Regional forest land cover characterisation using medium spatial resolution satellite data

USGS Publications Warehouse

Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.

2003-01-01

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

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.

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

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

PubMed

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.

Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI.

PubMed

Olafsson, Valur T; Noll, Douglas C; Fessler, Jeffrey A

2018-02-01

Penalized least-squares iterative image reconstruction algorithms used for spatial resolution-limited imaging, such as functional magnetic resonance imaging (fMRI), commonly use a quadratic roughness penalty to regularize the reconstructed images. When used for complex-valued images, the conventional roughness penalty regularizes the real and imaginary parts equally. However, these imaging methods sometimes benefit from separate penalties for each part. The spatial smoothness from the roughness penalty on the reconstructed image is dictated by the regularization parameter(s). One method to set the parameter to a desired smoothness level is to evaluate the full width at half maximum of the reconstruction method's local impulse response. Previous work has shown that when using the conventional quadratic roughness penalty, one can approximate the local impulse response using an FFT-based calculation. However, that acceleration method cannot be applied directly for separate real and imaginary regularization. This paper proposes a fast and stable calculation for this case that also uses FFT-based calculations to approximate the local impulse responses of the real and imaginary parts. This approach is demonstrated with a quadratic image reconstruction of fMRI data that uses separate roughness penalties for the real and imaginary parts.

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.

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.

Fiber optic sensors for sub-centimeter spatially resolved measurements: Review and biomedical applications

NASA Astrophysics Data System (ADS)

Tosi, Daniele; Schena, Emiliano; Molardi, Carlo; Korganbayev, Sanzhar

2018-07-01

One of the current frontier of optical fiber sensors, and a unique asset of this sensing technology is the possibility to use a whole optical fiber, or optical fiber device, as a sensor. This solution allows shifting the whole sensing paradigm, from the measurement of a single physical parameter (such as temperature, strain, vibrations, pressure) to the measurement of a spatial distribution, or profiling, of a physical parameter along the fiber length. In the recent years, several technologies are achieving this task with unprecedentedly narrow spatial resolution, ranging from the sub-millimeter to the centimeter-level. In this work, we review the main fiber optic sensing technologies that achieve a narrow spatial resolution: Fiber Bragg Grating (FBG) dense arrays, chirped FBG (CFBG) sensors, optical frequency domain reflectometry (OFDR) based on either Rayleigh scattering or reflective elements, and microwave photonics (MWP). In the second part of the work, we present the impact of spatially dense fiber optic sensors in biomedical applications, where they find the main impact, presenting the key results obtained in thermo-therapies monitoring, high-resolution diagnostic, catheters monitoring, smart textiles, and other emerging applicative fields.

Dual Double-Wedge Pseudo-Depolarizer with Anamorphic PSF

NASA Technical Reports Server (NTRS)

Hill, Peter; Thompson, Patrick

2012-01-01

A polarized scene, which may occur at oblique illumination angles, creates a radiometric signal that varies as a function of viewing angle. One common optical component that is used to minimize such an effect is a polarization scrambler or depolarizer. As part of the CLARREO mission, the SOLARIS instrument project at Goddard Space Flight Center has developed a new class of polarization scramblers using a dual double-wedge pseudo-depolarizer that produces an anamorphic point spread function (PSF). The SOLARIS instrument uses two Wollaston type scramblers in series, each with a distinct wedge angle, to image a pseudo-depolarized scene that is free of eigenstates. Since each wedge is distinct, the scrambler is able to produce an anamorphic PSF that maintains high spatial resolution in one dimension by sacrificing the spatial resolution in the other dimension. This scrambler geometry is ideal for 1-D imagers, such as pushbroom slit spectrometers, which require high spectral resolution, high spatial resolution, and low sensitivity to polarized light. Moreover, the geometry is applicable to a wide range of scientific instruments that require both high SNR (signal-to-noise ratio) and low sensitivity to polarized scenes

Long-term, high-spatial resolution carbon balance monitoring of the Amazonian frontier: Predisturbance and postdisturbance carbon emissions and uptake

NASA Astrophysics Data System (ADS)

Toomey, Michael; Roberts, Dar A.; Caviglia-Harris, Jill; Cochrane, Mark A.; Dewes, Candida F.; Harris, Daniel; Numata, Izaya; Sales, Marcio H.; Sills, Erin; Souza, Carlos M.

2013-06-01

We performed high-spatial and high-temporal resolution modeling of carbon stocks and fluxes in the state of Rondônia, Brazil for the period 1985-2009, using annual Landsat-derived land cover classifications and a modified bookkeeping modeling approach. According to these results, Rondônia contributed 3.5-4% of pantropical humid forest deforestation emissions over this period. Similar to well-known figures reported by the Brazilian Space Agency, we found a decline in deforestation rates since 2006. However, we estimate a lesser decrease, with deforestation rates continuing at levels similar to the early 2000s. Forest carbon stocks declined at an annual rate of 1.51%; emissions from postdisturbance land use nearly equaled those of the initial deforestation events. Carbon uptake by secondary forest was negligible due to limited spatial extent and high turnover rates. Net carbon emissions represented 93% of initial forest carbon stocks, due in part to repeated slash and pasture burnings and secondary forest clearing. We analyzed potential error incurred when spatially aggregating land cover by comparing results based on coarser-resolution (250 m) and full-resolution land cover products. At the coarser resolution, more than 90% of deforestation and secondary forest would be unresolvable, assuming that a 50% change threshold is necessary for detection. Therefore, we strongly suggest the use of Landsat-scale ( 30m) resolution carbon monitoring in tropical regions dominated by nonmechanized, smallholder land use change.

Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Schroedter-Homscheidt, Marion

Some applications, e.g. from traffic or energy management, require air temperature data in high spatial and temporal resolution at two metres height above the ground ( T2m), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (SEVIRI data aboard the MSG and MODIS data aboard Terra and Aqua satellites). The method consists of two parts. First, a downscaling procedure from the SEVIRI pixel resolution of several kilometres to a one kilometre spatial resolution is performed using a regression analysis between the land surface temperature ( LST) and the normalized differential vegetation index ( NDVI) acquired by the MODIS instrument. Second, the lapse rate between the LST and T2m is removed using an empirical parameterization that requires albedo, down-welling surface short-wave flux, relief characteristics and NDVI data. The method was successfully tested for Slovenia, the French region Franche-Comté and southern Germany for the period from May to December 2005, indicating that the parameterization is valid for Central Europe. This parameterization results in a root mean square deviation RMSD of 2.0 K during the daytime with a bias of -0.01 K and a correlation coefficient of 0.95. This is promising, especially considering the high temporal (30 min) and spatial resolution (1000 m) of the results.

Improving the Non-Hydrostatic Numerical Dust Model by Integrating Soil Moisture and Greenness Vegetation Fraction Data with Different Spatiotemporal Resolutions.

