database that contains super- and low-resolution image pairs of biological structures of interest. The computational imaging of cellular microtubules agrees approximately with the experimental super-resolution STORM results. This new approach may offer potential improvements in temporal resolution for experimental super-resolution fluorescence microscopy and provide a new path for large-data aided biomedical imaging.

Large-Scale High-Resolution Cylinder Wake Measurements in a Wind Tunnel using Tomographic PIV with sCMOS Cameras

NASA Astrophysics Data System (ADS)

Michaelis, Dirk; Schroeder, Andreas

2012-11-01

Tomographic PIV has triggered vivid activity, reflected in a large number of publications, covering both: development of the technique and a wide range of fluid dynamic experiments. Maturing of tomo PIV allows the application in medium to large scale wind tunnels. Limiting factor for wind tunnel application is the small size of the measurement volume, being typically about of 50 × 50 × 15 mm3. Aim of this study is the optimization towards large measurement volumes and high spatial resolution performing cylinder wake measurements in a 1 meter wind tunnel. Main limiting factors for the volume size are the laser power and the camera sensitivity. So, a high power laser with 800 mJ per pulse is used together with low noise sCMOS cameras, mounted in forward scattering direction to gain intensity due to the Mie scattering characteristics. A mirror is used to bounce the light back, to have all cameras in forward scattering. Achievable particle density is growing with number of cameras, so eight cameras are used for a high spatial resolution. Optimizations lead to volume size of 230 × 200 × 52 mm3 = 2392 cm3, more than 60 times larger than previously. 281 × 323 × 68 vectors are calculated with spacing of 0.76 mm. The achieved measurement volume size and spatial resolution is regarded as a major step forward in the application of tomo PIV in wind tunnels. Supported by EU-project: no. 265695.

Development and calibration of a new gamma camera detector using large square Photomultiplier Tubes

NASA Astrophysics Data System (ADS)

Zeraatkar, N.; Sajedi, S.; Teimourian Fard, B.; Kaviani, S.; Akbarzadeh, A.; Farahani, M. H.; Sarkar, S.; Ay, M. R.

2017-09-01

Large area scintillation detectors applied in gamma cameras as well as Single Photon Computed Tomography (SPECT) systems, have a major role in in-vivo functional imaging. Most of the gamma detectors utilize hexagonal arrangement of Photomultiplier Tubes (PMTs). In this work we applied large square-shaped PMTs with row/column arrangement and positioning. The Use of large square PMTs reduces dead zones in the detector surface. However, the conventional center of gravity method for positioning may not introduce an acceptable result. Hence, the digital correlated signal enhancement (CSE) algorithm was optimized to obtain better linearity and spatial resolution in the developed detector. The performance of the developed detector was evaluated based on NEMA-NU1-2007 standard. The acquired images using this method showed acceptable uniformity and linearity comparing to three commercial gamma cameras. Also the intrinsic and extrinsic spatial resolutions with low-energy high-resolution (LEHR) collimator at 10 cm from surface of the detector were 3.7 mm and 7.5 mm, respectively. The energy resolution of the camera was measured 9.5%. The performance evaluation demonstrated that the developed detector maintains image quality with a reduced number of used PMTs relative to the detection area.

Space- and time-resolved raman and breakdown spectroscopy: advanced lidar techniques

NASA Astrophysics Data System (ADS)

Silviu, Gurlui; Marius Mihai, Cazacu; Adrian, Timofte; Oana, Rusu; Georgiana, Bulai; Dimitriu, Dan

2018-04-01

DARLIOES - the advanced LIDAR is based on space- and time-resolved RAMAN and breakdown spectroscopy, to investigate chemical and toxic compounds, their kinetics and physical properties at high temporal (2 ns) and spatial (1 cm) resolution. The high spatial and temporal resolution are needed to resolve a large variety of chemical troposphere compounds, emissions from aircraft, the self-organization space charges induced light phenomena, temperature and humidity profiles, ice nucleation, etc.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Relaxation in two dimensions and the 'sinh-Poisson' equation

NASA Technical Reports Server (NTRS)

Montgomery, D.; Matthaeus, W. H.; Stribling, W. T.; Martinez, D.; Oughton, S.

1992-01-01

Long-time states of a turbulent, decaying, two-dimensional, Navier-Stokes flow are shown numerically to relax toward maximum-entropy configurations, as defined by the "sinh-Poisson" equation. The large-scale Reynolds number is about 14,000, the spatial resolution is (512)-squared, the boundary conditions are spatially periodic, and the evolution takes place over nearly 400 large-scale eddy-turnover times.

Single Photon Counting Large Format Imaging Sensors with High Spatial and Temporal Resolution

NASA Astrophysics Data System (ADS)

Siegmund, O. H. W.; Ertley, C.; Vallerga, J. V.; Cremer, T.; Craven, C. A.; Lyashenko, A.; Minot, M. J.

High time resolution astronomical and remote sensing applications have been addressed with microchannel plate based imaging, photon time tagging detector sealed tube schemes. These are being realized with the advent of cross strip readout techniques with high performance encoding electronics and atomic layer deposited (ALD) microchannel plate technologies. Sealed tube devices up to 20 cm square have now been successfully implemented with sub nanosecond timing and imaging. The objective is to provide sensors with large areas (25 cm2 to 400 cm2) with spatial resolutions of <20 μm FWHM and timing resolutions of <100 ps for dynamic imaging. New high efficiency photocathodes for the visible regime are discussed, which also allow response down below 150nm for UV sensing. Borosilicate MCPs are providing high performance, and when processed with ALD techniques are providing order of magnitude lifetime improvements and enhanced photocathode stability. New developments include UV/visible photocathodes, ALD MCPs, and high resolution cross strip anodes for 100 mm detectors. Tests with 50 mm format cross strip readouts suitable for Planacon devices show spatial resolutions better than 20 μm FWHM, with good image linearity while using low gain ( 106). Current cross strip encoding electronics can accommodate event rates of >5 MHz and event timing accuracy of 100 ps. High-performance ASIC versions of these electronics are in development with better event rate, power and mass suitable for spaceflight instruments.

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

DOE PAGES

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy; ...

2018-02-07

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

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

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

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.

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

High Resolution Temperature Measurement of Liquid Stainless Steel Using Hyperspectral Imaging

PubMed Central

Devesse, Wim; De Baere, Dieter; Guillaume, Patrick

2017-01-01

A contactless temperature measurement system is presented based on a hyperspectral line camera that captures the spectra in the visible and near infrared (VNIR) region of a large set of closely spaced points. The measured spectra are used in a nonlinear least squares optimization routine to calculate a one-dimensional temperature profile with high spatial resolution. Measurements of a liquid melt pool of AISI 316L stainless steel show that the system is able to determine the absolute temperatures with an accuracy of 10%. The measurements are made with a spatial resolution of 12 µm/pixel, justifying its use in applications where high temperature measurements with high spatial detail are desired, such as in the laser material processing and additive manufacturing fields. PMID:28067764

High-resolution mid-infrared observations of NGC 7469

NASA Technical Reports Server (NTRS)

Miles, J. W.; Houck, J. R.; Hayward, T. L.

1994-01-01

We present a high-resolution 11.7 micrometer image of the starburst/Seyfert hybrid galaxy NGC 7469 using the Hale 5 m telescope at Palomar Observatory. Our map, with diffraction limited spatial resolution of 0.6 sec, shows a 3 sec diameter ring of emission around an unresolved nucleus. The map is similar to the Very Large Array (VLA) 6 cm map of this galaxy made with 0.4 sec resolution by Wilson et al. (1991). About half of the mid-infrared flux in our map emerges from the unresolved nucleus. We also present spatially resolved low resolution spectra that show that the 11.3 micrometer polycyclic aromatic hydrocarbon (PAH) feature comes from the circumnuclear ring but not from the nucleus of the galaxy.

Investigation of spatial resolution and temporal performance of SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout) with integrated electrostatic focusing

NASA Astrophysics Data System (ADS)

Scaduto, David A.; Lubinsky, Anthony R.; Rowlands, John A.; Kenmotsu, Hidenori; Nishimoto, Norihito; Nishino, Takeshi; Tanioka, Kenkichi; Zhao, Wei

2014-03-01

We have previously proposed SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout), a novel detector concept with potentially superior spatial resolution and low-dose performance compared with existing flat-panel imagers. The detector comprises a scintillator that is optically coupled to an amorphous selenium photoconductor operated with avalanche gain, known as high-gain avalanche rushing photoconductor (HARP). High resolution electron beam readout is achieved using a field emitter array (FEA). This combination of avalanche gain, allowing for very low-dose imaging, and electron emitter readout, providing high spatial resolution, offers potentially superior image quality compared with existing flat-panel imagers, with specific applications to fluoroscopy and breast imaging. Through the present collaboration, a prototype HARP sensor with integrated electrostatic focusing and nano- Spindt FEA readout technology has been fabricated. The integrated electron-optic focusing approach is more suitable for fabricating large-area detectors. We investigate the dependence of spatial resolution on sensor structure and operating conditions, and compare the performance of electrostatic focusing with previous technologies. Our results show a clear dependence of spatial resolution on electrostatic focusing potential, with performance approaching that of the previous design with external mesh-electrode. Further, temporal performance (lag) of the detector is evaluated and the results show that the integrated electrostatic focusing design exhibits comparable or better performance compared with the mesh-electrode design. This study represents the first technical evaluation and characterization of the SAPHIRE concept with integrated electrostatic focusing.

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.

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.

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

The Atacama Large Millimeter/submillimeter Array (alma): Early Results

NASA Astrophysics Data System (ADS)

Wootten, Alwyn

2012-06-01

New radioastronomical instruments, such as ALMA or the Jansky VLA, have increased spectral throughput by orders of magnitude over previously available capabilities. ALMA brings orders of magnitude increases in spectral sensitivity and spatial resolution over what has previously been available. These increased capabilities open new possibilities for studies of complex molecules in the interstellar medium. Complex interstellar molecules may form on the surfaces of interstellar grains, after which they may be liberated into the gas phase by shocks, radiation, or other external influences. Emission from complex molecules may be diluted owing to the large number of transitions large molecules may undergo, particularly in warm regions of interstellar clouds. High sensitivity and spatial resolution are necessary to explore the distributions and relationships of these molecules. Of particular interest are the distributions of large organic molecules. Observations which establish the relationships between various large molecules are now emerging from these new instruments and will be discussed.

A new PET detector concept for compact preclinical high-resolution hybrid MR-PET

NASA Astrophysics Data System (ADS)

Berneking, Arne; Gola, Alberto; Ferri, Alessandro; Finster, Felix; Rucatti, Daniele; Paternoster, Giovanni; Jon Shah, N.; Piemonte, Claudio; Lerche, Christoph

2018-04-01

This work presents a new PET detector concept for compact preclinical hybrid MR-PET. The detector concept is based on Linearly-Graded SiPM produced with current FBK RGB-HD technology. One 7.75 mm x 7.75 mm large sensor chip is coupled with optical grease to a black coated 8 mm x 8 mm large and 3 mm thick monolithic LYSO crystal. The readout is obtained from four readout channels with the linear encoding based on integrated resistors and the Center of Gravity approach. To characterize the new detector concept, the spatial and energy resolutions were measured. Therefore, the measurement setup was prepared to radiate a collimated beam to 25 different points perpendicular to the monolithic scintillator crystal. Starting in the center point of the crystal at 0 mm / 0 mm and sampling a grid with a pitch of 1.75 mm, all significant points of the detector were covered by the collimator beam. The measured intrinsic spatial resolution (FWHM) was 0.74 +/- 0.01 mm in x- and 0.69 +/- 0.01 mm in the y-direction at the center of the detector. At the same point, the measured energy resolution (FWHM) was 13.01 +/- 0.05 %. The mean intrinsic spatial resolution (FWHM) over the whole detector was 0.80 +/- 0.28 mm in x- and 0.72 +/- 0.19 mm in y-direction. The energy resolution (FWHM) of the detector was between 13 and 17.3 % with an average energy resolution of 15.7 +/- 1.0 %. Due to the reduced thickness, the sensitivity of this gamma detector is low but still higher than pixelated designs with the same thickness due to the monolithic crystals. Combining compact design, high spatial resolution, and high sensitivity, the detector concept is particularly suitable for applications where the scanner bore size is limited and high resolution is required - as is the case in small animal hybrid MR-PET.

Simulated Performances of a Very High Energy Tomograph for Non-Destructive Characterization of large objects

NASA Astrophysics Data System (ADS)

Kistler, Marc; Estre, Nicolas; Merle, Elsa

2018-01-01

As part of its R&D activities on high-energy X-ray imaging for non-destructive characterization, the Nuclear Measurement Laboratory has started an upgrade of its imaging system currently implemented at the CEA-Cadarache center. The goals are to achieve a sub-millimeter spatial resolution and the ability to perform tomographies on very large objects (more than 100-cm standard concrete or 40-cm steel). This paper presentsresults on the detection part of the imaging system. The upgrade of the detection part needs a thorough study of the performance of two detectors: a series of CdTe semiconductor sensors and two arrays of segmented CdWO4 scintillators with different pixel sizes. This study consists in a Quantum Accounting Diagram (QAD) analysis coupled with Monte-Carlo simulations. The scintillator arrays are able to detect millimeter details through 140 cm of concrete, but are limited to 120 cm for smaller ones. CdTe sensors have lower but more stable performance, with a 0.5 mm resolution for 90 cm of concrete. The choice of the detector then depends on the preferred characteristic: the spatial resolution or the use on large volumes. The combination of the features of the source and the studies on the detectors gives the expected performance of the whole equipment, in terms of signal-over-noise ratio (SNR), spatial resolution and acquisition time.

Monitoring Termite-Mediated Ecosystem Processes Using Moderate and High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Lind, B. M.; Hanan, N. P.

2016-12-01

Termites are considered dominant decomposers and prominent ecosystem engineers in the global tropics and they build some of the largest and architecturally most complex non-human-made structures in the world. Termite mounds significantly alter soil texture, structure, and nutrients, and have major implications for local hydrological dynamics, vegetation characteristics, and biological diversity. An understanding of how these processes change across large scales has been limited by our ability to detect termite mounds at high spatial resolutions. Our research develops methods to detect large termite mounds in savannas across extensive geographic areas using moderate and high resolution satellite imagery. We also investigate the effect of termite mounds on vegetation productivity using Landsat-8 maximum composite NDVI data as a proxy for production. Large termite mounds in arid and semi-arid Senegal generate highly reflective `mound scars' with diameters ranging from 10 m at minimum to greater than 30 m. As Sentinel-2 has several bands with 10 m resolution and Landsat-8 has improved calibration, higher radiometric resolution, 15 m spatial resolution (pansharpened), and improved contrast between vegetated and bare surfaces compared to previous Landsat missions, we found that the largest and most influential mounds in the landscape can be detected. Because mounds as small as 4 m in diameter are easily detected in high resolution imagery we used these data to validate detection results and quantify omission errors for smaller mounds.

Reserch on Spatial and Temporal Distribution of Color Steel Building Based on Multi-Source High-Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Yang, S. W.; Ma, J. J.; Wang, J. M.

2018-04-01

As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city's image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building's special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

USDA-ARS?s Scientific Manuscript database

Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

Resolution Analysis of finite fault inversions: A back-projection approach.

NASA Astrophysics Data System (ADS)

Ji, C.; Shao, G.

2007-12-01

The resolution of inverted source models of large earthquakes is controlled by frequency contents of "coherent" (or "useful") seismic observations and their spatial distribution. But it is difficult to distinguish whether some features consistent during different inversions are really required by data or a consequence of "prior" information, such as velocity structures, fault geometry, model parameterizations. Here, we investigate the model spatial resolution by first back projecting and stacking the data at the source regions and then analyzing the spatial- temporal variations of the focusing regions, which arbitrarily defined as the regions with 90% of the peak focusing amplitude. Our preliminary results indicated 1) The spatial-temporal resolution at a particularly direction is controlled by the region of directivity parameter [pcos(θ)] within the seismic network, where p is the horizontal slowness from the hypocenter and θ is the difference between the station azimuth and this orientation. Therefore, the network aperture is more important than the number of stations. 2) Simple stacking method is a robust method to capture the asperities but the sizes of focusing regions are usually much larger than what data could resolve. By carefully weighting the data before the stacking could enhance the spatial resolution in a particular direction. 3) The results based on the teleseismic P waves of a local network usually surfers the trade-off between the source's spatial location and its rupture time. The resolution of the 2001 Kunlunshan earthquake and 2006 Kuril island earthquake will be investigated.

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects.

PubMed

Sollmann, Nico; Hauck, Theresa; Tussis, Lorena; Ille, Sebastian; Maurer, Stefanie; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-10-24

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated. Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7-30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0-26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9-27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0-24.2 mm) were measured. According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

Electro-optical design of a long slit streak tube

NASA Astrophysics Data System (ADS)

Tian, Liping; Tian, Jinshou; Wen, Wenlong; Chen, Ping; Wang, Xing; Hui, Dandan; Wang, Junfeng

2017-11-01

A small size and long slit streak tube with high spatial resolution was designed and optimized. Curved photocathode and screen were adopted to increase the photocathode working area and spatial resolution. High physical temporal resolution obtained by using a slit accelerating electrode. Deflection sensitivity of the streak tube was improved by adopting two-folded deflection plates. The simulations indicate that the photocathode effective working area can reach 30mm × 5mm. The static spatial resolution is higher than 40lp/mm and 12lp/mm along scanning and slit directions respectively while the physical temporal resolution is higher than 60ps. The magnification is 0.75 and 0.77 in scanning and slit directions. And also, the deflection sensitivity is as high as 37mm/kV. The external dimension of the streak tube are only ∅74mm×231mm. Thus, it can be applied to laser imaging radar system for large field of view and high range precision detection.

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

Toward a RPC-based muon tomography system for cargo containers.

NASA Astrophysics Data System (ADS)

Baesso, P.; Cussans, D.; Thomay, C.; Velthuis, J.

2014-10-01

A large area scanner for cosmic muon tomography is currently being developed at University of Bristol. Thanks to their abundance and penetrating power, cosmic muons have been suggested as ideal candidates to scan large containers in search of special nuclear materials, which are characterized by high-Z and high density. The feasibility of such a scanner heavily depends on the detectors used to track the muons: for a typical container, the minimum required sensitive area is of the order of 100 2. The spatial resolution required depends on the geometrical configuration of the detectors. For practical purposes, a resolution of the order of 1 mm or better is desirable. A good time resolution can be exploited to provide momentum information: a resolution of the order of nanoseconds can be used to separate sub-GeV muons from muons with higher energies. Resistive plate chambers have a low cost per unit area and good spatial and time resolution; these features make them an excellent choice as detectors for muon tomography. In order to instrument a large area demonstrator we have produced 25 new readout boards and 30 glass RPCs. The RPCs measure 1800 mm× 600 mm and are read out using 1.68 mm pitch copper strips. The chambers were tested with a standardized procedure, i.e. without optimizing the working parameters to take into account differences in the manufacturing process, and the results show that the RPCs have an efficiency between 87% and 95%. The readout electronics show a signal to noise ratio greater than 20 for minimum ionizing particles. Spatial resolution better than 500 μm can easily be achieved using commercial read out ASICs. These results are better than the original minimum requirements to pass the tests and we are now ready to install the detectors.

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.

Ultrabroadband infrared nanospectroscopic imaging

PubMed Central

Bechtel, Hans A.; Muller, Eric A.; Olmon, Robert L.; Martin, Michael C.; Raschke, Markus B.

2014-01-01

Characterizing and ultimately controlling the heterogeneity underlying biomolecular functions, quantum behavior of complex matter, photonic materials, or catalysis requires large-scale spectroscopic imaging with simultaneous specificity to structure, phase, and chemical composition at nanometer spatial resolution. However, as with any ultrahigh spatial resolution microscopy technique, the associated demand for an increase in both spatial and spectral bandwidth often leads to a decrease in desired sensitivity. We overcome this limitation in infrared vibrational scattering-scanning probe near-field optical microscopy using synchrotron midinfrared radiation. Tip-enhanced localized light–matter interaction is induced by low-noise, broadband, and spatially coherent synchrotron light of high spectral irradiance, and the near-field signal is sensitively detected using heterodyne interferometric amplification. We achieve sub-40-nm spatially resolved, molecular, and phonon vibrational spectroscopic imaging, with rapid spectral acquisition, spanning the full midinfrared (700–5,000 cm−1) with few cm−1 spectral resolution. We demonstrate the performance of synchrotron infrared nanospectroscopy on semiconductor, biomineral, and protein nanostructures, providing vibrational chemical imaging with subzeptomole sensitivity. PMID:24803431

Influence of hydration and annealing on structure, PSL yield and spatial resolution of pressed powder imaging plates of the X-ray storage phosphor CsBr:Eu2+

NASA Astrophysics Data System (ADS)

Kersting, E.; von Seggern, H.

2017-08-01

A new production route for europium doped cesium bromide (CsBr:Eu2+) imaging plates has been developed, synthesizing CsBr:Eu2+ powder from a precipitation reaction of aqueous CsBr solution with ethanol. This new route allows the control of features like homogeneous grain size and grain shape of the obtained powder. After drying and subsequent compacting the powder, disk-like samples were fabricated, and their resulting photostimulated luminescence (PSL) properties like yield and spatial resolution were determined. It will be shown that hydration of such disks causes the CsBr:Eu2+ powder to recrystallize starting from the humidity exposed surfaces to the sample interior up to a completely polycrystalline sample resulting in a decreasing PSL yield and an increasing resolution. Subsequent annealing leads to grain refinement combined with a large PSL yield increment and a minor effect on the spatial resolution. By first annealing the "as made" disk, one observes a strong increment of the PSL yield and almost no effect on the spatial resolution. During subsequent hydration, the recrystallization is hindered by minor structural changes of the grains. The related PSL yield drops slightly with increasing hydration time, and the spatial resolution drops considerably. The obtained PSL properties with respect to structure will be discussed with a simple model.

A PIXEL COMPOSITION-BASED REFERENCE DATA SET FOR THEMATIC ACCURACY ASSESSMENT

EPA Science Inventory

Developing reference data sets for accuracy assessment of land-cover classifications derived from coarse spatial resolution sensors such as MODIS can be difficult due to the large resolution differences between the image data and available reference data sources. Ideally, the spa...

Spatially resolved Spectroscopy of Europa’s Large-scale Compositional Units at 3-4 μm with Keck NIRSPEC

NASA Astrophysics Data System (ADS)

Fischer, P. D.; Brown, M. E.; Trumbo, S. K.; Hand, K. P.

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3-4 μm obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3-4 μm. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μm compared to icy regions. These observations complement previous spectra of large-scale chaos, and can aid efforts to identify the endogenous non-ice species.

Micromirror structured illumination microscope for high-speed in vivo drosophila brain imaging.

PubMed

Masson, A; Pedrazzani, M; Benrezzak, S; Tchenio, P; Preat, T; Nutarelli, D

2014-01-27

Genetic tools and especially genetically encoded fluorescent reporters have given a special place to optical microscopy in drosophila neurobiology research. In order to monitor neural networks activity, high speed and sensitive techniques, with high spatial resolution are required. Structured illumination microscopies are wide-field approaches with optical sectioning ability. Despite the large progress made with the introduction of the HiLo principle, they did not meet the criteria of speed and/or spatial resolution for drosophila brain imaging. We report on a new implementation that took advantage of micromirror matrix technology to structure the illumination. Thus, we showed that the developed instrument exhibits a spatial resolution close to that of confocal microscopy but it can record physiological responses with a speed improved by more than an order a magnitude.

On-road black carbon instrument intercomparison and aerosol characteristics by driving environment

EPA Science Inventory

Large spatial variations of black carbon (BC) concentrations in the on-road and near-road environments necessitate measurements with high spatial resolution to assess exposure accurately. A series of measurements was made comparing the performance of several different BC instrume...

Spatial imaging of UV emission from Jupiter and Saturn

NASA Technical Reports Server (NTRS)

Clarke, J. T.; Moos, H. W.

1981-01-01

Spatial imaging with the IUE is accomplished both by moving one of the apertures in a series of exposures and within the large aperture in a single exposure. The image of the field of view subtended by the large aperture is focussed directly onto the detector camera face at each wavelength; since the spatial resolution of the instrument is 5 to 6 arc sec and the aperture extends 23.0 by 10.3 arc sec, imaging both parallel and perpendicular to dispersion is possible in a single exposure. The correction for the sensitivity variation along the slit at 1216 A is obtained from exposures of diffuse geocoronal H Ly alpha emission. The relative size of the aperture superimposed on the apparent discs of Jupiter and Saturn in typical observation is illustrated. By moving the planet image 10 to 20 arc sec along the major axis of the aperture (which is constrained to point roughly north-south) maps of the discs of these planets are obtained with 6 arc sec spatial resolution.

Lessons Learned From Large-Scale Evapotranspiration and Root Zone Soil Moisture Mapping Using Ground Measurements (meteorological, LAS, EC) and Remote Sensing (METRIC)

NASA Astrophysics Data System (ADS)

Hendrickx, J. M. H.; Allen, R. G.; Myint, S. W.; Ogden, F. L.

2015-12-01

Large scale mapping of evapotranspiration and root zone soil moisture is only possible when satellite images are used. The spatial resolution of this imagery typically depends on its temporal resolution or the satellite overpass time. For example, the Landsat satellite acquires images at 30 m resolution every 16 days while the MODIS satellite acquires images at 250 m resolution every day. In this study we deal with optical/thermal imagery that is impacted by cloudiness contrary to radar imagery that penetrates through clouds. Due to cloudiness, the temporal resolution of Landsat drops from 16 days to about one clear sky Landsat image per month in the southwestern USA and about one every ten years in the humid tropics of Panama. Only by launching additional satellites can the temporal resolution be improved. Since this is too costly, an alternative is found by using ground measurements with high temporal resolution (from minutes to days) but poor spatial resolution. The challenge for large-scale evapotranspiration and root zone soil moisture mapping is to construct a layer stack consisting of N time layers covering the period of interest each containing M pixels covering the region of interest. We will present examples of the Phoenix Active Management Area in AZ (14,600 km2), Green River Basin in WY (44,000 km2), the Kishwaukee Watershed in IL (3,150 km2), the area covered by Landsat Path 28/Row 35 in OK (30,000 km2) and the Agua Salud Watershed in Panama (200 km2). In these regions we used Landsat or MODIS imagery for mapping evapotranspiration and root zone soil moisture by the algorithm Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) together with meteorological measurements and sometimes either Large Aperture Scintillometers (LAS) or Eddy Covariance (EC). We conclude with lessons learned for future large-scale hydrological studies.

GIEMS-D3: A new long-term, dynamical, high-spatial resolution inundation extent dataset at global scale

NASA Astrophysics Data System (ADS)

Aires, Filipe; Miolane, Léo; Prigent, Catherine; Pham Duc, Binh; Papa, Fabrice; Fluet-Chouinard, Etienne; Lehner, Bernhard

2017-04-01

The Global Inundation Extent from Multi-Satellites (GIEMS) provides multi-year monthly variations of the global surface water extent at 25kmx25km resolution. It is derived from multiple satellite observations. Its spatial resolution is usually compatible with climate model outputs and with global land surface model grids but is clearly not adequate for local applications that require the characterization of small individual water bodies. There is today a strong demand for high-resolution inundation extent datasets, for a large variety of applications such as water management, regional hydrological modeling, or for the analysis of mosquitos-related diseases. A new procedure is introduced to downscale the GIEMS low spatial resolution inundations to a 3 arc second (90 m) dataset. The methodology is based on topography and hydrography information from the HydroSHEDS database. A new floodability index is adopted and an innovative smoothing procedure is developed to ensure the smooth transition, in the high-resolution maps, between the low-resolution boxes from GIEMS. Topography information is relevant for natural hydrology environments controlled by elevation, but is more limited in human-modified basins. However, the proposed downscaling approach is compatible with forthcoming fusion with other more pertinent satellite information in these difficult regions. The resulting GIEMS-D3 database is the only high spatial resolution inundation database available globally at the monthly time scale over the 1993-2007 period. GIEMS-D3 is assessed by analyzing its spatial and temporal variability, and evaluated by comparisons to other independent satellite observations from visible (Google Earth and Landsat), infrared (MODIS) and active microwave (SAR).

Intensity-hue-saturation-based image fusion using iterative linear regression

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

The image fusion process basically produces a high-resolution image by combining the superior features of a low-resolution spatial image and a high-resolution panchromatic image. Despite its common usage due to its fast computing capability and high sharpening ability, the intensity-hue-saturation (IHS) fusion method may cause some color distortions, especially when a large number of gray value differences exist among the images to be combined. This paper proposes a spatially adaptive IHS (SA-IHS) technique to avoid these distortions by automatically adjusting the exact spatial information to be injected into the multispectral image during the fusion process. The SA-IHS method essentially suppresses the effects of those pixels that cause the spectral distortions by assigning weaker weights to them and avoiding a large number of redundancies on the fused image. The experimental database consists of IKONOS images, and the experimental results both visually and statistically prove the enhancement of the proposed algorithm when compared with the several other IHS-like methods such as IHS, generalized IHS, fast IHS, and generalized adaptive IHS.

A new approach to large area microchannel plate manufacture

NASA Technical Reports Server (NTRS)

1986-01-01

Methods of manufacture of twisted single elements as the base for producing microchannel plates (MCP) are discussed. Initial evaluations validated the off-axis channel concept and no technological roadblocks were identified which would prevent fabrication of high gain, high spatial resolution, large format MCP's using this technique. The first MP's have operated at stable gains of 3 million with pulse height resolution superior to results obtained by standard chevron MCP's.

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

Treesearch

Ryan R. McShane; Katelyn P. Driscoll; Roy Sando

2017-01-01

Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large...

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff; Skalka, Christian

2012-01-01

This invention is designed to ascertain the snow water equivalence (SWE) of snowpacks with better spatial and temporal resolutions than present techniques. The approach is ground-based, as opposed to some techniques that are air-based. In addition, the approach is compact, non-destructive, and can be communicated with remotely, and thus can be deployed in areas not possible with current methods. Presently there are two principal ground-based techniques for obtaining SWE measurements. The first is manual snow core measurements of the snowpack. This approach is labor-intensive, destructive, and has poor temporal resolution. The second approach is to deploy a large (e.g., 3x3 m) snowpillow, which requires significant infrastructure, is potentially hazardous [uses a approximately equal to 200-gallon (approximately equal to 760-L) antifreeze-filled bladder], and requires deployment in a large, flat area. High deployment costs necessitate few installations, thus yielding poor spatial resolution of data. Both approaches have limited usefulness in complex and/or avalanche-prone terrains. This approach is compact, non-destructive to the snowpack, provides high temporal resolution data, and due to potential low cost, can be deployed with high spatial resolution. The invention consists of three primary components: a robust wireless network and computing platform designed for harsh climates, new SWE sensing strategies, and algorithms for smart sampling, data logging, and SWE computation.

Coastal habitat mapping in the Aegean Sea using high resolution orthophoto maps

NASA Astrophysics Data System (ADS)

Topouzelis, Konstantinos; Papakonstantinou, Apostolos; Doukari, Michaela; Stamatis, Panagiotis; Makri, Despina; Katsanevakis, Stelios

2017-09-01

The significance of coastal habitat mapping lies in the need to prevent from anthropogenic interventions and other factors. Until 2015, Landsat-8 (30m) imagery were used as medium spatial resolution satellite imagery. So far, Sentinel-2 satellite imagery is very useful for more detailed regional scale mapping. However, the use of high resolution orthophoto maps, which are determined from UAV data, is expected to improve the mapping accuracy. This is due to small spatial resolution of the orthophoto maps (30 cm). This paper outlines the integration of UAS for data acquisition and Structure from Motion (SfM) pipeline for the visualization of selected coastal areas in the Aegean Sea. Additionally, the produced orthophoto maps analyzed through an object-based image analysis (OBIA) and nearest-neighbor classification for mapping the coastal habitats. Classification classes included the main general habitat types, i.e. seagrass, soft bottom, and hard bottom The developed methodology applied at the Koumbara beach (Ios Island - Greece). Results showed that UAS's data revealed the sub-bottom complexity in large shallow areas since they provide such information in the spatial resolution that permits the mapping of seagrass meadows with extreme detail. The produced habitat vectors are ideal as reference data for studies with satellite data of lower spatial resolution.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Improved wetland classification using eight-band high-resolution satellite imagery and a hybrid approach

EPA Science Inventory

Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of derived wetland maps were limited or often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. This re...

Contribution of the channel electron multiplier to the race of vacuum tubes towards picosecond resolution time

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

Pietri, G.

1977-02-01

The ability to tightly pack millions of microscopic secondary emitting channels into a two-dimensional, very thin, array known as a microchannel plate (MCP) provides excellent electrical charge or current amplification associated with an extremely short response time as well as very good spatial resolution. The ultimate performances in spatial and temporal resolutions achieved by MCP-based vacuum devices are discussed and illustrated by the description of a large range of experimental prototypes (photomultipliers, oscilloscope tubes, streak camera tubes, etc.) designed and produced at LEP, then tested in cooperation with Nuclear Research and Plasma Physics Centers in Europe and USA.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

High-spatial resolution and high-spectral resolution detector for use in the measurement of solar flare hard X-rays

NASA Technical Reports Server (NTRS)

Desai, U. D.; Orwig, Larry E.

1988-01-01

In the areas of high spatial resolution, the evaluation of a hard X-ray detector with 65 micron spatial resolution for operation in the energy range from 30 to 400 keV is proposed. The basic detector is a thick large-area scintillator faceplate, composed of a matrix of high-density scintillating glass fibers, attached to a proximity type image intensifier tube with a resistive-anode digital readout system. Such a detector, combined with a coded-aperture mask, would be ideal for use as a modest-sized hard X-ray imaging instrument up to X-ray energies as high as several hundred keV. As an integral part of this study it was also proposed that several techniques be critically evaluated for X-ray image coding which could be used with this detector. In the area of high spectral resolution, it is proposed to evaluate two different types of detectors for use as X-ray spectrometers for solar flares: planar silicon detectors and high-purity germanium detectors (HPGe). Instruments utilizing these high-spatial-resolution detectors for hard X-ray imaging measurements from 30 to 400 keV and high-spectral-resolution detectors for measurements over a similar energy range would be ideally suited for making crucial solar flare observations during the upcoming maximum in the solar cycle.

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

NASA Technical Reports Server (NTRS)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Large-Scale, High-Resolution Neurophysiological Maps Underlying fMRI of Macaque Temporal Lobe

PubMed Central

Papanastassiou, Alex M.; DiCarlo, James J.

2013-01-01

Maps obtained by functional magnetic resonance imaging (fMRI) are thought to reflect the underlying spatial layout of neural activity. However, previous studies have not been able to directly compare fMRI maps to high-resolution neurophysiological maps, particularly in higher level visual areas. Here, we used a novel stereo microfocal x-ray system to localize thousands of neural recordings across monkey inferior temporal cortex (IT), construct large-scale maps of neuronal object selectivity at subvoxel resolution, and compare those neurophysiology maps with fMRI maps from the same subjects. While neurophysiology maps contained reliable structure at the sub-millimeter scale, fMRI maps of object selectivity contained information at larger scales (>2.5 mm) and were only partly correlated with raw neurophysiology maps collected in the same subjects. However, spatial smoothing of neurophysiology maps more than doubled that correlation, while a variety of alternative transforms led to no significant improvement. Furthermore, raw spiking signals, once spatially smoothed, were as predictive of fMRI maps as local field potential signals. Thus, fMRI of the inferior temporal lobe reflects a spatially low-passed version of neurophysiology signals. These findings strongly validate the widespread use of fMRI for detecting large (>2.5 mm) neuronal domains of object selectivity but show that a complete understanding of even the most pure domains (e.g., faces vs nonface objects) requires investigation at fine scales that can currently only be obtained with invasive neurophysiological methods. PMID:24048850

Rapid orthophoto development system.

DOT National Transportation Integrated Search

2013-06-01

The DMC system procured in the project represented state-of-the-art, large-format digital aerial camera systems at the start of : project. DMC is based on the frame camera model, and to achieve large ground coverage with high spatial resolution, the ...

Analyzing Snowpack Metrics Over Large Spatial Extents Using Calibrated, Enhanced-Resolution Brightness Temperature Data and Long Short Term Memory Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Norris, W.; J Q Farmer, C.

2017-12-01

Snow water equivalence (SWE) is a difficult metric to measure accurately over large spatial extents; snow-tell sites are too localized, and traditional remotely sensed brightness temperature data is at too coarse of a resolution to capture variation. The new Calibrated Enhanced-Resolution Brightness Temperature (CETB) data from the National Snow and Ice Data Center (NSIDC) offers remotely sensed brightness temperature data at an enhanced resolution of 3.125 km versus the original 25 km, which allows for large spatial extents to be analyzed with reduced uncertainty compared to the 25km product. While the 25km brightness temperature data has proved useful in past research — one group found decreasing trends in SWE outweighed increasing trends three to one in North America; other researchers used the data to incorporate winter conditions, like snow cover, into ecological zoning criterion — with the new 3.125 km data, it is possible to derive more accurate metrics for SWE, since we have far more spatial variability in measurements. Even with higher resolution data, using the 37 - 19 GHz frequencies to estimate SWE distorts the data during times of melt onset and accumulation onset. Past researchers employed statistical splines, while other successful attempts utilized non-parametric curve fitting to smooth out spikes distorting metrics. In this work, rather than using legacy curve fitting techniques, a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) was trained to perform curve fitting on the data. LSTM ANN have shown great promise in modeling time series data, and with almost 40 years of data available — 14,235 days — there is plenty of training data for the ANN. LSTM's are ideal for this type of time series analysis because they allow important trends to persist for long periods of time, but ignore short term fluctuations; since LSTM's have poor mid- to short-term memory, they are ideal for smoothing out the large spikes generated in the melt and accumulation onset seasons, while still capturing the overall trends in the data.

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.

Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction

PubMed Central

Proust, Gwénaëlle; Trimby, Patrick; Piazolo, Sandra; Retraint, Delphine

2017-01-01

One of the challenges in microstructure analysis nowadays resides in the reliable and accurate characterization of ultra-fine grained (UFG) and nanocrystalline materials. The traditional techniques associated with scanning electron microscopy (SEM), such as electron backscatter diffraction (EBSD), do not possess the required spatial resolution due to the large interaction volume between the electrons from the beam and the atoms of the material. Transmission electron microscopy (TEM) has the required spatial resolution. However, due to a lack of automation in the analysis system, the rate of data acquisition is slow which limits the area of the specimen that can be characterized. This paper presents a new characterization technique, Transmission Kikuchi Diffraction (TKD), which enables the analysis of the microstructure of UFG and nanocrystalline materials using an SEM equipped with a standard EBSD system. The spatial resolution of this technique can reach 2 nm. This technique can be applied to a large range of materials that would be difficult to analyze using traditional EBSD. After presenting the experimental set up and describing the different steps necessary to realize a TKD analysis, examples of its use on metal alloys and minerals are shown to illustrate the resolution of the technique and its flexibility in term of material to be characterized. PMID:28447998

Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction.

PubMed

Proust, Gwénaëlle; Trimby, Patrick; Piazolo, Sandra; Retraint, Delphine

2017-04-01

One of the challenges in microstructure analysis nowadays resides in the reliable and accurate characterization of ultra-fine grained (UFG) and nanocrystalline materials. The traditional techniques associated with scanning electron microscopy (SEM), such as electron backscatter diffraction (EBSD), do not possess the required spatial resolution due to the large interaction volume between the electrons from the beam and the atoms of the material. Transmission electron microscopy (TEM) has the required spatial resolution. However, due to a lack of automation in the analysis system, the rate of data acquisition is slow which limits the area of the specimen that can be characterized. This paper presents a new characterization technique, Transmission Kikuchi Diffraction (TKD), which enables the analysis of the microstructure of UFG and nanocrystalline materials using an SEM equipped with a standard EBSD system. The spatial resolution of this technique can reach 2 nm. This technique can be applied to a large range of materials that would be difficult to analyze using traditional EBSD. After presenting the experimental set up and describing the different steps necessary to realize a TKD analysis, examples of its use on metal alloys and minerals are shown to illustrate the resolution of the technique and its flexibility in term of material to be characterized.

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

SPATIALLY RESOLVED SPECTROSCOPY OF EUROPA’S LARGE-SCALE COMPOSITIONAL UNITS AT 3–4 μ m WITH KECK NIRSPEC

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

Fischer, P. D.; Brown, M. E.; Trumbo, S. K.

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3–4 μ m obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3–4 μ m. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μ m compared to icy regions. These observations complement previous spectra of large-scalemore » chaos, and can aid efforts to identify the endogenous non-ice species.« less

Off-axis electron holography combining summation of hologram series with double-exposure phase-shifting: Theory and application.

PubMed

Boureau, Victor; McLeod, Robert; Mayall, Benjamin; Cooper, David

2018-06-04

In this paper we discuss developments for Lorentz mode or "medium resolution" off-axis electron holography such that it is now routinely possible obtain very high sensitivity phase maps with high spatial resolution whilst maintaining a large field of view. Modifications of the usual Fourier reconstruction procedure have been used to combine series of holograms for sensitivity improvement with a phase-shifting method for doubling the spatial resolution. In the frame of these developments, specific attention is given to the phase standard deviation description and its interaction with the spatial resolution as well as the processing of reference holograms. An experimental study based on Dark-Field Electron Holography (DFEH), using a SiGe/Si multilayer epitaxy sample is compared with theory. The method's efficiency of removing the autocorrelation term during hologram reconstruction is discussed. Software has been written in DigitalMicrograph that can be used to routinely perform these tasks. To illustrate the real improvements made using these methods we show that a strain measurement sensitivity of  ±  0.025 % can be achieved with a spatial resolution of 2 nm and  ±  0.13 % with a spatial resolution of 1 nm whilst maintaining a useful field of view of 300 nm. In the frame of these measurements a model of strain noise for DFEH has also been developed. Copyright © 2018. Published by Elsevier B.V.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Far Infrared Imaging Spectrometer for Large Aperture Infrared Telescope System

DTIC Science & Technology

1985-12-01

resolution Fabry - Perot spectrometer (103 < Resolution < 104) for wavelengths from about 50 to 200 micrometer, employing extended field diffraction limited...photo- metry. The Naval Research Laboratory will provide a high resolution Far Infrared Imaging Spectrometer (FIRIS) using Fabry - Perot techniques in...detectors to provide spatial information. The Fabry - Perot uses electromagnetic coil displacement drivers with a lead screw drive to obtain parallel

Monte Carlo simulation of the spatial resolution and depth sensitivity of two-dimensional optical imaging of the brain

PubMed Central

Tian, Peifang; Devor, Anna; Sakadžić, Sava; Dale, Anders M.; Boas, David A.

2011-01-01

Absorption or fluorescence-based two-dimensional (2-D) optical imaging is widely employed in functional brain imaging. The image is a weighted sum of the real signal from the tissue at different depths. This weighting function is defined as “depth sensitivity.” Characterizing depth sensitivity and spatial resolution is important to better interpret the functional imaging data. However, due to light scattering and absorption in biological tissues, our knowledge of these is incomplete. We use Monte Carlo simulations to carry out a systematic study of spatial resolution and depth sensitivity for 2-D optical imaging methods with configurations typically encountered in functional brain imaging. We found the following: (i) the spatial resolution is <200 μm for NA ≤0.2 or focal plane depth ≤300 μm. (ii) More than 97% of the signal comes from the top 500 μm of the tissue. (iii) For activated columns with lateral size larger than spatial resolution, changing numerical aperature (NA) and focal plane depth does not affect depth sensitivity. (iv) For either smaller columns or large columns covered by surface vessels, increasing NA and∕or focal plane depth may improve depth sensitivity at deeper layers. Our results provide valuable guidance for the optimization of optical imaging systems and data interpretation. PMID:21280912

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

NASA Astrophysics Data System (ADS)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size < 0.1 m) may compensate for some low spectral resolution drawbacks. In this regard, it is shown that the post-classification majority filtering substantially improves the accuracy of all pixel sizes up to the point where the kernel size reaches the average unit size (pixel < 0.25 m). However, careful investigation as to the effect of band distribution and choice could improve the sensor suitability for the marine environment task. This in mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

Recent observations with phase-contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji; Tu, Jinhong; Hirano, Keiichi

1999-09-01

Recent development in phase-contrast X-ray computed tomography using an X-ray interferometer is reported. To observe larger samples than is possible with our previous X-ray interferometer, a large monolithic X-ray interferometer and a separated-type X-ray interferometer were studied. At the present time, 2.5 cm X 1.5 cm interference patterns have been generated with the X-ray interferometers using synchrotron X-rays. The large monolithic X-ray interferometer has produced interference fringes with 80% visibility, and has been used to measure various tissues. To produce images with higher spatial resolution, we fabricated another X-ray interferometer whose wafer was partially thinned by chemical etching. A preliminary test suggested that the spatial resolution has been improved.

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

The Influence of Spatial Resolutions on the Retrieval Accuracy of Sea Surface Wind Speed with Cross-polarized C-band SAR images

NASA Astrophysics Data System (ADS)

Zhang, K.; Han, B.; Mansaray, L. R.; Xu, X.; Guo, Q.; Jingfeng, H.

2017-12-01

Synthetic aperture radar (SAR) instruments on board satellites are valuable for high-resolution wind field mapping, especially for coastal studies. Since the launch of Sentinel-1A on April 3, 2014, followed by Sentinel-1B on April 25, 2016, large amount of C-band SAR data have been added to a growing accumulation of SAR datasets (ERS-1/2, RADARSAT-1/2, ENVISAT). These new developments are of great significance for a wide range of applications in coastal sea areas, especially for high spatial resolution wind resource assessment, in which the accuracy of retrieved wind fields is extremely crucial. Recently, it is reported that wind speeds can also be retrieved from C-band cross-polarized SAR images, which is an important complement to wind speed retrieval from co-polarization. However, there is no consensus on the optimal resolution for wind speed retrieval from cross-polarized SAR images. This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized SAR images. Firstly, for wind speeds retrieved from VV-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Secondly, the most suitable C-band cross-polarized ocean (C-2PO) model was selected between two C-2POs for the VH-polarized image dataset. Then, the VH-wind speeds retrieved by the selected C-2PO were compared with the VV-polarized sea surface wind speeds retrieved using the optimal CMOD, which served as reference, at different spatial resolutions. Results show that the VH-polarized wind speed retrieval accuracy increases rapidly with the decrease in spatial resolutions from 100 m to 1000 m, with a drop in RMSE of 42%. However, the improvement in wind speed retrieval accuracy levels off with spatial resolutions decreasing from 1000 m to 5000 m. This demonstrates that the pixel spacing of 1 km may be the compromising choice for the tradeoff between the spatial resolution and wind speed retrieval accuracy with cross-polarized images obtained from RADASAT-2 fine quad polarization mode. Figs. 1 illustrate the variation of the following statistical parameters: Bias, Corr, R2, RMSE and STD as a function of spatial resolution.

Influence of resolution in irrigated area mapping and area estimation

USGS Publications Warehouse

Velpuri, N.M.; Thenkabail, P.S.; Gumma, M.K.; Biradar, C.; Dheeravath, V.; Noojipady, P.; Yuanjie, L.

2009-01-01

The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM+ 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R2 = 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that "the finer the spatial resolution of the sensor used, greater was the irrigated area derived," since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent). ?? 2009 American Society for Photogrammetry and Remote Sensing.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Methods and spatial extent of geophysical Investigations, Mono Lake, California, 2009 to 2011

USGS Publications Warehouse

Jayko, A.S.; Hart, P.E.; Childs, J. R.; Cormier, M.-H.; Ponce, D.A.; Athens, N.D.; McClain, J.S.

2013-01-01

This report summarizes the methods and spatial extent of geophysical surveys conducted on Mono Lake and Paoha Island by U.S. Geological Survey during 2009 and 2011. The surveys include acquisition of new high resolution seismic reflection data, shipborne high resolution magnetic data, and ground magnetic and gravity data on Paoha Island. Several trials to acquire swath bathymetry and side scan sonar were conducted, but were largely unsuccessful likely due to physical properties of the water column and (or) physical properites of the highly organic bottom sediment.

High spatial resolution detection of low-energy electrons using an event-counting method, application to point projection microscopy

NASA Astrophysics Data System (ADS)

Salançon, Evelyne; Degiovanni, Alain; Lapena, Laurent; Morin, Roger

2018-04-01

An event-counting method using a two-microchannel plate stack in a low-energy electron point projection microscope is implemented. 15 μm detector spatial resolution, i.e., the distance between first-neighbor microchannels, is demonstrated. This leads to a 7 times better microscope resolution. Compared to previous work with neutrons [Tremsin et al., Nucl. Instrum. Methods Phys. Res., Sect. A 592, 374 (2008)], the large number of detection events achieved with electrons shows that the local response of the detector is mainly governed by the angle between the hexagonal structures of the two microchannel plates. Using this method in point projection microscopy offers the prospect of working with a greater source-object distance (350 nm instead of 50 nm), advancing toward atomic resolution.

Nanoscale Spatial Organization of Prokaryotic Cells Studied by Super-Resolution Optical Microscopy

NASA Astrophysics Data System (ADS)

McEvoy, Andrea Lynn

All cells spatially organize their interiors, and this arrangement is necessary for cell viability. Until recently, it was believed that only eukaryotic cells spatially segregate their components. However, it is becoming increasingly clear that bacteria also assemble their proteins into complex patterns. In eukaryotic cells, spatial organization arises from membrane bound organelles as well as motor transport proteins which can move cargos within the cell. To date, there are no known motor transport proteins in bacteria and most microbes lack membrane bound organelles, so it remains a mystery how bacterial spatial organization emerges. In hind-sight it is not surprising that bacteria also exhibit complex spatial organization considering much of what we have learned about the basic processes that take place in all cells, such as transcription and translation was first discovered in prokaryotic cells. Perhaps the fundamental principles that govern spatial organization in prokaryotic cells may be applicable in eukaryotic cells as well. In addition, bacteria are attractive model organism for spatial organization studies because they are genetically tractable, grow quickly and much biochemical and structural data is known about them. A powerful tool for observing spatial organization in cells is the fluorescence microscope. By specifically tagging a protein of interest with a fluorescent probe, it is possible to examine how proteins organize and dynamically assemble inside cells. A significant disadvantage of this technology is its spatial resolution (approximately 250 nm laterally and 500 nm axially). This limitation on resolution causes closely spaced proteins to look blurred making it difficult to observe the fine structure within the complexes. This resolution limit is especially problematic within small cells such as bacteria. With the recent invention of new optical microscopies, we now can surpass the existing limits of fluorescence imaging. In some cases, we can now see individual proteins inside of large complexes or observe structures with ten times the resolution of conventional imaging. These techniques are known as super-resolution microscopes. In this dissertation, I use super-resolution microscopes to understand how a model microbe, Escherichia coli, assembles complex protein structures. I focus on two spatially organized systems, the chemotaxis network and the cell division machinery. These assembly mechanisms could be general mechanisms for protein assembly in all organisms. I also characterize new fluorescent probes for use in multiple super-resolution imaging modalities and discuss the practicalities of using different super-resolution microscopes. The chemotaxis network in E. coli is the best understood signal transduction network in biology. Chemotaxis receptors cluster into complexes of thousands of proteins located at the cell poles and are used to move bacteria towards favorable stimuli in the environment. In these dense clusters, the receptors can bind each other and communicate to filter out noise and amplify weak signals. It is surprising that chemotaxis receptors are spatially segregated and the mechanism for polar localization of these complexes remains unclear. Using data from PALM images, we develop a model to understand how bacteria organize their receptors into large clusters. The model, stochastic cluster nucleation, is surprising in that is generates micron-scale periodic patterns without the need for accessory proteins to provide scaffolding or active transport. This model may be a general mechanism that cells utilize to organize small and large complexes of proteins. During cell division, E. coli must elongate, replicate its DNA and position its components properly prior to binary fission. Prior to septum formation, a ubiquitous protein called FtsZ, assembles into a ring at mid-cell (Z-ring) which constricts during cell division and recruits the remaining proteins necessary for cytokinesis. Though many details have been revealed about FtsZ, the detailed in vivo structure of the Z-ring is not well understood, and many questions remain about how ring constriction occurs. Using multiple super-resolution imaging modalities, in combination with conventional time-lapse fluorescence imaging, we show that the Z-ring does not form a long uniform filament around the circumference of the bacterium. We detail how this structure changes during division and how removal of proteins that help to position FtsZ affects the Z-ring as it proceeds through cytokinesis. Ultimately we present a simple model for Z-ring constriction during division.

Validation of Satellite Retrieved Land Surface Variables

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Terahertz Near-Field Imaging Using Enhanced Transmission through a Single Subwavelength Aperture

NASA Astrophysics Data System (ADS)

Ishihara, Kunihiko; Ikari, Tomofumi; Minamide, Hiroaki; Shikata, Jun-ichi; Ohashi, Keishi; Yokoyama, Hiroyuki; Ito, Hiromasa

2005-07-01

We demonstrate terahertz (THz) near-field imaging using resonantly enhanced transmission of THz-wave radiation (λ˜ 200 μm) through a bull’s eye structure (a single subwavelength aperture surrounded by concentric periodic grooves in a metal plate). The bull’s eye structure shows extremely large enhanced transmission, which has the advantage for a single subwavelength aperture. The spatial resolution for the bull’s eye structure (with an aperture diameter d=100 μm) is evaluated in the near-field region, and a resolution of 50 μm (corresponding to λ/4) is achieved. We obtain the THz near-field images of the subwavelength metal pattern with a spatial resolution below the diffraction limit.

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

A High-Resolution Capability for Large-Eddy Simulation of Jet Flows

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2011-01-01

A large-eddy simulation (LES) code that utilizes high-resolution numerical schemes is described and applied to a compressible jet flow. The code is written in a general manner such that the accuracy/resolution of the simulation can be selected by the user. Time discretization is performed using a family of low-dispersion Runge-Kutta schemes, selectable from first- to fourth-order. Spatial discretization is performed using central differencing schemes. Both standard schemes, second- to twelfth-order (3 to 13 point stencils) and Dispersion Relation Preserving schemes from 7 to 13 point stencils are available. The code is written in Fortran 90 and uses hybrid MPI/OpenMP parallelization. The code is applied to the simulation of a Mach 0.9 jet flow. Four-stage third-order Runge-Kutta time stepping and the 13 point DRP spatial discretization scheme of Bogey and Bailly are used. The high resolution numerics used allows for the use of relatively sparse grids. Three levels of grid resolution are examined, 3.5, 6.5, and 9.2 million points. Mean flow, first-order turbulent statistics and turbulent spectra are reported. Good agreement with experimental data for mean flow and first-order turbulent statistics is shown.

Spatial resolution requirements for urban land cover mapping from space

NASA Technical Reports Server (NTRS)

Todd, William J.; Wrigley, Robert C.

1986-01-01

Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.

Towards large dynamic range and ultrahigh measurement resolution in distributed fiber sensing based on multicore fiber.

PubMed

Dang, Yunli; Zhao, Zhiyong; Tang, Ming; Zhao, Can; Gan, Lin; Fu, Songnian; Liu, Tongqing; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-08-21

Featuring a dependence of Brillouin frequency shift (BFS) on temperature and strain changes over a wide range, Brillouin distributed optical fiber sensors are however essentially subjected to the relatively poor temperature/strain measurement resolution. On the other hand, phase-sensitive optical time-domain reflectometry (Φ-OTDR) offers ultrahigh temperature/strain measurement resolution, but the available frequency scanning range is normally narrow thereby severely restricts its measurement dynamic range. In order to achieve large dynamic range and high measurement resolution simultaneously, we propose to employ both the Brillouin optical time domain analysis (BOTDA) and Φ-OTDR through space-division multiplexed (SDM) configuration based on the multicore fiber (MCF), in which the two sensors are spatially separately implemented in the central core and a side core, respectively. As a proof of concept, the temperature sensing has been performed for validation with 2.5 m spatial resolution over 1.565 km MCF. Large temperature range (10 °C) has been measured by BOTDA and the 0.1 °C small temperature variation is successfully identified by Φ-OTDR with ~0.001 °C resolution. Moreover, the temperature changing process has been recorded by continuously performing the measurement of Φ-OTDR with 80 s frequency scanning period, showing about 0.02 °C temperature spacing at the monitored profile. The proposed system enables the capability to see finer and/or farther upon requirement in distributed optical fiber sensing.

Identification of mosquito larval habitats in high resolution satellite data

NASA Astrophysics Data System (ADS)

Kiang, Richard K.; Hulina, Stephanie M.; Masuoka, Penny M.; Claborn, David M.

2003-09-01

Mosquito-born infectious diseases are a serious public health concern, not only for the less developed countries, but also for developed countries like the U.S. Larviciding is an effective method for vector control and adverse effects to non-target species are minimized when mosquito larval habitats are properly surveyed and treated. Remote sensing has proven to be a useful technique for large-area ground cover mapping, and hence, is an ideal tool for identifying potential larval habitats. Locating small larval habitats, however, requires data with very high spatial resolution. Textural and contextual characteristics become increasingly evident at higher spatial resolution. Per-pixel classification often leads to suboptimal results. In this study, we use pan-sharpened Ikonos data, with a spatial resolution approaching 1 meter, to classify potential mosquito larval habitats for a test site in South Korea. The test site is in a predominantly agricultural region. When spatial characteristics were used in conjunction with spectral data, reasonably good classification accuracy was obtained for the test site. In particular, irrigation and drainage ditches are important larval habitats but their footprints are too small to be detected with the original spectral data at 4-meter resolution. We show that the ditches are detectable using automated classification on pan-sharpened data.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

Recent Developments in Transition-Edge Strip Detectors for Solar X-Rays

NASA Technical Reports Server (NTRS)

Rausch, Adam J.; Deiker, Steven W.; Hilton, Gene; Irwin, Kent D.; Martinez-Galarce, Dennis S.; Shing, Lawrence; Stern, Robert A.; Ullom, Joel N.; Vale, Leila R.

2008-01-01

LMSAL and NIST are developing position-sensitive x-ray strip detectors based on Transition Edge Sensor (TES) microcalorimeters optimized for solar physics. By combining high spectral (E/ delta E approximately equals 1600) and temporal (single photon delta t approximately equals 10 micro s) resolutions with imaging capabilities, these devices will be able to study high-temperature (>l0 MK) x-ray lines as never before. Diagnostics from these lines should provide significant new insight into the physics of both microflares and the early stages of flares. Previously, the large size of traditional TESs, along with the heat loads associated with wiring large arrays, presented obstacles to using these cryogenic detectors for solar missions. Implementing strip detector technology at small scales, however, addresses both issues: here, a line of substantially smaller effective pixels requires only two TESs, decreasing both the total array size and the wiring requirements for the same spatial resolution. Early results show energy resolutions of delta E(sub fwhm) approximately equals 30 eV and spatial resolutions of approximately 10-15 micron, suggesting the strip-detector concept is viable.

Mixel camera--a new push-broom camera concept for high spatial resolution keystone-free hyperspectral imaging.

PubMed

Høye, Gudrun; Fridman, Andrei

2013-05-06

Current high-resolution push-broom hyperspectral cameras introduce keystone errors to the captured data. Efforts to correct these errors in hardware severely limit the optical design, in particular with respect to light throughput and spatial resolution, while at the same time the residual keystone often remains large. The mixel camera solves this problem by combining a hardware component--an array of light mixing chambers--with a mathematical method that restores the hyperspectral data to its keystone-free form, based on the data that was recorded onto the sensor with large keystone. A Virtual Camera software, that was developed specifically for this purpose, was used to compare the performance of the mixel camera to traditional cameras that correct keystone in hardware. The mixel camera can collect at least four times more light than most current high-resolution hyperspectral cameras, and simulations have shown that the mixel camera will be photon-noise limited--even in bright light--with a significantly improved signal-to-noise ratio compared to traditional cameras. A prototype has been built and is being tested.

Fizeau interferometric imaging of Io volcanism with LBTI/LMIRcam

NASA Astrophysics Data System (ADS)

Leisenring, J. M.; Hinz, P. M.; Skrutskie, M.; Skemer, A.; Woodward, C. E.; Veillet, C.; Arcidiacono, C.; Bailey, V.; Bertero, M.; Boccacci, P.; Conrad, A.; de Kleer, K.; de Pater, I.; Defrère, D.; Hill, J.; Hofmann, K.-H.; Kaltenegger, L.; La Camera, A.; Nelson, M. J.; Schertl, D.; Spencer, J.; Weigelt, G.; Wilson, J. C.

2014-07-01

The Large Binocular Telescope (LBT) houses two 8.4-meter mirrors separated by 14.4 meters on a common mount. Coherent combination of these two AO-corrected apertures via the LBT Interferometer (LBTI) produces Fizeau interferometric images with a spatial resolution equivalent to that of a 22.8-meter telescope and the light- gathering power of single 11.8-meter mirror. Capitalizing on these unique capabilities, we used LBTI/LMIRcam to image thermal radiation from volcanic activity on the surface of Io at M-Band (4.8 μm) over a range of parallactic angles. At the distance of Io, the M-Band resolution of the interferometric baseline corresponds to a physical distance of ~135 km, enabling high-resolution monitoring of Io volcanism such as ares and outbursts inaccessible from other ground-based telescopes operating in this wavelength regime. Two deconvolution routines are used to recover the full spatial resolution of the combined images, resolving at least sixteen known volcanic hot spots. Coupling these observations with advanced image reconstruction algorithms demonstrates the versatility of Fizeau interferometry and realizes the LBT as the first in a series of extremely large telescopes.

Microchannel plate detector technology potential for LUVOIR and HabEx

NASA Astrophysics Data System (ADS)

Siegmund, O. H. W.; Ertley, C.; Vallerga, J. V.; Schindhelm, E. R.; Harwit, A.; Fleming, B. T.; France, K. C.; Green, J. C.; McCandliss, S. R.; Harris, W. M.

2017-08-01

Microchannel plate (MCP) detectors have been the detector of choice for ultraviolet (UV) instruments onboard many NASA missions. These detectors have many advantages, including high spatial resolution (<20 μm), photon counting, radiation hardness, large formats (up to 20 cm), and ability for curved focal plane matching. Novel borosilicate glass MCPs with atomic layer deposition combine extremely low backgrounds, high strength, and tunable secondary electron yield. GaN and combinations of bialkali/alkali halide photocathodes show promise for broadband, higher quantum efficiency. Cross-strip anodes combined with compact ASIC readout electronics enable high spatial resolution over large formats with high dynamic range. The technology readiness levels of these technologies are each being advanced through research grants for laboratory testing and rocket flights. Combining these capabilities would be ideal for UV instruments onboard the Large UV/Optical/IR Surveyor (LUVOIR) and the Habitable Exoplanet Imaging Mission (HABEX) concepts currently under study for NASA's Astrophysics Decadal Survey.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Equally sloped tomography based X-ray full-field nano-CT at Shanghai Synchrotron Radiation Facility

NASA Astrophysics Data System (ADS)

Wang, Yudan; Ren, Yuqi; Zhou, Guangzhao; Du, Guohao; Xie, Honglan; Deng, Biao; Xiao, Tiqiao

2018-07-01

X-ray full-field nano-computed tomography (nano-CT) has non-destructive three-dimensional imaging capabilities with high spatial resolution, and has been widely applied to investigate morphology and structures in various areas. Conventional tomography reconstructs a 3D object from a large number of equal-angle projections. For nano-CT, it takes long collecting time due to the large projection numbers and long exposure time. Here, equally-sloped tomography (EST) based nano-CT was implemented and constructed on X-ray imaging beamline at the Shanghai Synchrotron Radiation Facility (SSRF) to overcome or alleviate these difficulties. Preliminary results show that hard TXM with the spatial resolution of 100 nm and the EST-based nano-CT with the ability of 3D nano non-destructive characterization have been realized. This technique promotes hard X-ray imaging capability to nano scales at SSRF and could have applications in many fields including nanomaterials, new energy and life sciences. The study will be helpful for the construction of the new full field X-ray nano-imaging beamline with the spatial resolution of 20 nm at SSRF phase II project.

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

Multiwire proportional chamber development

NASA Technical Reports Server (NTRS)

Doolittle, R. F.; Pollvogt, U.; Eskovitz, A. J.

1973-01-01

The development of large area multiwire proportional chambers, to be used as high resolution spatial detectors in cosmic ray experiments is described. A readout system was developed which uses a directly coupled, lumped element delay-line whose characteristics are independent of the MWPC design. A complete analysis of the delay-line and the readout electronic system shows that a spatial resolution of about 0.1 mm can be reached with the MWPC operating in the strictly proportional region. This was confirmed by measurements with a small MWPC and Fe-55 X-rays. A simplified analysis was carried out to estimate the theoretical limit of spatial resolution due to delta-rays, spread of the discharge along the anode wire, and inclined trajectories. To calculate the gas gain of MWPC's of different geometrical configurations a method was developed which is based on the knowledge of the first Townsend coefficient of the chamber gas.

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.

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Temporal and spatial scaling impacts on extreme precipitation

NASA Astrophysics Data System (ADS)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

NASA Astrophysics Data System (ADS)

Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin

2017-06-01

Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

A Japanese plan: Large radio heliograph in the solar max no. 22

NASA Technical Reports Server (NTRS)

Enome, Shinzo

1986-01-01

An outline as of February, 1986 is briefly described of a Japanese plan to construct a large radio heliograph in the next solar maximum. The principal performance specifications of the heliograph are 10 arsec by 10 arcsec x SEC(Zenith Distance) spatial resolution, 1 arc degree by 1 arc degree field of view, 1-sec temporal resolution, and six hour coverage of observing time. It will be operated at 17 GHz with possible other frequency of 35GHz.

High resolution MR microscopy

NASA Astrophysics Data System (ADS)

Ciobanu, Luisa

Magnetic resonance imaging (MRI) microscopy [1] has the potential to bring the full capabilities of NMR to arbitrarily specified localized positions within small samples. The most interesting target of study is the living biological cell, with typical dimensions ˜100 mum, but with substructures that are much smaller, such as the cell nucleus (typically ˜10 mu m) and mitochondria (1--10 mum). One anticipates that the development of MR microscopy with resolution at the level of these substructures or better and with a wide, three dimensional field-of-view could open a new avenue of investigation into the biology of the living cell. Although the first MR image of a single biological cell was reported in 1987 [2], the cell imaged had quite large (˜1 mm diameter) spatial dimensions and the resolution obtained (on the order of 10 mu m) was not adequate for meaningful imaging of more typically sized cells. The quest for higher resolution has continued. In 1989 Zhou et al. [3] obtained fully three dimensional images with spatial resolution of (6.37 mum)3, or 260 femtoliters. While better "in-plane" resolutions (i.e., the resolution in 2 of the 3 spatial dimensions) have since been obtained, [4, 5] this volume resolution was not exceeded until quite recently by Lee et al., [6] who report 2D images having volume resolution of 75 mum 3 and in-plane resolution of 1 mum. In parallel with these advances in raw resolution several investigators [7, 8, 9] have focused on localized spectroscopy and/or chemical shift imaging. The key obstacles to overcome in MR microscopy are (1) the loss of signal to noise that occurs when observing small volumes and (2) molecular diffusion during the measurement or encoding. To date the problem of sensitivity has typically been addressed by employing small micro-coil receivers. [10] The problem of molecular diffusion can only be defeated with strong magnetic field gradients that can encode spatial information quickly. We report MR microscopy images on phantoms [11, 12] and biological samples (paramecia, algae, brain tissue, lipidic mesophases) obtained using using magnetic field gradients as large as 50 Tesla/meter (5000 G/cm) [13] and micro-coils [14]. Images have voxel resolution as high as (3.7 mum by 3.3 mum by 3.3 mum), or 41 mu m3 (41 femtoliters, containing 2.7 x 10 12 proton spins) [12], marginally the highest voxel resolution reported to date. They are also fully three dimensional, with wide fields of view.

Terahertz-wave near-field imaging with subwavelength resolution using surface-wave-assisted bow-tie aperture

NASA Astrophysics Data System (ADS)

Ishihara, Kunihiko; Ohashi, Keishi; Ikari, Tomofumi; Minamide, Hiroaki; Yokoyama, Hiroyuki; Shikata, Jun-ichi; Ito, Hiromasa

2006-11-01

We demonstrate the terahertz-wave near-field imaging with subwavelength resolution using a bow-tie shaped aperture surrounded by concentric periodic structures in a metal film. A subwavelength aperture with concentric periodic grooves, which are known as a bull's eye structure, shows extremely large enhanced transmission beyond the diffraction limit caused by the resonant excitation of surface waves. Additionally, a bow-tie aperture exhibits extraordinary field enhancement at the sharp tips of the metal, which enhances the transmission and the subwavelength spatial resolution. We introduced a bow-tie aperture to the bull's eye structure and achieved high spatial resolution (˜λ/17) in the near-field region. The terahertz-wave near-field image of the subwavelength metal pattern (pattern width=20μm) was obtained for the wavelength of 207μm.

Fine resolution probabilistic land cover classification of landscapes in the southeastern United States

Treesearch

Joseph St. Peter; John Hogland; Nathaniel Anderson; Jason Drake; Paul Medley

2018-01-01

Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a...

Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis

USGS Publications Warehouse

Xian, George; Homer, Collin G.; Granneman, Brian; Meyer, Debra K.

2012-01-01

Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.

Probing spatial locality in ionic liquids with the grand canonical adaptive resolution molecular dynamics technique

NASA Astrophysics Data System (ADS)

Shadrack Jabes, B.; Krekeler, C.; Klein, R.; Delle Site, L.

2018-05-01

We employ the Grand Canonical Adaptive Resolution Simulation (GC-AdResS) molecular dynamics technique to test the spatial locality of the 1-ethyl 3-methyl imidazolium chloride liquid. In GC-AdResS, atomistic details are kept only in an open sub-region of the system while the environment is treated at coarse-grained level; thus, if spatial quantities calculated in such a sub-region agree with the equivalent quantities calculated in a full atomistic simulation, then the atomistic degrees of freedom outside the sub-region play a negligible role. The size of the sub-region fixes the degree of spatial locality of a certain quantity. We show that even for sub-regions whose radius corresponds to the size of a few molecules, spatial properties are reasonably reproduced thus suggesting a higher degree of spatial locality, a hypothesis put forward also by other researchers and that seems to play an important role for the characterization of fundamental properties of a large class of ionic liquids.

Landsat continuity: issues and opportunities for land cover monitoring

Treesearch

Michael A. Wulder; Joanne C. White; Samuel N. Goward; Jeffrey G. Masek; James R. Irons; Martin Herold; Warren B. Cohen; Thomas R. Loveland; Curtis E. Woodcock

2008-01-01

Initiated in 1972, the Landsat program has provided a continuous record of Earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and...

Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

NASA Astrophysics Data System (ADS)

Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.

2017-07-01

The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations

NASA Astrophysics Data System (ADS)

Shi, Xiaoqin; Zhao, Chuanfeng; Jiang, Jonathan H.; Wang, Chunying; Yang, Xin; Yung, Yuk L.

2018-03-01

Haze has been a focused air pollution phenomenon in China, and its characterization is highly desired. Aerosol properties obtained from a single station are frequently used to represent the haze condition over a large domain, such as tens of kilometers, which could result in high uncertainties due to their spatial variation. Using a high-resolution network observation over an urban city in North China from November 2015 to February 2016, this study examines the spatial representativeness of ground station observations of particulate matter with diameters less than 2.5 μm (PM2.5). We developed a new method to determine the representative area of PM2.5 measurements from limited stations. The key idea is to determine the PM2.5 spatial representative area using its spatial variability and temporal correlation. We also determine stations with large representative area using two grid networks with different resolutions. Based on the high spatial resolution measurements, the representative area of PM2.5 at one station can be determined from the grids with high correlations and small differences of PM2.5. The representative area for a single station in the study period ranges from 0.25 to 16.25 km2 but is less than 3 km2 for more than half of the stations. The representative area varies with locations, and observation at 10 optimal stations would have a good representativeness of those obtained from 169 stations for the 4 month time scale studied. Both evaluations with an empirical orthogonal function analysis and with independent data set corroborate the validity of the results found in this study.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

PubMed

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes

PubMed Central

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J.; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales. PMID:24069206

Method of composing two-dimensional scanned spectra observed by the New Vacuum Solar Telescope

NASA Astrophysics Data System (ADS)

Cai, Yun-Fang; Xu, Zhi; Chen, Yu-Chao; Xu, Jun; Li, Zheng-Gang; Fu, Yu; Ji, Kai-Fan

2018-04-01

In this paper we illustrate the technique used by the New Vacuum Solar Telescope (NVST) to increase the spatial resolution of two-dimensional (2D) solar spectroscopy observations involving two dimensions of space and one of wavelength. Without an image stabilizer at the NVST, large scale wobble motion is present during the spatial scanning, whose instantaneous amplitude can reach 1.3″ due to the Earth’s atmosphere and the precision of the telescope guiding system, and seriously decreases the spatial resolution of 2D spatial maps composed with scanned spectra. We make the following effort to resolve this problem: the imaging system (e.g., the TiO-band) is used to record and detect the displacement vectors of solar image motion during the raster scan, in both the slit and scanning directions. The spectral data (e.g., the Hα line) which are originally obtained in time sequence are corrected and re-arranged in space according to those displacement vectors. Raster scans are carried out in several active regions with different seeing conditions (two rasters are illustrated in this paper). Given a certain spatial sampling and temporal resolution, the spatial resolution of the composed 2D map could be close to that of the slit-jaw image. The resulting quality after correction is quantitatively evaluated with two methods. A physical quantity, such as the line-of-sight velocities in multiple layers of the solar atmosphere, is also inferred from the re-arranged spectrum, demonstrating the advantage of this technique.

Building Daily 30-meter Spatial Resolution Maps of Surface Water Bodies from MODIS Data Using a Novel Technique for Transferring Information Across Space and Time

NASA Astrophysics Data System (ADS)

Khandelwal, A.; Karpatne, A.; Kumar, V.