PubMed

Yu, Manzhu; Yang, Chaowei

2016-01-01

Dust storms are devastating natural disasters that cost billions of dollars and many human lives every year. Using the Non-Hydrostatic Mesoscale Dust Model (NMM-dust), this research studies how different spatiotemporal resolutions of two input parameters (soil moisture and greenness vegetation fraction) impact the sensitivity and accuracy of a dust model. Experiments are conducted by simulating dust concentration during July 1-7, 2014, for the target area covering part of Arizona and California (31, 37, -118, -112), with a resolution of ~ 3 km. Using ground-based and satellite observations, this research validates the temporal evolution and spatial distribution of dust storm output from the NMM-dust, and quantifies model error using measurements of four evaluation metrics (mean bias error, root mean square error, correlation coefficient and fractional gross error). Results showed that the default configuration of NMM-dust (with a low spatiotemporal resolution of both input parameters) generates an overestimation of Aerosol Optical Depth (AOD). Although it is able to qualitatively reproduce the temporal trend of the dust event, the default configuration of NMM-dust cannot fully capture its actual spatial distribution. Adjusting the spatiotemporal resolution of soil moisture and vegetation cover datasets showed that the model is sensitive to both parameters. Increasing the spatiotemporal resolution of soil moisture effectively reduces model's overestimation of AOD, while increasing the spatiotemporal resolution of vegetation cover changes the spatial distribution of reproduced dust storm. The adjustment of both parameters enables NMM-dust to capture the spatial distribution of dust storms, as well as reproducing more accurate dust concentration.

Development of ultrahigh resolution alpha particle imaging detector using 1 mm channel size Si-PM array

NASA Astrophysics Data System (ADS)

Yamamoto, Seiichi; Kawaguchi, Wataru

2018-06-01

For precise distribution measurements of alpha particles, a high-resolution alpha particle imaging detector is required. Although combining a thin scintillator with a silicon photomultiplier (Si-PM) array is a promising method for achieving high resolution, the spatial resolution is limited. Reducing the size of the Si-PM array is a possible approach to improving the spatial resolution of the alpha particle imaging detector. Consequently, we employed a 1 mm channel size Si-PM array combined with a thin ZnS(Ag) sheet to form an alpha particle imaging detector and evaluated the performance. For the developed alpha particle imaging detector, an Si-PM array with 1 mm x 1 mm channel size arranged 8 x 8 was optically coupled to a ZnS(Ag) sheet with a 1-mm-thick light guide between them. The size of the alpha particle imaging detector was 9.5 mm x 9.5 mm. The spatial resolution of the developed alpha particle imaging detector was 0.14 mm FWHM, and the energy resolution was 74% FWHM for 5.5 MeV alpha particles. The uniformity of the imaging detector at the central part of the field of view (FOV) was ±4.7%. The background count rate was 0.06 counts/min. We obtained various high-resolution phantom images for alpha particles with the developed system. We conclude that the developed imaging detector is promising for high-resolution distribution measurements of alpha particles.

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.

WE-EF-303-08: Proton Radiography Using Pencil Beam Scanning and Novel Micromegas Detectors

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

Dolney, D; Lustig, R; Teo, B

Purpose: While the energy of therapeutic proton beams can be adjusted to penetrate to any given depth in water, range uncertainties arise in patients due in part to imprecise knowledge of the stopping power of protons in human tissues. Proton radiography is one approach to reduce the beam range uncertainty, thereby allowing for a reduction in treatment margins and dose escalation. Methods: The authors have adapted a novel detector technology based on Micromesh Gaseous Structure (“Micromegas”) for proton therapy beams and have demonstrated fine spatial and time resolution of magnetically scanned proton pencil beams, as well as wide dynamic rangemore » for dosimetry. In this work, proton radiographs were obtained using Micromegas 2D planes positioned downstream of solid water assemblies. The position-sensitive monitor chambers in the IBA proton delivery nozzle provide the beam entrance position. Results: Radiography with Micromegas detectors and actively scanned beams provide spatial resolution of up to 300 µm and water-equivalent thickness (WET) resolution as good as 0.02% (60 µm out of 31 cm total thickness), with the dose delivered to the patient kept below 2 cGy. The spatial resolution as a function of sample rate and number of delivered protons is found to be near the theoretical Cramer-Rao lower bound. Using the CR bound, we argue that the imaging dose could be further lowered to 1 mGy, while still achieving sub-mm spatial resolution, by relatively simple instrumentation upgrades and beam delivery modifications. Conclusion: For proton radiography, high spatial and WET resolution can be achieved, with minimal additional dose to patient, by using magnetically scanned proton pencil beams and Micromegas detectors.« less

SU-C-207A-02: Proton Radiography Using Pencil Beam Scanning and a Novel, Low-Cost Range Telescope

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

Dolney, D; Mayers, G; Newcomer, M

Purpose: While the energy of therapeutic proton beams can be adjusted to penetrate to any given depth in water, range uncertainties arise in patients due in part to imprecise knowledge of the stopping power of protons in human tissues [1]. Proton radiography is one approach to reduce the beam range uncertainty [2], thereby allowing for a reduction in treatment margins and dose escalation. Methods: The authors have adapted a novel detector technology based on Micromesh Gaseous Structure (“Micromegas”) for proton therapy beams and have demonstrated fine spatial and time resolution of magnetically scanned proton pencil beams, as well as widemore » dynamic range for dosimetry [3]. The authors have constructed a prototype imaging system comprised of 5 Micromegas layers. Proton radiographs were obtained downstream of solid water assemblies. The position-sensitive monitor chambers in the IBA proton delivery nozzle provide the beam entrance position. Results: Our technique achieves spatial resolution as low as 300 µm and water-equivalent thickness (WET) resolution as good as 0.02% (60 µm out of 31 cm total thickness). The dose delivered to the patient is kept below 2 cGy. The spatial resolution as a function of sample rate and number of delivered protons is found to be near the theoretical Cramer-Rao lower bound. By extrapolating the CR bound, we argue that the imaging dose could be further lowered to 1 mGy, while still achieving submillimeter spatial resolution, by achievable instrumentation and beam delivery modifications. Conclusion: For proton radiography, high spatial and WET resolution can be achieved, with minimal additional dose to patient, by using magnetically scanned proton pencil beams and Micromegas detectors.« less

Study of the central part of Mare Moscoviense by combining near-infrared spectrometer, SIR-2 and Hyper Spectral Imager (HySI) data onboard Chandrayaan-1

NASA Astrophysics Data System (ADS)

Upendra Bhatt, Megha; Mall, Urs; Bugiolacchi, Roberto; Bhattacharya, Satadru

2010-05-01

The impact basins on lunar surface act as a window into the lunar interior and allow investigations of the composition of lower crust and upper mantle. Mare Moscoviense is one of the oldest impact basins on the far side of the Moon. We report on our preliminary analysis conducted in the central region of Mare Moscoviense using the near-infrared spectrometer, SIR-2 data in combination with the Hyperspectral Imager (HySI) data from the Chandrayaan-1 mission. SIR-2 is a compact, monolithic grating type point spectrometer which collected data with high spatial resolution (~200 m) and spectral resolution (6 nm) at wavelengths between 0.93 to 2.41 µm. The Indian HySI instrument mapped the lunar surface in the spectral range of 0.42 to 0.96 µm in 64 contiguous bands with a spectral bandwidth ~20 nm and spatial resolution of 80 m. We will explain the method of combining the response of SIR-2 and HySI to get a complete spectral coverage from 0.42-2.40 µm with high spatial and spectral resolution. We compare average reflectance spectra for spatially, spectrally and compositionally varying areas with the published literature.