2017-12-01

In this paper, we present novel methods for producing surface water maps at 30 meter spatial resolution at a daily temporal resolution. These new methods will make use of the MODIS spectral data from Terra (available daily since 2000) to produce daily maps at 250 meter and 500 meter resolution, and then refine them using the relative elevation ordering of pixels at 30 meter resolution. The key component of these methods is the use of elevation structure (relative elevation ordering) of a water body. Elevation structure is not explicitly available at desired resolution for most water bodies in the world and hence it will be estimated using our previous work that uses the history of imperfect labels. In this paper, we will present a new technique that uses elevation structure (unlike existing pixel based methods) to enforce temporal consistency in surface water extents (lake area on nearby dates is likely to be very similar). This will greatly improve the quality of the MODIS scale land/water labels since daily MODIS data can have a large amount of missing (or poor quality) data due to clouds and other factors. The quality of these maps will be further improved using elevation based resolution refinement approach that will make use of elevation structure estimated at Landsat scale. With the assumption that elevation structure does not change over time, it provides a very effective way to transfer information between datasets even when they are not observed concurrently. In this work, we will derive elevation structure at Landsat scale from monthly water extent maps spanning 1984-2015, publicly available through a joint effort of Google Earth Engine and the European Commission's Joint Research Centre (JRC). This elevation structure will then be used to refine spatial resolution of Modis scale maps from 2000 onwards. We will present the analysis of these methods on a large and diverse set of water bodies across the world.

The scale dependence of optical diversity in a prairie ecosystem

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.; Stilwell, A.; Zygielbaum, A. I.; Cavender-Bares, J.; Townsend, P. A.

2015-12-01

Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing. Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with extensive experience in species identification. Remote sensing can be used for such assessment based upon patterns of optical variation. This provides efficient and cost-effective means to determine ecosystem diversity at different scales and over large areas. Sampling scale has been described as a "fundamental conceptual problem" in ecology, and is an important practical consideration in both remote sensing and traditional biodiversity studies. On the one hand, with decreasing spatial and spectral resolution, the differences among different optical types may become weak or even disappear. Alternately, high spatial and/or spectral resolution may introduce redundant or contradictory information. For example, at high resolution, the variation within optical types (e.g., between leaves on a single plant canopy) may add complexity unrelated to specie richness. We studied the scale-dependence of optical diversity in a prairie ecosystem at Cedar Creek Ecosystem Science Reserve, Minnesota, USA using a variety of spectrometers from several platforms on the ground and in the air. Using the coefficient of variation (CV) of spectra as an indicator of optical diversity, we found that high richness plots generally have a higher coefficient of variation. High resolution imaging spectrometer data (1 mm pixels) showed the highest sensitivity to richness level. With decreasing spatial resolution, the difference in CV between richness levels decreased, but remained significant. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.

Towards a New Assessment of Urban Areas from Local to Global Scales

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Roy Chowdhury, P. K.; McKee, J.; Weaver, J.; Bright, E.; Weber, E.

2015-12-01

Since early 2000s, starting with NASA MODIS, satellite based remote sensing has facilitated collection of imagery with medium spatial resolution but high temporal resolution (daily). This trend continues with an increasing number of sensors and data products. Increasing spatial and temporal resolutions of remotely sensed data archives, from both public and commercial sources, have significantly enhanced the quality of mapping and change data products. However, even with automation of such analysis on evolving computing platforms, rates of data processing have been suboptimal largely because of the ever-increasing pixel to processor ratio coupled with limitations of the computing architectures. Novel approaches utilizing spatiotemporal data mining techniques and computational architectures have emerged that demonstrates the potential for sustained and geographically scalable landscape monitoring to be operational. We exemplify this challenge with two broad research initiatives on High Performance Geocomputation at Oak Ridge National Laboratory: (a) mapping global settlement distribution; (b) developing national critical infrastructure databases. Our present effort, on large GPU based architectures, to exploit high resolution (1m or less) satellite and airborne imagery for extracting settlements at global scale is yielding understanding of human settlement patterns and urban areas at unprecedented resolution. Comparison of such urban land cover database, with existing national and global land cover products, at various geographic scales in selected parts of the world is revealing intriguing patterns and insights for urban assessment. Early results, from the USA, Taiwan, and Egypt, indicate closer agreements (5-10%) in urban area assessments among databases at larger, aggregated geographic extents. However, spatial variability at local scales could be significantly different (over 50% disagreement).

Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

NASA Technical Reports Server (NTRS)

Kurtz, Nathan T.; Markus, Thorsten; Cavalieri, Donald J.; Sparling, Lynn C.; Krabill, William B.; Gasiewski, Albin J.; Sonntag, John G.

2009-01-01

Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

Solar Confocal interferometers for Sub-Picometer-Resolution Spectral Filters

NASA Technical Reports Server (NTRS)

Gary, G. Allen; Pietraszewski, Chris; West, Edward A.; Dines. Terence C.

2007-01-01

The confocal Fabry-Perot interferometer allows sub-picometer spectral resolution of Fraunhofer line profiles. Such high spectral resolution is needed to keep pace with the higher spatial resolution of the new set of large-aperture solar telescopes. The line-of-sight spatial resolution derived for line profile inversions would then track the improvements of the transverse spatial scale provided by the larger apertures. In particular, profile inversion allows improved velocity and magnetic field gradients to be determined independent of multiple line analysis using different energy levels and ions. The confocal interferometer's unique properties allow a simultaneous increase in both etendue and spectral power. The higher throughput for the interferometer provides significant decrease in the aperture, which is important in spaceflight considerations. We have constructed and tested two confocal interferometers. A slow-response thermal-controlled interferometer provides a stable system for laboratory investigation, while a piezoelectric interferometer provides a rapid response for solar observations. In this paper we provide design parameters, show construction details, and report on the laboratory test for these interferometers. The field of view versus aperture for confocal interferometers is compared with other types of spectral imaging filters. We propose a multiple etalon system for observing with these units using existing planar interferometers as pre-filters. The radiometry for these tests established that high spectral resolution profiles can be obtained with imaging confocal interferometers. These sub-picometer spectral data of the photosphere in both the visible and near-infrared can provide important height variation information. However, at the diffraction-limited spatial resolution of the telescope, the spectral data is photon starved due to the decreased spectral passband.

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients.

PubMed

Guo, Yi; Lebel, R Marc; Zhu, Yinghua; Lingala, Sajan Goud; Shiroishi, Mark S; Law, Meng; Nayak, Krishna

2016-05-01

To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm(3), FOV 22 × 22 × 4.2 cm(3), and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm(3), and broader coverage 22 × 22 × 19 cm(3). Temporal resolution was 5 s for both protocols. Time-resolved images and blood-brain barrier permeability maps were qualitatively evaluated by two radiologists. The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Low-Cost Ultra-High Spatial and Temporal Resolution Mapping of Intertidal Rock Platforms

NASA Astrophysics Data System (ADS)

Bryson, M.; Johnson-Roberson, M.; Murphy, R.

2012-07-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

NASA Astrophysics Data System (ADS)

Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

2017-06-01

The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.

Propagation phasor approach for holographic image reconstruction

PubMed Central

Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

2016-01-01

To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa

2016-01-01

Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.

High axial resolution imaging system for large volume tissues using combination of inclined selective plane illumination and mechanical sectioning

PubMed Central

Zhang, Qi; Yang, Xiong; Hu, Qinglei; Bai, Ke; Yin, Fangfang; Li, Ning; Gang, Yadong; Wang, Xiaojun; Zeng, Shaoqun

2017-01-01

To resolve fine structures of biological systems like neurons, it is required to realize microscopic imaging with sufficient spatial resolution in three dimensional systems. With regular optical imaging systems, high lateral resolution is accessible while high axial resolution is hard to achieve in a large volume. We introduce an imaging system for high 3D resolution fluorescence imaging of large volume tissues. Selective plane illumination was adopted to provide high axial resolution. A scientific CMOS working in sub-array mode kept the imaging area in the sample surface, which restrained the adverse effect of aberrations caused by inclined illumination. Plastic embedding and precise mechanical sectioning extended the axial range and eliminated distortion during the whole imaging process. The combination of these techniques enabled 3D high resolution imaging of large tissues. Fluorescent bead imaging showed resolutions of 0.59 μm, 0.47μm, and 0.59 μm in the x, y, and z directions, respectively. Data acquired from the volume sample of brain tissue demonstrated the applicability of this imaging system. Imaging of different depths showed uniform performance where details could be recognized in either the near-soma area or terminal area, and fine structures of neurons could be seen in both the xy and xz sections. PMID:29296503

The VIRUS-P Exploration of Nearby Galaxies (VENGA): spatially resolved gas-phase metallicity distributions in barred and unbarred spirals

NASA Astrophysics Data System (ADS)

Kaplan, Kyle F.; Jogee, Shardha; Kewley, Lisa; Blanc, Guillermo A.; Weinzirl, Tim; Song, Mimi; Drory, Niv; Luo, Rongxin; van den Bosch, Remco C. E.

2016-10-01

We present a study of the excitation conditions and metallicity of ionized gas (Zgas) in eight nearby barred and unbarred spiral galaxies from the VIRUS-P Exploration of Nearby Galaxies (VENGA) survey, which provides high spatial sampling and resolution (median ˜387 pc), large coverage from the bulge to outer disc, broad wavelength range (3600-6800 Å), and medium spectral resolution (˜120 km s-1 at 5000 Å). Our results are: (1) We present high resolution gas excitation maps to differentiate between regions with excitation typical of Seyfert, LINER, or recent star formation. We find LINER-type excitation at large distances (3-10 kpc) from the centre, and associate this excitation with diffuse ionized gas (DIG). (2) After excluding spaxels dominated by Seyfert, LINER, or DIG, we produce maps with the best spatial resolution and sampling to date of the ionization parameter q, star formation rate, and Zgas using common strong line diagnostics. We find that isolated barred and unbarred spirals exhibit similarly shallow Zgas profiles from the inner kpc out to large radii (7-10 kpc or 0.5-1.0 R25). This implies that if profiles had steeper gradients at earlier epochs, then the present-day bar is not the primary driver flattening gradients over time. This result contradicts earlier claims, but agrees with recent IFU studies. (3) The Zgas gradients in our z ˜ 0 massive spirals are markedly shallower, by ˜0.2 dex kpc-1, than published gradients for lensed lower mass galaxies at z ˜ 1.5-2.0. Cosmologically motivated hydrodynamical simulations best match this inferred evolution, but the match is sensitive to adopted stellar feedback prescriptions.

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.

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Beyond MOS and fibers: Optical Fourier-transform Imaging Unit for Cananea Observatory (OFIUCO)

NASA Astrophysics Data System (ADS)

Nieto-Suárez, M. A.; Rosales-Ortega, F. F.; Castillo, E.; García, P.; Escobedo, G.; Sánchez, S. F.; González, J.; Iglesias-Páramo, J.; Mollá, M.; Chávez, M.; Bertone, E.; et al.

2017-11-01

Many physical processes in astronomy are still hampered by the lack of spatial and spectral resolution, and also restricted to the field-of-view (FoV) of current 2D spectroscopy instruments available worldwide. It is due to that, many of the ongoing or proposed studies are based on large-scale imaging and/or spectroscopic surveys. Under this philosophy, large aperture telescopes are dedicated to the study of intrinsically faint and/or distance objects, covering small FoVs, with high spatial resolution, while smaller telescopes are devoted to wide-field explorations. However, future astronomical surveys, should be addressed by acquiring un-biases, spatially resolved, high-quality spectroscopic information for a wide FoV. Therefore, and in order to improve the current instrumental offer in the Observatorio Astrofísico Guillermo Haro (OAGH) in Cananea, Mexico (INAOE); and to explore a possible instrument for the future Telescopio San Pedro Mártir (6.5m), we are currently integrating at INAOE an instrument prototype that will provide us with un-biased wide-field (few arcmin) spectroscopic information, and with the flexibility of operating at different spectral resolutions (R 1-20000), with a spatial resolution limited by seeing, and therefore, to be used in a wide range of astronomical problems. This instrument called OFIUCO: Optical Fourier-transform Imaging Unit for Cananea Observatory, will make use of the Fourier Transform Spectroscopic technique, which has been proved to be feasible in the optical wavelength range (350-1000 nm) with designs such as SITELLE (CFHT). We describe here the basic technical description of a Fourier transform spectrograph with important modifications from previous astronomical versions, as well as the technical advantages and weakness, and the science cases in which this instrument can be implemented.

French Meteor Network for High Precision Orbits of Meteoroids

NASA Technical Reports Server (NTRS)

Atreya, P.; Vaubaillon, J.; Colas, F.; Bouley, S.; Gaillard, B.; Sauli, I.; Kwon, M. K.

2011-01-01

There is a lack of precise meteoroids orbit from video observations as most of the meteor stations use off-the-shelf CCD cameras. Few meteoroids orbit with precise semi-major axis are available using film photographic method. Precise orbits are necessary to compute the dust flux in the Earth s vicinity, and to estimate the ejection time of the meteoroids accurately by comparing them with the theoretical evolution model. We investigate the use of large CCD sensors to observe multi-station meteors and to compute precise orbit of these meteoroids. An ideal spatial and temporal resolution to get an accuracy to those similar of photographic plates are discussed. Various problems faced due to the use of large CCD, such as increasing the spatial and the temporal resolution at the same time and computational problems in finding the meteor position are illustrated.

TOPEM: A PET-TOF endorectal probe, compatible with MRI for diagnosis and follow up of prostate cancer

NASA Astrophysics Data System (ADS)

Garibaldi, F.; Capuani, S.; Colilli, S.; Cosentino, L.; Cusanno, F.; De Leo, R.; Finocchiaro, P.; Foresta, M.; Giove, F.; Giuliani, F.; Gricia, M.; Loddo, F.; Lucentini, M.; Maraviglia, B.; Meddi, F.; Monno, E.; Musico, P.; Pappalardo, A.; Perrino, R.; Ranieri, A.; Rivetti, A.; Santavenere, F.; Tamma, C.

2013-02-01

Prostate cancer is the most common disease in men and the second leading cause of cancer death. Generic large instruments for diagnosis have sensitivity, spatial resolution, and contrast inferior with respect to dedicated prostate imagers. Multimodality imaging can play a significant role merging anatomical and functional details coming from simultaneous PET and MRI. The TOPEM project has the goal of designing, building, and testing an endorectal PET-TOF MRI probe. The performance is dominated by the detector close to the source. Results from simulation show spatial resolution of ∼1.5 mm for source distances up to 80 mm. The efficiency is significantly improved with respect to the external PET. Mini-detectors have been built and tested. We obtained, for the first time, to our best knowledge, timing resolution of <400 ps and at the same time Depth Of Interaction (DOI) resolution of 1 mm or less.

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Unlocking the spatial inversion of large scanning magnetic microscopy datasets

NASA Astrophysics Data System (ADS)

Myre, J. M.; Lascu, I.; Andrade Lima, E.; Feinberg, J. M.; Saar, M. O.; Weiss, B. P.

2013-12-01

Modern scanning magnetic microscopy provides the ability to perform high-resolution, ultra-high sensitivity moment magnetometry, with spatial resolutions better than 10^-4 m and magnetic moments as weak as 10^-16 Am^2. These microscopy capabilities have enhanced numerous magnetic studies, including investigations of the paleointensity of the Earth's magnetic field, shock magnetization and demagnetization of impacts, magnetostratigraphy, the magnetic record in speleothems, and the records of ancient core dynamos of planetary bodies. A common component among many studies utilizing scanning magnetic microscopy is solving an inverse problem to determine the non-negative magnitude of the magnetic moments that produce the measured component of the magnetic field. The two most frequently used methods to solve this inverse problem are classic fast Fourier techniques in the frequency domain and non-negative least squares (NNLS) methods in the spatial domain. Although Fourier techniques are extremely fast, they typically violate non-negativity and it is difficult to implement constraints associated with the space domain. NNLS methods do not violate non-negativity, but have typically been computation time prohibitive for samples of practical size or resolution. Existing NNLS methods use multiple techniques to attain tractable computation. To reduce computation time in the past, typically sample size or scan resolution would have to be reduced. Similarly, multiple inversions of smaller sample subdivisions can be performed, although this frequently results in undesirable artifacts at subdivision boundaries. Dipole interactions can also be filtered to only compute interactions above a threshold which enables the use of sparse methods through artificial sparsity. To improve upon existing spatial domain techniques, we present the application of the TNT algorithm, named TNT as it is a "dynamite" non-negative least squares algorithm which enhances the performance and accuracy of spatial domain inversions. We show that the TNT algorithm reduces the execution time of spatial domain inversions from months to hours and that inverse solution accuracy is improved as the TNT algorithm naturally produces solutions with small norms. Using sIRM and NRM measures of multiple synthetic and natural samples we show that the capabilities of the TNT algorithm allow very large samples to be inverted without the need for alternative techniques to make the problems tractable. Ultimately, the TNT algorithm enables accurate spatial domain analysis of scanning magnetic microscopy data on an accelerated time scale that renders spatial domain analyses tractable for numerous studies, including searches for the best fit of unidirectional magnetization direction and high-resolution step-wise magnetization and demagnetization.

The 10 m-resolution TINITALY DEM as a trans-disciplinary basis for the analysis of the Italian territory: Current trends and new perspectives

NASA Astrophysics Data System (ADS)

Tarquini, Simone; Nannipieri, Luca

2017-03-01

The increasing availability of high resolution digital elevation models (DEMs) is changing our viewpoint towards Earth surface landforms. Nevertheless, large-coverage, intermediate-resolution DEMs are still largely used, and can be the ideal choice in several applications based on the processing of spatially-integrated information. In 2012 the Istituto Nazionale di Geofisica e Vulcanologia opened a website for the free download of the "TINTALY" Digital Elevation Model (DEM), which covers the whole Italian territory. Since then, about 700 users from 28 different countries have been accredited for data download, and a report of 4 years of data dissemination and use is presented. The analysis of the intended use reveals that the 10 m-resolution, seamless TINITALY DEM is of use for an extremely assorted research community. Accredited users are working in virtually any branch of the Earth Sciences (e.g. Volcanology, Seismology, and Geomorphology), in spatially integrated humanities (e.g. History and Archaeology), and in other thematic areas such as in applied Physics and Zoology. Many users are also working in local administrations (e.g. Regions and Municipalities) for civil protection or land use planning purposes. In summary, the documented activity shows that the dissemination of seamless, large coverage elevation datasets can fertilize the technological progress of the whole society providing a significant benefit to stakeholders.

Co-Phasing the Large Binocular Telescope:. [Status and Performance of LBTI-PHASECam

NASA Technical Reports Server (NTRS)

Defrere, D.; Hinz, P.; Downey, E.; Ashby, D.; Bailey, V.; Brusa, G.; Christou, J.; Danchi, W. C.; Grenz, P.; Hill, J. M.;

Dynamic full-field infrared imaging with multiple synchrotron beams

PubMed Central

Stavitski, Eli; Smith, Randy J.; Bourassa, Megan W.; Acerbo, Alvin S.; Carr, G. L.; Miller, Lisa M.

2013-01-01

Microspectroscopic imaging in the infrared (IR) spectral region allows for the examination of spatially resolved chemical composition on the microscale. More than a decade ago, it was demonstrated that diffraction limited spatial resolution can be achieved when an apertured, single pixel IR microscope is coupled to the high brightness of a synchrotron light source. Nowadays, many IR microscopes are equipped with multi-pixel Focal Plane Array (FPA) detectors, which dramatically improve data acquisition times for imaging large areas. Recently, progress been made toward efficiently coupling synchrotron IR beamlines to multi-pixel detectors, but they utilize expensive and highly customized optical schemes. Here we demonstrate the development and application of a simple optical configuration that can be implemented on most existing synchrotron IR beamlines in order to achieve full-field IR imaging with diffraction-limited spatial resolution. Specifically, the synchrotron radiation fan is extracted from the bending magnet and split into four beams that are combined on the sample, allowing it to fill a large section of the FPA. With this optical configuration, we are able to oversample an image by more than a factor of two, even at the shortest wavelengths, making image restoration through deconvolution algorithms possible. High chemical sensitivity, rapid acquisition times, and superior signal-to-noise characteristics of the instrument are demonstrated. The unique characteristics of this setup enabled the real time study of heterogeneous chemical dynamics with diffraction-limited spatial resolution for the first time. PMID:23458231

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Accessing High Spatial Resolution in Astronomy Using Interference Methods

NASA Astrophysics Data System (ADS)

Carbonel, Cyril; Grasset, Sébastien; Maysonnave, Jean

2018-04-01

In astronomy, methods such as direct imaging or interferometry-based techniques (Michelson stellar interferometry for example) are used for observations. A particular advantage of interferometry is that it permits greater spatial resolution compared to direct imaging with a single telescope, which is limited by diffraction owing to the aperture of the instrument as shown by Rueckner et al. in a lecture demonstration. The focus of this paper, addressed to teachers and/or students in high schools and universities, is to easily underline both an application of interferometry in astronomy and stress its interest for resolution. To this end very simple optical experiments are presented to explain all the concepts. We show how an interference pattern resulting from the combined signals of two telescopes allows us to measure the distance between two stars with a resolution beyond the diffraction limit. Finally this work emphasizes the breathtaking resolution obtained in state-of-the-art instruments such as the VLTi (Very Large Telescope interferometer).

Ultra-large field-of-view two-photon microscopy.

PubMed

Tsai, Philbert S; Mateo, Celine; Field, Jeffrey J; Schaffer, Chris B; Anderson, Matthew E; Kleinfeld, David

2015-06-01

We present a two-photon microscope that images the full extent of murine cortex with an objective-limited spatial resolution across an 8 mm by 10 mm field. The lateral resolution is approximately 1 µm and the maximum scan speed is 5 mm/ms. The scan pathway employs large diameter compound lenses to minimize aberrations and performs near theoretical limits. We demonstrate the special utility of the microscope by recording resting-state vasomotion across both hemispheres of the murine brain through a transcranial window and by imaging histological sections without the need to stitch.

LANDSAT 4 investigations of Thematic Mapper and multispectral scanner applications. [Death Valley, California; Silver Bell Copper Mine, Arizona, and Dulles Airport near Washington, D.C.

NASA Technical Reports Server (NTRS)

Lauer, D. T. (Principal Investigator)

1984-01-01

The optimum index factor package was used to choose TM band for color compositing. Processing techniques were also used on TM data over several sites to: (1) reduce the amount of data that needs to be processed and analyzed by using statistical methods or by combining full-resolution products with spatially compressed products; (2) digitally process small subareas to improve the visual appearance of large-scale products or to merge different-resolution image data; and (3) evaluate and compare the information content of the different three-band combinations that can be made using the TM data. Results indicate that for some applications the added spectral information over MSS is even more important than the TM's increased spatial resolution.

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

Spectrographs have traditionally suffered from the inability to obtain line intensities, widths, and Doppler shifts over large spatial regions of the Sun quickly because of the narrow instantaneous field of view. This has limited the spectroscopic analysis of rapidly varying solar features like, flares, CME eruptions, coronal jets, and reconnection regions. Imagers have provided high time resolution images of the full Sun with limited spectral resolution. In this paper we present recent advances in deconvolving spectrally dispersed images obtained through broad slits. We use this new theoretical formulation to examine the effectiveness of various potential observing scenarios, spatial and spectral resolutions, signal to noise ratio, and other instrument characteristics. This information will lay the foundation for a new generation of spectral imagers optimized for slitless spectral operation, while retaining the ability to obtain spectral information in transient solar events.

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

Derivation of Sky-View Factors from LIDAR Data

NASA Technical Reports Server (NTRS)

Kidd, Christopher; Chapman, Lee

2013-01-01

The use of Lidar (Light Detection and Ranging), an active light-emitting instrument, is becoming increasingly common for a range of potential applications. Its ability to provide fine resolution spatial and vertical resolution elevation data makes it ideal for a wide range of studies. This paper demonstrates the capability of Lidar data to measure sky view factors (SVF). The Lidar data is used to generate a spatial map of SVFs which are then compared against photographically-derived SVF at selected point locations. At each location three near-surface elevations measurements were taken and compared with collocated Lidar-derived estimated. It was found that there was generally good agreement between the two methodologies, although with decreasing SVF the Lidar-derived technique tended to overestimate the SVF: this can be attributed in part to the spatial resolution of the Lidar sampling. Nevertheless, airborne Lidar systems can map sky view factors over a large area easily, improving the utility of such data in atmospheric and meteorological models.

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

High Resolution PET with 250 micrometer LSO Detectors and Adaptive Zoom

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

Cherry, Simon R.; Qi, Jinyi

2012-01-08

There have been impressive improvements in the performance of small-animal positron emission tomography (PET) systems since their first development in the mid 1990s, both in terms of spatial resolution and sensitivity, which have directly contributed to the increasing adoption of this technology for a wide range of biomedical applications. Nonetheless, current systems still are largely dominated by the size of the scintillator elements used in the detector. Our research predicts that developing scintillator arrays with an element size of 250 {micro}m or smaller will lead to an image resolution of 500 {micro}m when using 18F- or 64Cu-labeled radiotracers, giving amore » factor of 4-8 improvement in volumetric resolution over the highest resolution research systems currently in existence. This proposal had two main objectives: (i) To develop and evaluate much higher resolution and efficiency scintillator arrays that can be used in the future as the basis for detectors in a small-animal PET scanner where the spatial resolution is dominated by decay and interaction physics rather than detector size. (ii) To optimize one such high resolution, high sensitivity detector and adaptively integrate it into the existing microPET II small animal PET scanner as a 'zoom-in' detector that provides higher spatial resolution and sensitivity in a limited region close to the detector face. The knowledge gained from this project will provide valuable information for building future PET systems with a complete ring of very high-resolution detector arrays and also lay the foundations for utilizing high-resolution detectors in combination with existing PET systems for localized high-resolution imaging.« less

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

USGS Publications Warehouse

McShane, Ryan R.; Driscoll, Katelyn P.; Sando, Roy

2017-09-27

Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ETa estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ETa and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ETa that are currently applied successfully in the United States. The METRIC model can produce maps of ETa at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ETa against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ETa. The SSEBop model has been used to produce maps of ETa over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ETa estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ETa estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth EngineTM has been used to implement METRIC with automated calibration for regional-scale estimates of ETa using Landsat data. The U.S. Geological Survey also is using Google Earth EngineTM to implement SSEBop for estimating ETa in the United States at a continental scale using Landsat data.

A generic method for improving the spatial interoperability of medical and ecological databases.

PubMed

Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M

2017-10-03

The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review

PubMed Central

Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-01-01

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on. PMID:29614024

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review.

PubMed

Ding, Zhenyang; Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-04-03

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Near-field microscopy with a microfabricated solid immersion lens

NASA Astrophysics Data System (ADS)

Fletcher, Daniel Alden

2001-07-01

Diffraction of focused light prevents optical microscopes from resolving features in air smaller than half the wavelength, λ Spatial resolution can be improved by passing light through a sub-wavelength metal aperture scanned close to a sample, but aperture-based probes suffer from low optical throughput, typically below 10-4. An alternate and more efficient technique is solid immersion microscopy in which light is focused through a high refractive index Solid Immersion Lens (SIL). This work describes the fabrication, modeling, and use of a microfabricated SIL to obtain spatial resolution better than the diffraction limit in air with high optical throughput for infrared applications. SILs on the order of 10 μm in diameter are fabricated from single-crystal silicon and integrated onto silicon cantilevers with tips for scanning. We measure a focused spot size of λ/5 with optical throughput better than 10-1 at a wavelength of λ = 9.3 μm. Spatial resolution is improved to λ/10 with metal apertures fabricated directly on the tip of the silicon SIL. Microlenses have reduced spherical aberration and better transparency than large lenses but cannot be made arbitrarily small and still focus. We model the advantages and limitations of focusing in lenses close to the wavelength in diameter using an extension of Mie theory. We also investigate a new contrast mechanism unique to microlenses resulting from the decrease in field-of-view with lens diameter. This technique is shown to achieve λ/4 spatial resolution. We explore applications of the microfabricated silicon SIL for high spatial resolution thermal microscopy and biological spectroscopy. Thermal radiation is collected through the SIL from a heated surface with spatial resolution four times better than that of a diffraction- limited infrared microscope. Using a Fourier-transform infrared spectrometer, we observe absorption peaks in bacteria cells positioned at the focus of the silicon SIL.

Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

PubMed

Martinuzzi, Sebastián; Ramos-González, Olga M; Muñoz-Erickson, Tischa A; Locke, Dexter H; Lugo, Ariel E; Radeloff, Volker C

2018-04-01

Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (<1 m) resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities. © 2017 by the Ecological Society of America.

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

In-situ device integration of large-area patterned organic nanowire arrays for high-performance optical sensors

PubMed Central

Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng

2013-01-01

Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887

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

Sadoulet, B.

The use of drift chambers in the field of high energy physics is reviewed including existing apparatus, plans and dreams. Comments are made especially on low cost large area drift chambers, use of pulse height information and high spatial resolution applications. (auth)

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.

Performance study of large area encoding readout MRPC

NASA Astrophysics Data System (ADS)

Chen, X. L.; Wang, Y.; Chen, G.; Han, D.; Wang, X.; Zeng, M.; Zeng, Z.; Zhao, Z.; Guo, B.

2018-02-01

Muon tomography system built by the 2-D readout high spatial resolution Multi-gap Resistive Plate Chamber (MRPC) detector is a project of Tsinghua University. An encoding readout method based on the fine-fine configuration has been used to minimize the number of the readout electronic channels resulting in reducing the complexity and the cost of the system. In this paper, we provide a systematic comparison of the MRPC detector performance with and without fine-fine encoding readout. Our results suggest that the application of the fine-fine encoding readout leads us to achieve a detecting system with slightly worse spatial resolution but dramatically reduce the number of electronic channels.

Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study

USGS Publications Warehouse

Chander, G.; Helder, D.L.; Aaron, David; Mishra, N.; Shrestha, A.K.

2013-01-01

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.

Evaluation of multiple-scale 3D characterization for coal physical structure with DCM method and synchrotron X-ray CT.

PubMed

Wang, Haipeng; Yang, Yushuang; Yang, Jianli; Nie, Yihang; Jia, Jing; Wang, Yudan

2015-01-01

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.

Soil organic carbon - a large scale paired catchment assessment

NASA Astrophysics Data System (ADS)

Kunkel, V.; Hancock, G. R.; Wells, T.

2016-12-01

Soil organic carbon (SOC) concentration can vary both spatially and temporally driven by differences in soil properties, topography and climate. However most studies have focused on point scale data sets with a paucity of studies examining larger scale catchments. Here we examine the spatial and temporal distribution of SOC for two large catchments. The Krui (575 km2) and Merriwa River (675km2) catchments (New South Wales, Australia). Both have similar shape, soils, topography and orientation. We show that SOC distribution is very similar for both catchments and that elevation (and associated increase in soil moisture) is a major influence on SOC. We also show that there is little change in SOC from the initial assessment in 2006 to 2015 despite a major drought from 2003 to 2010 and extreme rainfall events in 2007 and 2010 -therefore SOC concentration appears robust. However, we found significant relationships between erosion and deposition patterns (as quantified using 137Cs) and SOC for both catchments again demonstrating a strong geomorphic relationship. Vegetation across the catchments was assessed using remote sensing (Landsat and MODIS). Vegetation patterns were temporally consistent with above ground biomass increasing with elevation. SOC could be predicted using both these low and high resolution remote sensing platforms. Results indicate that, although moderate resolution (250 m) allows for reasonable prediction of the spatial distribution of SOC, the higher resolution (30 m) improved the strength of the SOC-NDVI relationship. The relationship between SOC and 137Cs, as a surrogate for the erosion and deposition of SOC, suggested that sediment transport and deposition influences the distribution of SOC within the catchment. The findings demonstrate that over the large catchment scale and at the decadal time scale that SOC is relatively constant and can largely be predicted by topography.

Factors affecting the performance of large-aperture microphone arrays.

PubMed

Silverman, Harvey F; Patterson, William R; Sachar, Joshua

2002-05-01

Large arrays of microphones have been proposed and studied as a possible means of acquiring data in offices, conference rooms, and auditoria without requiring close-talking microphones. When such an array essentially surrounds all possible sources, it is said to have a large aperture. Large-aperture arrays have attractive properties of spatial resolution and signal-to-noise enhancement. This paper presents a careful comparison of theoretical and measured performance for an array of 256 microphones using simple delay-and-sum beamforming. This is the largest currently functional, all digital-signal-processing array that we know of. The array is wall-mounted in the moderately adverse environment of a general-purpose laboratory (8 m x 8 m x 3 m). The room has a T60 reverberation time of 550 ms. Reverberation effects in this room severely impact the array's performance. However, the width of the main lobe remains comparable to that of a simplified prediction. Broadband spatial resolution shows a single central peak with 10 dB gain about 0.4 m in diameter at the -3 dB level. Away from that peak, the response is approximately flat over most of the room. Optimal weighting for signal-to-noise enhancement degrades the spatial resolution minimally. Experimentally, we verify that signal-to-noise gain is less than proportional to the square root of the number of microphones probably due to the partial correlation of the noise between channels, to variation of signal intensity with polar angle about the source, and to imperfect correlation of the signal over the array caused by reverberations. We show measurements of the relative importance of each effect in our environment.

Factors affecting the performance of large-aperture microphone arrays

NASA Astrophysics Data System (ADS)

Silverman, Harvey F.; Patterson, William R.; Sachar, Joshua

2002-05-01

Large arrays of microphones have been proposed and studied as a possible means of acquiring data in offices, conference rooms, and auditoria without requiring close-talking microphones. When such an array essentially surrounds all possible sources, it is said to have a large aperture. Large-aperture arrays have attractive properties of spatial resolution and signal-to-noise enhancement. This paper presents a careful comparison of theoretical and measured performance for an array of 256 microphones using simple delay-and-sum beamforming. This is the largest currently functional, all digital-signal-processing array that we know of. The array is wall-mounted in the moderately adverse environment of a general-purpose laboratory (8 m×8 m×3 m). The room has a T60 reverberation time of 550 ms. Reverberation effects in this room severely impact the array's performance. However, the width of the main lobe remains comparable to that of a simplified prediction. Broadband spatial resolution shows a single central peak with 10 dB gain about 0.4 m in diameter at the -3 dB level. Away from that peak, the response is approximately flat over most of the room. Optimal weighting for signal-to-noise enhancement degrades the spatial resolution minimally. Experimentally, we verify that signal-to-noise gain is less than proportional to the square root of the number of microphones probably due to the partial correlation of the noise between channels, to variation of signal intensity with polar angle about the source, and to imperfect correlation of the signal over the array caused by reverberations. We show measurements of the relative importance of each effect in our environment.

Evolution of precipitation extremes in two large ensembles of climate simulations

NASA Astrophysics Data System (ADS)

Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

2017-04-01

Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

Carbon Nanotubes as an Ultrafast Emitter with a Narrow Energy Spread at Optical Frequency.

PubMed

Li, Chi; Zhou, Xu; Zhai, Feng; Li, Zhenjun; Yao, Fengrui; Qiao, Ruixi; Chen, Ke; Cole, Matthew Thomas; Yu, Dapeng; Sun, Zhipei; Liu, Kaihui; Dai, Qing

2017-08-01

Ultrafast electron pulses, combined with laser-pump and electron-probe technologies, allow ultrafast dynamics to be characterized in materials. However, the pursuit of simultaneous ultimate spatial and temporal resolution of microscopy and spectroscopy is largely subdued by the low monochromaticity of the electron pulses and their poor phase synchronization to the optical excitation pulses. Field-driven photoemission from metal tips provides high light-phase synchronization, but suffers large electron energy spreads (3-100 eV) as driven by a long wavelength laser (>800 nm). Here, ultrafast electron emission from carbon nanotubes (≈1 nm radius) excited by a 410 nm femtosecond laser is realized in the field-driven regime. In addition, the emitted electrons have great monochromaticity with energy spread as low as 0.25 eV. This great performance benefits from the extraordinarily high field enhancement and great stability of carbon nanotubes, superior to metal tips. The new nanotube-based ultrafast electron source opens exciting prospects for extending current characterization to sub-femtosecond temporal resolution as well as sub-nanometer spatial resolution. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Use of Aerial high resolution visible imagery to produce large river bathymetry: a multi temporal and spatial study over the by-passed Upper Rhine

NASA Astrophysics Data System (ADS)

Béal, D.; Piégay, H.; Arnaud, F.; Rollet, A.; Schmitt, L.