Where can pixel counting area estimates meet user-defined accuracy requirements?

NASA Astrophysics Data System (ADS)

Waldner, François; Defourny, Pierre

2017-08-01

Pixel counting is probably the most popular way to estimate class areas from satellite-derived maps. It involves determining the number of pixels allocated to a specific thematic class and multiplying it by the pixel area. In the presence of asymmetric classification errors, the pixel counting estimator is biased. The overarching objective of this article is to define the applicability conditions of pixel counting so that the estimates are below a user-defined accuracy target. By reasoning in terms of landscape fragmentation and spatial resolution, the proposed framework decouples the resolution bias and the classifier bias from the overall classification bias. The consequence is that prior to any classification, part of the tolerated bias is already committed due to the choice of the spatial resolution of the imagery. How much classification bias is affordable depends on the joint interaction of spatial resolution and fragmentation. The method was implemented over South Africa for cropland mapping, demonstrating its operational applicability. Particular attention was paid to modeling a realistic sensor's spatial response by explicitly accounting for the effect of its point spread function. The diagnostic capabilities offered by this framework have multiple potential domains of application such as guiding users in their choice of imagery and providing guidelines for space agencies to elaborate the design specifications of future instruments.

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.

Bayesian geostatistical modelling of soil-transmitted helminth survey data in the People's Republic of China.

PubMed

Lai, Ying-Si; Zhou, Xiao-Nong; Utzinger, Jürg; Vounatsou, Penelope

2013-12-18

Soil-transmitted helminth infections affect tens of millions of individuals in the People's Republic of China (P.R. China). There is a need for high-resolution estimates of at-risk areas and number of people infected to enhance spatial targeting of control interventions. However, such information is not yet available for P.R. China. A geo-referenced database compiling surveys pertaining to soil-transmitted helminthiasis, carried out from 2000 onwards in P.R. China, was established. Bayesian geostatistical models relating the observed survey data with potential climatic, environmental and socioeconomic predictors were developed and used to predict at-risk areas at high spatial resolution. Predictors were extracted from remote sensing and other readily accessible open-source databases. Advanced Bayesian variable selection methods were employed to develop a parsimonious model. Our results indicate that the prevalence of soil-transmitted helminth infections in P.R. China considerably decreased from 2005 onwards. Yet, some 144 million people were estimated to be infected in 2010. High prevalence (>20%) of the roundworm Ascaris lumbricoides infection was predicted for large areas of Guizhou province, the southern part of Hubei and Sichuan provinces, while the northern part and the south-eastern coastal-line areas of P.R. China had low prevalence (<5%). High infection prevalence (>20%) with hookworm was found in Hainan, the eastern part of Sichuan and the southern part of Yunnan provinces. High infection prevalence (>20%) with the whipworm Trichuris trichiura was found in a few small areas of south P.R. China. Very low prevalence (<0.1%) of hookworm and whipworm infections were predicted for the northern parts of P.R. China. We present the first model-based estimates for soil-transmitted helminth infections throughout P.R. China at high spatial resolution. Our prediction maps provide useful information for the spatial targeting of soil-transmitted helminthiasis control interventions and for long-term monitoring and surveillance in the frame of enhanced efforts to control and eliminate the public health burden of these parasitic worm infections.

Bayesian geostatistical modelling of soil-transmitted helminth survey data in the People’s Republic of China

PubMed Central

2013-01-01

Background Soil-transmitted helminth infections affect tens of millions of individuals in the People’s Republic of China (P.R. China). There is a need for high-resolution estimates of at-risk areas and number of people infected to enhance spatial targeting of control interventions. However, such information is not yet available for P.R. China. Methods A geo-referenced database compiling surveys pertaining to soil-transmitted helminthiasis, carried out from 2000 onwards in P.R. China, was established. Bayesian geostatistical models relating the observed survey data with potential climatic, environmental and socioeconomic predictors were developed and used to predict at-risk areas at high spatial resolution. Predictors were extracted from remote sensing and other readily accessible open-source databases. Advanced Bayesian variable selection methods were employed to develop a parsimonious model. Results Our results indicate that the prevalence of soil-transmitted helminth infections in P.R. China considerably decreased from 2005 onwards. Yet, some 144 million people were estimated to be infected in 2010. High prevalence (>20%) of the roundworm Ascaris lumbricoides infection was predicted for large areas of Guizhou province, the southern part of Hubei and Sichuan provinces, while the northern part and the south-eastern coastal-line areas of P.R. China had low prevalence (<5%). High infection prevalence (>20%) with hookworm was found in Hainan, the eastern part of Sichuan and the southern part of Yunnan provinces. High infection prevalence (>20%) with the whipworm Trichuris trichiura was found in a few small areas of south P.R. China. Very low prevalence (<0.1%) of hookworm and whipworm infections were predicted for the northern parts of P.R. China. Conclusions We present the first model-based estimates for soil-transmitted helminth infections throughout P.R. China at high spatial resolution. Our prediction maps provide useful information for the spatial targeting of soil-transmitted helminthiasis control interventions and for long-term monitoring and surveillance in the frame of enhanced efforts to control and eliminate the public health burden of these parasitic worm infections. PMID:24350825

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited)

DOE PAGES

MacPhee, A. G.; Dymoke-Bradshaw, A. K. L.; Hares, J. D.; ...

2016-08-08

Here, we report simulationsand experiments that demonstrate an increasein spatial resolution ofthe NIF core diagnostic x-ray streak camerasby a factor of two, especially off axis. A designwas achieved by usinga corrector electron optic to flatten the field curvature at the detector planeand corroborated by measurement. In addition, particle in cell simulations were performed to identify theregions in the streak camera that contribute most to space charge blurring. Our simulations provide a tool for convolving syntheticpre-shot spectra with the instrument functionso signal levels can be set to maximize dynamic range for the relevant part of the streak record.

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

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring, which is caused by inadequate density of observations that will be mitigated once data from Sentinel-2B are available. Overall, our results highlight the potential for using moderate spatial resolution data from Landsat and Sentinel-2 for developing operational phenology algorithms and products in support of the science community.