2011-12-01

Aerial high resolution visible imagery allows producing large river bathymetry assuming that water depth is related to water colour (Beer-Bouguer-Lambert law). In this paper we aim at monitoring Rhine River geometry changes for a diachronic study as well as sediment transport after an artificial injection (25.000 m3 restoration operation). For that a consequent data base of ground measurements of river depth is used, built on 3 different sources: (i) differential GPS acquisitions, (ii) sounder data and (iii) lateral profiles realized by experts. Water depth is estimated using a multi linear regression over neo channels built on a principal component analysis over red, green and blue bands and previously cited depth data. The study site is a 12 km long reach of the by-passed section of the Rhine River that draws French and German border. This section has been heavily impacted by engineering works during the last two centuries: channelization since 1842 for navigation purposes and the construction of a 45 km long lateral canal and 4 consecutive hydroelectric power plants of since 1932. Several bathymetric models are produced based on 3 different spatial resolutions (6, 13 and 20 cm) and 5 acquisitions (January, March, April, August and October) since 2008. Objectives are to find the optimal spatial resolution and to characterize seasonal effects. Best performances according to the 13 cm resolution show a 18 cm accuracy when suspended matters impacted less water transparency. Discussions are oriented to the monitoring of the artificial reload after 2 flood events during winter 2010-2011. Bathymetric models produced are also useful to build 2D hydraulic model's mesh.

Flexible proton 3D MR spectroscopic imaging of the prostate with low-power adiabatic pulses for volume selection and spiral readout.

PubMed

Steinseifer, Isabell K; Philips, Bart W J; Gagoski, Borjan; Weiland, Elisabeth; Scheenen, Tom W J; Heerschap, Arend

2017-03-01

Cartesian k-space sampling in three-dimensional magnetic resonance spectroscopic imaging (MRSI) of the prostate limits the selection of voxel size and acquisition time. Therefore, large prostates are often scanned at reduced spatial resolutions to stay within clinically acceptable measurement times. Here we present a semilocalized adiabatic selective refocusing (sLASER) sequence with gradient-modulated offset-independent adiabatic (GOIA) refocusing pulses and spiral k-space acquisition (GOIA-sLASER-Spiral) for fast prostate MRSI with enhanced resolution and extended matrix sizes. MR was performed at 3 tesla with an endorectal receive coil. GOIA-sLASER-Spiral at an echo time (TE) of 90 ms was compared to a point-resolved spectroscopy sequence (PRESS) with weighted, elliptical phase encoding at an TE of 145 ms using simulations and measurements of phantoms and patients (n = 9). GOIA-sLASER-Spiral acquisition allows prostate MR spectra to be obtained in ∼5 min with a quality comparable to those acquired with a common Cartesian PRESS protocol in ∼9 min, or at an enhanced spatial resolution showing more precise tissue allocation of metabolites. Extended field of views (FOVs) and matrix sizes for large prostates are possible without compromising spatial resolution or measurement time. The flexibility of spiral sampling enables prostate MRSI with a wide range of resolutions and FOVs without undesirable increases in acquisition times, as in Cartesian encoding. This approach is suitable for routine clinical exams of prostate metabolites. Magn Reson Med 77:928-935, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Computed tomography imaging and angiography - principles.

PubMed

Kamalian, Shervin; Lev, Michael H; Gupta, Rajiv

2016-01-01

The evaluation of patients with diverse neurologic disorders was forever changed in the summer of 1973, when the first commercial computed tomography (CT) scanners were introduced. Until then, the detection and characterization of intracranial or spinal lesions could only be inferred by limited spatial resolution radioisotope scans, or by the patterns of tissue and vascular displacement on invasive pneumoencaphalography and direct carotid puncture catheter arteriography. Even the earliest-generation CT scanners - which required tens of minutes for the acquisition and reconstruction of low-resolution images (128×128 matrix) - could, based on density, noninvasively distinguish infarct, hemorrhage, and other mass lesions with unprecedented accuracy. Iodinated, intravenous contrast added further sensitivity and specificity in regions of blood-brain barrier breakdown. The advent of rapid multidetector row CT scanning in the early 1990s created renewed enthusiasm for CT, with CT angiography largely replacing direct catheter angiography. More recently, iterative reconstruction postprocessing techniques have made possible high spatial resolution, reduced noise, very low radiation dose CT scanning. The speed, spatial resolution, contrast resolution, and low radiation dose capability of present-day scanners have also facilitated dual-energy imaging which, like magnetic resonance imaging, for the first time, has allowed tissue-specific CT imaging characterization of intracranial pathology. © 2016 Elsevier B.V. All rights reserved.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift.

PubMed

Venkataraman, Abinaya Priya; Lewis, Peter; Unsbo, Peter; Lundström, Linda

2017-04-01

Optimal temporal modulation of the stimulus can improve foveal contrast sensitivity. This study evaluates the characteristics of the peripheral spatiotemporal contrast sensitivity function in normal-sighted subjects. The purpose is to identify a temporal modulation that can potentially improve the remaining peripheral visual function in subjects with central visual field loss. High contrast resolution cut-off for grating stimuli with four temporal frequencies (0, 5, 10 and 15Hz drift) was first evaluated in the 10° nasal visual field. Resolution contrast sensitivity for all temporal frequencies was then measured at four spatial frequencies between 0.5 cycles per degree (cpd) and the measured stationary cut-off. All measurements were performed with eccentric optical correction. Similar to foveal vision, peripheral contrast sensitivity is highest for a combination of low spatial frequency and 5-10Hz drift. At higher spatial frequencies, there was a decrease in contrast sensitivity with 15Hz drift. Despite this decrease, the resolution cut-off did not vary largely between the different temporal frequencies tested. Additional measurements of contrast sensitivity at 0.5 cpd and resolution cut-off for stationary (0Hz) and 7.5Hz stimuli performed at 10, 15, 20 and 25° in the nasal visual field also showed the same characteristics across eccentricities. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Space-based observations of nitrogen dioxide: Trends in anthropogenic emissions

NASA Astrophysics Data System (ADS)

Russell, Ashley Ray

Space-based instruments provide routine global observations, offering a unique perspective on the spatial and temporal variation of atmospheric constituents. In this dissertation, trends in regional-scale anthropogenic nitrogen oxide emissions (NO + NO2 ≡ NOx) are investigated using high resolution observations from the Ozone Monitoring Instrument (OMI). By comparing trends in OMI observations with those from ground-based measurements and an emissions inventory, I show that satellite observations are well-suited for capturing changes in emissions over time. The high spatial and temporal resolutions of the observations provide a uniquely complete view of regional-scale changes in the spatial patterns of NO 2. I show that NOx concentrations have decreased significantly in urban regions of the United States between 2005 and 2011, with an average reduction of 32 ± 7%. By examining day-of-week and interannual trends, I show that these reductions can largely be attributed to improved emission control technology in the mobile source fleet; however, I also show that the economic downturn of the late 2000's has impacted emissions. Additionally, I describe the development of a high-resolution retrieval of NO2 from OMI observations known as the Berkeley High Resolution (BEHR) retrieval. The BEHR product uses higher spatial and temporal resolution terrain and profile parameters than the operational retrievals and is shown to provide a more quantitative measure of tropospheric NO2 column density. These results have important implications for future retrievals of NO2 from space-based observations.

Monitoring Tamarisk Defoliation and Scaling Evapotranspiration Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Dennison, P. E.; Hultine, K. R.; Nagler, P. L.; Miura, T.; Glenn, E. P.; Ehleringer, J. R.

2008-12-01

Non-native tamarisk (Tamarix spp.) has invaded riparian ecosystems throughout the Western United States. Another non-native species, the saltcedar leaf beetle (Diorhabda elongata), has been released in an attempt to control tamarisk infestations. Most efforts directed towards monitoring tamarisk defoliation by Diorhabda have focused on changes in leaf area or sap flux, but these measurements only give a local view of defoliation impacts. We are assessing the ability of remote sensing data for monitoring tamarisk defoliation and measuring resulting changes in evapotranspiration over space and time. Tamarisk defoliation by Diorhabda has taken place during the past two summers along the Colorado River and its tributaries near Moab, Utah. We are using 15 meter spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and 250 meter spatial resolution Moderate Resolution Imaging Spectrometer (MODIS) data to monitor tamarisk defoliation. An ASTER normalized difference vegetation index (NDVI) time series has revealed large drops in index values associated with loss of leaf area due to defoliation. MODIS data have superior temporal monitoring abilities, but at the sacrifice of much lower spatial resolution. A MODIS enhanced vegetation index time series has revealed that for pixels where the percentage of riparian cover is moderate or high, defoliation is detectable even at 250 meter spatial resolution. We are comparing MODIS vegetation index time series to site measurements of leaf area and sap flux. We are also using an evapotranspiration model to scale potential water savings resulting from the biocontrol of tamarisk.

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

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

Guo, Yi, E-mail: yiguo@usc.edu; Zhu, Yinghua; Lingala, Sajan Goud

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm{sup 3}, FOV 22 × 22 × 4.2 cm{sup 3}, and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm{sup 3}, and broader coverage 22 × 22 × 19 cm{sup 3}. Temporal resolution was 5 smore » for both protocols. Time-resolved images and blood–brain barrier permeability maps were qualitatively evaluated by two radiologists. Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.« less

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

PubMed

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Opportunistic mobile air pollution monitoring: A case study with city wardens in Antwerp

NASA Astrophysics Data System (ADS)

Van den Bossche, Joris; Theunis, Jan; Elen, Bart; Peters, Jan; Botteldooren, Dick; De Baets, Bernard

2016-09-01

The goal of this paper is to explore the potential of opportunistic mobile monitoring to map the exposure to air pollution in the urban environment at a high spatial resolution. Opportunistic mobile monitoring makes use of existing mobile infrastructure or people's common daily routines to move measurement devices around. Opportunistic mobile monitoring can also play a crucial role in participatory monitoring campaigns as a typical way to gather data. A case study to measure black carbon was set up in Antwerp, Belgium, with the collaboration of city employees (city wardens). The Antwerp city wardens are outdoors for a large part of the day on surveillance tours by bicycle or on foot, and gathered a total of 393 h of measurements. The data collection is unstructured both in space and time, leading to sampling bias. A temporal adjustment can only partly counteract this bias. Although a high spatial coverage was obtained, there is still a rather large uncertainty on the average concentration levels at a spatial resolution of 50 m due to a limited number of measurements and sampling bias. Despite of this uncertainty, large spatial patterns within the city are clearly captured. This study illustrates the potential of campaigns with unstructured opportunistic mobile monitoring, including participatory monitoring campaigns. The results demonstrate that such an approach can indeed be used to identify broad spatial trends over a wider area, enabling applications including hotspot identification, personal exposure studies, regression mapping, etc. But, they also emphasize the need for repeated measurements and careful processing and interpretation of the data.

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

Schaap, M.; Cuvelier, C.; Hendriks, C.; Bessagnet, B.; Baldasano, J. M.; Colette, A.; Thunis, P.; Karam, D.; Fagerli, H.; Graff, A.; Kranenburg, R.; Nyiri, A.; Pay, M. T.; Rouïl, L.; Schulz, M.; Simpson, D.; Stern, R.; Terrenoire, E.; Wind, P.

2015-07-01

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models' responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.

Abstract ID: 242 Simulation of a Fast Timing Micro-Pattern Gaseous Detector for TOF-PET.

PubMed

Radogna, Raffaella; Verwilligen, Piet

2018-01-01

Micro-Pattern Gas Detectors (MPGDs) are a new generation of gaseous detectors that have been developed thanks to advances in micro-structure technology. The main features of the MPGDs are: high rate capability (>50 MHz/cm 2 ); excellent spatial resolution (down to 50 μm); good time resolution (down to 3 ns); reduced radiation length, affordable costs, and possible flexible geometries. A new detector layout has been recently proposed that aims at combining both the high spatial resolution and high rate capability (100 MHz/cm 2 ) of the current state-of-the-art MPGDs with a high time resolution. This new type of MPGD is named the Fast Timing MPGD (FTM) detector [1,2]. The FTM developed for detecting charged particles can potentially reach sub-millimeter spatial resolution and 100 ps time resolution. This contribution introduces a Fast Timing MPGD technology optimized to detect photons, as an innovative PET imaging detector concept and emphases the importance of full detector simulation to guide the design of the detector geometry. The design and development of a new FTM, combining excellent time and spatial resolution, while exploiting the advantages of a reasonable energy resolution, will be a boost for the design of affordable TOF-PET scanner with improved image contrast. The use of such an affordable gas detector allows to instrument large areas in a cost-effective way, and to increase in image contrast for shorter scanning times (lowering the risk for the patient) and better diagnosis of the disease. In this report a dedicated simulation study is performed to optimize the detector design in the contest of the INFN project MPGD-Fatima. Results are obtained with ANSYS, COMSOL, GARFIELD++ and GEANT4 simulation tools. The final detector layout will be trade-off between fast time and good energy resolution. Copyright © 2017.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Nonlinear ultrasonic imaging with X wave

NASA Astrophysics Data System (ADS)

Du, Hongwei; Lu, Wei; Feng, Huanqing

2009-10-01

X wave has a large depth of field and may have important application in ultrasonic imaging to provide high frame rate (HFR). However, the HFR system suffers from lower spatial resolution. In this paper, a study of nonlinear imaging with X wave is presented to improve the resolution. A theoretical description of realizable nonlinear X wave is reported. The nonlinear field is simulated by solving the KZK nonlinear wave equation with a time-domain difference method. The results show that the second harmonic field of X wave has narrower mainlobe and lower sidelobes than the fundamental field. In order to evaluate the imaging effect with X wave, an imaging model involving numerical calculation of the KZK equation, Rayleigh-Sommerfeld integral, band-pass filtering and envelope detection is constructed to obtain 2D fundamental and second harmonic images of scatters in tissue-like medium. The results indicate that if X wave is used, the harmonic image has higher spatial resolution throughout the entire imaging region than the fundamental image, but higher sidelobes occur as compared to conventional focus imaging. A HFR imaging method with higher spatial resolution is thus feasible provided an apodization method is used to suppress sidelobes.

Evolution of Satellite Imagers and Sounders for Low Earth Orbit and Technology Directions at NASA

NASA Technical Reports Server (NTRS)

Pagano, Thomas S.; McClain, Charles R.

2010-01-01

Imagers and Sounders for Low Earth Orbit (LEO) provide fundamental global daily observations of the Earth System for scientists, researchers, and operational weather agencies. The imager provides the nominal 1-2 km spatial resolution images with global coverage in multiple spectral bands for a wide range of uses including ocean color, vegetation indices, aerosol, snow and cloud properties, and sea surface temperature. The sounder provides vertical profiles of atmospheric temperature, water vapor cloud properties, and trace gases including ozone, carbon monoxide, methane and carbon dioxide. Performance capabilities of these systems has evolved with the optical and sensing technologies of the decade. Individual detectors were incorporated on some of the first imagers and sounders that evolved to linear array technology in the '80's. Signal-to-noise constraints limited these systems to either broad spectral resolution as in the case of the imager, or low spatial resolution as in the case of the sounder. Today's area 2-dimensional large format array technology enables high spatial and high spectral resolution to be incorporated into a single instrument. This places new constraints on the design of these systems and enables new capabilities for scientists to examine the complex processes governing the Earth System.

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

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.

Effects of Cloud Horizontal Inhomogeneity and Drizzle on Remote Sensing of Cloud Droplet Effective Radius: Case Studies Based on Large-eddy Simulations

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Ackerman, Andrew S.; Feingold, Graham; Platnick, Steven; Pincus, Robert; Xue, Huiwen

2012-01-01

This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (re) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution (100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals ofre based on reflectance at 2.1 m (re,2.1) and 3.7 m (re,3.7). It is also found that 3-D effects tend to have stronger impact onre,2.1 than re,3.7, leading to positive difference between the two (re,3.72.1) from illumination and negative re,3.72.1from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement betweenre,2.1 and re,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, re,2.1 is systematically larger than re,3.7when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on bothre,2.1and an index of the sub-pixel variability in reflectance (H), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact reretrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects onre retrievals. The large difference at MODIS resolution between re,3.7 and re,2.1 for highly inhomogeneous pixels with H 0.4 can be largely attributed to what we refer to as the plane-parallelrebias, which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness onre retrievals and is greater for re,2.1 than re,3.7. These results suggest that there are substantial uncertainties attributable to 3-D radiative effects and plane-parallelre bias in the MODIS re,2.1retrievals for pixels with strong sub-pixel scale variability, and theH index can be used to identify these uncertainties.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

PubMed

Glaser, Joshua I; Zamft, Bradley M; Church, George M; Kording, Konrad P

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

Temporal mapping of photochemical reactions and molecular excited states with carbon specificity

NASA Astrophysics Data System (ADS)

Wang, K.; Murahari, P.; Yokoyama, K.; Lord, J. S.; Pratt, F. L.; He, J.; Schulz, L.; Willis, M.; Anthony, J. E.; Morley, N. A.; Nuccio, L.; Misquitta, A.; Dunstan, D. J.; Shimomura, K.; Watanabe, I.; Zhang, S.; Heathcote, P.; Drew, A. J.

2017-04-01

Photochemical reactions are essential to a large number of important industrial and biological processes. A method for monitoring photochemical reaction kinetics and the dynamics of molecular excitations with spatial resolution within the active molecule would allow a rigorous exploration of the pathway and mechanism of photophysical and photochemical processes. Here we demonstrate that laser-excited muon pump-probe spin spectroscopy (photo-μSR) can temporally and spatially map these processes with a spatial resolution at the single-carbon level in a molecule with a pentacene backbone. The observed time-dependent light-induced changes of an avoided level crossing resonance demonstrate that the photochemical reactivity of a specific carbon atom is modified as a result of the presence of the excited state wavefunction. This demonstrates the sensitivity and potential of this technique in probing molecular excitations and photochemistry.

Impacts of rainfall spatial variability on hydrogeological response

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Jódar, Jorge; Navarro, Vicente; Slooten, Luit Jan; Carrera, Jesús; Gupta, Hoshin V.

2015-02-01

There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semiarid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5 km × 2.5 km, medium → 50 km × 50 km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river-aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall.

Automated Topographic Change Detection via Dem Differencing at Large Scales Using The Arcticdem Database

NASA Astrophysics Data System (ADS)

Candela, S. G.; Howat, I.; Noh, M. J.; Porter, C. C.; Morin, P. J.

2016-12-01

In the last decade, high resolution satellite imagery has become an increasingly accessible tool for geoscientists to quantify changes in the Arctic land surface due to geophysical, ecological and anthropomorphic processes. However, the trade off between spatial coverage and spatial-temporal resolution has limited detailed, process-level change detection over large (i.e. continental) scales. The ArcticDEM project utilized over 300,000 Worldview image pairs to produce a nearly 100% coverage elevation model (above 60°N) offering the first polar, high spatial - high resolution (2-8m by region) dataset, often with multiple repeats in areas of particular interest to geo-scientists. A dataset of this size (nearly 250 TB) offers endless new avenues of scientific inquiry, but quickly becomes unmanageable computationally and logistically for the computing resources available to the average scientist. Here we present TopoDiff, a framework for a generalized. automated workflow that requires minimal input from the end user about a study site, and utilizes cloud computing resources to provide a temporally sorted and differenced dataset, ready for geostatistical analysis. This hands-off approach allows the end user to focus on the science, without having to manage thousands of files, or petabytes of data. At the same time, TopoDiff provides a consistent and accurate workflow for image sorting, selection, and co-registration enabling cross-comparisons between research projects.

Initial evaluation of the Celesteion large-bore PET/CT scanner in accordance with the NEMA NU2-2012 standard and the Japanese guideline for oncology FDG PET/CT data acquisition protocol version 2.0.

PubMed

Kaneta, Tomohiro; Ogawa, Matsuyoshi; Motomura, Nobutoku; Iizuka, Hitoshi; Arisawa, Tetsu; Hino-Shishikura, Ayako; Yoshida, Keisuke; Inoue, Tomio

2017-10-11

The goal of this study was to evaluate the performance of the Celesteion positron emission tomography/computed tomography (PET/CT) scanner, which is characterized by a large-bore and time-of-flight (TOF) function, in accordance with the NEMA NU-2 2012 standard and version 2.0 of the Japanese guideline for oncology fluorodeoxyglucose PET/CT data acquisition protocol. Spatial resolution, sensitivity, count rate characteristic, scatter fraction, energy resolution, TOF timing resolution, and image quality were evaluated according to the NEMA NU-2 2012 standard. Phantom experiments were performed using 18 F-solution and an IEC body phantom of the type described in the NEMA NU-2 2012 standard. The minimum scanning time required for the detection of a 10-mm hot sphere with a 4:1 target-to-background ratio, the phantom noise equivalent count (NEC phantom ), % background variability (N 10mm ), % contrast (Q H,10mm ), and recovery coefficient (RC) were calculated according to the Japanese guideline. The measured spatial resolution ranged from 4.5- to 5-mm full width at half maximum (FWHM). The sensitivity and scatter fraction were 3.8 cps/kBq and 37.3%, respectively. The peak noise-equivalent count rate was 70 kcps in the presence of 29.6 kBq mL -1 in the phantom. The system energy resolution was 12.4% and the TOF timing resolution was 411 ps at FWHM. Minimum scanning times of 2, 7, 6, and 2 min per bed position, respectively, are recommended for visual score, noise-equivalent count (NEC) phantom , N 10mm , and the Q H,10mm to N 10mm ratio (QNR) by the Japanese guideline. The RC of a 10-mm-diameter sphere was 0.49, which exceeded the minimum recommended value. The Celesteion large-bore PET/CT system had low sensitivity and NEC, but good spatial and time resolution when compared to other PET/CT scanners. The QNR met the recommended values of the Japanese guideline even at 2 min. The Celesteion is therefore thought to provide acceptable image quality with 2 min/bed position acquisition, which is the most common scan protocol in Japan.

High-resolution Observations of Hα Spectra with a Subtractive Double Pass

NASA Astrophysics Data System (ADS)

Beck, C.; Rezaei, R.; Choudhary, D. P.; Gosain, S.; Tritschler, A.; Louis, R. E.

2018-02-01

High-resolution imaging spectroscopy in solar physics has relied on Fabry-Pérot interferometers (FPIs) in recent years. FPI systems, however, become technically challenging and expensive for telescopes larger than the 1 m class. A conventional slit spectrograph with a diffraction-limited performance over a large field of view (FOV) can be built at much lower cost and effort. It can be converted into an imaging spectro(polari)meter using the concept of a subtractive double pass (SDP). We demonstrate that an SDP system can reach a similar performance as FPI-based systems with a high spatial and moderate spectral resolution across a FOV of 100^'' ×100^' ' with a spectral coverage of 1 nm. We use Hα spectra taken with an SDP system at the Dunn Solar Telescope and complementary full-disc data to infer the properties of small-scale superpenumbral filaments. We find that the majority of all filaments end in patches of opposite-polarity fields. The internal fine-structure in the line-core intensity of Hα at spatial scales of about 0.5'' exceeds that in other parameters such as the line width, indicating small-scale opacity effects in a larger-scale structure with common properties. We conclude that SDP systems in combination with (multi-conjugate) adaptive optics are a valid alternative to FPI systems when high spatial resolution and a large FOV are required. They can also reach a cadence that is comparable to that of FPI systems, while providing a much larger spectral range and a simultaneous multi-line capability.

High-resolution observations of the globular cluster NGC 7099

NASA Astrophysics Data System (ADS)

Sams, Bruce Jones, III

The globular cluster NGC 7099 is a prototypical collapsed core cluster. Through a series of instrumental, observational, and theoretical observations, I have resolved its core structure using a ground based telescope. The core has a radius of 2.15 arcsec when imaged with a V band spatial resolution of 0.35 arcsec. Initial attempts at speckle imaging produced images of inadequate signal to noise and resolution. To explain these results, a new, fully general signal-to-noise model has been developed. It properly accounts for all sources of noise in a speckle observation, including aliasing of high spatial frequencies by inadequate sampling of the image plane. The model, called Full Speckle Noise (FSN), can be used to predict the outcome of any speckle imaging experiment. A new high resolution imaging technique called ACT (Atmospheric Correlation with a Template) was developed to create sharper astronomical images. ACT compensates for image motion due to atmospheric turbulence. ACT is similar to the Shift and Add algorithm, but uses apriori spatial knowledge about the image to further constrain the shifts. In this instance, the final images of NGC 7099 have resolutions of 0.35 arcsec from data taken in 1 arcsec seeing. The PAPA (Precision Analog Photon Address) camera was used to record data. It is subject to errors when imaging cluster cores in a large field of view. The origin of these errors is explained, and several ways to avoid them proposed. New software was created for the PAPA camera to properly take flat field images taken in a large field of view. Absolute photometry measurements of NGC 7099 made with the PAPA camera are accurate to 0.1 magnitude. Luminosity sampling errors dominate surface brightness profiles of the central few arcsec in a collapsed core cluster. These errors set limits on the ultimate spatial accuracy of surface brightness profiles.

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.

2018-06-01

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

The Large Deployable Reflector (LDR) report of the Science Coordination Group

NASA Technical Reports Server (NTRS)

1986-01-01

The Large Deployable Reflector (LDR) is a telescope designed to carry out high-angular resolution, high-sensitivity observations at far-infrared and submillimeter wavelengths. The scientific rationale for the LDR is discussed in light of the recent Infrared Astronomical Satellite (IRAS) and Kuiper Airborne Observatory (KAO) results and the several new ground-based observatories planned for the late 1980s. The importance of high sensitivity and high angular resolution observations from space in the submillimeter region is stressed. The scientific and technical problems of using the LDR in a light bucket mode at approx. less than 5 microns and in designing the LDR as an unfilled aperture with subarcsecond resolution are also discussed. The need for an aperture as large as 20 m is established, along with the requirements of beam-shape stability, spatial chopping, thermal control, and surface figure stability. The instrument complement required to cover the wavelength-spectral resolution region of interest to the LDR is defined.

Ultra-large field-of-view two-photon microscopy

PubMed Central

Tsai, Philbert S.; Mateo, Celine; Field, Jeffrey J.; Schaffer, Chris B.; Anderson, Matthew E.; Kleinfeld, David

2015-01-01

We present a two-photon microscope that images the full extent of murine cortex with an objective-limited spatial resolution across an 8 mm by 10 mm field. The lateral resolution is approximately 1 µm and the maximum scan speed is 5 mm/ms. The scan pathway employs large diameter compound lenses to minimize aberrations and performs near theoretical limits. We demonstrate the special utility of the microscope by recording resting-state vasomotion across both hemispheres of the murine brain through a transcranial window and by imaging histological sections without the need to stitch. PMID:26072755

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2015-03-01

Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

Large Deployable Reflector Science and Technology Workshop. Volume 2: Scientific Rationale and Technology Requirements

NASA Technical Reports Server (NTRS)

Hollenbach, D. (Editor)

1983-01-01

The scientific rationale for the large deployable reflector (LDR) and the overall technological requirements are discussed. The main scientific objectives include studies of the origins of planets, stars and galaxies, and of the ultimate fate of the universe. The envisioned studies require a telescope with a diameter of at least 20 m, diffraction-limited to wavelengths as short as 30-50 micron. In addition, light-bucket operation with 1 arcsec spatial resolution in the 2-4 microns wavelength region would be useful in studies of high-redshifted galaxies. Such a telescope would provide a large increase in spectroscopic sensitivity and spatial resolving power compared with existing or planned infrared telescopes.

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.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

PubMed

Shi, Yue; Huang, Wenjiang; Ye, Huichun; Ruan, Chao; Xing, Naichen; Geng, Yun; Dong, Yingying; Peng, Dailiang

2018-06-11

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast ( Magnaporthe oryzae ), and glume blight ( Phyllosticta glumarum ) in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.

Radiometric infrared focal plane array imaging system for thermographic applications

NASA Technical Reports Server (NTRS)

Esposito, B. J.; Mccafferty, N.; Brown, R.; Tower, J. R.; Kosonocky, W. F.

1992-01-01

This document describes research performed under the Radiometric Infrared Focal Plane Array Imaging System for Thermographic Applications contract. This research investigated the feasibility of using platinum silicide (PtSi) Schottky-barrier infrared focal plane arrays (IR FPAs) for NASA Langley's specific radiometric thermal imaging requirements. The initial goal of this design was to develop a high spatial resolution radiometer with an NETD of 1 percent of the temperature reading over the range of 0 to 250 C. The proposed camera design developed during this study and described in this report provides: (1) high spatial resolution (full-TV resolution); (2) high thermal dynamic range (0 to 250 C); (3) the ability to image rapid, large thermal transients utilizing electronic exposure control (commandable dynamic range of 2,500,000:1 with exposure control latency of 33 ms); (4) high uniformity (0.5 percent nonuniformity after correction); and (5) high thermal resolution (0.1 C at 25 C background and 0.5 C at 250 C background).

Radiometric infrared focal plane array imaging system for thermographic applications

NASA Astrophysics Data System (ADS)

Esposito, B. J.; McCafferty, N.; Brown, R.; Tower, J. R.; Kosonocky, W. F.

1992-11-01

This document describes research performed under the Radiometric Infrared Focal Plane Array Imaging System for Thermographic Applications contract. This research investigated the feasibility of using platinum silicide (PtSi) Schottky-barrier infrared focal plane arrays (IR FPAs) for NASA Langley's specific radiometric thermal imaging requirements. The initial goal of this design was to develop a high spatial resolution radiometer with an NETD of 1 percent of the temperature reading over the range of 0 to 250 C. The proposed camera design developed during this study and described in this report provides: (1) high spatial resolution (full-TV resolution); (2) high thermal dynamic range (0 to 250 C); (3) the ability to image rapid, large thermal transients utilizing electronic exposure control (commandable dynamic range of 2,500,000:1 with exposure control latency of 33 ms); (4) high uniformity (0.5 percent nonuniformity after correction); and (5) high thermal resolution (0.1 C at 25 C background and 0.5 C at 250 C background).

High-resolution imaging of the large non-human primate brain using microPET: a feasibility study

NASA Astrophysics Data System (ADS)

Naidoo-Variawa, S.; Hey-Cunningham, A. J.; Lehnert, W.; Kench, P. L.; Kassiou, M.; Banati, R.; Meikle, S. R.

2007-11-01

The neuroanatomy and physiology of the baboon brain closely resembles that of the human brain and is well suited for evaluating promising new radioligands in non-human primates by PET and SPECT prior to their use in humans. These studies are commonly performed on clinical scanners with 5 mm spatial resolution at best, resulting in sub-optimal images for quantitative analysis. This study assessed the feasibility of using a microPET animal scanner to image the brains of large non-human primates, i.e. papio hamadryas (baboon) at high resolution. Factors affecting image accuracy, including scatter, attenuation and spatial resolution, were measured under conditions approximating a baboon brain and using different reconstruction strategies. Scatter fraction measured 32% at the centre of a 10 cm diameter phantom. Scatter correction increased image contrast by up to 21% but reduced the signal-to-noise ratio. Volume resolution was superior and more uniform using maximum a posteriori (MAP) reconstructed images (3.2-3.6 mm3 FWHM from centre to 4 cm offset) compared to both 3D ordered subsets expectation maximization (OSEM) (5.6-8.3 mm3) and 3D reprojection (3DRP) (5.9-9.1 mm3). A pilot 18F-2-fluoro-2-deoxy-d-glucose ([18F]FDG) scan was performed on a healthy female adult baboon. The pilot study demonstrated the ability to adequately resolve cortical and sub-cortical grey matter structures in the baboon brain and improved contrast when images were corrected for attenuation and scatter and reconstructed by MAP. We conclude that high resolution imaging of the baboon brain with microPET is feasible with appropriate choices of reconstruction strategy and corrections for degrading physical effects. Further work to develop suitable correction algorithms for high-resolution large primate imaging is warranted.

High-throughput isotropic mapping of whole mouse brain using multi-view light-sheet microscopy

NASA Astrophysics Data System (ADS)

Nie, Jun; Li, Yusha; Zhao, Fang; Ping, Junyu; Liu, Sa; Yu, Tingting; Zhu, Dan; Fei, Peng

2018-02-01

Light-sheet fluorescence microscopy (LSFM) uses an additional laser-sheet to illuminate selective planes of the sample, thereby enabling three-dimensional imaging at high spatial-temporal resolution. These advantages make LSFM a promising tool for high-quality brain visualization. However, even by the use of LSFM, the spatial resolution remains insufficient to resolve the neural structures across a mesoscale whole mouse brain in three dimensions. At the same time, the thick-tissue scattering prevents a clear observation from the deep of brain. Here we use multi-view LSFM strategy to solve this challenge, surpassing the resolution limit of standard light-sheet microscope under a large field-of-view (FOV). As demonstrated by the imaging of optically-cleared mouse brain labelled with thy1-GFP, we achieve a brain-wide, isotropic cellular resolution of 3μm. Besides the resolution enhancement, multi-view braining imaging can also recover complete signals from deep tissue scattering and attenuation. The identification of long distance neural projections across encephalic regions can be identified and annotated as a result.

Seafloor observations indicate spatial separation of coseismic and postseismic slips in the 2011 Tohoku earthquake

NASA Astrophysics Data System (ADS)

Iinuma, Takeshi; Hino, Ryota; Uchida, Naoki; Nakamura, Wataru; Kido, Motoyuki; Osada, Yukihito; Miura, Satoshi

2016-11-01

Large interplate earthquakes are often followed by postseismic slip that is considered to occur in areas surrounding the coseismic ruptures. Such spatial separation is expected from the difference in frictional and material properties in and around the faults. However, even though the 2011 Tohoku Earthquake ruptured a vast area on the plate interface, the estimation of high-resolution slip is usually difficult because of the lack of seafloor geodetic data. Here using the seafloor and terrestrial geodetic data, we investigated the postseismic slip to examine whether it was spatially separated with the coseismic slip by applying a comprehensive finite-element method model to subtract the viscoelastic components from the observed postseismic displacements. The high-resolution co- and postseismic slip distributions clarified the spatial separation, which also agreed with the activities of interplate and repeating earthquakes. These findings suggest that the conventional frictional property model is valid for the source region of gigantic earthquakes.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Seafloor observations indicate spatial separation of coseismic and postseismic slips in the 2011 Tohoku earthquake

PubMed Central

Iinuma, Takeshi; Hino, Ryota; Uchida, Naoki; Nakamura, Wataru; Kido, Motoyuki; Osada, Yukihito; Miura, Satoshi

2016-01-01

Large interplate earthquakes are often followed by postseismic slip that is considered to occur in areas surrounding the coseismic ruptures. Such spatial separation is expected from the difference in frictional and material properties in and around the faults. However, even though the 2011 Tohoku Earthquake ruptured a vast area on the plate interface, the estimation of high-resolution slip is usually difficult because of the lack of seafloor geodetic data. Here using the seafloor and terrestrial geodetic data, we investigated the postseismic slip to examine whether it was spatially separated with the coseismic slip by applying a comprehensive finite-element method model to subtract the viscoelastic components from the observed postseismic displacements. The high-resolution co- and postseismic slip distributions clarified the spatial separation, which also agreed with the activities of interplate and repeating earthquakes. These findings suggest that the conventional frictional property model is valid for the source region of gigantic earthquakes. PMID:27853138

Soil water sensor response to bulk electrical conductivity

USDA-ARS?s Scientific Manuscript database

Soil water monitoring using electromagnetic (EM) sensors can facilitate observations of water content at high temporal and spatial resolutions. These sensors measure soil dielectric permittivity (Ka) which is largely a function of volumetric water content. However, bulk electrical conductivity BEC c...

An atlas of high-resolution IRAS maps on nearby galaxies

NASA Technical Reports Server (NTRS)

Rice, Walter

1993-01-01

An atlas of far-infrared IRAS maps with near 1 arcmin angular resolution of 30 optically large galaxies is presented. The high-resolution IRAS maps were produced with the Maximum Correlation Method (MCM) image construction and enhancement technique developed at IPAC. The MCM technique, which recovers the spatial information contained in the overlapping detector data samples of the IRAS all-sky survey scans, is outlined and tests to verify the structural reliability and photometric integrity of the high-resolution maps are presented. The infrared structure revealed in individual galaxies is discussed. The atlas complements the IRAS Nearby Galaxy High-Resolution Image Atlas, the high-resolution galaxy images encoded in FITS format, which is provided to the astronomical community as an IPAC product.

Low--resolution vision in a velvet worm (Onychophora).

PubMed

Kirwan, John D; Graf, Josefine; Smolka, Jochen; Mayer, Georg; Henze, Miriam J; Nilsson, Dan-Eric

2018-06-04

Onychophorans, also known as velvet worms, possess a pair of simple lateral eyes, and are a key lineage with regard to the evolution of vision. They resemble ancient Cambrian forms, and are closely related to arthropods, which boast an unrivalled diversity of eye designs. Nonetheless, the visual capabilities of onychophorans have not been well explored. Here, we assessed the spatial resolution of the onychophoran Euperipatoides rowelli using behavioural experiments, three-dimensional reconstruction, anatomical and optical examinations, and modelling. Exploiting their spontaneous attraction towards dark objects, we found that E. rowelli can resolve stimuli that have the same average luminance as the background. Depending on the assumed contrast sensitivity of the animals, we estimate the spatial resolution to be in the range 15-40 deg. This results from an arrangement where the cornea and lens project the image largely behind the retina. The peculiar ellipsoid shape of the eye in combination with the asymmetric position and tilted orientation of the lens may improve spatial resolution in the forward direction. Nonetheless, the unordered network of interdigitating photoreceptors, which fills the whole eye chamber, precludes high-acuity vision. Our findings suggest that adult specimens of E. rowelli cannot spot or visually identify prey or conspecifics beyond a few centimetres from the eye, but the coarse spatial resolution that the animals exhibited in our experiments is likely to be sufficient to find shelter and suitable microhabitats from further away. To our knowledge, this is the first evidence of resolving vision in an onychophoran. © 2018. Published by The Company of Biologists Ltd.

An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions

Treesearch

Jian Yang; Hong S. He; Stephen R. Shifley; Frank R. Thompson; Yangjian Zhang

2011-01-01

Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine...

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Spatial Resolution Requirements for Traffic-Related Air Pollutant Exposure Evaluations

PubMed Central

Batterman, Stuart; Chambliss, Sarah; Isakov, Vlad

2014-01-01

Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9,700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 hr, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification. PMID:25132794

Large High Resolution Displays for Co-Located Collaborative Sensemaking: Display Usage and Territoriality

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

Bradel, Lauren; Endert, Alexander; Koch, Kristen

2013-08-01

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional textual intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the space management strategies of users partitioned by type of tool philosophy followed (visualization- or text-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with information on the display (integrated or independent workspaces). Next,more » we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we offer design suggestions for building future co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays.« less

Vibrational spectroscopy in the electron microscope.

PubMed

Krivanek, Ondrej L; Lovejoy, Tracy C; Dellby, Niklas; Aoki, Toshihiro; Carpenter, R W; Rez, Peter; Soignard, Emmanuel; Zhu, Jiangtao; Batson, Philip E; Lagos, Maureen J; Egerton, Ray F; Crozier, Peter A

2014-10-09

Vibrational spectroscopies using infrared radiation, Raman scattering, neutrons, low-energy electrons and inelastic electron tunnelling are powerful techniques that can analyse bonding arrangements, identify chemical compounds and probe many other important properties of materials. The spatial resolution of these spectroscopies is typically one micrometre or more, although it can reach a few tens of nanometres or even a few ångströms when enhanced by the presence of a sharp metallic tip. If vibrational spectroscopy could be combined with the spatial resolution and flexibility of the transmission electron microscope, it would open up the study of vibrational modes in many different types of nanostructures. Unfortunately, the energy resolution of electron energy loss spectroscopy performed in the electron microscope has until now been too poor to allow such a combination. Recent developments that have improved the attainable energy resolution of electron energy loss spectroscopy in a scanning transmission electron microscope to around ten millielectronvolts now allow vibrational spectroscopy to be carried out in the electron microscope. Here we describe the innovations responsible for the progress, and present examples of applications in inorganic and organic materials, including the detection of hydrogen. We also demonstrate that the vibrational signal has both high- and low-spatial-resolution components, that the first component can be used to map vibrational features at nanometre-level resolution, and that the second component can be used for analysis carried out with the beam positioned just outside the sample--that is, for 'aloof' spectroscopy that largely avoids radiation damage.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce.

PubMed

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-08-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS - a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce

PubMed Central

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-01-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS – a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive. PMID:24187650

Development and characterization of high-resolution neutron pixel detectors based on Timepix read-out chips

NASA Astrophysics Data System (ADS)

Krejci, F.; Zemlicka, J.; Jakubek, J.; Dudak, J.; Vavrik, D.; Köster, U.; Atkins, D.; Kaestner, A.; Soltes, J.; Viererbl, L.; Vacik, J.; Tomandl, I.

2016-12-01

Using a suitable isotope such as 6Li and 10B semiconductor hybrid pixel detectors can be successfully adapted for position sensitive detection of thermal and cold neutrons via conversion into energetic light ions. The adapted devices then typically provides spatial resolution at the level comparable to the pixel pitch (55 μm) and sensitive area of about few cm2. In this contribution, we describe further progress in neutron imaging performance based on the development of a large-area hybrid pixel detector providing practically continuous neutron sensitive area of 71 × 57 mm2. The measurements characterising the detector performance at the cold neutron imaging instrument ICON at PSI and high-flux imaging beam-line Neutrograph at ILL are presented. At both facilities, high-resolution high-contrast neutron radiography with the newly developed detector has been successfully applied for objects which imaging were previously difficult with hybrid pixel technology (such as various composite materials, objects of cultural heritage etc.). Further, a significant improvement in the spatial resolution of neutron radiography with hybrid semiconductor pixel detector based on the fast read-out Timepix-based detector is presented. The system is equipped with a thin planar 6LiF convertor operated effectively in the event-by-event mode enabling position sensitive detection with spatial resolution better than 10 μm.

Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling

NASA Astrophysics Data System (ADS)

Her, Y. G.

2017-12-01

Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

USGS Publications Warehouse

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.

Beam test results of the BTeV silicon pixel detector

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

Gabriele Chiodini et al.

2000-09-28

The authors have described the results of the BTeV silicon pixel detector beam test. The pixel detectors under test used samples of the first two generations of Fermilab pixel readout chips, FPIX0 and FPIX1, (indium bump-bonded to ATLAS sensor prototypes). The spatial resolution achieved using analog charge information is excellent for a large range of track inclination. The resolution is still very good using only 2-bit charge information. A relatively small dependence of the resolution on bias voltage is observed. The resolution is observed to depend dramatically on the discriminator threshold, and it deteriorates rapidly for threshold above 4000e{sup {minus}}.

Solar microwave bursts - A review

NASA Technical Reports Server (NTRS)

Kundu, M. R.; Vlahos, L.

1982-01-01

Observational and theoretical results on the physics of microwave bursts that occur in the solar atmosphere are reviewed. Special attention is given to the advances made in burst physics over the last few years with the great improvement in spatial and time resolution, especially with instruments like the NRAO three-element interferometer, the Westerbork Synthesis Radio Telescope, and more recently the Very Large Array. Observations made on the preflare build-up of an active region at centimeter wavelengths are reviewed. Three distinct phases in the evolution of cm bursts, namely the impulsive phase, the post-burst phase, and the gradual rise and fall, are discussed. Attention is also given to the flux density spectra of centimeter bursts. Descriptions are given of observations of fine structures with temporal resolution of 10-100 ms in the intensity profiles of cm-wavelength bursts. High spatial resolution observations are analyzed, with special reference to the one- and two-dimensional maps of cm burst sources.

Design Parameters and Objectives of a High-­Resolution X-­ray Imaging Crystal Spectrometer for the Large Helical Device (LHD)

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

Bitter, M; Gates, D; Neilson, H

A high-resolution X-ray imaging crystal spectrometer, whose instrumental concept was thoroughly tested on NSTX and Alcator C-Mod, is presently being designed for LHD. The instrument will record spatially resolved spectra of helium-like Ar16+ and provide ion temperature profiles with spatial and temporal resolutions of 1 cm and > 10 ms which are obtained by a tomographic inversion of the spectral data, using the stellarator equilibrium reconstruction codes, STELLOPT and PIES. Since the spectrometer will be equipped with radiation hardened, high count rate, PILATUS detectors,, it is expected to be operational for all experimental conditions on LHD, which include plasmas ofmore » high density and plasmas with auxiliary RF and neutral beam heating. The special design features required by the magnetic field structure at LHD will be described.« less

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

Bache, S; Rong, J

Purpose: To quantify a radiology team’s assessment of image quality differences between two CT scanner models currently in clinical use, with emphasis on spatial resolution that could be impacted by focal spot size. Methods: Modulation Transfer Functions (MTF) measurements were performed by scanning the impulse source insert module of the Catphan 600 at 120/140 kVp with both large (LFS) and small (SFS) focal spots and reconstructed to 2.5mm and 5.0mm thicknesses on a GE Discovery CT750 HD and a LightSpeed VCT CT scanner. MTFs were calculated by summing the 2D PSF along one-dimension to obtain line-spread-function (LSF), and calculating themore » Fourier Transform of the zero-padded and background corrected LSF. Spatial resolution performance was evaluated by comparing MTF curves, 50% and 10% MTF cutoff, and total area under the MTF curve (AUC). In addition, images of the Catphan high-contrast module and a Kagaku anthropomorphic body phantom were acquired from the HD scanner for visual comparisons. Results: For each scanner model, SFS was superior to LFS spatial resolution with respect to 50%/10% MTF cutoff and AUC. For the HD, 50%/10% cutoff was 4.29/7.22cm-1 for the LFS and 4.43/7.45cm-1 for the SFS. VCT outperformed HD, with 50%/10% cutoff of 4.40/7.29 cm-1 for LFS and 4.62/7.47cm-1 for SFS. Scanner model performance in order of decreasing AUC performance was VCT SFS (7.43), HD SFS (7.20), VCT LFS (7.09) and HD LFS (6.93). Visual evaluations of Kagaku phantom images confirmed that VCT outperformed HD. Conclusion: VCT outperformed HD and small focal spot is desired for either model over large focal spot in term of spatial resolution – in agreement with radiologist feedback of overall image quality. In-depth evaluations of clinical impact and focal spot selection mechanisms is currently being assessed.« less

Submicrometre geometrically encoded fluorescent barcodes self-assembled from DNA

NASA Astrophysics Data System (ADS)

Lin, Chenxiang; Jungmann, Ralf; Leifer, Andrew M.; Li, Chao; Levner, Daniel; Church, George M.; Shih, William M.; Yin, Peng

2012-10-01

The identification and differentiation of a large number of distinct molecular species with high temporal and spatial resolution is a major challenge in biomedical science. Fluorescence microscopy is a powerful tool, but its multiplexing ability is limited by the number of spectrally distinguishable fluorophores. Here, we used (deoxy)ribonucleic acid (DNA)-origami technology to construct submicrometre nanorods that act as fluorescent barcodes. We demonstrate that spatial control over the positioning of fluorophores on the surface of a stiff DNA nanorod can produce 216 distinct barcodes that can be decoded unambiguously using epifluorescence or total internal reflection fluorescence microscopy. Barcodes with higher spatial information density were demonstrated via the construction of super-resolution barcodes with features spaced by ˜40 nm. One species of the barcodes was used to tag yeast surface receptors, which suggests their potential applications as in situ imaging probes for diverse biomolecular and cellular entities in their native environments.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization

PubMed Central

Glaser, Joshua I.; Zamft, Bradley M.; Church, George M.; Kording, Konrad P.

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, “puzzle imaging,” that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples. PMID:26192446

Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

PubMed Central

Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

2010-01-01

We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354

X-ray simulations method for the large field of view

NASA Astrophysics Data System (ADS)

Schelokov, I. A.; Grigoriev, M. V.; Chukalina, M. V.; Asadchikov, V. E.

2018-03-01

In the standard approach, X-ray simulation is usually limited to the step of spatial sampling to calculate the convolution of integrals of the Fresnel type. Explicitly the sampling step is determined by the size of the last Fresnel zone in the beam aperture. In other words, the spatial sampling is determined by the precision of integral convolution calculations and is not connected with the space resolution of an optical scheme. In the developed approach the convolution in the normal space is replaced by computations of the shear strain of ambiguity function in the phase space. The spatial sampling is then determined by the space resolution of an optical scheme. The sampling step can differ in various directions because of the source anisotropy. The approach was used to simulate original images in the X-ray Talbot interferometry and showed that the simulation can be applied to optimize the methods of postprocessing.

Sub-micrometer Geometrically Encoded Fluorescent Barcodes Self-Assembled from DNA

PubMed Central

Lin, Chenxiang; Jungmann, Ralf; Leifer, Andrew M.; Li, Chao; Levner, Daniel; Church, George M.; Shih, William M.; Yin, Peng

2012-01-01

The identification and differentiation of a large number of distinct molecular species with high temporal and spatial resolution is a major challenge in biomedical science. Fluorescence microscopy is a powerful tool, but its multiplexing ability is limited by the number of spectrally distinguishable fluorophores. Here we use DNA-origami technology to construct sub-micrometer nanorods that act as fluorescent barcodes. We demonstrate that spatial control over the positioning of fluorophores on the surface of a stiff DNA nanorod can produce 216 distinct barcodes that can be unambiguously decoded using epifluorescence or total internal reflection fluorescence (TIRF) microscopy. Barcodes with higher spatial information density were demonstrated via the construction of super-resolution barcodes with features spaced by ~40 nm. One species of the barcodes was used to tag yeast surface receptors, suggesting their potential applications as in situ imaging probes for diverse biomolecular and cellular entities in their native environments. PMID:23000997

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.

North Atlantic Tropical Cyclone Precipitation and Climate Interactions Using a High-Resolution Dataset for the Eastern United States, 1948-2015.

NASA Astrophysics Data System (ADS)

Bregy, J. C.; Maxwell, J. T.; Robeson, S. M.

2017-12-01

Tropical cyclone (TC) impacts are typically concentrated along the coast, yet some TC hazards have wider spatial distributions and affect inland regions. For example, large volumes of TC precipitation (TCP) can cause severe inland flooding, initiate slope failure, and create large sinkholes. Previous studies show that TCP contributes substantially to seasonal precipitation budgets in the eastern United States. However, present knowledge of TCP climatology in the US is limited by the spatial coverage of weather stations. Here we develop a new high resolution (0.25°x0.25°) TCP climatology using HURDAT2 and CPC US Unified Precipitation data (1948-2015). From June to November (JJASON), maximum total TCP for the study period ranges from 2200 to 3800 mm along much of the coast and decreases inland. Likewise, spatial patterns of TCP contribution to total JJASON precipitation largely mirror those of total TCP, with maxima (6-8%) located in coastal Texas and North Carolina. Similar spatial patterns are seen in the mean JJASON TCP and mean TCP contribution over the study period, with maxima extending beyond coastal Texas and North Carolina. JJASON TCP (total, mean, and contribution) was correlated with mean annual JJASON values for the Bermuda High Index (BHI), El Niño-Southern Oscillation combined Niño3.4/Southern Oscillation Index (ENSO-BEST), and North Atlantic Oscillation (NAO). Correlations between climate indices and JJASON TCP show the degree to which BHI, ENSO-BEST, and NAO influence spatiotemporal changes in TCP. Of the three indices, the BHI had the strongest and most spatially consistent correlation with TCP, with significant correlations in the interior of the southeast. These results indicate a strong regional relationship between the North Atlantic Subtropical High (NASH; represented by the BHI) and regional TCP distribution. TCP distribution depends on TC track direction, and is therefore connected to the NASH, which acts as a steering mechanism for TCs. Our derived high resolution TCP climatology further aids our understanding of TC-climate interactions. Moreover, it can be used to understand hazards associated with TCs, serving as an invaluable tool in hazard mitigation efforts.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.

2015-12-01

Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of multi-temporal vegetation index data derived from satellite images. Determined changes were exported to GIS environment and spatial overlay and intersection analyses were performed with use of forest type maps and authorized area maps in order to demonstrate the actual situation of destructions and infractions.

Photosynthesis in high definition

NASA Astrophysics Data System (ADS)

Hilton, Timothy W.

2018-01-01

Photosynthesis is the foundation for almost all known life, but quantifying it at scales above a single plant is difficult. A new satellite illuminates plants' molecular machinery at much-improved spatial resolution, taking us one step closer to combined `inside-outside' insights into large-scale photosynthesis.

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.

Physical studies of Centaurs and Trans-Neptunian Objects with the Atacama Large Millimeter Array

NASA Astrophysics Data System (ADS)

Moullet, Arielle; Lellouch, Emmanuel; Moreno, Raphael; Gurwell, Mark

2011-05-01

Once completed, the Atacama Large Millimeter Array (ALMA) will be the most powerful (sub)millimeter interferometer in terms of sensitivity, spatial resolution and imaging. This paper presents the capabilities of ALMA applied to the observation of Centaurs and Trans-Neptunian Objects, and their possible output in terms of physical properties. Realistic simulations were performed to explore the performances of the different frequency bands and array configurations, and several projects are detailed along with their feasibility, their limitations and their possible targets. Determination of diameters and albedos via the radiometric method appears to be possible on ˜500 objects, while sampling of the thermal lightcurve to derive the bodies' ellipticity could be performed at least 30 bodies that display a significant optical lightcurve. On a limited number of objects, the spatial resolution allows for direct measurement of the size or even surface mapping with a resolution down to 13 milliarcsec. Finally, ALMA could separate members of multiple systems with a separation power comparable to that of the HST. The overall performance of ALMA will make it an invaluable instrument to explore the outer Solar System, complementary to space-based telescopes and spacecrafts.

4D electron microscopy: principles and applications.

PubMed

Flannigan, David J; Zewail, Ahmed H

2012-10-16

The transmission electron microscope (TEM) is a powerful tool enabling the visualization of atoms with length scales smaller than the Bohr radius at a factor of only 20 larger than the relativistic electron wavelength of 2.5 pm at 200 keV. The ability to visualize matter at these scales in a TEM is largely due to the efforts made in correcting for the imperfections in the lens systems which introduce aberrations and ultimately limit the achievable spatial resolution. In addition to the progress made in increasing the spatial resolution, the TEM has become an all-in-one characterization tool. Indeed, most of the properties of a material can be directly mapped in the TEM, including the composition, structure, bonding, morphology, and defects. The scope of applications spans essentially all of the physical sciences and includes biology. Until recently, however, high resolution visualization of structural changes occurring on sub-millisecond time scales was not possible. In order to reach the ultrashort temporal domain within which fundamental atomic motions take place, while simultaneously retaining high spatial resolution, an entirely new approach from that of millisecond-limited TEM cameras had to be conceived. As shown below, the approach is also different from that of nanosecond-limited TEM, whose resolution cannot offer the ultrafast regimes of dynamics. For this reason "ultrafast electron microscopy" is reserved for the field which is concerned with femtosecond to picosecond resolution capability of structural dynamics. In conventional TEMs, electrons are produced by heating a source or by applying a strong extraction field. Both methods result in the stochastic emission of electrons, with no control over temporal spacing or relative arrival time at the specimen. The timing issue can be overcome by exploiting the photoelectric effect and using pulsed lasers to generate precisely timed electron packets of ultrashort duration. The spatial and temporal resolutions achievable with short intense pulses containing a large number of electrons, however, are limited to tens of nanometers and nanoseconds, respectively. This is because Coulomb repulsion is significant in such a pulse, and the electrons spread in space and time, thus limiting the beam coherence. It is therefore not possible to image the ultrafast elementary dynamics of complex transformations. The challenge was to retain the high spatial resolution of a conventional TEM while simultaneously enabling the temporal resolution required to visualize atomic-scale motions. In this Account, we discuss the development of four-dimensional ultrafast electron microscopy (4D UEM) and summarize techniques and applications that illustrate the power of the approach. In UEM, images are obtained either stroboscopically with coherent single-electron packets or with a single electron bunch. Coulomb repulsion is absent under the single-electron condition, thus permitting imaging, diffraction, and spectroscopy, all with high spatiotemporal resolution, the atomic scale (sub-nanometer and femtosecond). The time resolution is limited only by the laser pulse duration and energy carried by the electron packets; the CCD camera has no bearing on the temporal resolution. In the regime of single pulses of electrons, the temporal resolution of picoseconds can be attained when hundreds of electrons are in the bunch. The applications given here are selected to highlight phenomena of different length and time scales, from atomic motions during structural dynamics to phase transitions and nanomechanical oscillations. We conclude with a brief discussion of emerging methods, which include scanning ultrafast electron microscopy (S-UEM), scanning transmission ultrafast electron microscopy (ST-UEM) with convergent beams, and time-resolved imaging of biological structures at ambient conditions with environmental cells.

Photonics and microarray technology

NASA Astrophysics Data System (ADS)

Skovsen, E.; Duroux, M.; Neves-Petersen, M. T.; Duroux, L.; Petersen, S. B.

2007-05-01

Photonic induced immobilization of biosensor molecules is a novel technology that results in spatially oriented and spatially localized covalent coupling of a large variety of biomolecules onto thiol reactive surfaces, e.g. thiolated glass, quartz, gold or silicon. The reaction mechanism behind the reported new technology involves light-induced breakage of disulphide bridges in proteins upon UV illumination of nearby aromatic amino acids resulting in the formation of reactive molecules that will form covalent bonds with thiol reactive surfaces. This new technology has the potential of replacing present micro dispensing arraying technologies, where the size of the individual sensor spots are limited by the size of the dispensed droplets. Using light-induced immobilization the spatial resolution is defined by the area of the sensor surface that is illuminated by UV light and not by the physical size of the dispensed droplets of sensor molecules. This new technology allows for dense packing of different biomolecules on a surface, allowing the creation of multi-potent functionalized materials, such as biosensors with micrometer sized individual sensor spots. Thus, we have developed the necessary technology for preparing large protein arrays of enzymes and fragments of antibodies, with micrometer resolution, without the need for liquid micro dispensing.

X-ray fluorescence imaging system for fast mapping of pigment distributions in cultural heritage paintings

NASA Astrophysics Data System (ADS)

Zielińska, A.; Dąbrowski, W.; Fiutowski, T.; Mindur, B.; Wiącek, P.; Wróbel, P.

2013-10-01

Conventional X-ray fluorescence imaging technique uses a focused X-ray beam to scan through the sample and an X-ray detector with high energy resolution but no spatial resolution. The spatial resolution of the image is then determined by the size of the exciting beam, which can be obtained either from a synchrotron source or from an X-ray tube with a micro-capillary lens. Such a technique based on a pixel-by-pixel measurement is very slow and not suitable for imaging large area samples. The goal of this work is to develop a system capable of simultaneous imaging of large area samples by using a wide field uniform excitation X-ray beam and a position sensitive and energy dispersive detector. The development is driven by possible application of such a system to imaging of distributions of hidden pigments containing specific elements in cultural heritage paintings, which is of great interest for the cultural heritage research. The fluorescence radiation from the area of 10 × 10 cm2 is projected through a pinhole camera on the Gas Electron Multiplier detector of the same area. The detector is equipped with two sets of orthogonal readout strips. The strips are read out by the GEMROC Application Specific Integrated Circuits (ASIC)s, which deliver time and amplitude information for each hit. This ASIC architecture combined with a Field Programmable Gate Array (FPGA) based readout system allows us to reconstruct the position and the total energy of each detected photon for high count rates up to 5 × 106 cps. Energy resolution better than 20% FWHM for the 5.9 keV line and spatial resolution of 1 mm FWHM have been achieved for the prototype system. Although the energy resolution of the Gas Electron Multiplier (GEM) detector is, by principle, not competitive with that of specialised high energy resolution semiconductor detectors, it is sufficient for a number of applications. Compared to conventional micro-XRF techniques the developed system allows shortening of the measurement time by 2-3 orders of magnitude.

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.

Remote sensing in support of high-resolution terrestrial carbon monitoring and modeling

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Zhao, M.; Dubayah, R.; Huang, C.; Swatantran, A.; ONeil-Dunne, J.; Johnson, K. D.; Birdsey, R.; Fisk, J.; Flanagan, S.; Sahajpal, R.; Huang, W.; Tang, H.; Armstrong, A. H.

2014-12-01

As part of its Phase 1 Carbon Monitoring System (CMS) activities, NASA initiated a Local-Scale Biomass Pilot study. The goals of the pilot study were to develop protocols for fusing high-resolution remotely sensed observations with field data, provide accurate validation test areas for the continental-scale biomass product, and demonstrate efficacy for prognostic terrestrial ecosystem modeling. In Phase 2, this effort was expanded to the state scale. Here, we present results of this activity focusing on the use of remote sensing in high-resolution ecosystem modeling. The Ecosystem Demography (ED) model was implemented at 90 m spatial resolution for the entire state of Maryland. We rasterized soil depth and soil texture data from SSURGO. For hourly meteorological data, we spatially interpolated 32-km 3-hourly NARR into 1-km hourly and further corrected them at monthly level using PRISM data. NLCD data were used to mask sand, seashore, and wetland. High-resolution 1 m forest/non-forest mapping was used to define forest fraction of 90 m cells. Three alternative strategies were evaluated for initialization of forest structure using high-resolution lidar, and the model was used to calculate statewide estimates of forest biomass, carbon sequestration potential, time to reach sequestration potential, and sensitivity to future forest growth and disturbance rates, all at 90 m resolution. To our knowledge, no dynamic ecosystem model has been run at such high spatial resolution over such large areas utilizing remote sensing and validated as extensively. There are over 3 million 90 m land cells in Maryland, greater than 43 times the ~73,000 half-degree cells in a state-of-the-art global land model.

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

First characterization of a digital SiPM based time-of-flight PET detector with 1 mm spatial resolution

NASA Astrophysics Data System (ADS)

Seifert, Stefan; van der Lei, Gerben; van Dam, Herman T.; Schaart, Dennis R.

2013-05-01

Monolithic scintillator detectors can offer a combination of spatial resolution, energy resolution, timing performance, depth-of-interaction information, and detection efficiency that make this type of detector a promising candidate for application in clinical, time-of-flight (TOF) positron emission tomography (PET). In such detectors the scintillation light is distributed over a relatively large number of photosensor pixels and the light intensity per pixel can be relatively low. Therefore, monolithic scintillator detectors are expected to benefit from the low readout noise offered by a novel photosensor called the digital silicon photomultiplier (dSiPM). Here, we present a first experimental characterization of a TOF PET detector comprising a 24 × 24 × 10 mm3 LSO:Ce,0.2%Ca scintillator read out by a dSiPM array (DPC-6400-44-22) developed by Philips Digital Photon Counting. A spatial resolution of ˜1 mm full-width-at-half-maximum (FWHM) averaged over the entire crystal was obtained (varying from just below 1 mm FWHM in the detector center to ˜1.2 mm FWHM close to the edges). Furthermore, the bias in the position estimation at the crystal edges that is typically found in monolithic scintillators is well below 1 mm even in the corners of the crystal.

Design studies of large aperture, high-resolution Earth science microwave radiometers compatible with small launch vehicles

NASA Technical Reports Server (NTRS)

Schroeder, Lyle C.; Bailey, M. C.; Harrington, Richard F.; Kendall, Bruce M.; Campbell, Thomas G.

1994-01-01

High-spatial-resolution microwave radiometer sensing from space with reasonable swath widths and revisit times favors large aperture systems. However, with traditional precision antenna design, the size and weight requirements for such systems are in conflict with the need to emphasize small launch vehicles. This paper describes tradeoffs between the science requirements, basic operational parameters, and expected sensor performance for selected satellite radiometer concepts utilizing novel lightweight compactly packaged real apertures. Antenna, feed, and radiometer subsystem design and calibration are presented. Preliminary results show that novel lightweight real aperture coupled with state-of-the-art radiometer designs are compatible with small launch systems, and hold promise for high-resolution earth science measurements of sea ice, precipitation, soil moisture, sea surface temperature, and ocean wind speeds.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Mapping disease at an approximated individual level using aggregate data: a case study of mapping New Hampshire birth defects.

PubMed

Shi, Xun; Miller, Stephanie; Mwenda, Kevin; Onda, Akikazu; Reese, Judy; Onega, Tracy; Gui, Jiang; Karagas, Margret; Demidenko, Eugene; Moeschler, John

2013-09-06

Limited by data availability, most disease maps in the literature are for relatively large and subjectively-defined areal units, which are subject to problems associated with polygon maps. High resolution maps based on objective spatial units are needed to more precisely detect associations between disease and environmental factors. We propose to use a Restricted and Controlled Monte Carlo (RCMC) process to disaggregate polygon-level location data to achieve mapping aggregate data at an approximated individual level. RCMC assigns a random point location to a polygon-level location, in which the randomization is restricted by the polygon and controlled by the background (e.g., population at risk). RCMC allows analytical processes designed for individual data to be applied, and generates high-resolution raster maps. We applied RCMC to the town-level birth defect data for New Hampshire and generated raster maps at the resolution of 100 m. Besides the map of significance of birth defect risk represented by p-value, the output also includes a map of spatial uncertainty and a map of hot spots. RCMC is an effective method to disaggregate aggregate data. An RCMC-based disease mapping maximizes the use of available spatial information, and explicitly estimates the spatial uncertainty resulting from aggregation.

High-resolution wavefront control of high-power laser systems

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

Brase, J; Brown, C; Carrano, C

1999-07-08

Nearly every new large-scale laser system application at LLNL has requirements for beam control which exceed the current level of available technology. For applications such as inertial confinement fusion, laser isotope separation, laser machining, and laser the ability to transport significant power to a target while maintaining good beam quality is critical. There are many ways that laser wavefront quality can be degraded. Thermal effects due to the interaction of high-power laser or pump light with the internal optical components or with the ambient gas are common causes of wavefront degradation. For many years, adaptive optics based on thing deformablemore » glass mirrors with piezoelectric or electrostrictive actuators have be used to remove the low-order wavefront errors from high-power laser systems. These adaptive optics systems have successfully improved laser beam quality, but have also generally revealed additional high-spatial-frequency errors, both because the low-order errors have been reduced and because deformable mirrors have often introduced some high-spatial-frequency components due to manufacturing errors. Many current and emerging laser applications fall into the high-resolution category where there is an increased need for the correction of high spatial frequency aberrations which requires correctors with thousands of degrees of freedom. The largest Deformable Mirrors currently available have less than one thousand degrees of freedom at a cost of approximately $1M. A deformable mirror capable of meeting these high spatial resolution requirements would be cost prohibitive. Therefore a new approach using a different wavefront control technology is needed. One new wavefront control approach is the use of liquid-crystal (LC) spatial light modulator (SLM) technology for the controlling the phase of linearly polarized light. Current LC SLM technology provides high-spatial-resolution wavefront control, with hundreds of thousands of degrees of freedom, more than two orders of magnitude greater than the best Deformable Mirrors currently made. Even with the increased spatial resolution, the cost of these devices is nearly two orders of magnitude less than the cost of the largest deformable mirror.« less

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Towards high temporal and moderate spatial resolutions in the remote sensing retrieval of evapotranspiration by combining geostationary and polar orbit satellite data

NASA Astrophysics Data System (ADS)

Barrios, José Miguel; Ghilain, Nicolas; Arboleda, Alirio; Gellens-Meulenberghs, Françoise

2014-05-01

Evapotranspiration (ET) is the water flux going from the surface into the atmosphere as result of soil and surface water evaporation and plant transpiration. It constitutes a key component of the water cycle and its quantification is of crucial importance for a number of applications like water management, climatic modelling, agriculture monitoring and planning, etc. Estimating ET is not an easy task; specially if large areas are envisaged and various spatio-temporal patterns of ET are present as result of heterogeneity in land cover, land use and climatic conditions. In this respect, spaceborne remote sensing (RS) provides the only alternative to continuously measure surface parameters related to ET over large areas. The Royal Meteorological Institute (RMI) of Belgium, in the framework of EUMETSAT's "Land Surface Analysis-Satellite Application Facility" (LSA-SAF), has developed a model for the estimation of ET. The model is forced by RS data, numerical weather predictions and land cover information. The RS forcing is derived from measurements by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. This ET model is operational and delivers ET estimations over the whole field of view of the MSG satellite (Europe, Africa and Eastern South America) (http://landsaf.meteo.pt) every 30 minutes. The spatial resolution of MSG is 3 x 3 km at subsatellite point and about 4 x 5 km in continental Europe. The spatial resolution of this product may constrain its full exploitation as the interest of potential users (farmers and natural resources scientists) may lie on smaller spatial units. This study aimed at testing methodological alternatives to combine RS imagery (geostationary and polar orbit satellites) for the estimation of ET such that the spatial resolution of the final product is improved. In particular, the study consisted in the implementation of two approaches for combining the current ET estimations with RS data containing information over vegetation parameters and captured by polar orbit spaceborne sensors. The first tested approach consisted in forcing the operational ET algorithm with RS measurements obtained from a moderate spatial resolution sensor. The variables with improved spatial resolution were leaf area index and albedo. Other variables of the model remained unchanged with respect to the operational version. In the second approach, a two phases procedure was implemented. Firstly, a preliminary approximation of ET was obtained as a function of solar radiation, air temperature and a vegetation index. The value was then statistically adjusted on the basis of the ET estimations by the operational algorithm. The results of implementing the different approaches were tested against eddy covariance ET derived from measurements in Fluxnet towers spread across Europe and representing different landscape characteristics. The analysis allowed the identification of pros and cons of the tested methodological approaches as well as their performance in different land cover arrangements.

High resolution phoswich gamma-ray imager utilizing monolithic MPPC arrays with submillimeter pixelized crystals

NASA Astrophysics Data System (ADS)

Kato, T.; Kataoka, J.; Nakamori, T.; Kishimoto, A.; Yamamoto, S.; Sato, K.; Ishikawa, Y.; Yamamura, K.; Kawabata, N.; Ikeda, H.; Kamada, K.

2013-05-01

We report the development of a high spatial resolution tweezers-type coincidence gamma-ray camera for medical imaging. This application consists of large-area monolithic Multi-Pixel Photon Counters (MPPCs) and submillimeter pixelized scintillator matrices. The MPPC array has 4 × 4 channels with a three-side buttable, very compact package. For typical operational gain of 7.5 × 105 at + 20 °C, gain fluctuation over the entire MPPC device is only ± 5.6%, and dark count rates (as measured at the 1 p.e. level) amount to <= 400 kcps per channel. We selected Ce-doped (Lu,Y)2(SiO4)O (Ce:LYSO) and a brand-new scintillator, Ce-doped Gd3Al2Ga3O12 (Ce:GAGG) due to their high light yield and density. To improve the spatial resolution, these scintillators were fabricated into 15 × 15 matrices of 0.5 × 0.5 mm2 pixels. The Ce:LYSO and Ce:GAGG scintillator matrices were assembled into phosphor sandwich (phoswich) detectors, and then coupled to the MPPC array along with an acrylic light guide measuring 1 mm thick, and with summing operational amplifiers that compile the signals into four position-encoded analog outputs being used for signal readout. Spatial resolution of 1.1 mm was achieved with the coincidence imaging system using a 22Na point source. These results suggest that the gamma-ray imagers offer excellent potential for applications in high spatial medical imaging.

Io’s volcanoes at high spatial, spectral, and temporal resolution from ground-based observations

NASA Astrophysics Data System (ADS)

de Kleer, Katherine R.; de Pater, Imke

2017-10-01

Io’s dynamic volcanic eruptions provide a laboratory for studying large-scale volcanism on a body vastly different from Earth, and for unraveling the connections between tidal heating and the geological activity it powers. Ground-based near-infrared observatories allow for high-cadence, long-time-baseline observing programs using diverse instrumentation, and yield new information into the nature and variability of this activity. I will summarize results from four years of ground-based observations of Io’s volcanism, including: (1) A multi-year cadence observing campaign using adaptive optics on 8-10 meter telescopes, which places constraints on tidal heating models through sampling the spatial distribution of Io’s volcanic heat flow, and provides estimates of the occurrence rate of Io’s most energetic eruptions; (2) High-spectral-resolution (R~25,000) studies of Io’s volcanic SO gas emission at 1.7 microns, which resolves this rovibronic line into its different branches, and thus contains detailed information on the temperature and thermal state of the gas; and (3) The highest-spatial-resolution map ever produced of the entire Loki Patera, a 20,000 km2 volcanic feature on Io, derived from adaptive-optics observations of an occultation of Io by Europa. The map achieves a spatial resolution of ~10 km and indicates compositional differences across the patera. These datasets both reveal specific characteristics of Io’s individual eruptions, and provide clues into the sub-surface systems connecting Io’s tidally-heated interior to its surface expressions of volcanism.

Optimal arrangements of fiber optic probes to enhance the spatial resolution in depth for 3D reflectance diffuse optical tomography with time-resolved measurements performed with fast-gated single-photon avalanche diodes

NASA Astrophysics Data System (ADS)

Puszka, Agathe; Di Sieno, Laura; Dalla Mora, Alberto; Pifferi, Antonio; Contini, Davide; Boso, Gianluca; Tosi, Alberto; Hervé, Lionel; Planat-Chrétien, Anne; Koenig, Anne; Dinten, Jean-Marc

2014-02-01

Fiber optic probes with a width limited to a few centimeters can enable diffuse optical tomography (DOT) in intern organs like the prostate or facilitate the measurements on extern organs like the breast or the brain. We have recently shown on 2D tomographic images that time-resolved measurements with a large dynamic range obtained with fast-gated single-photon avalanche diodes (SPADs) could push forward the imaged depth range in a diffusive medium at short source-detector separation compared with conventional non-gated approaches. In this work, we confirm these performances with the first 3D tomographic images reconstructed with such a setup and processed with the Mellin- Laplace transform. More precisely, we investigate the performance of hand-held probes with short interfiber distances in terms of spatial resolution and specifically demonstrate the interest of having a compact probe design featuring small source-detector separations. We compare the spatial resolution obtained with two probes having the same design but different scale factors, the first one featuring only interfiber distances of 15 mm and the second one, 10 mm. We evaluate experimentally the spatial resolution obtained with each probe on the setup with fast-gated SPADs for optical phantoms featuring two absorbing inclusions positioned at different depths and conclude on the potential of short source-detector separations for DOT.

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

PubMed

Gangodagamage, Chandana; Rowland, Joel C; Hubbard, Susan S; Brumby, Steven P; Liljedahl, Anna K; Wainwright, Haruko; Wilson, Cathy J; Altmann, Garrett L; Dafflon, Baptiste; Peterson, John; Ulrich, Craig; Tweedie, Craig E; Wullschleger, Stan D

2014-08-01

Landscape attributes that vary with microtopography, such as active layer thickness ( ALT ), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km 2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r 2  = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT , consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

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.