Super-resolved all-refocused image with a plenoptic camera

NASA Astrophysics Data System (ADS)

Wang, Xiang; Li, Lin; Hou, Guangqi

2015-12-01

This paper proposes an approach to produce the super-resolution all-refocused images with the plenoptic camera. The plenoptic camera can be produced by putting a micro-lens array between the lens and the sensor in a conventional camera. This kind of camera captures both the angular and spatial information of the scene in one single shot. A sequence of digital refocused images, which are refocused at different depth, can be produced after processing the 4D light field captured by the plenoptic camera. The number of the pixels in the refocused image is the same as that of the micro-lens in the micro-lens array. Limited number of the micro-lens will result in poor low resolution refocused images. Therefore, not enough details will exist in these images. Such lost details, which are often high frequency information, are important for the in-focus part in the refocused image. We decide to super-resolve these in-focus parts. The result of image segmentation method based on random walks, which works on the depth map produced from the 4D light field data, is used to separate the foreground and background in the refocused image. And focusing evaluation function is employed to determine which refocused image owns the clearest foreground part and which one owns the clearest background part. Subsequently, we employ single image super-resolution method based on sparse signal representation to process the focusing parts in these selected refocused images. Eventually, we can obtain the super-resolved all-focus image through merging the focusing background part and the focusing foreground part in the way of digital signal processing. And more spatial details will be kept in these output images. Our method will enhance the resolution of the refocused image, and just the refocused images owning the clearest foreground and background need to be super-resolved.

Non-invasive measurement of frog skin reflectivity in high spatial resolution using a dual hyperspectral approach.

PubMed

Pinto, Francisco; Mielewczik, Michael; Liebisch, Frank; Walter, Achim; Greven, Hartmut; Rascher, Uwe

2013-01-01

Most spectral data for the amphibian integument are limited to the visible spectrum of light and have been collected using point measurements with low spatial resolution. In the present study a dual camera setup consisting of two push broom hyperspectral imaging systems was employed, which produces reflectance images between 400 and 2500 nm with high spectral and spatial resolution and a high dynamic range. We briefly introduce the system and document the high efficiency of this technique analyzing exemplarily the spectral reflectivity of the integument of three arboreal anuran species (Litoria caerulea, Agalychnis callidryas and Hyla arborea), all of which appear green to the human eye. The imaging setup generates a high number of spectral bands within seconds and allows non-invasive characterization of spectral characteristics with relatively high working distance. Despite the comparatively uniform coloration, spectral reflectivity between 700 and 1100 nm differed markedly among the species. In contrast to H. arborea, L. caerulea and A. callidryas showed reflection in this range. For all three species, reflectivity above 1100 nm is primarily defined by water absorption. Furthermore, the high resolution allowed examining even small structures such as fingers and toes, which in A. callidryas showed an increased reflectivity in the near infrared part of the spectrum. Hyperspectral imaging was found to be a very useful alternative technique combining the spectral resolution of spectrometric measurements with a higher spatial resolution. In addition, we used Digital Infrared/Red-Edge Photography as new simple method to roughly determine the near infrared reflectivity of frog specimens in field, where hyperspectral imaging is typically difficult.

Using Aerosol Reflectance for Dust Detection

NASA Astrophysics Data System (ADS)

Bahramvash Shams, S.; Mohammadzade, A.

2013-09-01

In this study we propose an approach for dust detection by aerosol reflectance over arid and urban region in clear sky condition. In urban and arid areas surface reflectance in red and infrared spectral is bright and hence shorter wavelength is required for this detections. Main step of our approach can be mentioned as: cloud mask for excluding cloudy pixels from our calculation, calculate Rayleigh path radiance, construct a surface reflectance data base, estimate aerosol reflectance, detect dust aerosol, dust detection and evaluations of dust detection. Spectral with wavelength 0.66, 0.55, 0.47 μm has been used in our dust detection. Estimating surface reflectance is the most challenging step of obtaining aerosol reflectance from top of atmosphere (TOA) reflectance. Hence for surface estimation we had created a surface reflectance database of 0.05 degree latitude by 0.05 degree longitude resolution by using minimum reflectivity technique (MRT). In order to evaluate our dust detection algorithm MODIS aerosol product MOD04 and common dust detection method named Brightness Temperature Difference (BTD) had been used. We had implemented this method to Moderate Resolution Imaging Spectroradiometer (MODIS) image of part of Iran (7 degree latitude and 8 degree longitude) spring 2005 dust phenomenon from April to June. This study uses MODIS LIB calibrated reflectance high spatial resolution (500 m) MOD02Hkm on TERRA spacecraft. Hence our dust detection spatial resolution will be higher spatial resolution than MODIS aerosol product MOD04 which has 10 × 10 km2 and BTD resolution is 1 km due to the band 29 (8.7 μm), 31 (11 μm), and 32 (12 μm) spatial resolutions.

High spatial resolution imaging for structural health monitoring based on virtual time reversal

NASA Astrophysics Data System (ADS)

Cai, Jian; Shi, Lihua; Yuan, Shenfang; Shao, Zhixue

2011-05-01

Lamb waves are widely used in structural health monitoring (SHM) of plate-like structures. Due to the dispersion effect, Lamb wavepackets will be elongated and the resolution for damage identification will be strongly affected. This effect can be automatically compensated by the time reversal process (TRP). However, the time information of the compensated waves is also removed at the same time. To improve the spatial resolution of Lamb wave detection, virtual time reversal (VTR) is presented in this paper. In VTR, a changing-element excitation and reception mechanism (CERM) rather than the traditional fixed excitation and reception mechanism (FERM) is adopted for time information conservation. Furthermore, the complicated TRP procedure is replaced by simple signal operations which can make savings in the hardware cost for recording and generating the time-reversed Lamb waves. After the effects of VTR for dispersive damage scattered signals are theoretically analyzed, the realization of VTR involving the acquisition of the transfer functions of damage detecting paths under step pulse excitation is discussed. Then, a VTR-based imaging method is developed to improve the spatial resolution of the delay-and-sum imaging with a sparse piezoelectric (PZT) wafer array. Experimental validation indicates that the damage scattered wavepackets of A0 mode in an aluminum plate are partly recompressed and focalized with their time information preserved by VTR. Both the single damage and the dual adjacent damages in the plate can be clearly displayed with high spatial resolution by the proposed VTR-based imaging method.

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.

Computation of Surface Laplacian for tri-polar ring electrodes on high-density realistic geometry head model.

PubMed

Junwei Ma; Han Yuan; Sunderam, Sridhar; Besio, Walter; Lei Ding

2017-07-01

Neural activity inside the human brain generate electrical signals that can be detected on the scalp. Electroencephalograph (EEG) is one of the most widely utilized techniques helping physicians and researchers to diagnose and understand various brain diseases. Due to its nature, EEG signals have very high temporal resolution but poor spatial resolution. To achieve higher spatial resolution, a novel tri-polar concentric ring electrode (TCRE) has been developed to directly measure Surface Laplacian (SL). The objective of the present study is to accurately calculate SL for TCRE based on a realistic geometry head model. A locally dense mesh was proposed to represent the head surface, where the local dense parts were to match the small structural components in TCRE. Other areas without dense mesh were used for the purpose of reducing computational load. We conducted computer simulations to evaluate the performance of the proposed mesh and evaluated possible numerical errors as compared with a low-density model. Finally, with achieved accuracy, we presented the computed forward lead field of SL for TCRE for the first time in a realistic geometry head model and demonstrated that it has better spatial resolution than computed SL from classic EEG recordings.

Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

USGS Publications Warehouse

Husak, G.J.; Marshall, M. T.; Michaelsen, J.; Pedreros, Diego; Funk, Christopher C.; Galu, G.

2008-01-01

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

NASA Astrophysics Data System (ADS)

Husak, G. J.; Marshall, M. T.; Michaelsen, J.; Pedreros, D.; Funk, C.; Galu, G.

2008-07-01

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

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

Deutsch, Jared L., E-mail: jdeutsch@ualberta.ca; Palmer, Kevin; Deutsch, Clayton V.

High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit inmore » South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.« less

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Dynamic granularity of imaging systems

DOE PAGES

Geissel, Matthias; Smith, Ian C.; Shores, Jonathon E.; ...

2015-11-04

Imaging systems that include a specific source, imaging concept, geometry, and detector have unique properties such as signal-to-noise ratio, dynamic range, spatial resolution, distortions, and contrast. Some of these properties are inherently connected, particularly dynamic range and spatial resolution. It must be emphasized that spatial resolution is not a single number but must be seen in the context of dynamic range and consequently is better described by a function or distribution. We introduce the “dynamic granularity” G dyn as a standardized, objective relation between a detector’s spatial resolution (granularity) and dynamic range for complex imaging systems in a given environmentmore » rather than the widely found characterization of detectors such as cameras or films by themselves. We found that this relation can partly be explained through consideration of the signal’s photon statistics, background noise, and detector sensitivity, but a comprehensive description including some unpredictable data such as dust, damages, or an unknown spectral distribution will ultimately have to be based on measurements. Measured dynamic granularities can be objectively used to assess the limits of an imaging system’s performance including all contributing noise sources and to qualify the influence of alternative components within an imaging system. Our article explains the construction criteria to formulate a dynamic granularity and compares measured dynamic granularities for different detectors used in the X-ray backlighting scheme employed at Sandia’s Z-Backlighter facility.« less

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

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

Wang, Jian; Pikridas, Michael; Spielman, Steven R.

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

DOE PAGES

Wang, Jian; Pikridas, Michael; Spielman, Steven R.; ...

2017-06-01

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

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.

Coastal circulation and sediment dynamics along West Maui, Hawaii; PART IV: measurements of waves, currents, temperature, salinity and turbidity in Honolua Bay, Northwest Maui: 2003-2004

USGS Publications Warehouse

Storlazzi, Curt D.; Presto, M. Kathy

2005-01-01

High-resolution measurements of waves, currents, water levels, temperature, salinity and turbidity were made in Honolua Bay, northwest Maui, Hawaii, during 2003 and 2004 to better understand coastal dynamics in coral reef habitats. Measurements were acquired through two different collection methods. Two hydrographic survey cruises were conducted to acquire spatially-extensive, but temporally-limited, three-dimensional measurements of currents, temperature, salinity and turbidity in the winter and summer of 2003. From mid 2003 through early 2004, a bottom-mounted instrument package was deployed in a water depth of 10 m to collect long-term, single-point high-resolution measurements of waves, currents, water levels, temperature, salinity and turbidity. The purpose of these measurements was to collect hydrographic data to learn how waves, currents and water column properties such as water temperature, salinity and turbidity vary spatially and temporally in a near-shore coral reef system adjacent to a major stream drainage. These measurements support the ongoing process studies being conducted as part of the U.S. Geological Survey (USGS) Coastal and Marine Geology Program's Coral Reef Project; the ultimate goal is to better understand the transport mechanisms of sediment, larvae, pollutants and other particles in coral reef settings. This report, the final part in a series, describes data acquisition, processing and analysis. Previous reports provided data and results on: Long-term measurements of currents, temperature, salinity and turbidity off Kahana (PART I), the spatial structure of currents, temperature, salinity and suspended sediment along West Maui (PART II), and flow and coral larvae and sediment dynamics during the 2003 summer spawning season (PART III).

Non-Invasive Measurement of Frog Skin Reflectivity in High Spatial Resolution Using a Dual Hyperspectral Approach

PubMed Central

Liebisch, Frank; Walter, Achim; Greven, Hartmut; Rascher, Uwe

2013-01-01

Background Most spectral data for the amphibian integument are limited to the visible spectrum of light and have been collected using point measurements with low spatial resolution. In the present study a dual camera setup consisting of two push broom hyperspectral imaging systems was employed, which produces reflectance images between 400 and 2500 nm with high spectral and spatial resolution and a high dynamic range. Methodology/Principal Findings We briefly introduce the system and document the high efficiency of this technique analyzing exemplarily the spectral reflectivity of the integument of three arboreal anuran species (Litoria caerulea, Agalychnis callidryas and Hyla arborea), all of which appear green to the human eye. The imaging setup generates a high number of spectral bands within seconds and allows non-invasive characterization of spectral characteristics with relatively high working distance. Despite the comparatively uniform coloration, spectral reflectivity between 700 and 1100 nm differed markedly among the species. In contrast to H. arborea, L. caerulea and A. callidryas showed reflection in this range. For all three species, reflectivity above 1100 nm is primarily defined by water absorption. Furthermore, the high resolution allowed examining even small structures such as fingers and toes, which in A. callidryas showed an increased reflectivity in the near infrared part of the spectrum. Conclusion/Significance Hyperspectral imaging was found to be a very useful alternative technique combining the spectral resolution of spectrometric measurements with a higher spatial resolution. In addition, we used Digital Infrared/Red-Edge Photography as new simple method to roughly determine the near infrared reflectivity of frog specimens in field, where hyperspectral imaging is typically difficult. PMID:24058464

Evaluations of UltraiQ software for objective ultrasound image quality assessment using images from a commercial scanner.