On the Fringe Field of Wide Angle LC Optical Phased Array

NASA Technical Reports Server (NTRS)

Wang, Xighua; Wang, Bin; Bos, Philip J.; Anderson, James E.; Pouch, John; Miranda, Felix; McManamon, Paul F.

2004-01-01

For free space laser communication, light weighted large deployable optics is a critical component for the transmitter. However, such an optical element will introduce large aberrations due to the fact that the surface figure of the large optics is susceptable to deformation in the space environment. We propose to use a high-resolution liquid crystal spatial light modulator to correct for wavefront aberrations introduced by the primary optical element, and to achieve very fine beam steering and shaping at the same time. A 2-D optical phased array (OPA) antenna based on a Liquid Crystal on Silicon (LCOS) spatial light modulator is described. This device offers a combination of low cost, high resolution, high accuracy, high diffraction efficiency at video speed. To quantitatively understand the influence factor of the different design parameters, a computer simulation of the device is given by the 2-D director simulation and the Finite Difference Time domain (FDTD) simulation. For the 1-D OPA, we define the maximum steering angle to have a grating period of 8 pixel/reset scheme; as for larger steering angles than this criterion, the diffraction efficiency drops dramatically. In this case, the diffraction efficiency of 0.86 and the Strehl ratio of 0.9 are obtained in the simulation. The performance of the device in achieving high resolution wavefront correction and beam steering is also characterized experimentally.

Region-of-interest image reconstruction in circular cone-beam microCT

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

Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.

2007-12-15

Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolutionmore » entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.« less

The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland.

PubMed

Wang, Ran; Gamon, John A; Cavender-Bares, Jeannine; Townsend, Philip A; Zygielbaum, Arthur I

2018-03-01

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm 2 to 1 m 2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm 2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods. ©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, T.; Ahmed, M.

2015-12-01

Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.

Future VIIRS enhancements for the integrated polar-orbiting environmental satellite system

NASA Astrophysics Data System (ADS)

Puschell, Jeffery J.; Silny, John; Cook, Lacy; Kim, Eugene

2010-08-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) is the next-generation imaging spectroradiometer for the future operational polar-orbiting environmental satellite system. A successful Flight Unit 1 has been delivered and integrated onto the NPP spacecraft. The flexible VIIRS architecture can be adapted and enhanced to respond to a wide range of requirements and to incorporate new technology as it becomes available. This paper reports on recent design studies to evaluate building a MW-VLWIR dispersive hyperspectral module with active cooling into the existing VIIRS architecture. Performance of a two-grating VIIRS hyperspectral module was studied across a broad trade space defined primarily by spatial sampling, spectral range, spectral sampling interval, along-track field of view and integration time. The hyperspectral module studied here provides contiguous coverage across 3.9 - 15.5 μm with a spectral sampling interval of 10 nm or better, thereby extending VIIRS spectral range to the shortwave side of the 15.5 μm CO2 band and encompassing the 6.7 μm H2O band. Spatial sampling occurs at VIIRS I-band (~0.4 km at nadir) spatial resolution with aggregation to M-band (~0.8 km) and larger pixel sizes to improve sensitivity. Radiometric sensitivity (NEdT) at a spatial resolution of ~4 km is ~0.1 K or better for a 250 K scene across a wavelength range of 4.5 μm to 15.5 μm. The large number of high spectral and spatial resolution FOVs in this instrument improves chances for retrievals of information on the physical state and composition of the atmosphere all the way to the surface in cloudy regions relative to current systems. Spectral aggregation of spatial resolution measurements to MODIS and VIIRS multispectral bands would continue legacy measurements with better sensitivity in nearly all bands. Additional work is needed to optimize spatial sampling, spectral range and spectral sampling approaches for the hyperspectral module and to further refine this powerful imager concept.

Resolution testing and limitations of geodetic and tsunami datasets for finite fault inversions along subduction zones

NASA Astrophysics Data System (ADS)

Williamson, A.; Newman, A. V.

2017-12-01

Finite fault inversions utilizing multiple datasets have become commonplace for large earthquakes pending data availability. The mixture of geodetic datasets such as Global Navigational Satellite Systems (GNSS) and InSAR, seismic waveforms, and when applicable, tsunami waveforms from Deep-Ocean Assessment and Reporting of Tsunami (DART) gauges, provide slightly different observations that when incorporated together lead to a more robust model of fault slip distribution. The merging of different datasets is of particular importance along subduction zones where direct observations of seafloor deformation over the rupture area are extremely limited. Instead, instrumentation measures related ground motion from tens to hundreds of kilometers away. The distance from the event and dataset type can lead to a variable degree of resolution, affecting the ability to accurately model the spatial distribution of slip. This study analyzes the spatial resolution attained individually from geodetic and tsunami datasets as well as in a combined dataset. We constrain the importance of distance between estimated parameters and observed data and how that varies between land-based and open ocean datasets. Analysis focuses on accurately scaled subduction zone synthetic models as well as analysis of the relationship between slip and data in recent large subduction zone earthquakes. This study shows that seafloor deformation sensitive datasets, like open-ocean tsunami waveforms or seafloor geodetic instrumentation, can provide unique offshore resolution for understanding most large and particularly tsunamigenic megathrust earthquake activity. In most environments, we simply lack the capability to resolve static displacements using land-based geodetic observations.

New Possibilities for High-Resolution, Large-Scale Ecosystem Assessment of the World's Semi-Arid Regions

NASA Astrophysics Data System (ADS)

Burney, J. A.; Goldblatt, R.

2016-12-01

Understanding drivers of land use change - and in particular, levels of ecosystem degradation - in semi-arid regions is of critical importance because these agroecosystems (1) are home to the world's poorest populations, almost all of whom depend on agriculture for their livelihoods, (2) play a critical role in the global carbon and climate cycles, and (3) have in many cases seen dramatic changes in temperature and precipitation, relative to global averages, over the past several decades. However, assessing ecosystem health (or, conversely, degradation) presents a difficult measurement problem. Established methods are very labor intensive and rest on detailed questionnaires and field assessments. High-resolution satellite imagery has a unique role semi-arid ecosystem assessment in that it can be used for rapid (or repeated) and very simple measurements of tree and shrub density, an excellent overall indicator for dryland ecosystem health. Because trees and large shrubs are more sparse in semi-arid regions, sub-meter resolution imagery in conjunction with automated image analysis can be used to assess density differences at high spatial resolution without expensive and time-consuming ground-truthing. This could be used down to the farm level, for example, to better assess the larger-scale ecosystem impacts of different management practices, to assess compliance with REDD+ carbon offset protocols, or to evaluate implementation of conservation goals. Here we present results comparing spatial and spectral remote sensing methods for semi-arid ecosystem assessment across new data sources, using the Brazilian Sertão as an example, and the implications for large-scale use in semi-arid ecosystem science.

High spatial resolution grain orientation and strain mapping in thin films using polychromatic submicron x-ray diffraction

NASA Astrophysics Data System (ADS)

Tamura, N.; MacDowell, A. A.; Celestre, R. S.; Padmore, H. A.; Valek, B.; Bravman, J. C.; Spolenak, R.; Brown, W. L.; Marieb, T.; Fujimoto, H.; Batterman, B. W.; Patel, J. R.

2002-05-01

The availability of high brilliance synchrotron sources, coupled with recent progress in achromatic focusing optics and large area two-dimensional detector technology, has allowed us to develop an x-ray synchrotron technique that is capable of mapping orientation and strain/stress in polycrystalline thin films with submicron spatial resolution. To demonstrate the capabilities of this instrument, we have employed it to study the microstructure of aluminum thin film structures at the granular and subgranular levels. Due to the relatively low absorption of x-rays in materials, this technique can be used to study passivated samples, an important advantage over most electron probes given the very different mechanical behavior of buried and unpassivated materials.

Modeling very large-fire occurrences over the continental United States from weather and climate forcing

Treesearch

R Barbero; J T Abatzoglou; E A Steel

2014-01-01

Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡­60 km spatial and weekly temporal resolutions using solely atmospheric...

A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data

Treesearch

B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann

2012-01-01

The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...

Comparison of H-alpha synoptic charts with the large-scale solar magnetic field as observed at Stanford

NASA Technical Reports Server (NTRS)

Duvall, T. L., Jr.; Wilcox, J. M.; Svalgaard, L.; Scherrer, P. H.; Mcintosh, P. S.

1977-01-01

Two methods of observing the neutral line of the large-scale photospheric magnetic field are compared: neutral line positions inferred from H-alpha photographs (McIntosh and Nolte, 1975) and observations of the photospheric magnetic field made with low spatial resolution (three minutes) and high sensitivity using the Stanford magnetograph. The comparison is found to be very favorable.

Cherenkov detectors for spatial imaging applications using discrete-energy photons

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

Rose, Paul B.; Erickson, Anna S., E-mail: erickson@gatech.edu

Cherenkov detectors can offer a significant advantage in spatial imaging applications when excellent timing response, low noise and cross talk, large area coverage, and the ability to operate in magnetic fields are required. We show that an array of Cherenkov detectors with crude energy resolution coupled with monochromatic photons resulting from a low-energy nuclear reaction can be used to produce a sharp image of material while providing large and inexpensive detector coverage. The analysis of the detector response to relative transmission of photons with various energies allows for reconstruction of material's effective atomic number further aiding in high-Z material identification.

PP-SWAT: A phython-based computing software for efficient multiobjective callibration of SWAT

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

An approach for mapping large-area impervious surfaces: Synergistic use of Landsat-7 ETM+ and high spatial resolution imagery

USGS Publications Warehouse

Yang, Limin; Huang, Chengquan; Homer, Collin G.; Wylie, Bruce K.; Coan, Michael

2003-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning, and resource management, require current and accurate geospatial data of urban impervious surfaces. We developed an approach to quantify urban impervious surfaces as a continuous variable by using multisensor and multisource datasets. Subpixel percent impervious surfaces at 30-m resolution were mapped using a regression tree model. The utility, practicality, and affordability of the proposed method for large-area imperviousness mapping were tested over three spatial scales (Sioux Falls, South Dakota, Richmond, Virginia, and the Chesapeake Bay areas of the United States). Average error of predicted versus actual percent impervious surface ranged from 8.8 to 11.4%, with correlation coefficients from 0.82 to 0.91. The approach is being implemented to map impervious surfaces for the entire United States as one of the major components of the circa 2000 national land cover database.

Scale and modeling issues in water resources planning

USGS Publications Warehouse

Lins, H.F.; Wolock, D.M.; McCabe, G.J.

1997-01-01

Resource planners and managers interested in utilizing climate model output as part of their operational activities immediately confront the dilemma of scale discordance. Their functional responsibilities cover relatively small geographical areas and necessarily require data of relatively high spatial resolution. Climate models cover a large geographical, i.e. global, domain and produce data at comparatively low spatial resolution. Although the scale differences between model output and planning input are large, several techniques have been developed for disaggregating climate model output to a scale appropriate for use in water resource planning and management applications. With techniques in hand to reduce the limitations imposed by scale discordance, water resource professionals must now confront a more fundamental constraint on the use of climate models-the inability to produce accurate representations and forecasts of regional climate. Given the current capabilities of climate models, and the likelihood that the uncertainty associated with long-term climate model forecasts will remain high for some years to come, the water resources planning community may find it impractical to utilize such forecasts operationally.

Fiber optic sensing technology for detecting gas hydrate formation and decomposition.

PubMed

Rawn, C J; Leeman, J R; Ulrich, S M; Alford, J E; Phelps, T J; Madden, M E

2011-02-01

A fiber optic-based distributed sensing system (DSS) has been integrated with a large volume (72 l) pressure vessel providing high spatial resolution, time-resolved, 3D measurement of hybrid temperature-strain (TS) values within experimental sediment-gas hydrate systems. Areas of gas hydrate formation (exothermic) and decomposition (endothermic) can be characterized through this proxy by time series analysis of discrete data points collected along the length of optical fibers placed within a sediment system. Data are visualized as an animation of TS values along the length of each fiber over time. Experiments conducted in the Seafloor Process Simulator at Oak Ridge National Laboratory clearly indicate hydrate formation and dissociation events at expected pressure-temperature conditions given the thermodynamics of the CH(4)-H(2)O system. The high spatial resolution achieved with fiber optic technology makes the DSS a useful tool for visualizing time-resolved formation and dissociation of gas hydrates in large-scale sediment experiments.

Fiber optic sensing technology for detecting gas hydrate formation and decomposition

NASA Astrophysics Data System (ADS)

Rawn, C. J.; Leeman, J. R.; Ulrich, S. M.; Alford, J. E.; Phelps, T. J.; Madden, M. E.

2011-02-01

A fiber optic-based distributed sensing system (DSS) has been integrated with a large volume (72 l) pressure vessel providing high spatial resolution, time-resolved, 3D measurement of hybrid temperature-strain (TS) values within experimental sediment-gas hydrate systems. Areas of gas hydrate formation (exothermic) and decomposition (endothermic) can be characterized through this proxy by time series analysis of discrete data points collected along the length of optical fibers placed within a sediment system. Data are visualized as an animation of TS values along the length of each fiber over time. Experiments conducted in the Seafloor Process Simulator at Oak Ridge National Laboratory clearly indicate hydrate formation and dissociation events at expected pressure-temperature conditions given the thermodynamics of the CH4-H2O system. The high spatial resolution achieved with fiber optic technology makes the DSS a useful tool for visualizing time-resolved formation and dissociation of gas hydrates in large-scale sediment experiments.

Large uncertainties in observed daily precipitation extremes over land

NASA Astrophysics Data System (ADS)

Herold, Nicholas; Behrangi, Ali; Alexander, Lisa V.

2017-01-01

We explore uncertainties in observed daily precipitation extremes over the terrestrial tropics and subtropics (50°S-50°N) based on five commonly used products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset, the Global Precipitation Climatology Centre-Full Data Daily (GPCC-FDD) dataset, the Tropical Rainfall Measuring Mission (TRMM) multi-satellite research product (T3B42 v7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Global Precipitation Climatology Project's One-Degree Daily (GPCP-1DD) dataset. We use the precipitation indices R10mm and Rx1day, developed by the Expert Team on Climate Change Detection and Indices, to explore the behavior of "moderate" and "extreme" extremes, respectively. In order to assess the sensitivity of extreme precipitation to different grid sizes we perform our calculations on four common spatial resolutions (0.25° × 0.25°, 1° × 1°, 2.5° × 2.5°, and 3.75° × 2.5°). The impact of the chosen "order of operation" in calculating these indices is also determined. Our results show that moderate extremes are relatively insensitive to product and resolution choice, while extreme extremes can be very sensitive. For example, at 0.25° × 0.25° quasi-global mean Rx1day values vary from 37 mm in PERSIANN-CDR to 62 mm in T3B42. We find that the interproduct spread becomes prominent at resolutions of 1° × 1° and finer, thus establishing a minimum effective resolution at which observational products agree. Without improvements in interproduct spread, these exceedingly large observational uncertainties at high spatial resolution may limit the usefulness of model evaluations. As has been found previously, resolution sensitivity can be largely eliminated by applying an order of operation where indices are calculated prior to regridding. However, this approach is not appropriate when true area averages are desired (e.g., for model evaluations).

An evaluation of semi-automated methods for collecting ecosystem-level data in temperate marine systems.

PubMed

Griffin, Kingsley J; Hedge, Luke H; González-Rivero, Manuel; Hoegh-Guldberg, Ove I; Johnston, Emma L

2017-07-01

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m 2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.

Impact of resolution on aerosol radiative feedbacks with in online-coupled chemistry/climate simulations (WRF-Chem) for EURO-CORDEX compliant domains

NASA Astrophysics Data System (ADS)

López-Romero, Jose Maria; Baró, Rocío; Palacios-Peña, Laura; Jerez, Sonia; Jiménez-Guerrero, Pedro; Montávez, Juan Pedro

2016-04-01

Several studies have shown that a high spatial resolution in atmospheric model runs improves the simulation of some meteorological variables, such as precipitation, particularly extreme events and in regions with complex orography [1]. However, increasing model spatial resolution makes the computational time rise exponentially. Hence, very high resolution experiments on large domains can hamper the execution of climatic runs. This problem shoots up when using online-coupled chemistry climate models, making a careful evaluation of improvements versus costs mandatory. Under this umbrella, the objective of this work is to investigate the sensitivity of aerosol radiative feedbacks from online-coupled chemistry regional model simulations to the spatial resolution. For that, the WRF-Chem [2] model is used for a case study to simulate the episode occurring between July 25th and August 15th of 2010. It is characterized by a high loading of atmospheric aerosol particles coming mainly from wildfires over large European regions (Russia, Iberian Peninsula). Three spatial resolutions are used defined for Euro-Cordex compliant domains [3]: 0.44°, 0.22° and 0.11°. Anthropogenic emissions come from TNO databases [4]. The analysis focuses on air quality variables (mainly PM10, PM2.5), meteorological variables (temperature, radiation) and other aerosol optical properties (aerosol optical depth). The CPU time ratio for the different domains is 1 (0.44°), 4(0.22°) and 28(0.11°) (normalized times). Comparison among simulations and observations are analyzed. Preliminary results show the difficulty to justify the much larger computational cost of high-resolution experiments when comparing with observations from a meteorological point of view, despite the finer spatio-temporal detail of the obtained pollutant fields. [1] Prein, A. F. (2014, December). Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits?. In AGU Fall Meeting Abstracts (Vol. 1, p. 3893). [2] Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., & Eder, B. (2005). Fully coupled "online" chemistry within the WRF model. Atmospheric Environment, 39(37), 6957-6975. [3] Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., ... & Georgopoulou, E. (2014). EURO-CORDEX: new high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563-578. [4] Pouliot, G., Denier van der Gon, H., Kuenen, J., Makar, P., Zhang, J., Moran, M., 2015. Analysis of the emission inventories and model-ready emission datasets of Europe and North America for phase 2 of the AQMEII project. Atmos. Environ. 115, 345-360.

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

Large-area super-resolution optical imaging by using core-shell microfibers

NASA Astrophysics Data System (ADS)

Liu, Cheng-Yang; Lo, Wei-Chieh

2017-09-01

We first numerically and experimentally report large-area super-resolution optical imaging achieved by using core-shell microfibers. The particular spatial electromagnetic waves for different core-shell microfibers are studied by using finite-difference time-domain and ray tracing calculations. The focusing properties of photonic nanojets are evaluated in terms of intensity profile and full width at half-maximum along propagation and transversal directions. In experiment, the general optical fiber is chemically etched down to 6 μm diameter and coated with different metallic thin films by using glancing angle deposition. The direct imaging of photonic nanojets for different core-shell microfibers is performed with a scanning optical microscope system. We show that the intensity distribution of a photonic nanojet is highly related to the metallic shell due to the surface plasmon polaritons. Furthermore, large-area super-resolution optical imaging is performed by using different core-shell microfibers placed over the nano-scale grating with 150 nm line width. The core-shell microfiber-assisted imaging is achieved with super-resolution and hundreds of times the field-of-view in contrast to microspheres. The possible applications of these core-shell optical microfibers include real-time large-area micro-fluidics and nano-structure inspections.

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

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.

Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model

USGS Publications Warehouse

Crimmins, Shawn M.; Walleser, Liza R.; Hertel, Dan R.; McKann, Patrick C.; Rohweder, Jason J.; Thogmartin, Wayne E.

2016-01-01

There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture.

PubMed

Yamamoto, Kyosuke; Togami, Takashi; Yamaguchi, Norio

2017-11-06

Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture-in cooperation with image processing technologies-for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture

PubMed Central

Togami, Takashi; Yamaguchi, Norio

2017-01-01

Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture—in cooperation with image processing technologies—for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis. PMID:29113104

The x-ray light valve: a low-cost, digital radiographic imaging system-spatial resolution

NASA Astrophysics Data System (ADS)

MacDougall, Robert D.; Koprinarov, Ivaylo; Webster, Christie A.; Rowlands, J. A.

2007-03-01

In recent years, new x-ray radiographic systems based on large area flat panel technology have revolutionized our capability to produce digital x-ray radiographic images. However, these active matrix flat panel imagers (AMFPIs) are extraordinarily expensive compared to the systems they are replacing. Thus there is a need for a low cost digital imaging system for general applications in radiology. Different approaches have been considered to make lower cost, integrated x-ray imaging devices for digital radiography, including: scanned projection x-ray, an integrated approach based on computed radiography technology and optically demagnified x-ray screen/CCD systems. These approaches suffer from either high cost or high mechanical complexity and do not have the image quality of AMFPIs. We have identified a new approach - the X-ray Light Valve (XLV). The XLV has the potential to achieve the immediate readout in an integrated system with image quality comparable to AMFPIs. The XLV concept combines three well-established and hence lowcost technologies: an amorphous selenium (a-Se) layer to convert x-rays to image charge, a liquid crystal (LC) cell as an analog display, and an optical scanner for image digitization. Here we investigate the spatial resolution possible with XLV systems. Both a-Se and LC cells have both been shown separately to have inherently very high spatial resolution. Due to the close electrostatic coupling in the XLV, it can be expected that the spatial resolution of this system will also be very high. A prototype XLV was made and a typical office scanner was used for image digitization. The Modulation Transfer Function was measured and the limiting factor was seen to be the optical scanner. However, even with this limitation the XLV system is able to meet or exceed the resolution requirements for chest radiography.

Visualization and Quality Control Web Tools for CERES Products

NASA Astrophysics Data System (ADS)

Mitrescu, C.; Doelling, D.; Chu, C.; Mlynczak, P.

2014-12-01

The CERES project continues to provide the scientific community a wide variety of satellite-derived data products. The flagship products TOA broadband shortwave and longwave observed fluxes, computed TOA and Surface fluxes, as well as cloud, aerosol, and other atmospheric parameters. These datasets encompass a wide range of temporal and spatial resolutions, suited to specific applications. We thus offer time resolutions that range from instantaneous to monthly means, with spatial resolutions that range from 20-km footprint to global scales. The 14-year record is mostly used by climate modeling communities that focus on global mean energetics, meridianal heat transport, and climate trend studies. CERES products are also used by the remote sensing community for their climatological studies. In the last years however, our CERES products had been used by an even broader audience, like the green energy, health and environmental research communities, and others. Because of that, the CERES project has implemented a now well-established web-oriented Ordering and Visualization Tool (OVT), which is well into its fifth year of development. In order to help facilitate a comprehensive quality control of CERES products, the OVT Team began introducing a series of specialized functions. These include the 1- and 2-D histogram, anomaly, deseasonalization, temporal and spatial averaging, side-by-side parameter comparison, and other specialized scientific application capabilities. Over time increasingly higher order temporal and spatial resolution products are being made available to the public through the CERES OVT. These high-resolution products require accessing the existing long-term archive - thus the reading of many very large netCDF or HDF files that pose a real challenge to the task of near instantaneous visualization. An overview of the CERES OVT basic functions and QC capabilities as well as future steps in expanding its capabilities will be presented at the meeting.

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography.

PubMed

Muller, Leah; Hamilton, Liberty S; Edwards, Erik; Bouchard, Kristofer E; Chang, Edward F

2016-10-01

Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography

NASA Astrophysics Data System (ADS)

Muller, Leah; Hamilton, Liberty S.; Edwards, Erik; Bouchard, Kristofer E.; Chang, Edward F.

2016-10-01

Objective. Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Simulation of semi-arid hydrological processes at different spatial resolutions using the AgroEcoSystem-Watershed (AgES-W) model

NASA Astrophysics Data System (ADS)

Green, T. R.; Erksine, R. H.; David, O.; Ascough, J. C., II; Kipka, H.; Lloyd, W. J.; McMaster, G. S.

2015-12-01

Water movement and storage within a watershed may be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Here, effects of HRU size on simulated soil water and surface runoff are tested using the AgroEcoSystem-Watershed (AgES-W) model with three different resolutions of HRUs. We studied a 56-ha agricultural watershed in northern Colorado, USA farmed primarily under a wheat-fallow rotation. The delineation algorithm was based upon topography (surface flow paths), land use (crop management strips and native grass), and mapped soil units (three types), which produced HRUs that follow the land use and soil boundaries. AgES-W model parameters that control surface and subsurface hydrology were calibrated using simulated daily soil moisture at different landscape positions and depths where soil moisture was measured hourly and averaged up to daily values. Parameter sets were both uniform and spatially variable with depth and across the watershed (5 different calibration approaches). Although forward simulations were computationally efficient (less than 1 minute each), each calibration required thousands of model runs. Execution of such large jobs was facilitated by using the Object Modeling System with the Cloud Services Innovation Platform to manage four virtual machines on a commercial web service configured with a total of 64 computational cores and 120 GB of memory. Results show how spatially distributed and averaged soil moisture and runoff at the outlet vary with different HRU delineations. The results will help guide HRU delineation, spatial resolution and parameter estimation methods for improved hydrological simulations in this and other semi-arid agricultural watersheds.

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.

Study of Structure and Small-Scale Fragmentation in TMC-1

NASA Technical Reports Server (NTRS)

Langer, W. D.; Velusamy, T.; Kuiper, T. B.; Levin, S.; Olsen, E.; Migenes, V.

1995-01-01

Large-scale C(sup 18)O maps show that the Taurus molecular cloud 1 (TMC-1) has numerous cores located along a ridge which extends about 12 minutes by at least 35 minutes. The cores traced by C(sup 18)O are about a few arcminutes (0.1-0.2 pc) in extent, typically contain about 0.5-3 solar mass, and are probably gravitationally bound. We present a detailed study of the small-scale fragmentary structure of one of these cores, called core D, within TMC-1 using very high spectral and spatial resolution maps of CCS and CS. The CCS lines are excellent tracers for investigating the density, temperature, and velocity structure in dense cores. The high spectral resolution, 0.008 km /s, data consist mainly of single-dish, Nyquist-sampled maps of CCS at 22 GHz with 45 sec spatial resolution taken with NASA's 70 m DSN antenna at Goldstone. The high spatial resolution spectral line maps were made with the Very Large Array (9 sec resolution) at 22 GHz and with the OVRO millimeter array in CCS and CS at 93 GHz and 98 GHz, respectively, with 6 sec resolution. These maps are supplemented with single-dish observations of CCS and CC(sup 34)S spectra at 33 GHz using a NASA 34 m DSN antenna, CCS 93 GHz, C(sup 34)S (2-1), and C(sup 18)O (1-0) single-dish observations made with the AT&T Bell Laboratories 7 m antenna. Our high spectral and spatial CCS and CS maps show that core D is highly fragmented. The single-dish CCS observations map out several clumps which range in size from approx. 45 sec to 90 sec (0.03-0.06 pc). These clumps have very narrow intrinsic line widths, 0.11-0.25 km/s, slightly larger than the thermal line width for CCS at 10 K, and masses about 0.03-0.2 solar mass. Interferometer observations of some of these clumps show that they have considerable additional internal structure, consisting of several condensations ranging in size from approx. 10 sec- 30 sec (0.007-0.021 pc), also with narrow line widths. The mass of these smallest fragments is of order 0.01 solar mass. These small-scale structures traced by CCS appear to be gravitationally unbound by a large factor. Most of these objects have masses that fall below those of the putative proto-brown dwarfs (approx. less than 0.1 solar mass). The presence of many small gravitationally unbound clumps suggests that fragmentation mechanisms other than a purely Jeans gravitational instability may be important for the dynamics of these cold dense cores.

Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

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

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary

2006-01-01

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Utilising Structure-From-Motion Approaches to Develop a Spatial Understanding of Soil Erosion Processes, in an Experimental Setting.

NASA Astrophysics Data System (ADS)

Benaud, P.; Anderson, K.; Quine, T. A.; James, M. R.; Quinton, J.; Brazier, R. E.

2016-12-01

While total sediment capture can accurately quantify soil loss via water erosion, it isn't practical at the field scale and provides little information on the spatial nature of soil erosion processes. Consequently, high-resolution, remote sensing, point cloud data provide an alternative method for quantifying soil loss. The accessibility of Structure-from-Motion Multi-Stereo View (SfM) and the potential for multi-temporal applications, offers an exciting opportunity to spatially quantify soil erosion. Accordingly, published research provides examples of the successful quantification of large erosion features and events, to centimetre accuracy. Through rigorous control of the camera and image network geometry, the centimetre accuracy achievable at the field scale, can translate to sub-millimetre accuracies within a laboratory environment. Accordingly, this study looks to understand how the ultra-high-resolution spatial information on soil surface topography, derived from SfM, can be integrated with a multi-element sediment tracer to develop a mechanistic understanding of rill and inter-rill erosion, under experimental conditions. A rainfall simulator was used to create three soil surface conditions; compaction and rainsplash, inter-rill erosion, and rill erosion, at two experimental scales (0.15 m2 and 3 m2). Total sediment capture was the primary validation for the experiments, allowing the comparison between structurally and volumetrically derived change, and true soil loss. A Terrestrial Laser Scanner (resolution of ca. 0.8mm) has been employed to assess spatial discrepancies within the SfM data sets and to provide an alternative measure of volumetric change. Preliminary results show the SfM approach used can achieve a ground resolution of less than 0.2 mm per pixel, and a RMSE of less than 0.3 mm. Consequently, it is expected that the ultra-high-resolution SfM point clouds can be utilised to provide a detailed assessment of soil loss via water erosion processes.

Simulating air quality in the Netherlands with WRF-Chem 3.8.1 at high resolution

NASA Astrophysics Data System (ADS)

Hilboll, Andreas; Kuenen, Jeroen; Denier van der Gon, Hugo; Vrekoussis, Mihalis

2017-04-01

Air pollution is the single most important environmental hazard for public health. Especially nitrogen dioxide (NO(2)) plays a key role in air quality research, both due to its immediate importance for the production of tropospheric ozone and acid rain, and as a general indicator of fossil fuel burning. To improve the quality and reproducibility of measurements of NO(2) vertical distribution from MAX-DOAS instruments, the CINDI-2 campaign was held in Cabauw (NL) in September 2016, featuring instruments from many of the leading atmospheric research institutions in the world. The measurement site in Cabauw is located in a rather rural region, surrounded by several major pollution centers (Utrecht, Rotterdam, Amsterdam). Since the instruments measure in several azimuthal directions, the measurements are able to provide information about the high spatial and temporal variability in pollutant concentrations, caused by both the spatial heterogeneity of emissions and meteorological conditions. When using air quality models in the analysis of the measured data to identify pollution sources, this mandates high spatial resolution in order to resolve the expected fine spatial structure in NO(2) concentrations. In spite of constant advances in computing power, this remains a challenge, mostly due to the uncertainties and large spatial heterogeneity of emissions and the need to parameterize small-scale processes. In this study, we use the most recent version 3.8.1 of the Weather Research and Forecasting Model with Chemistry (WRF-Chem) to simulate air pollutant concentrations over the Netherlands, to facilitate the analysis of the CINDI-2 NO(2}) measurements. The model setup contains three nested domains with horizontal resolutions of 15, 3, and 1 km. Anthropogenic emissions are taken from the TNO-MACC III inventory and, where available, from the Dutch Pollutant Release and Transfer Register (Emissieregistratie), at a spatial resolution of 7 and 1 km, respectively. We use the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) with the MOSAIC aerosol module. The high spatial resolution of model and emissions will allow us to resolve the strong spatial gradients in the NO(2) concentrations measured during the CINDI-2 campaign, allowing for an unprecedented level of detail in the analysis of individual pollution sources.

Resolution requirements for aero-optical simulations

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

Mani, Ali; Wang Meng; Moin, Parviz

2008-11-10

Analytical criteria are developed to estimate the error of aero-optical computations due to inadequate spatial resolution of refractive index fields in high Reynolds number flow simulations. The unresolved turbulence structures are assumed to be locally isotropic and at low turbulent Mach number. Based on the Kolmogorov spectrum for the unresolved structures, the computational error of the optical path length is estimated and linked to the resulting error in the computed far-field optical irradiance. It is shown that in the high Reynolds number limit, for a given geometry and Mach number, the spatial resolution required to capture aero-optics within a pre-specifiedmore » error margin does not scale with Reynolds number. In typical aero-optical applications this resolution requirement is much lower than the resolution required for direct numerical simulation, and therefore, a typical large-eddy simulation can capture the aero-optical effects. The analysis is extended to complex turbulent flow simulations in which non-uniform grid spacings are used to better resolve the local turbulence structures. As a demonstration, the analysis is used to estimate the error of aero-optical computation for an optical beam passing through turbulent wake of flow over a cylinder.« less

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

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.

Application of Unmanned Aerial Systems in Spatial Downscaling of Landsat VIR imageries of Agricultural Fields

NASA Astrophysics Data System (ADS)

Torres, A.; Hassan Esfahani, L.; Ebtehaj, A.; McKee, M.

2016-12-01

While coarse space-time resolution of satellite observations in visible to near infrared (VIR) is a serious limiting factor for applications in precision agriculture, high resolution remotes sensing observation by the Unmanned Aerial Systems (UAS) systems are also site-specific and still practically restrictive for widespread applications in precision agriculture. We present a modern spatial downscaling approach that relies on new sparse approximation techniques. The downscaling approach learns from a large set of coincident low- and high-resolution satellite and UAS observations to effectively downscale the satellite imageries in VIR bands. We focus on field experiments using the AggieAirTM platform and Landsat 7 ETM+ and Landsat 8 OLI observations obtained in an intensive field campaign in 2013 over an agriculture field in Scipio, Utah. The results show that the downscaling methods can effectively increase the resolution of Landsat VIR imageries by the order of 2 to 4 from 30 m to 15 and 7.5 m, respectively. Specifically, on average, the downscaling method reduces the root mean squared errors up to 26%, considering bias corrected AggieAir imageries as the reference.

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.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

On the analysis of time-of-flight spin-echo modulated dark-field imaging data

NASA Astrophysics Data System (ADS)

Sales, Morten; Plomp, Jeroen; Bouwman, Wim G.; Tremsin, Anton S.; Habicht, Klaus; Strobl, Markus

2017-06-01

Spin-Echo Modulated Small Angle Neutron Scattering with spatial resolution, i.e. quantitative Spin-Echo Dark Field Imaging, is an emerging technique coupling neutron imaging with spatially resolved quantitative small angle scattering information. However, the currently achieved relatively large modulation periods of the order of millimeters are superimposed to the images of the samples. So far this required an independent reduction and analyses of the image and scattering information encoded in the measured data and is involving extensive curve fitting routines. Apart from requiring a priori decisions potentially limiting the information content that is extractable also a straightforward judgment of the data quality and information content is hindered. In contrast we propose a significantly simplified routine directly applied to the measured data, which does not only allow an immediate first assessment of data quality and delaying decisions on potentially information content limiting further reduction steps to a later and better informed state, but also, as results suggest, generally better analyses. In addition the method enables to drop the spatial resolution detector requirement for non-spatially resolved Spin-Echo Modulated Small Angle Neutron Scattering.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

A 3D imaging system integrating photoacoustic and fluorescence orthogonal projections for anatomical, functional and molecular assessment of rodent models

NASA Astrophysics Data System (ADS)

Brecht, Hans P.; Ivanov, Vassili; Dumani, Diego S.; Emelianov, Stanislav Y.; Anastasio, Mark A.; Ermilov, Sergey A.

2018-03-01

We have developed a preclinical 3D imaging instrument integrating photoacoustic tomography and fluorescence (PAFT) addressing known deficiencies in sensitivity and spatial resolution of the individual imaging components. PAFT is designed for simultaneous acquisition of photoacoustic and fluorescence orthogonal projections at each rotational position of a biological object, enabling direct registration of the two imaging modalities. Orthogonal photoacoustic projections are utilized to reconstruct large (21 cm3 ) volumes showing vascularized anatomical structures and regions of induced optical contrast with spatial resolution exceeding 100 µm. The major advantage of orthogonal fluorescence projections is significant reduction of background noise associated with transmitted or backscattered photons. The fluorescence imaging component of PAFT is used to boost detection sensitivity by providing low-resolution spatial constraint for the fluorescent biomarkers. PAFT performance characteristics were assessed by imaging optical and fluorescent contrast agents in tissue mimicking phantoms and in vivo. The proposed PAFT technology will enable functional and molecular volumetric imaging using fluorescent biomarkers, nanoparticles, and other photosensitive constructs mapped with high fidelity over robust anatomical structures, such as skin, central and peripheral vasculature, and internal organs.

Real-time and sub-wavelength ultrafast coherent diffraction imaging in the extreme ultraviolet.

PubMed

Zürch, M; Rothhardt, J; Hädrich, S; Demmler, S; Krebs, M; Limpert, J; Tünnermann, A; Guggenmos, A; Kleineberg, U; Spielmann, C

2014-12-08

Coherent Diffraction Imaging is a technique to study matter with nanometer-scale spatial resolution based on coherent illumination of the sample with hard X-ray, soft X-ray or extreme ultraviolet light delivered from synchrotrons or more recently X-ray Free-Electron Lasers. This robust technique simultaneously allows quantitative amplitude and phase contrast imaging. Laser-driven high harmonic generation XUV-sources allow table-top realizations. However, the low conversion efficiency of lab-based sources imposes either a large scale laser system or long exposure times, preventing many applications. Here we present a lensless imaging experiment combining a high numerical aperture (NA = 0.8) setup with a high average power fibre laser driven high harmonic source. The high flux and narrow-band harmonic line at 33.2 nm enables either sub-wavelength spatial resolution close to the Abbe limit (Δr = 0.8λ) for long exposure time, or sub-70 nm imaging in less than one second. The unprecedented high spatial resolution, compactness of the setup together with the real-time capability paves the way for a plethora of applications in fundamental and life sciences.