PubMed

Long, Zaiyang; Tradup, Donald J; Stekel, Scott F; Gorny, Krzysztof R; Hangiandreou, Nicholas J

2018-03-01

We evaluated a commercially available software package that uses B-mode images to semi-automatically measure quantitative metrics of ultrasound image quality, such as contrast response, depth of penetration (DOP), and spatial resolution (lateral, axial, and elevational). Since measurement of elevational resolution is not a part of the software package, we achieved it by acquiring phantom images with transducers tilted at 45 degrees relative to the phantom. Each measurement was assessed in terms of measurement stability, sensitivity, repeatability, and semi-automated measurement success rate. All assessments were performed on a GE Logiq E9 ultrasound system with linear (9L or 11L), curved (C1-5), and sector (S1-5) transducers, using a CIRS model 040GSE phantom. In stability tests, the measurements of contrast, DOP, and spatial resolution remained within a ±10% variation threshold in 90%, 100%, and 69% of cases, respectively. In sensitivity tests, contrast, DOP, and spatial resolution measurements followed the expected behavior in 100%, 100%, and 72% of cases, respectively. In repeatability testing, intra- and inter-individual coefficients of variations were equal to or less than 3.2%, 1.3%, and 4.4% for contrast, DOP, and spatial resolution (lateral and axial), respectively. The coefficients of variation corresponding to the elevational resolution test were all within 9.5%. Overall, in our assessment, the evaluated package performed well for objective and quantitative assessment of the above-mentioned image qualities under well-controlled acquisition conditions. We are finding it to be useful for various clinical ultrasound applications including performance comparison between scanners from different vendors. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

High quality high spatial resolution functional classification in low dose dynamic CT perfusion using singular value decomposition (SVD) and k-means clustering

NASA Astrophysics Data System (ADS)

Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc

2017-03-01

Dynamic CT perfusion acquisitions are intrinsically high-dose examinations, due to repeated scanning. To keep radiation dose under control, relatively noisy images are acquired. Noise is then further enhanced during the extraction of functional parameters from the post-processing of the time attenuation curves of the voxels (TACs) and normally some smoothing filter needs to be employed to better visualize any perfusion abnormality, but sacrificing spatial resolution. In this study we propose a new method to detect perfusion abnormalities keeping both high spatial resolution and high CNR. To do this we first perform the singular value decomposition (SVD) of the original noisy spatial temporal data matrix to extract basis functions of the TACs. Then we iteratively cluster the voxels based on a smoothed version of the three most significant singular vectors. Finally, we create high spatial resolution 3D volumes where to each voxel is assigned a distance from the centroid of each cluster, showing how functionally similar each voxel is compared to the others. The method was tested on three noisy clinical datasets: one brain perfusion case with an occlusion in the left internal carotid, one healthy brain perfusion case, and one liver case with an enhancing lesion. Our method successfully detected all perfusion abnormalities with higher spatial precision when compared to the functional maps obtained with a commercially available software. We conclude this method might be employed to have a rapid qualitative indication of functional abnormalities in low dose dynamic CT perfusion datasets. The method seems to be very robust with respect to both spatial and temporal noise and does not require any special a priori assumption. While being more robust respect to noise and with higher spatial resolution and CNR when compared to the functional maps, our method is not quantitative and a potential usage in clinical routine could be as a second reader to assist in the maps evaluation, or to guide a dataset smoothing before the modeling part.

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

2005-01-01

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

EVOLUTION OF NEAR-SURFACE FLOWS INFERRED FROM HIGH-RESOLUTION RING-DIAGRAM ANALYSIS

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

Bogart, Richard S.; Baldner, Charles S.; Basu, Sarbani

2015-07-10

Ring-diagram analysis of acoustic waves observed at the photosphere can provide a relatively robust determination of the sub-surface flows at a particular time under a particular region. The depth of penetration of the waves is related to the size of the region, hence the depth extent of the measured flows is inversely proportional to the spatial resolution. Most ring-diagram analysis has focused on regions of extent ∼15° (180 Mm) or more in order to provide reasonable mode sets for inversions. Helioseismic and Magnetic Imager (HMI) data analysis also provides a set of ring fit parameters on a scale three timesmore » smaller. These provide flow estimates for the outer 1% (7 Mm) of the Sun only, with very limited depth resolution, but with spatial resolution adequate to map structures potentially associated with the belts and regions of magnetic activity. There are a number of systematic effects affecting the determination of flows from a local helioseismic analysis of regions over different parts of the observable disk, and not all of them are well understood. In this study we characterize those systematic effects with higher spatial resolution so that they may be accounted for more effectively in mapping the temporal and spatial evolution of the flows. Leaving open the question of the mean structure of the global meridional circulation and the differential rotation, we describe the near-surface flow anomalies in time and latitude corresponding to the torsional oscillation pattern in differential rotation and analogous patterns in the meridional cell structure as observed by the Solar Dynamics Observatory/HMI.« less

A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Devadiga, Sadashiva; Tang, Yuan-Liang

1994-01-01

This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).

PubMed

Gavaret, M; Maillard, L; Jung, J

2015-03-01

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG) allow the recording of spontaneous or evoked electromagnetic brain activity with excellent temporal resolution. Data must be recorded with high temporal resolution (sampling rate) and high spatial resolution (number of channels). Data analyses are based on several steps with selection of electromagnetic signals, elaboration of a head model and use of algorithms in order to solve the inverse problem. Due to considerable technical advances in spatial resolution, these tools now represent real methods of ElectroMagnetic Source Imaging. HR-EEG and MEG constitute non-invasive and complementary examinations, characterized by distinct sensitivities according to the location and orientation of intracerebral generators. In the presurgical assessment of drug-resistant partial epilepsies, HR-EEG and MEG can characterize and localize interictal activities and thus the irritative zone. HR-EEG and MEG often yield significant additional data that are complementary to other presurgical investigations and particularly relevant in MRI-negative cases. Currently, the determination of the epileptogenic zone and functional brain mapping remain rather less well-validated indications. In France, in 2014, HR-EEG is now part of standard clinical investigation of epilepsy, while MEG remains a research technique. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Operational multisensor sea ice concentration algorithm utilizing Sentinel-1 and AMSR2 data

NASA Astrophysics Data System (ADS)

Dinessen, Frode

2017-04-01

The Norwegian Ice Service provide ice charts of the European part of the Arctic every weekday. The charts are produced from a manually interpretation of satellite data where SAR (Synthetic Aperture Radar) data plays a central role because of its high spatial resolution and Independence of cloud cover. A new chart is produced every weekday and the charts are distributed through the CMEMS portal. After the launch of Sentinel-1A and B the number of available SAR data have significant increased making it difficult to utilize all the data in a manually process. This in combination with a user demand for a more frequent update of the ice conditions, also during the weekends, have made it important to focus the development on utilizing the high resolution Sentinel-1 data in an automatic sea ice concentration analysis. The algorithm developed here is based on a multi sensor approach using an optimal interpolation to combine sea ice concentration products derived from Sentinel-1 and passive microwave data from AMSR2. The Sentinel-1 data is classified with a Bayesian SAR classification algorithm using data in extra wide mode dual polarization (HH/HV) to separate ice and water in the full 40x40 meter spatial resolution. From the classification of ice/water the sea ice concentration is estimated by calculating amount of ice within an area of 1x1 km. The AMSR2 sea ice concentration are produced as part of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) project and utilize the 89 GHz channel to produce a concentration product with a 3km spatial resolution. Results from the automatic classification will be presented.

Submicron-resolution photoacoustic microscopy of endogenous light-absorbing biomolecules

NASA Astrophysics Data System (ADS)

Zhang, Chi

Photoacoustic imaging in biomedicine has the unique advantage of probing endogenous light absorbers at various length scales with a 100% relative sensitivity. Among the several modalities of photoacoustic imaging, optical-resolution photoacoustic microscopy (OR-PAM) can achieve high spatial resolution, on the order of optical wavelength, at <1 mm depth in biological tissue (the optical ballistic regime). OR-PAM has been applied successfully to structural and functional imaging of blood vasculature and red blood cells in vivo. Any molecules which absorb sufficient light at certain wavelengths can potentially be imaged by PAM. Compared with pure optical imaging, which typically targets fluorescent markers, label-free PAM avoids the major concerns that the fluorescent labeling probes may disturb the function of biomolecules and may have an insufficient density. This dissertation aims to advance label-free OR-PAM to the subcellular scale. The first part of this dissertation describes the technological advancement of PAM yielding high spatial resolution in 3D. The lateral resolution was improved by using optical objectives with high numerical apertures for optical focusing. The axial resolution was improved by using broadband ultrasonic transducers for ultrasound detection. We achieved 220 nm lateral resolution in transmission mode, 0.43 microm lateral resolution in reflection mode, 7.6 microm axial resolution in normal tissue, and 5.8 microm axial resolution with silicone oil immersion/injection. The achieved lateral resolution and axial resolution were the finest reported at the time. With high-resolution in 3D, PAM was demonstrated to resolve cellular and subcellular structures in vivo, such as red blood cells and melanosomes in melanoma cells. Compared with previous PAM systems, our high-resolution PAM could resolve capillaries in mouse ears more clearly. As an example application, we demonstrated intracellular temperature imaging, assisted by fluorescence signal detection, with sub-degree temperature resolution and sub-micron lateral resolution. The second part of this dissertation describes the exploration of endogenous light-absorbing biomolecules for PAM. We demonstrated cytochromes and myoglobin as new absorption contrasts for PAM and identified the corresponding optimal wavelengths for imaging. Fixed fibroblasts on slides and mouse ear sections were imaged by PAM at 422 nm and 250 nm wavelengths to reveal cytoplasms and nuclei, respectively, as confirmed by standard hematoxylin and eosin (H&E) histology. By imaging a blood-perfused mouse heart at 532 nm down to 150 microm in depth, we derived the myocardial sheet thickness and the cleavage height from an undehydrated heart for the first time. The findings promote PAM at new wavelengths and open up new possibilities for characterizing biological tissue. Of particular interest, dual-wavelength PAM around 250 nm and 420 nm wavelengths is analogous to H&E histology. The last part of this dissertation describes the development of sectioning photoacoustic microscopy (SPAM), based on the advancement in spatial resolution and new contrasts for PAM, with applications in brain histology. Label-free SPAM, assisted by a microtome, acquires serial distortion-free images of a specimen on the surface. By exciting cell nuclei at 266 nm wavelength with high resolution, SPAM could pinpoint cell nuclei sensitively and specifically in the mouse brain section, as confirmed by H&E histology. SPAM was demonstrated to generate high-resolution 3D images, highlighting cell nuclei, of formalin-fixed paraffin-embedded mouse brains without tissue staining or clearing. SPAM can potentially serve as a high-throughput and minimal-artifact substitute for histology, probe many other biomolecules and cells, and become a universal tool for animal or human whole-organ microscopy, with diverse applications in life sciences.

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

An Attention-Information-Based Spatial Adaptation Framework for Browsing Videos via Mobile Devices

NASA Astrophysics Data System (ADS)

Li, Houqiang; Wang, Yi; Chen, Chang Wen

2007-12-01

With the growing popularity of personal digital assistant devices and smart phones, more and more consumers are becoming quite enthusiastic to appreciate videos via mobile devices. However, limited display size of the mobile devices has been imposing significant barriers for users to enjoy browsing high-resolution videos. In this paper, we present an attention-information-based spatial adaptation framework to address this problem. The whole framework includes two major parts: video content generation and video adaptation system. During video compression, the attention information in video sequences will be detected using an attention model and embedded into bitstreams with proposed supplement-enhanced information (SEI) structure. Furthermore, we also develop an innovative scheme to adaptively adjust quantization parameters in order to simultaneously improve the quality of overall encoding and the quality of transcoding the attention areas. When the high-resolution bitstream is transmitted to mobile users, a fast transcoding algorithm we developed earlier will be applied to generate a new bitstream for attention areas in frames. The new low-resolution bitstream containing mostly attention information, instead of the high-resolution one, will be sent to users for display on the mobile devices. Experimental results show that the proposed spatial adaptation scheme is able to improve both subjective and objective video qualities.

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited)

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

MacPhee, A. G., E-mail: macphee2@llnl.gov; Hatch, B. W.; Bell, P. M.

2016-11-15

We report simulations and experiments that demonstrate an increase in spatial resolution of the NIF core diagnostic x-ray streak cameras by at least a factor of two, especially off axis. A design was achieved by using a corrector electron optic to flatten the field curvature at the detector plane and corroborated by measurement. In addition, particle in cell simulations were performed to identify the regions in the streak camera that contribute the most to space charge blurring. These simulations provide a tool for convolving synthetic pre-shot spectra with the instrument function so signal levels can be set to maximize dynamicmore » range for the relevant part of the streak record.« less

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited).

PubMed

MacPhee, A G; Dymoke-Bradshaw, A K L; Hares, J D; Hassett, J; Hatch, B W; Meadowcroft, A L; Bell, P M; Bradley, D K; Datte, P S; Landen, O L; Palmer, N E; Piston, K W; Rekow, V V; Hilsabeck, T J; Kilkenny, J D

2016-11-01

We report simulations and experiments that demonstrate an increase in spatial resolution of the NIF core diagnostic x-ray streak cameras by at least a factor of two, especially off axis. A design was achieved by using a corrector electron optic to flatten the field curvature at the detector plane and corroborated by measurement. In addition, particle in cell simulations were performed to identify the regions in the streak camera that contribute the most to space charge blurring. These simulations provide a tool for convolving synthetic pre-shot spectra with the instrument function so signal levels can be set to maximize dynamic range for the relevant part of the streak record.