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.

Scale criticality in estimating ecosystem carbon dynamics

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang

2014-01-01

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km2) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to An (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

ALMA Observations of Dust Polarization and Molecular Line Emission from the Class 0 Protostellar Source Serpens SMM1

NASA Astrophysics Data System (ADS)

Hull, Charles L. H.; Girart, Josep M.; Tychoniec, Łukasz; Rao, Ramprasad; Cortés, Paulo C.; Pokhrel, Riwaj; Zhang, Qizhou; Houde, Martin; Dunham, Michael M.; Kristensen, Lars E.; Lai, Shih-Ping; Li, Zhi-Yun; Plambeck, Richard L.

2017-10-01

We present high angular resolution dust polarization and molecular line observations carried out with the Atacama Large Millimeter/submillimeter Array (ALMA) toward the Class 0 protostar Serpens SMM1. By complementing these observations with new polarization observations from the Submillimeter Array (SMA) and archival data from the Combined Array for Research in Millimeter-wave Astronomy (CARMA) and the James Clerk Maxwell Telescopes (JCMT), we can compare the magnetic field orientations at different spatial scales. We find major changes in the magnetic field orientation between large (˜0.1 pc) scales—where the magnetic field is oriented E-W, perpendicular to the major axis of the dusty filament where SMM1 is embedded—and the intermediate and small scales probed by CARMA (˜1000 au resolution), the SMA (˜350 au resolution), and ALMA (˜140 au resolution). The ALMA maps reveal that the redshifted lobe of the bipolar outflow is shaping the magnetic field in SMM1 on the southeast side of the source; however, on the northwestern side and elsewhere in the source, low-velocity shocks may be causing the observed chaotic magnetic field pattern. High-spatial-resolution continuum and spectral-line observations also reveal a tight (˜130 au) protobinary system in SMM1-b, the eastern component of which is launching an extremely high-velocity, one-sided jet visible in both {CO}(J=2\\to 1) and {SiO}(J=5\\to 4); however, that jet does not appear to be shaping the magnetic field. These observations show that with the sensitivity and resolution of ALMA, we can now begin to understand the role that feedback (e.g., from protostellar outflows) plays in shaping the magnetic field in very young, star-forming sources like SMM1.

Analysis of terrestrial conditions and dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N. (Principal Investigator)

1984-01-01

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

The Earth Viewed as a Deforming Polyhedron: Method and Results

NASA Technical Reports Server (NTRS)

Blewitt, G.; Heflin, M. B.; Vigue, Y.; Zumberge, J. F.; Jefferson, D.; Webb, F. H.

1993-01-01

GPS is quite unlike any other geodetic technique, because we can use it to look at the Earth with high spatial and temporal resolution. For example, the GPS global network provides us with a daily snapshot of the Earth, allowing us to look with high temporal resolution at the motion of sites before, during, and after a large earthquake.The main focus of this paper is to view the Earth as an evolving polyhedron, whose vertices are defined by the GPS sites.

Initial Data of Digital Correlation ECE with a Giga Hertz Sampling Digitizer

NASA Astrophysics Data System (ADS)

Tsuchiya, Hayato; Inagaki, Shigeru; Tokuzawa, Tokihiko; Nagayama, Yoshio

2015-03-01

The proposed Digital Correlation ECE (DCECE) technique is applied in Large Helical Device. DCECE is realized by the use of the Giga Hertz Sampling Digitizer. The waveform of intermediate frequency band of ECE, whose frequency is several giga hertz, can be discretized and saved directly. The discretized IF data can be used for the analysis of correlation ECE with arbitrary parameter of spatial resolution and temporal resolution. In this paper, the characteristic of DCECE and initial Data in LHD is introduced.

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

Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica

Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOVmore » ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.« less

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.

An imaging vector magnetograph for the next solar maximum

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; Mickey, Donald L.

1988-01-01

Measurements of the vector magnetic field in the solar atmosphere with high spatial and temporal resolution over a large field of view are critical to understanding the nature and evolution of currents in active regions. Such measurements, when combined with the thermal and nonthermal X-ray images from the upcoming Solar-A mission, will reveal the large-scale relationship between these currents and sites of heating and particle acceleration in flaring coronal magnetic flux tubes. The conceptual design of an imaging vector magnetograph that combines a modest solar telescope with a rotating quarter-wave plate, an acousto-optical tunable prefilter as a blocker for a servo-controlled Fabry-Perot etalon, CCD cameras, and a rapid digital tape recorder are described. Its high spatial resolution (1/2 arcsec pixel size) over a large field of view (4 x 5 arcmin) will be sufficient to significantly measure, for the first time, the magnetic energy dissipated in major solar flares. Its millisecond tunability and wide spectra range (5000 to 8000 A) enable nearly simultaneous vector magnetic field measurements in the gas-pressure-dominated photosphere and magnetically dominated chromosphere, as well as effective co-alignment with Solar-A's X-ray images.

Twenty-four-micrometer-pitch microelectrode array with 6912-channel readout at 12 kHz via highly scalable implementation for high-spatial-resolution mapping of action potentials.

PubMed

Ogi, Jun; Kato, Yuri; Matoba, Yoshihisa; Yamane, Chigusa; Nagahata, Kazunori; Nakashima, Yusaku; Kishimoto, Takuya; Hashimoto, Shigeki; Maari, Koichi; Oike, Yusuke; Ezaki, Takayuki

2017-12-19

A 24-μm-pitch microelectrode array (MEA) with 6912 readout channels at 12 kHz and 23.2-μV rms random noise is presented. The aim is to reduce noise in a "highly scalable" MEA with a complementary metal-oxide-semiconductor integration circuit (CMOS-MEA), in which a large number of readout channels and a high electrode density can be expected. Despite the small dimension and the simplicity of the in-pixel circuit for the high electrode-density and the relatively large number of readout channels of the prototype CMOS-MEA chip developed in this work, the noise within the chip is successfully reduced to less than half that reported in a previous work, for a device with similar in-pixel circuit simplicity and a large number of readout channels. Further, the action potential was clearly observed on cardiomyocytes using the CMOS-MEA. These results indicate the high-scalability of the CMOS-MEA. The highly scalable CMOS-MEA provides high-spatial-resolution mapping of cell action potentials, and the mapping can aid understanding of complex activities in cells, including neuron network activities.

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

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Design Studies of a CZT-based Detector Combined with a Pixel-Geometry-Matching Collimator for SPECT Imaging.

PubMed

Weng, Fenghua; Bagchi, Srijeeta; Huang, Qiu; Seo, Youngho

2013-10-01

Single Photon Emission Computed Tomography (SPECT) suffers limited efficiency due to the need for collimators. Collimator properties largely decide the data statistics and image quality. Various materials and configurations of collimators have been investigated in many years. The main thrust of our study is to evaluate the design of pixel-geometry-matching collimators to investigate their potential performances using Geant4 Monte Carlo simulations. Here, a pixel-geometry-matching collimator is defined as a collimator which is divided into the same number of pixels as the detector's and the center of each pixel in the collimator is a one-to-one correspondence to that in the detector. The detector is made of Cadmium Zinc Telluride (CZT), which is one of the most promising materials for applications to detect hard X-rays and γ -rays due to its ability to obtain good energy resolution and high light output at room temperature. For our current project, we have designed a large-area, CZT-based gamma camera (20.192 cm×20.192 cm) with a small pixel pitch (1.60 mm). The detector is pixelated and hence the intrinsic resolution can be as small as the size of the pixel. Materials of collimator, collimator hole geometry, detection efficiency, and spatial resolution of the CZT detector combined with the pixel-matching collimator were calculated and analyzed under different conditions. From the simulation studies, we found that such a camera using rectangular holes has promising imaging characteristics in terms of spatial resolution, detection efficiency, and energy resolution.

Comparing long-term geomorphic model outcomes with sediment archives highlights the need for high-resolution Holocene land cover reconstructions

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert

2013-04-01

During the last decade, several global land cover reconstructions have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models potentially allows to estimate the anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, current land cover reconstructions face some drawbacks. First of all, their low spatial resolution (i.e. 5 arc-minutes at best) questions their use in geomorphic models, as sub-catchment vegetation patterns play an important role in sediment dynamics. Existing global land cover reconstructions also do not differentiate the typology of human impact (cropland, grazing land, disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. Finally, the various land cover reconstructions differ significantly regarding the estimated intensity of human impact for the preindustrial period. In this study, we assessed the performance of a spatially distributed erosion and sediment redistribution model that operates at high resolution (100 m) to the quality and spatial resolution of input land cover maps. This was done through a comparison of two sets of model runs. Firstly, low-resolution land cover (expressed as percentage of non-natural vegetation) maps were resampled to a spatial resolution of 100 m without differentiation of non-natural vegetation types. For the second set of model runs, estimated non-natural vegetation was differentiated in areas of cropland and grassland, and spatially allocated to a high-resolution grid (100 m) using a logistic model that relates contemporary land cover classes to slope, soil characteristics, landforms and distance to rivers. For both land cover maps, different scenarios for the ratio between cropland and grassland were simulated. Analyses were performed for several time periods throughout the Holocene, for the Scheldt River Basin (19,000 km2) in Belgium and northern France. Results indicate that low-resolution land cover information, regardless of the considered cropland/grassland ratio, leads to largely overestimated sediment fluxes when compared to field-based sediment budgets. Allocation of land cover to a higher spatial resolution yields far better results. Variations in model outcomes are related to differences in landscape connectivity between allocated and non-allocated land cover. These results point towards the need for higher-resolution land cover maps that incorporate the patchiness of vegetation at relevant scales regarding geomorphic processes. Also, model results with allocated and non-allocated land cover maps differ greatly for different cropland/grassland ratios. This indicates that there is not only a need for land cover reconstructions at high spatial resolution, but also that differentiation between cropland and grassland is essential for accurate geomorphic modeling. Further improvements in land cover reconstructions are thus needed before reliable quantitative estimates of anthropogenic impact on soil profiles and sediment redistribution can be simulated at continental scales. Detailed historic sediment budgets can provide an important tool not only for validating but also for reconstructing land cover histories.

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

Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

Effects of image spatial and radiometric resolutions on the detection of cotton plants

USDA-ARS?s Scientific Manuscript database

Accurate and timely detection of volunteer and regrowth cotton plants is important for the eradication of boll weevils in south Texas. Airborne remote sensing imagery has the potential to identify volunteer and regrowth cotton plants over large geographic regions. The objective of this study was to ...

: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”

EPA Science Inventory

Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...

Tracking MODIS NDVI time series to estimate fuel accumulation

Treesearch

Kellie A. Uyeda; Douglas A. Stow; Philip J. Riggan

2015-01-01

Patterns of post-fire recovery in southern California chaparral shrublands are important for understanding fuel available for future fires. Satellite remote sensing provides an opportunity to examine these patterns over large spatial extents and at high temporal resolution. The relatively limited temporal range of satellite remote sensing products has previously...

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

StePS: Stereographically Projected Cosmological Simulations

NASA Astrophysics Data System (ADS)

Rácz, Gábor; Szapudi, István; Csabai, István; Dobos, László

2018-05-01

StePS (Stereographically Projected Cosmological Simulations) compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to simulate the evolution of the large-scale structure. This eliminates the need for periodic boundary conditions, which are a numerical convenience unsupported by observation and which modifies the law of force on large scales in an unrealistic fashion. StePS uses stereographic projection for space compactification and naive O(N2) force calculation; this arrives at a correlation function of the same quality more quickly than standard (tree or P3M) algorithms with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence StePS can function as a high-speed prediction tool for modern large-scale surveys.

Optimization of the Performance of Segmented Scintillators for Radiotherapy Imaging through Novel Binning Techniques

PubMed Central

El-Mohri, Youcef; Antonuk, Larry E.; Choroszucha, Richard B.; Zhao, Qihua; Jiang, Hao; Liu, Langechuan

2014-01-01

Thick, segmented crystalline scintillators have shown increasing promise as replacement x-ray converters for the phosphor screens currently used in active matrix flat-panel imagers (AMFPIs) in radiotherapy, by virtue of providing over an order of magnitude improvement in the DQE. However, element-to-element misalignment in current segmented scintillator prototypes creates a challenge for optimal registration with underlying AMFPI arrays, resulting in degradation of spatial resolution. To overcome this challenge, a methodology involving the use of a relatively high resolution AMFPI array in combination with novel binning techniques is presented. The array, which has a pixel pitch of 0.127 mm, was coupled to prototype segmented scintillators based on BGO, LYSO and CsI:Tl materials, each having a nominal element-to-element pitch of 1.016 mm and thickness of ~1 cm. The AMFPI systems incorporating these prototypes were characterized at a radiotherapy energy of 6 MV in terms of MTF, NPS, DQE, and reconstructed images of a resolution phantom acquired using a cone-beam CT geometry. For each prototype, the application of 8×8 pixel binning to achieve a sampling pitch of 1.016 mm was optimized through use of an alignment metric which minimized misregistration and thereby improved spatial resolution. In addition, the application of alternative binning techniques that exclude the collection of signal near septal walls resulted in further significant improvement in spatial resolution for the BGO and LYSO prototypes, though not for the CsI:Tl prototype due to the large amount of optical cross-talk resulting from significant light spread between scintillator elements in that device. The efficacy of these techniques for improving spatial resolution appears to be enhanced for scintillator materials that exhibit mechanical hardness, high density and high refractive index, such as BGO. Moreover, materials that exhibit these properties as well as offer significantly higher light output than BGO, such as CdWO4, should provide the additional benefit of preserving DQE performance. PMID:24487347

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

PubMed Central

Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

Development of a Dual-PIV system for high-speed flow applications

NASA Astrophysics Data System (ADS)

Schreyer, Anne-Marie; Lasserre, Jean J.; Dupont, Pierre

2015-10-01

A new Dual-particle image velocimetry (Dual-PIV) system for application in supersonic flows was developed. The system was designed for shock wave/turbulent boundary layer interactions with separation. This type of flow places demanding requirements on the system, from the large range of characteristic frequencies O(100 Hz-100 kHz) to spatial and temporal resolutions necessary for the measurement of turbulent quantities (Dolling in AIAA J 39(8):1517-1531, 2001; Dupont et al. in J Fluid Mech 559:255-277, 2006; Smits and Dussauge in Turbulent shear layers in supersonic flow, 2nd edn. Springer, New York, 2006). While classic PIV systems using high-resolution CCD sensors allow high spatial resolution, these systems cannot provide the required temporal resolution. Existing high-speed PIV systems provide temporal and CMOS sensor resolutions, and even laser pulse energies, that are not adapted to our needs. The only obvious solution allowing sufficiently high spatial resolution, access to high frequencies, and a high laser pulse energy is a multi-frame system: a Dual-PIV system, consisting of two synchronized PIV systems observing the same field of view, will give access to temporal characteristics of the flow. The key technology of our system is frequency-based image separation: two lasers of different wavelengths illuminate the field of view. The cross-pollution with laser light from the respective other branches was quantified during system validation. The overall system noise was quantified, and the prevailing error of only 2 % reflects the good spatial and temporal alignment. The quality of the measurement system is demonstrated with some results on a subsonic jet flow including the spatio-temporal inter-correlation functions between the systems. First measurements in a turbulent flat-plate boundary layer at Mach 2 show the same satisfactory data quality and are also presented and discussed.

[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.

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

UAS applications in high alpine, snow-covered terrain

NASA Astrophysics Data System (ADS)

Bühler, Y.; Stoffel, A.; Ginzler, C.

2017-12-01

Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology research.

Monitoring Forest Degradation for a Case Study in Cambodia: Comparison of Landsat 8 and Sentinel-2 Imagery

NASA Astrophysics Data System (ADS)

Langner, Andreas; Miettinen, Jukka; Stibig, Hans-Jurgen

2016-08-01

We use a Normalized Burned Ratio (NBR) differential approach for detecting forest canopy disturbance caused by selective logging in evergreen tropical moist forests of central Cambodia. The general disturbance pattern obtained from Landsat 8 (30 m) imagery is largely compatible to Sentinel-2 (10 m), showing good conformity to high resolution RapidEye reference data. However, the 10 m spatial resolution of Sentinel-2 provides notably higher spatial detail and purer pixel values, increasing the potential for detecting fine and subtle forest canopy changes as indicators for potential forest degradation. We can expect further improvement for detecting short-lived disturbance signals in tropical forest canopies due to an increased revisit frequency (5 days) after the Sentinel-2B launch.

Hartmann characterization of the PEEM-3 aberration-corrected X-ray photoemission electron microscope.

PubMed

Scholl, A; Marcus, M A; Doran, A; Nasiatka, J R; Young, A T; MacDowell, A A; Streubel, R; Kent, N; Feng, J; Wan, W; Padmore, H A

2018-05-01

Aberration correction by an electron mirror dramatically improves the spatial resolution and transmission of photoemission electron microscopes. We will review the performance of the recently installed aberration corrector of the X-ray Photoemission Electron Microscope PEEM-3 and show a large improvement in the efficiency of the electron optics. Hartmann testing is introduced as a quantitative method to measure the geometrical aberrations of a cathode lens electron microscope. We find that aberration correction leads to an order of magnitude reduction of the spherical aberrations, suggesting that a spatial resolution of below 100 nm is possible at 100% transmission of the optics when using x-rays. We demonstrate this improved performance by imaging test patterns employing element and magnetic contrast. Published by Elsevier B.V.

Simulation of heat and mass transfer in turbulent channel flow using the spectral-element method: effect of spatial resolution

NASA Astrophysics Data System (ADS)

Ryzhenkov, V.; Ivashchenko, V.; Vinuesa, R.; Mullyadzhanov, R.

2016-10-01

We use the open-source code nek5000 to assess the accuracy of high-order spectral element large-eddy simulations (LES) of a turbulent channel flow depending on the spatial resolution compared to the direct numerical simulation (DNS). The Reynolds number Re = 6800 is considered based on the bulk velocity and half-width of the channel. The filtered governing equations are closed with the dynamic Smagorinsky model for subgrid stresses and heat flux. The results show very good agreement between LES and DNS for time-averaged velocity and temperature profiles and their fluctuations. Even the coarse LES grid which contains around 30 times less points than the DNS one provided predictions of the friction velocity within 2.0% accuracy interval.

Distributed temperature and strain discrimination with stimulated brillouin scattering and rayleigh backscatter in an optical fiber.

PubMed

Zhou, Da-Peng; Li, Wenhai; Chen, Liang; Bao, Xiaoyi

2013-01-31

A distributed optical fiber sensor with the capability of simultaneously measuring temperature and strain is proposed using a large effective area non-zero dispersion shifted fiber (LEAF) with sub-meter spatial resolution. The Brillouin frequency shift is measured using Brillouin optical time-domain analysis (BOTDA) with differential pulse-width pair technique, while the spectrum shift of the Rayleigh backscatter is measured using optical frequency-domain reflectometry (OFDR). These shifts are the functions of both temperature and strain, and can be used as two independent parameters for the discrimination of temperature and strain. A 92 m measurable range with the spatial resolution of 50 cm is demonstrated experimentally, and accuracies of ±1.2 °C in temperature and ±15 με in strain could be achieved.

Optical high-resolution analysis of rotational movement: testing circular spatial filter velocimetry (CSFV) with rotating biological cells

NASA Astrophysics Data System (ADS)

Schaeper, M.; Schmidt, R.; Kostbade, R.; Damaschke, N.; Gimsa, J.

2016-07-01

Circular spatial filtering velocimetry (CSFV) was tested during the microscopic registration of the individual rotations of baker’s yeast cells. Their frequency-dependent rotation (electrorotation; ER) was induced in rotating electric fields, which were generated in a glass chip chamber with four electrodes (600 μm tip-to-tip distance). The electrodes were driven with sinusoidal quadrature signals of 5 or 8 V PP with frequencies up to 3 MHz. The observed cell rotation was of the order of 1-100 s per revolution. At each measuring frequency, the independent rotations of up to 20 cells were simultaneously recorded with a high-speed camera. CSFV was software-implemented using circular spatial filters with harmonic gratings. ER was proportional to the phase shift between the values of the spatial filtering signal of consecutive frames. ER spectra obtained by CSFV from the rotation velocities at different ER-field frequencies agreed well with manual measurements and theoretical spectra. Oscillations in the rotation velocity of a single cell in the elliptically polarized field near an electrode, which were resolved by CSFV, could not be visually discerned. ER step responses after field-on were recorded at 2500 frames per second. Analysis proved the high temporal resolution of CSFV and revealed a largely linear torque-friction relation during the acceleration phase of ER. Future applications of CSFV will allow for the simple and cheap automated high-resolution analysis of rotational movements where mechanical detection has too low a resolution or is not possible, e.g. in polluted environments or for gas and fluid vortices, microscopic objects, etc.

High Frequency High Spectral Resolution Focal Plane Arrays for AtLAST

NASA Astrophysics Data System (ADS)

Baryshev, Andrey

2018-01-01

Large collecting area single dish telescope such as ATLAST will be especially effective for medium (R 1000) and high (R 50000) spectral resolution observations. Large focal plane array is a natural solution to increase mapping speed. For medium resolution direct detectors with filter banks (KIDs) and or heterodyne technology can be employed. We will analyze performance limits of comparable KID and SIS focal plane array taking into account quantum limit and high background condition of terrestrial observing site. For large heterodyne focal plane arrays, a high current density AlN junctions open possibility of large instantaneous bandwidth >40%. This and possible multi frequency band FPSs presents a practical challenge for spatial sampling and scanning strategies. We will discuss phase array feeds as a possible solution, including a modular back-end system, which can be shared between KID and SIS based FPA. Finally we will discuss achievable sensitivities and pixel co unts for a high frequency (>500 GHz) FPAs and address main technical challenges: LO distribution, wire counts, bias line multiplexing, and monolithic vs. discrete mixer component integration.

Prospects for higher spatial resolution quantitative X-ray analysis using transition element L-lines

NASA Astrophysics Data System (ADS)

Statham, P.; Holland, J.

2014-03-01

Lowering electron beam kV reduces electron scattering and improves spatial resolution of X-ray analysis. However, a previous round robin analysis of steels at 5 - 6 kV using Lα-lines for the first row transition elements gave poor accuracies. Our experiments on SS63 steel using Lα-lines show similar biases in Cr and Ni that cannot be corrected with changes to self-absorption coefficients or carbon coating. The inaccuracy may be caused by different probabilities for emission and anomalous self-absorption for the La-line between specimen and pure element standard. Analysis using Ll(L3-M1)-lines gives more accurate results for SS63 plausibly because the M1-shell is not so vulnerable to the atomic environment as the unfilled M4,5-shell. However, Ll-intensities are very weak and WDS analysis may be impractical for some applications. EDS with large area SDD offers orders of magnitude faster analysis and achieves similar results to WDS analysis with Lα-lines but poorer energy resolution precludes the use of Ll-lines in most situations. EDS analysis of K-lines at low overvoltage is an alternative strategy for improving spatial resolution that could give higher accuracy. The trade-off between low kV versus low overvoltage is explored in terms of sensitivity for element detection for different elements.

Monitoring of Vegetation Impact Due to Trampling on Cadillac Mountain Summit Using High Spatial Resolution Remote Sensing Data Sets

NASA Astrophysics Data System (ADS)

Kim, Min-Kook; Daigle, John J.

2012-11-01

Cadillac Mountain—the highest peak along the eastern seaboard of the United States—is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies—based on placing physical barriers and educational messages for visitors—have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Landscape-scale accessibility of livestock to tigers: implications of spatial grain for modeling predation risk to mitigate human-carnivore conflict.

PubMed

Miller, Jennifer R B; Jhala, Yadvendradev V; Jena, Jyotirmay; Schmitz, Oswald J

2015-03-01

Innovative conservation tools are greatly needed to reduce livelihood losses and wildlife declines resulting from human-carnivore conflict. Spatial risk modeling is an emerging method for assessing the spatial patterns of predator-prey interactions, with applications for mitigating carnivore attacks on livestock. Large carnivores that ambush prey attack and kill over small areas, requiring models at fine spatial grains to predict livestock depredation hot spots. To detect the best resolution for predicting where carnivores access livestock, we examined the spatial attributes associated with livestock killed by tigers in Kanha Tiger Reserve, India, using risk models generated at 20, 100, and 200-m spatial grains. We analyzed land-use, human presence, and vegetation structure variables at 138 kill sites and 439 random sites to identify key landscape attributes where livestock were vulnerable to tigers. Land-use and human presence variables contributed strongly to predation risk models, with most variables showing high relative importance (≥0.85) at all spatial grains. The risk of a tiger killing livestock increased near dense forests and near the boundary of the park core zone where human presence is restricted. Risk was nonlinearly related to human infrastructure and open vegetation, with the greatest risk occurring 1.2 km from roads, 1.1 km from villages, and 8.0 km from scrubland. Kill sites were characterized by denser, patchier, and more complex vegetation with lower visibility than random sites. Risk maps revealed high-risk hot spots inside of the core zone boundary and in several patches in the human-dominated buffer zone. Validation against known kills revealed predictive accuracy for only the 20 m model, the resolution best representing the kill stage of hunting for large carnivores that ambush prey, like the tiger. Results demonstrate that risk models developed at fine spatial grains can offer accurate guidance on landscape attributes livestock should avoid to minimize human-carnivore conflict.

Monitoring of vegetation impact due to trampling on Cadillac Mountain summit using high spatial resolution remote sensing data sets.

PubMed

Kim, Min-Kook; Daigle, John J

2012-11-01

Cadillac Mountain--the highest peak along the eastern seaboard of the United States--is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies--based on placing physical barriers and educational messages for visitors--have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

PubMed

Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

2018-02-01

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

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

Sanders, Jeremiah, E-mail: jeremiah.sanders@duke.e

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF),more » and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this finding. Conclusions: Clinically informed, patient-specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.« less

An Assessment of Stream Confluence Flow Dynamics using Large Scale Particle Image Velocimetry Captured from Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Lewis, Q. W.; Rhoads, B. L.

2017-12-01

The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.

The Multi-Spectral Imaging Diagnostic on Alcator C-MOD and TCV

NASA Astrophysics Data System (ADS)

Linehan, B. L.; Mumgaard, R. T.; Duval, B. P.; Theiler, C. G.; TCV Team

2017-10-01

The Multi-Spectral Imaging (MSI) diagnostic is a new instrument that captures simultaneous spectrally filtered images from a common sight view while maintaining a large tendue and high spatial resolution. The system uses a polychromator layout where each image is sequentially filtered. This procedure yields a high transmission for each spectral channel with minimal vignetting and aberrations. A four-wavelength system was installed on Alcator C-Mod and then moved to TCV. The system uses industrial cameras to simultaneously image the divertor region at 95 frames per second at f/# 2.8 via a coherent fiber bundle (C-Mod) or a lens-based relay optic (TCV). The images are absolutely calibrated and spatially registered enabling accurate measurement of atomic line ratios and absolute line intensities. The images will be used to study divertor detachment by imaging impurities and Balmer series emissions. Furthermore, the large field of view and an ability to support many types of detectors opens the door for other novel approaches to optically measuring plasma with high temporal, spatial, and spectral resolution. Such measurements will allow for the study of Stark broadening and divertor turbulence. Here, we present the first measurements taken with this cavity imaging system. USDoE awards DE-FC02-99ER54512 and award DE-AC05-06OR23100, ORISE, administered by ORAU.

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

USGS Publications Warehouse

Smith, Kathryn E.L.; Nayegandhi, Amar; Brock, John C.

2010-01-01

INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

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.

Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations

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

Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara

This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.« less

Study of hyperspectral characteristics of different types of flares and smoke candles

NASA Astrophysics Data System (ADS)

Farley, Vincent; Chamberland, Martin; Lagueux, Philippe; Kastek, Mariusz; Piatkowski, Tadeusz; Dulski, Rafal

2012-06-01

Modern infrared camouflage and countermeasure technologies used in the context of military operations have evolved rapidly over the last decade. Indeed, some infrared seekers and decoy/flares tend to have spectral sensitivity tailored to closely match the emission signatures of military vehicles (such as aircrafts, tanks) and reject other sources. Similarly, some candles (or smoke bombs) are developed to generate large area screens with very high absorption in the infrared. The Military University of Technology has conducted an intensive field campaign where various types of flares and smoke candles were deployed in different conditions and measured. The high spectral, spatial and temporal resolution acquisition of these thermodynamic events was recorded with the Telops Hyper-Cam. The Hyper-Cam enables simultaneous acquisition of spatial and spectral information at high resolutions in both domains. The ability to study combustion systems with high resolution, co-registered imagery and spectral data is made possible. This paper presents the test campaign concept and definition and the analysis of the recorded measurements.

Research on Geometric Calibration of Spaceborne Linear Array Whiskbroom Camera

PubMed Central

Sheng, Qinghong; Wang, Qi; Xiao, Hui; Wang, Qing

2018-01-01

The geometric calibration of a spaceborne thermal-infrared camera with a high spatial resolution and wide coverage can set benchmarks for providing an accurate geographical coordinate for the retrieval of land surface temperature. The practice of using linear array whiskbroom Charge-Coupled Device (CCD) arrays to image the Earth can help get thermal-infrared images of a large breadth with high spatial resolutions. Focusing on the whiskbroom characteristics of equal time intervals and unequal angles, the present study proposes a spaceborne linear-array-scanning imaging geometric model, whilst calibrating temporal system parameters and whiskbroom angle parameters. With the help of the YG-14—China’s first satellite equipped with thermal-infrared cameras of high spatial resolution—China’s Anyang Imaging and Taiyuan Imaging are used to conduct an experiment of geometric calibration and a verification test, respectively. Results have shown that the plane positioning accuracy without ground control points (GCPs) is better than 30 pixels and the plane positioning accuracy with GCPs is better than 1 pixel. PMID:29337885

Development of high-resolution x-ray CT system using parallel beam geometry

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

Yoneyama, Akio, E-mail: akio.yoneyama.bu@hitachi.com; Baba, Rika; Hyodo, Kazuyuki

2016-01-28

For fine three-dimensional observations of large biomedical and organic material samples, we developed a high-resolution X-ray CT system. The system consists of a sample positioner, a 5-μm scintillator, microscopy lenses, and a water-cooled sCMOS detector. Parallel beam geometry was adopted to attain a field of view of a few mm square. A fine three-dimensional image of birch branch was obtained using a 9-keV X-ray at BL16XU of SPring-8 in Japan. The spatial resolution estimated from the line profile of a sectional image was about 3 μm.

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.

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.

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

NASA Astrophysics Data System (ADS)

Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

2017-11-01

Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (<< 1 μrad) are required, which are the major challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

Dynamic Moss Observed with Hi-C

NASA Technical Reports Server (NTRS)

Alexander, Caroline; Winebarger, Amy; Morton, Richard; Savage, Sabrina

2014-01-01

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-­-C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Dynamic Moss Observed with Hi-C

NASA Technical Reports Server (NTRS)

Alexander, Caroline; Winebarger, Amy; Morton, Richard; Savage, Sabrina

2014-01-01

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Measuring Te inclusion uniformity over large areas for CdTe/CZT imaging and spectrometry sensors

NASA Astrophysics Data System (ADS)

Bolke, Joe; O'Brien, Kathryn; Wall, Peter; Spicer, Mike; Gélinas, Guillaume; Beaudry, Jean-Nicolas; Alexander, W. Brock

2017-09-01

CdTe and CZT materials are technologies for gamma and x-ray imaging for applications in industry, homeland security, defense, space, medical, and astrophysics. There remain challenges in uniformity over large detector areas (50 75 mm) due to a combination of material purity, handling, growth process, grown in defects, doping/compensation, and metal contacts/surface states. The influence of these various factors has yet to be explored at the large substrate level required for devices with higher resolution both spatially and spectroscopically. In this study, we looked at how the crystal growth processes affect the size and density distributions of microscopic Te inclusion defects. We were able to grow single crystals as large as 75 mm in diameter and spatially characterize three-dimensional defects and map the uniformity using IR microscopy. We report on the pattern of observed defects within wafers and its relation to instabilities at the crystal growth interface.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

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.

Visible light high-resolution imaging system for large aperture telescope by liquid crystal adaptive optics with phase diversity technique.

PubMed

Xu, Zihao; Yang, Chengliang; Zhang, Peiguang; Zhang, Xingyun; Cao, Zhaoliang; Mu, Quanquan; Sun, Qiang; Xuan, Li

2017-08-30

There are more than eight large aperture telescopes (larger than eight meters) equipped with adaptive optics system in the world until now. Due to the limitations such as the difficulties of increasing actuator number of deformable mirror, most of them work in the infrared waveband. A novel two-step high-resolution optical imaging approach is proposed by applying phase diversity (PD) technique to the open-loop liquid crystal adaptive optics system (LC AOS) for visible light high-resolution adaptive imaging. Considering the traditional PD is not suitable for LC AOS, the novel PD strategy is proposed which can reduce the wavefront estimating error caused by non-modulated light generated by liquid crystal spatial light modulator (LC SLM) and make the residual distortions after open-loop correction to be smaller. Moreover, the LC SLM can introduce any aberration which realizes the free selection of phase diversity. The estimating errors are greatly reduced in both simulations and experiments. The resolution of the reconstructed image is greatly improved on both subjective visual effect and the highest discernible space resolution. Such technique can be widely used in large aperture telescopes for astronomical observations such as terrestrial planets, quasars and also can be used in other applications related to wavefront correction.

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

Low-cost Photoacoustic-based Measurement System for Carbon Dioxide Fluxes with the Potential for large-scale Monitoring

NASA Astrophysics Data System (ADS)

Scholz, L. T.; Bierer, B.; Ortiz Perez, A.; Woellenstein, J.; Sachs, T.; Palzer, S.

2016-12-01

The determination of carbon dioxide (CO2) fluxes between ecosystems and the atmosphere is crucial for understanding ecological processes on regional and global scales. High quality data sets with full uncertainty estimates are needed to evaluate model simulations. However, current flux monitoring techniques are unsuitable to provide reliable data of a large area at both a detailed level and an appropriate resolution, at best in combination with a high sampling rate. Currently used sensing technologies, such as non-dispersive infrared (NDIR) gas analyzers, cannot be deployed in large numbers to provide high spatial resolution due to their costs and complex maintenance requirements. Here, we propose a novel CO2 measurement system, whose gas sensing unit is made up of low-cost, low-power consuming components only, such as an IR-LED and a photoacoustic detector. The sensor offers a resolution of < 50 ppm in the interesting concentration range up to 5000 ppm and an almost linear and fast sensor response of just a few seconds. Since the sensor can be applied in-situ without special precautions, it allows for environmental monitoring in a non-invasive way. Its low energy consumption enables long-term measurements. The low overall costs favor the manufacturing in large quantities. This allows the operation of multiple sensors at a reasonable price and thus provides concentration measurements at any desired spatial coverage and at high temporal resolution. With appropriate 3D configuration of the units, vertical and horizontal fluxes can be determined. By applying a closely meshed wireless sensor network, inhomogeneities as well as CO2 sources and sinks in the lower atmosphere can be monitored. In combination with sensors for temperature, pressure and humidity, our sensor paves the way towards the reliable and extensive monitoring of ecosystem-atmosphere exchange rates. The technique can also be easily adapted to other relevant greenhouse gases.

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...

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.

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

DOE PAGES

Ozturk, Hande; Yan, Hanfei; He, Yan; ...

2018-05-09

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

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

Ozturk, Hande; Yan, Hanfei; He, Yan

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Simulation Based Exploration of Critical Zone Dynamics in Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, P.

2017-12-01

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale ( 1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions ( 1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before. We show how an integrated 3-D model at 1m grid resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes over large areas. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

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.

A new framework for UAV-based remote sensing data processing and its application in almond water stress quantification

USDA-ARS?s Scientific Manuscript database

With the rapid development of small imaging sensors and unmanned aerial vehicles (UAVs), remote sensing is undergoing a revolution with greatly increased spatial and temporal resolutions. While more relevant detail becomes available, it is a challenge to analyze the large number of images to extract...

Rationale and Application of Tangential Scanning to Industrial Inspection of Hardwood Logs

Treesearch

Nand K. Gupta; Daniel L. Schmoldt; Bruce Isaacson

1998-01-01

Industrial computed tomography (CT) inspection of hardwood logs has some unique requirements not found in other CT applications. Sawmill operations demand that large volumes of wood be scanned quickly at high spatial resolution for extended duty cycles. Current CT scanning geometries and commercial systems have both technical and economic [imitations. Tangential...

Comparing large-scale hydrological model predictions with observed streamflow in the Pacific Northwest: effects of climate and groundwater

Treesearch

Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee

2014-01-01

Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...

Ideas for a future earth observing system from geosynchronous orbit

NASA Technical Reports Server (NTRS)

Shenk, William E.; Hall, Forrest; Esaias, Wayne; Maxwell, Marvin; Suomi, Verner E.; Von Bun, Fritz

1986-01-01

Uses for the proposed geosynchronous platform are described. The geosynchronous satellite could provide good spatial and temporal resolution, a large field-of-view, easier calibration, stereography, and data relay. The limitations of the platform are discussed. The applications of the geosynchronous platform to meteorology, earth surveying, and oceanography are examined.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

The sensitivity of ecosystem service models to choices of input data and spatial resolution

USGS Publications Warehouse

Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

2018-01-01

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

PubMed

Veganzones, Miguel A; Simoes, Miguel; Licciardi, Giorgio; Yokoya, Naoto; Bioucas-Dias, Jose M; Chanussot, Jocelyn

2016-01-01

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-resolution HSI. Most approaches adopt an unmixing or a matrix factorization perspective. The derived methods have led to state-of-the-art results when the spectral information lies in a low-dimensional subspace/manifold. However, if the subspace/manifold dimensionality spanned by the complete data set is large, i.e., larger than the number of multispectral bands, the performance of these methods mainly decreases because the underlying sparse regression problem is severely ill-posed. In this paper, we propose a local approach to cope with this difficulty. Fundamentally, we exploit the fact that real world HSIs are locally low rank, that is, pixels acquired from a given spatial neighborhood span a very low-dimensional subspace/manifold, i.e., lower or equal than the number of multispectral bands. Thus, we propose to partition the image into patches and solve the data fusion problem independently for each patch. This way, in each patch the subspace/manifold dimensionality is low enough, such that the problem is not ill-posed anymore. We propose two alternative approaches to define the hyperspectral super-resolution through local dictionary learning using endmember induction algorithms. We also explore two alternatives to define the local regions, using sliding windows and binary partition trees. The effectiveness of the proposed approaches is illustrated with synthetic and semi real data.

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

Black hole mass measurement using molecular gas kinematics: what ALMA can do

NASA Astrophysics Data System (ADS)

Yoon, Ilsang

2017-04-01

We study the limits of the spatial and velocity resolution of radio interferometry to infer the mass of supermassive black holes (SMBHs) in galactic centres using the kinematics of circum-nuclear molecular gas, by considering the shapes of the galaxy surface brightness profile, signal-to-noise ratios (S/Ns) of the position-velocity diagram (PVD) and systematic errors due to the spatial and velocity structure of the molecular gas. We argue that for fixed galaxy stellar mass and SMBH mass, the spatial and velocity scales that need to be resolved increase and decrease, respectively, with decreasing Sérsic index of the galaxy surface brightness profile. We validate our arguments using simulated PVDs for varying beam size and velocity channel width. Furthermore, we consider the systematic effects on the inference of the SMBH mass by simulating PVDs including the spatial and velocity structure of the molecular gas, which demonstrates that their impacts are not significant for a PVD with good S/N unless the spatial and velocity scale associated with the systematic effects are comparable to or larger than the angular resolution and velocity channel width of the PVD from pure circular motion. Also, we caution that a bias in a galaxy surface brightness profile owing to the poor resolution of a galaxy photometric image can largely bias the SMBH mass by an order of magnitude. This study shows the promise and the limits of ALMA observations for measuring SMBH mass using molecular gas kinematics and provides a useful technical justification for an ALMA proposal with the science goal of measuring SMBH mass.

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.

Enhancing resolution in coherent x-ray diffraction imaging.

PubMed

Noh, Do Young; Kim, Chan; Kim, Yoonhee; Song, Changyong

2016-12-14

Achieving a resolution near 1 nm is a critical issue in coherent x-ray diffraction imaging (CDI) for applications in materials and biology. Albeit with various advantages of CDI based on synchrotrons and newly developed x-ray free electron lasers, its applications would be limited without improving resolution well below 10 nm. Here, we review the issues and efforts in improving CDI resolution including various methods for resolution determination. Enhancing diffraction signal at large diffraction angles, with the aid of interference between neighboring strong scatterers or templates, is reviewed and discussed in terms of increasing signal-to-noise ratio. In addition, we discuss errors in image reconstruction algorithms-caused by the discreteness of the Fourier transformations involved-which degrade the spatial resolution, and suggest ways to correct them. We expect this review to be useful for applications of CDI in imaging weakly scattering soft matters using coherent x-ray sources including x-ray free electron lasers.

Ultrafast random-access scanning in two-photon microscopy using acousto-optic deflectors.

PubMed

Salomé, R; Kremer, Y; Dieudonné, S; Léger, J-F; Krichevsky, O; Wyart, C; Chatenay, D; Bourdieu, L

2006-06-30

Two-photon scanning microscopy (TPSM) is a powerful tool for imaging deep inside living tissues with sub-cellular resolution. The temporal resolution of TPSM is however strongly limited by the galvanometric mirrors used to steer the laser beam. Fast physiological events can therefore only be followed by scanning repeatedly a single line within the field of view. Because acousto-optic deflectors (AODs) are non-mechanical devices, they allow access at any point within the field of view on a microsecond time scale and are therefore excellent candidates to improve the temporal resolution of TPSM. However, the use of AOD-based scanners with femtosecond pulses raises several technical difficulties. In this paper, we describe an all-digital TPSM setup based on two crossed AODs. It includes in particular an acousto-optic modulator (AOM) placed at 45 degrees with respect to the AODs to pre-compensate for the large spatial distortions of femtosecond pulses occurring in the AODs, in order to optimize the spatial resolution and the fluorescence excitation. Our setup allows recording from freely selectable point-of-interest at high speed (1kHz). By maximizing the time spent on points of interest, random-access TPSM (RA-TPSM) constitutes a promising method for multiunit recordings with millisecond resolution in biological tissues.

Edge technique lidar for high accuracy, high spatial resolution wind measurement in the Planetary Boundary Layer

NASA Technical Reports Server (NTRS)

Korb, C. L.; Gentry, Bruce M.

1995-01-01

The goal of the Army Research Office (ARO) Geosciences Program is to measure the three dimensional wind field in the planetary boundary layer (PBL) over a measurement volume with a 50 meter spatial resolution and with measurement accuracies of the order of 20 cm/sec. The objective of this work is to develop and evaluate a high vertical resolution lidar experiment using the edge technique for high accuracy measurement of the atmospheric wind field to meet the ARO requirements. This experiment allows the powerful capabilities of the edge technique to be quantitatively evaluated. In the edge technique, a laser is located on the steep slope of a high resolution spectral filter. This produces large changes in measured signal for small Doppler shifts. A differential frequency technique renders the Doppler shift measurement insensitive to both laser and filter frequency jitter and drift. The measurement is also relatively insensitive to the laser spectral width for widths less than the width of the edge filter. Thus, the goal is to develop a system which will yield a substantial improvement in the state of the art of wind profile measurement in terms of both vertical resolution and accuracy and which will provide a unique capability for atmospheric wind studies.

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

Solid state VRX CT detector

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Melnyk, Roman; Sambari, Aniket; Jordan, Lawrence M.; Laughter, Joseph S.; Zou, Ping

2000-04-01

A technique called Variable-Resolution X-ray (VRX) detection that greatly increases the spatial resolution in computed tomography (CT) and digital radiography (DR) is presented. The technique is based on a principle called 'projective compression' that allows the resolution element of a CT detector to scale with the subject or field size. For very large (40 - 50 cm) field sizes, resolution exceeding 2 cy/mm is possible and for very small fields, microscopy is attainable with resolution exceeding 100 cy/mm. Preliminary results from a 576-channel solid-state detector are presented. The detector has a dual-arm geometry and is comprised of CdWO4 scintillator crystals arranged in 24 modules of 24 channels/module. The scintillators are 0.85 mm wide and placed on 1 mm centers. Measurements of signal level, MTF and SNR, all versus detector angle, are presented.

Comparison of VRX CT scanners geometries

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Melnyk, Roman; Duckworth, Christopher N.; Russ, Stephan; Jordan, Lawrence M.; Laughter, Joseph S.

2001-06-01

A technique called Variable-Resolution X-ray (VRX) detection greatly increases the spatial resolution in computed tomography (CT) and digital radiography (DR) as the field size decreases. The technique is based on a principle called `projective compression' that allows both the resolution element and the sampling distance of a CT detector to scale with the subject or field size. For very large (40 - 50 cm) field sizes, resolution exceeding 2 cy/mm is possible and for very small fields, microscopy is attainable with resolution exceeding 100 cy/mm. This paper compares the benefits obtainable with two different VRX detector geometries: the single-arm geometry and the dual-arm geometry. The analysis is based on Monte Carlo simulations and direct calculations. The results of this study indicate that the dual-arm system appears to have more advantages than the single-arm technique.

Impact of large x-ray beam collimation on image quality

NASA Astrophysics Data System (ADS)

Racine, Damien; Ba, Alexandre; Ott, Julien G.; Bochud, François O.; Verdun, Francis R.

2016-03-01

Large X-ray beam collimation in computed tomography (CT) opens the way to new image acquisition techniques and improves patient management for several clinical indications. The systems that offer large X-ray beam collimation enable, in particular, a whole region of interest to be investigated with an excellent temporal resolution. However, one of the potential drawbacks of this option might be a noticeable difference in image quality along the z-axis when compared with the standard helical acquisition mode using more restricted X-ray beam collimations. The aim of this project is to investigate the impact of the use of large X-ray beam collimation and new iterative reconstruction on noise properties, spatial resolution and low contrast detectability (LCD). An anthropomorphic phantom and a custom made phantom were scanned on a GE Revolution CT. The images were reconstructed respectively with ASIR-V at 0% and 50%. Noise power spectra, to evaluate the noise properties, and Target Transfer Functions, to evaluate the spatial resolution, were computed. Then, a Channelized Hotelling Observer with Gabor and Dense Difference of Gaussian channels was used to evaluate the LCD using the Percentage correct as a figure of merit. Noticeable differences of 3D noise power spectra and MTF have been recorded; however no significant difference appeared when dealing with the LCD criteria. As expected the use of iterative reconstruction, for a given CTDIvol level, allowed a significant gain in LCD in comparison to ASIR-V 0%. In addition, the outcomes of the NPS and TTF metrics led to results that would contradict the outcomes of CHO model observers if used for a NPWE model observer (Non- Prewhitening With Eye filter). The unit investigated provides major advantages for cardiac diagnosis without impairing the image quality level of standard chest or abdominal acquisitions.

Effect of Te inclusions in CdZnTe crystals at different temperatures

NASA Astrophysics Data System (ADS)

Hossain, A.; Bolotnikov, A. E.; Camarda, G. S.; Gul, R.; Kim, K.-H.; Cui, Y.; Yang, G.; Xu, L.; James, R. B.

2011-02-01

CdZnTe crystals often exhibit nonuniformities due to the presence of Te inclusions and dislocations. High concentrations of such defects in these crystals generally entail severe charge-trapping, a major problem in ensuring the device's satisfactory performance. In this study, we employed a high-intensity, high-spatial-resolution synchrotron x-ray beam as the ideal tool to generate charges by focusing it over the large Te inclusions, and then observing the carrier's response at room- and at low-temperatures. A high spatial 5-μm resolution raster scan revealed the fine details of the presence of extended defects, like Te inclusions and dislocations in the CdZnTe crystals. A noticeable change was observed in the efficiency of electron charge collection at low temperature (1 °C), but it was hardly altered at room-temperature.

Characterizing Subpixel Spatial Resolution of a Hybrid CMOS Detector

NASA Astrophysics Data System (ADS)

Bray, Evan; Burrows, Dave; Chattopadhyay, Tanmoy; Falcone, Abraham; Hull, Samuel; Kern, Matthew; McQuaide, Maria; Wages, Mitchell

2018-01-01

The detection of X-rays is a unique process relative to other wavelengths, and allows for some novel features that increase the scientific yield of a single observation. Unlike lower photon energies, X-rays liberate a large number of electrons from the silicon absorber array of the detector. This number is usually on the order of several hundred to a thousand for moderate-energy X-rays. These electrons tend to diffuse outward into what is referred to as the charge cloud. This cloud can then be picked up by several pixels, forming a specific pattern based on the exact incident location. By conducting the first ever “mesh experiment" on a hybrid CMOS detector (HCD), we have experimentally determined the charge cloud shape and used it to characterize responsivity of the detector with subpixel spatial resolution.

Interference Confocal Microscope Integrated with Spatial Phase Shifter.

PubMed

Wang, Weibo; Gu, Kang; You, Xiaoyu; Tan, Jiubin; Liu, Jian

2016-08-24

We present an interference confocal microscope (ICM) with a new single-body four-step simultaneous phase-shifter device designed to obtain high immunity to vibration. The proposed ICM combines the respective advantages of simultaneous phase shifting interferometry and bipolar differential confocal microscopy to obtain high axis resolution, large dynamic range, and reduce the sensitivity to vibration and reflectance disturbance seamlessly. A compact single body spatial phase shifter is added to capture four phase-shifted interference signals simultaneously without time delay and construct a stable and space-saving simplified interference confocal microscope system. The test result can be obtained by combining the interference phase response and the bipolar property of differential confocal microscopy without phase unwrapping. Experiments prove that the proposed microscope is capable of providing stable measurements with 1 nm of axial depth resolution for either low- or high-numerical aperture objective lenses.

Remote Sensing and Reflectance Profiling in Entomology.

PubMed

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

Lead foil in dental X-ray film: Backscattering rejection or image intensifier?

NASA Astrophysics Data System (ADS)

Hönnicke, M. G.; Delben, G. J.; Godoi, W. C.; Swinka-Filho, V.

2014-11-01

Dental X-ray films are still largely used due to sterilization issues, simplicity and, mainly, economic reasons. These films almost always are double coated (double emulsion) and have a lead foil in contact with the film for X-ray backscattering rejection. Herein we explore the use of the lead foil as an image intensifier. In these studies, spatial resolution was investigated when images were acquired on the dental X-ray films with and without the lead foil. Also, the lead foil was subjected to atomic analysis (fluorescent measurements) and structure analysis (X-ray diffraction). We determined that the use of the lead foil reduces the exposure time, however, does not affect the spatial resolution on the acquired images. This suggests that the fluorescent radiation spread is smaller than the grain sizes of the dental X-ray films.

Operational Interoperable Web Coverage Service for Earth Observing Satellite Data: Issues and Lessons Learned

NASA Astrophysics Data System (ADS)

Yang, W.; Min, M.; Bai, Y.; Lynnes, C.; Holloway, D.; Enloe, Y.; di, L.

2008-12-01

In the past few years, there have been growing interests, among major earth observing satellite (EOS) data providers, in serving data through the interoperable Web Coverage Service (WCS) interface protocol, developed by the Open Geospatial Consortium (OGC). The interface protocol defined in WCS specifications allows client software to make customized requests of multi-dimensional EOS data, including spatial and temporal subsetting, resampling and interpolation, and coordinate reference system (CRS) transformation. A WCS server describes an offered coverage, i.e., a data product, through a response to a client's DescribeCoverage request. The description includes the offered coverage's spatial/temporal extents and resolutions, supported CRSs, supported interpolation methods, and supported encoding formats. Based on such information, a client can request the entire or a subset of coverage in any spatial/temporal resolutions and in any one of the supported CRSs, formats, and interpolation methods. When implementing a WCS server, a data provider has different approaches to present its data holdings to clients. One of the most straightforward, and commonly used, approaches is to offer individual physical data files as separate coverages. Such implementation, however, will result in too many offered coverages for large data holdings and it also cannot fully present the relationship among different, but spatially and/or temporally associated, data files. It is desirable to disconnect offered coverages from physical data files so that the former is more coherent, especially in spatial and temporal domains. Therefore, some servers offer one single coverage for a set of spatially coregistered time series data files such as a daily global precipitation coverage linked to many global single- day precipitation files; others offer one single coverage for multiple temporally coregistered files together forming a large spatial extent. In either case, a server needs to assemble an output coverage real-time by combining potentially large number of physical files, which can be operationally difficult. The task becomes more challenging if an offered coverage involves spatially and temporally un-registered physical files. In this presentation, we will discuss issues and lessons learned in providing NASA's AIRS Level 2 atmospheric products, which are in satellite swath CRS and in 6-minute segment granule files, as virtual global coverages. We"ll discuss the WCS server's on- the-fly georectification, mosaicking, quality screening, performance, and scalability.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

Fast Solar Polarimeter: Prototype Characterization and First Results

NASA Astrophysics Data System (ADS)

Iglesias, F. A.; Feller, A.; Krishnappa, N.; Solanki, S. K.

2016-04-01

Due to the differential and non-simultaneous nature of polarization measurements, seeing induced crosstalk (SIC) and seeing limited spatial resolution can easily counterbalance the benefits of solar imaging polarimetry from the ground. The development of instrumental techniques to treat these issues is necessary to fully exploit the next generation of large-aperture solar facilities, and maintain ground-based data at a competitive level with respect to its space-based counterpart. In particular, considering that many open questions in modern solar physics demand data with challenging specifications of resolution and polarimetric sensitivity that can only be achieved with large telescope apertures (Stenflo 1999). Even if state-of-the-art adaptive optics systems greatly improve image quality, their limited correction —due to finite bandwidth, mode number and seeing anisoplanat- ism— produces large residual values of SIC (Krishnappa & Feller 2012). Dual beam polarimeters are commonly used to reduce SIC between the intensity and polarization signals, however, they cannot compensate for the SIC introduced between circular and linear polarization, which can be relevant for high-precision polarimetry. It is known that fast modulation effectively reduces SIC, but the demodulation of the corresponding intensity signals imposes hard requirements on the frame rate of the associated cameras. One way to avoid a fast sensor, is to decouple the camera readout from the intensity demodulation step. This concept is the cornerstone of the very successful Zurich Imaging Polarimeter (ZIMPOL). Even though the ZIMPOL solution allows the detection of very faint signals (˜10-5), its design is not suitable for high-spatial-resolution applications. We are developing a polarimeter that focuses on both spatial resolution (<0.5 arcsec) and polarimetric sensitivity (10-4). The prototype of this Fast Solar Polarimeter (FSP, see Feller et al. 2014), employs a high frame-rate (400 fps), low-noise (<4 e- RMS), pnCCD camera (Hartmann et al. 2006) that is read in synchronization with a polarization modulator based on ferroelectric liquid crystals. The modulator package is similar to the SOLIS (Keller et al. 2003) design and optimized to have an achromatic total polarimetric efficiency above 80 % in the 400-700 nm wavelength range. The fast modulation frequency of FSP, yielding up to 100 full-Stokes measurements per second, and high duty cycle (>95%), have the double benefit of reducing seeing induced artifacts and improving the final spatial resolution by providing an optimal regime for the application of post-facto image reconstruction techniques. In this poster we describe the FSP prototype, including the characterization results, a technique to correct image smearing due to the sensor frame transfer (Iglesias et al. 2015) and some of the first measurements obtained with the 68-cm Vacuum Tower Telescope located at the Observatorio del Teide, Spain.

A comparison of earthquake backprojection imaging methods for dense local arrays

NASA Astrophysics Data System (ADS)

Beskardes, G. D.; Hole, J. A.; Wang, K.; Michaelides, M.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Brown, L. D.; Quiros, D. A.

2018-03-01

Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-term averaging/long-term averaging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveform method to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle.

PubMed

Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle

PubMed Central

Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656

Performance evaluation of the Trans-PET® BioCaliburn® LH system: a large FOV small-animal PET system

NASA Astrophysics Data System (ADS)

Wang, Luyao; Zhu, Jun; Liang, Xiao; Niu, Ming; Wu, Xiaoke; Kao, Chien-Min; Kim, Heejong; Xie, Qingguo

2015-01-01

The Trans-PET® BioCaliburn® LH is a commercial positron emission tomography (PET) system for animal imaging. The system offers a large transaxial field-of-view (FOV) of 13.0 cm to allow imaging of multiple rodents or larger animals. This paper evaluates and reports the performance characteristics of this system. Methods: in this paper, the system was evaluated for its spatial resolutions, sensitivity, scatter fraction, count rate performance and image quality in accordance with the National Electrical Manufacturers Association (NEMA) NU-4 2008 specification with modifications. Phantoms and animals not specified in the NEMA specification were also scanned to provide further demonstration of its imaging capability. Results: the spatial resolution is 1.0 mm at the center. When using a 350-650 keV energy window and a 5 ns coincidence time window, the sensitivity at the center is 2.04%. The noise equivalent count-rate curve reaches a peak value of 62 kcps at 28 MBq for the mouse-sized phantom and a peak value of 25 kcps at 31 MBq for the rat-sized phantom. The scatter fractions are 8.4% and 17.7% for the mouse- and rat-sized phantoms, respectively. The uniformity and recovery coefficients measured by using the NEMA image-quality phantom both indicate good imaging performance, even though the reconstruction algorithm provided by the vendor does not implement all desired corrections. The Derenzo-phantom images show that the system can resolve 1.0 mm diameter rods. Animal studies demonstrate the capabilities of the system in dynamic imaging and to image multiple rodents. Conclusion: the Trans-PET® BioCaliburn® LH system offers high spatial resolution, a large transaixal FOV and adequate sensitivity. It produces animal images of good quality and supports dynamic imaging. The system is an attractive imaging technology for preclinical research.

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.

Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging

PubMed Central

Dempsey, Graham T.; Vaughan, Joshua C.; Chen, Kok Hao; Bates, Mark; Zhuang, Xiaowei

2011-01-01

One approach to super-resolution fluorescence imaging uses sequential activation and localization of individual fluorophores to achieve high spatial resolution. Essential to this technique is the choice of fluorescent probes — the properties of the probes, including photons per switching event, on/off duty cycle, photostability, and number of switching cycles, largely dictate the quality of super-resolution images. While many probes have been reported, a systematic characterization of the properties of these probes and their impact on super-resolution image quality has been described in only a few cases. Here, we quantitatively characterized the switching properties of 26 organic dyes and directly related these properties to the quality of super-resolution images. This analysis provides a set of guidelines for characterization of super-resolution probes and a resource for selecting probes based on performance. Our evaluation identified several photoswitchable dyes with good to excellent performance in four independent spectral ranges, with which we demonstrated low crosstalk, four-color super-resolution imaging. PMID:22056676

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

A High Resolution View of Galactic Centers: Arp 220 and M31

NASA Astrophysics Data System (ADS)

Lockhart, Kelly E.

The centers of galaxy are small in size and yet incredibly complex. They play host to supermassive black holes and nuclear star clusters (NSCs) and are subject to large gas inows, nuclear starbursts, and active galactic nuclear (AGN) activity. They can also be the launching site for large-scale galactic outows. However, though these systems are quite important to galactic evolution, observations are quite difficult due to their small size. Using high spatial resolution narrowband imaging with HST/WFC3 of Arp 220, a latestage galaxy merger, I discover an ionized gas bubble feature ( r = 600 pc) just off the nucleus. The bubble is aligned with both the western nucleus and with the large-scale galactic outflow. Using energetics arguments, I link the bubble with a young, obscured AGN or with an intense nuclear starburst. Given its alignment along the large-scale outflow axis, I argue that the bubble presents evidence for a link between the galactic center and the large-scale outflow. I also present new observations of the NSC in M31, the closest large spiral galaxy to our own. Using the OSIRIS near-infrared integral field spectrograph (IFS) on Keck, I map the kinematics of the old stellar population in the eccentric disk of the NSC. I compare the observations to models to derive a precession speed of the disk of 0+/-5 km s-1 pc-1 , and hence confirm that winds from the old stellar population may be the source of gas needed to form the young stellar population in the NSC. Studies of galactic centers are dependent on high spatial resolution observations. In particular, IFSs are ideal instruments for these studies as they provide two-dimensional spectroscopy of the field of view, enabling 2D kinematic studies. I report on work to characterize and improve the data reduction pipeline of the OSIRIS IFS, and discuss implications for future generations of IFS instrumentation.

Steps toward a CONUS-wide reanalysis with archived NEXRAD data using National Mosaic and Multisensor Quantitative Precipitation Estimation (NMQ/Q2) algorithms

NASA Astrophysics Data System (ADS)

Stevens, S. E.; Nelson, B. R.; Langston, C.; Qi, Y.

2012-12-01

The National Mosaic and Multisensor QPE (NMQ/Q2) software suite, developed at NOAA's National Severe Storms Laboratory (NSSL) in Norman, OK, addresses a large deficiency in the resolution of currently archived precipitation datasets. Current standards, both radar- and satellite-based, provide for nationwide precipitation data with a spatial resolution of up to 4-5 km, with a temporal resolution as fine as one hour. Efforts are ongoing to process archived NEXRAD data for the period of record (1996 - present), producing a continuous dataset providing precipitation data at a spatial resolution of 1 km, on a timescale of only five minutes. In addition, radar-derived precipitation data are adjusted hourly using a wide variety of automated gauge networks spanning the United States. Applications for such a product range widely, from emergency management and flash flood guidance, to hydrological studies and drought monitoring. Results are presented from a subset of the NEXRAD dataset, providing basic statistics on the distribution of rainrates, relative frequency of precipitation types, and several other variables which demonstrate the variety of output provided by the software. Precipitation data from select case studies are also presented to highlight the increased resolution provided by this reanalysis and the possibilities that arise from the availability of data on such fine scales. A previously completed pilot project and steps toward a nationwide implementation are presented along with proposed strategies for managing and processing such a large dataset. Reprocessing efforts span several institutions in both North Carolina and Oklahoma, and data/software coordination are key in producing a homogeneous record of precipitation to be archived alongside NOAA's other Climate Data Records. Methods are presented for utilizing supercomputing capability in expediting processing, to allow for the iterative nature of a reanalysis effort.

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.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

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

Comparison of CO2 Emissions Data for 30 Cities from Different Sources

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Koide, D.; Ito, A.; Saito, M.; Hirata, R.

2017-12-01

Many sources suggest that cities account for a large proportion of global anthropogenic greenhouse gas emissions. Therefore, in search for the best ways to reduce total anthropogenic greenhouse gas emissions, a focus on the city emission is crucial. In this study, we collected CO2 emissions data in 30 cities during 1990-2015 and evaluated the degree of variance between data sources. The CO2 emissions data were obtained from academic papers, municipal reports, and high-resolution emissions maps (CIDIACv2016, EDGARv4.2, ODIACv2016, and FFDASv2.0). To extract urban CO2 emissions from the high-resolution emissions maps, urban fraction ranging from 0 to 1 was calculated for each 1×1 degree grid cell using the global land cover data (SYNMAP). Total CO2 emissions from the grid cells in which urban fraction occupies greater than or equal to 0.9 were regarded as urban CO2 emissions. The estimated CO2 emissions varied greatly depending on the information sources, even in the same year. There was a large difference between CO2 emissions collected from academic papers, municipal reports, and those extracted from high-resolution emissions maps. One reason is that they use different city boundaries. That is, the city proper (i.e. the political city boundary) is often defined as the city boundary in academic papers and municipal reports, whereas the urban area is used in the high-resolution emissions maps. Furthermore, there was a large variation in CO2 emissions collected from academic papers and municipal reports. These differences may be due to the difference in the assumptions such as allocation ratio of CO2 emissions to producers and consumers. In general, the consumption-based assignment of emissions gives higher estimates of urban CO2 emission in comparison with production-based assignment. Furthermore, there was also a large variation in CO2 emissions extracted from high-resolution emissions maps. This difference would be attributable to differences in information used in the spatial disaggregation of emissions. To identify the CO2 emissions from cities, it is necessary to determine common definitions of city boundaries, allocation ratio of CO2 emissions to consumption and production, and refined approach of the spatial disaggregation of CO2 emissions in high-resolution emissions maps.

Virtual scanning tunneling microscopy: A local spectroscopic probe of two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Sciambi, A.; Pelliccione, M.; Bank, S. R.; Gossard, A. C.; Goldhaber-Gordon, D.

2010-09-01

We propose a probe technique capable of performing local low-temperature spectroscopy on a two-dimensional electron system (2DES) in a semiconductor heterostructure. Motivated by predicted spatially-structured electron phases, the probe uses a charged metal tip to induce electrons to tunnel locally, directly below the tip, from a "probe" 2DES to a "subject" 2DES of interest. We test this concept with large-area (nonscanning) tunneling measurements, and predict a high spatial resolution and spectroscopic capability, with minimal influence on the physics in the subject 2DES.

Two-photon polymerization microfabrication of hydrogels: an advanced 3D printing technology for tissue engineering and drug delivery.

PubMed

Xing, Jin-Feng; Zheng, Mei-Ling; Duan, Xuan-Ming

2015-08-07

3D printing technology has attracted much attention due to its high potential in scientific and industrial applications. As an outstanding 3D printing technology, two-photon polymerization (TPP) microfabrication has been applied in the fields of micro/nanophotonics, micro-electromechanical systems, microfluidics, biomedical implants and microdevices. In particular, TPP microfabrication is very useful in tissue engineering and drug delivery due to its powerful fabrication capability for precise microstructures with high spatial resolution on both the microscopic and the nanometric scale. The design and fabrication of 3D hydrogels widely used in tissue engineering and drug delivery has been an important research area of TPP microfabrication. The resolution is a key parameter for 3D hydrogels to simulate the native 3D environment in which the cells reside and the drug is controlled to release with optimal temporal and spatial distribution in vitro and in vivo. The resolution of 3D hydrogels largely depends on the efficiency of TPP initiators. In this paper, we will review the widely used photoresists, the development of TPP photoinitiators, the strategies for improving the resolution and the microfabrication of 3D hydrogels.

Defining habitat covariates in camera-trap based occupancy studies

PubMed Central

Niedballa, Jürgen; Sollmann, Rahel; Mohamed, Azlan bin; Bender, Johannes; Wilting, Andreas

2015-01-01

In species-habitat association studies, both the type and spatial scale of habitat covariates need to match the ecology of the focal species. We assessed the potential of high-resolution satellite imagery for generating habitat covariates using camera-trapping data from Sabah, Malaysian Borneo, within an occupancy framework. We tested the predictive power of covariates generated from satellite imagery at different resolutions and extents (focal patch sizes, 10–500 m around sample points) on estimates of occupancy patterns of six small to medium sized mammal species/species groups. High-resolution land cover information had considerably more model support for small, patchily distributed habitat features, whereas it had no advantage for large, homogeneous habitat features. A comparison of different focal patch sizes including remote sensing data and an in-situ measure showed that patches with a 50-m radius had most support for the target species. Thus, high-resolution satellite imagery proved to be particularly useful in heterogeneous landscapes, and can be used as a surrogate for certain in-situ measures, reducing field effort in logistically challenging environments. Additionally, remote sensed data provide more flexibility in defining appropriate spatial scales, which we show to impact estimates of wildlife-habitat associations. PMID:26596779

Quantifying stream thermal regimes at management-pertinent scales: combining thermal infrared and stationary stream temperature data in a novel modeling framework.

USGS Publications Warehouse

Vatland, Shane J.; Gresswell, Robert E.; Poole, Geoffrey C.

2015-01-01

Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.

[Study of Image Quality Comparison Based on the MTF Method Between Different Medical Rigid Endoscopes in an In Vitro Model].

PubMed

Wang, Yunlong; Ji, Jun; Jiang, Changsong; Huang, Zengyue

2015-04-01

This study was aimed to use the method of modulation transfer function (MTF) to compare image quality among three different Olympus medical rigid cystoscopes in an in vitro model. During the experimental processes, we firstly used three different types of cystoscopes (i. e. OLYMPUS cystourethroscopy with FOV of 12 degrees, OLYMPUS Germany A22003A and OLYMPUS A2013A) to collect raster images at different brightness with industrial camera and computer from the resolution target which is with different spatial frequency, and then we processed the collected images using MALAB software with the optical transfer function MTF to obtain the values of MTF at different brightness and different spatial frequency. We then did data mathematical statistics and compared imaging quality. The statistical data showed that all three MTF values were smaller than 1. MTF values with the spatial frequency gradually increasing would decrease approaching 0 at the same brightness. When the brightness enhanced in the same process at the same spatial frequency, MTF values showed a slowly increasing trend. The three endoscopes' MTF values were completely different. In some cases the MTF values had a large difference, and the maximum difference could reach 0.7. Conclusion can be derived from analysis of experimental data that three Olympus medical rigid cystoscopes have completely different imaging quality abilities. The No. 3 endoscope OLYMPUS A2013A has low resolution but high contrast. The No. 1 endoscope OLYMPUS cystourethroscopy with FOV of 12 degrees, on the contrary, had high resolution and lower contrast. The No. 2 endoscope OLYMPUS Germany A22003A had high contrast and high resolution, and its image quality was the best.

Comparing Lagrangian and Eulerian models for CO2 transport - a step towards Bayesian inverse modeling using WRF/STILT-VPRM

NASA Astrophysics Data System (ADS)

Pillai, D.; Gerbig, C.; Kretschmer, R.; Beck, V.; Karstens, U.; Neininger, B.; Heimann, M.

2012-10-01

We present simulations of atmospheric CO2 concentrations provided by two modeling systems, run at high spatial resolution: the Eulerian-based Weather Research Forecasting (WRF) model and the Lagrangian-based Stochastic Time-Inverted Lagrangian Transport (STILT) model, both of which are coupled to a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration Model (VPRM). The consistency of the simulations is assessed with special attention paid to the details of horizontal as well as vertical transport and mixing of CO2 concentrations in the atmosphere. The dependence of model mismatch (Eulerian vs. Lagrangian) on models' spatial resolution is further investigated. A case study using airborne measurements during which two models showed large deviations from each other is analyzed in detail as an extreme case. Using aircraft observations and pulse release simulations, we identified differences in the representation of details in the interaction between turbulent mixing and advection through wind shear as the main cause of discrepancies between WRF and STILT transport at a spatial resolution such as 2 and 6 km. Based on observations and inter-model comparisons of atmospheric CO2 concentrations, we show that a refinement of the parameterization of turbulent velocity variance and Lagrangian time-scale in STILT is needed to achieve a better match between the Eulerian and the Lagrangian transport at such a high spatial resolution (e.g. 2 and 6 km). Nevertheless, the inter-model differences in simulated CO2 time series for a tall tower observatory at Ochsenkopf in Germany are about a factor of two smaller than the model-data mismatch and about a factor of three smaller than the mismatch between the current global model simulations and the data.

Large image microscope array for the compilation of multimodality whole organ image databases.

PubMed

Namati, Eman; De Ryk, Jessica; Thiesse, Jacqueline; Towfic, Zaid; Hoffman, Eric; Mclennan, Geoffrey

2007-11-01

Three-dimensional, structural and functional digital image databases have many applications in education, research, and clinical medicine. However, to date, apart from cryosectioning, there have been no reliable means to obtain whole-organ, spatially conserving histology. Our aim was to generate a system capable of acquiring high-resolution images, featuring microscopic detail that could still be spatially correlated to the whole organ. To fulfill these objectives required the construction of a system physically capable of creating very fine whole-organ sections and collecting high-magnification and resolution digital images. We therefore designed a large image microscope array (LIMA) to serially section and image entire unembedded organs while maintaining the structural integrity of the tissue. The LIMA consists of several integrated components: a novel large-blade vibrating microtome, a 1.3 megapixel peltier cooled charge-coupled device camera, a high-magnification microscope, and a three axis gantry above the microtome. A custom control program was developed to automate the entire sectioning and automated raster-scan imaging sequence. The system is capable of sectioning unembedded soft tissue down to a thickness of 40 microm at specimen dimensions of 200 x 300 mm to a total depth of 350 mm. The LIMA system has been tested on fixed lung from sheep and mice, resulting in large high-quality image data sets, with minimal distinguishable disturbance in the delicate alveolar structures. Copyright 2007 Wiley-Liss, Inc.

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

Spatial scale and sampling resolution affect measures of gap disturbance in a lowland tropical forest: implications for understanding forest regeneration and carbon storage.

PubMed

Lobo, Elena; Dalling, James W

2014-03-07

Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition.

Long-term monitoring on environmental disasters using multi-source remote sensing technique

NASA Astrophysics Data System (ADS)

Kuo, Y. C.; Chen, C. F.

2017-12-01

Environmental disasters are extreme events within the earth's system that cause deaths and injuries to humans, as well as causing damages and losses of valuable assets, such as buildings, communication systems, farmlands, forest and etc. In disaster management, a large amount of multi-temporal spatial data is required. Multi-source remote sensing data with different spatial, spectral and temporal resolutions is widely applied on environmental disaster monitoring. With multi-source and multi-temporal high resolution images, we conduct rapid, systematic and seriate observations regarding to economic damages and environmental disasters on earth. It is based on three monitoring platforms: remote sensing, UAS (Unmanned Aircraft Systems) and ground investigation. The advantages of using UAS technology include great mobility and availability in real-time rapid and more flexible weather conditions. The system can produce long-term spatial distribution information from environmental disasters, obtaining high-resolution remote sensing data and field verification data in key monitoring areas. It also supports the prevention and control on ocean pollutions, illegally disposed wastes and pine pests in different scales. Meanwhile, digital photogrammetry can be applied on the camera inside and outside the position parameters to produce Digital Surface Model (DSM) data. The latest terrain environment information is simulated by using DSM data, and can be used as references in disaster recovery in the future.