Analytical ultrasonics for evaluation of composite materials response. Part 2: Generation and detection

NASA Technical Reports Server (NTRS)

Duke, J. C., Jr.; Henneke, E. G., II

1986-01-01

To evaluate the response of composite materials, it is imperative that the input excitation as well as the observed output be well characterized. This characterization ideally should be in terms of displacements as a function of time with high spatial resolution. Additionally, the ability to prescribe these features for the excitation is highly desirable. Various methods for generating and detecting ultrasound in advanced composite materials are examined. Characterization and tailoring of input excitation is considered for contact and noncontact, mechanical, and electromechanical devices. Type of response as well as temporal and spatial resolution of detection methods are discussed as well. Results of investigations at Virginia Tech in application of these techniques to characterizing the response of advanced composites are presented.

Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas

NASA Astrophysics Data System (ADS)

Willgoose, G. R.

2006-12-01

In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically stable with time. In the second part of this presentation we will explore aspects of the calibration using data from the SASMAS site using the multiscale spatial resolution data (100m to 10km) provided by permanently installed reflectometry instruments, and how this single site measurement technique may complement satellite data.

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.

Estimation of net ecosystem production in Asia using the diagnostic-type ecosystem model with a 10 km grid-scale resolution

NASA Astrophysics Data System (ADS)

Sasai, Takahiro; Obikawa, Hiroki; Murakami, Kazutaka; Kato, Soushi; Matsunaga, Tsuneo; Nemani, Ramakrishna R.

2016-06-01

The terrestrial carbon cycle in Asia is highly uncertain, and it affects our understanding of global warming. One of the important issues is the need for an enhancement of spatial resolution, since local regions in Asia are heterogeneous with regard to meteorology, land form, and land cover type, which greatly impacts the detailed spatial patterns in its ecosystem. Thus, an important goal of this study is to reasonably reproduce the heterogeneous biogeochemical patterns in Asia by enhancing the spatial resolution of the ecosystem model biosphere model integrating eco-physiological and mechanistic approaches using satellite data (BEAMS). We estimated net ecosystem production (NEP) over eastern Asia and examined the spatial differences in the factors controlling NEP by using a 10 km grid-scale approach over two different decades (2001-2010 and 2091-2100). The present and future meteorological inputs were derived from satellite observations and the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) data set, respectively. The results showed that the present NEP in whole eastern Asia was carbon source (-214.9 TgC yr-1) and in future scenarios, the greatest positive (76.4 TgC yr-1) and least negative (-95.9 TgC yr-1) NEPs were estimated from the Representative Concentration Pathways (RCP) 6.0 and RCP8.5 scenarios, respectively. Calculated annual NEP in RCP8.5 was mostly positive in the southern part of East Asia and Southeast Asia and negative in northern and central parts of East Asia. Under the RCP scenario with higher greenhouse gases emission (RCP8.5), deciduous needleleaf and mixed forests distributed in the middle and high latitudes served as carbon source. In contrast, evergreen broadleaf forests distributed in low latitudes served as carbon sink. The sensitivity study demonstrated that the spatial tendency of NEP was largely influenced by atmospheric CO2 and temperature.

Mars Surface Compositional Units and Some Geological Implications from the Mars Express High Resolution Stereo Camera (HRSC)

NASA Astrophysics Data System (ADS)

McCord, T. B.; Combe, J.-P.; Hayne, P. O.

We are investigating the composition of the Martian surface partly by mapping the small spatial variations of water ice and salt minerals using the spectral images provided by the High Resolution Stereo Camera (HRSC). In order to identify the main mineral components, high spectral resolution data from the Observatoire pour la Mineralogie, l'Eau, les Glaces et l'Activite (OMEGA) imaging spectrometer are used. The join analysis of these two dataset makes the most of their respective abilities and, because of that, it requires a close agreement of their calibration [1]. The first part of this work is a comparison of HRSC and OMEGA measurements, exploration of atmosphere effects and checks of calibration. Then, an attempt to detect and map quantitatively at high spatial resolution (1) water ice both at the poles and in equatorial regions and (2) salts minerals is performed by exploring the spectral types evidenced in HRSC color data. For a given region, these two materials do or could represent additional endmember compositional units detectable with HRSC in addition to the basic units so far: 1) dark rock (basalt) and 2) red rock (iron oxide-rich material) [1]. Both materials also have been reported detected by OMEGA, but at much lower spatial resolution than HRSC. An ice mapping of the north polar regions is performed with OMEGA data by using a spectral index calibrated to ice fraction by using a set of linear combinations of various categories of materials with ice. In addition, a linear spectral unmixing model is used on HRSC data. Both ice fraction maps produce similar quantitative results, allowing us to interpret HRSC data at their full spatial resolution. Low-latitude sites are also explored where past but recent glacial activities have been reported as possible evidence of current water-ice. This includes looking for fresh frost and changes with time. The salt detection with HRSC firstly focused on the Candor Chasma area, where salt have been reported by using OMEGA [2]. The present work extends the analysis to other regions in order to constrain better the general geology and climate of Mars. References: [1] McCord T. B., et al. (2006). The Mars Express High Resolution Stereo Camera spectrophotometric data: Characteristics and science analysis, JGR, submitted. [2] Gendrin, A., N. Mangold, J-P. Bibring, Y. Langevin, B. Gondet, F. Poulet, G. Bonello, C. Quantin, J. Mustard, R. Arvidson, S. LeMouelic (2005), Sulfates in Martian layered terrains: The OMEGA/Mars Express View, Science, 307, 1587-1591

Daylight time-resolved photographs of lightning.

PubMed

Qrville, R E; Lala, G G; Idone, V P

1978-07-07

Lightning dart leaders and return strokes have been recorded in daylight with both good spatial resolution and good time resolution as part of the Thunder-storm Research International Program. The resulting time-resolved photographs are apparently equivalent to the best data obtained earlier only at night. Average two-dimensional return stroke velocities in four subsequent strokes between the ground and a height of 1400 meters were approximately 1.3 x 10(8) meters per second. The estimated systematic error is 10 to 15 percent.

Sensitivity of modeled estuarine circulation to spatial and temporal resolution of input meteorological forcing of a cold frontal passage

NASA Astrophysics Data System (ADS)

Weaver, Robert J.; Taeb, Peyman; Lazarus, Steven; Splitt, Michael; Holman, Bryan P.; Colvin, Jeffrey

2016-12-01

In this study, a four member ensemble of meteorological forcing is generated using the Weather Research and Forecasting (WRF) model in order to simulate a frontal passage event that impacted the Indian River Lagoon (IRL) during March 2015. The WRF model is run to provide high and low, spatial (0.005° and 0.1°) and temporal (30 min and 6 h) input wind and pressure fields. The four member ensemble is used to force the Advanced Circulation model (ADCIRC) coupled with Simulating Waves Nearshore (SWAN) and compute the hydrodynamic and wave response. Results indicate that increasing the spatial resolution of the meteorological forcing has a greater impact on the results than increasing the temporal resolution in coastal systems like the IRL where the length scales are smaller than the resolution of the operational meteorological model being used to generate the forecast. Changes in predicted water elevations are due in part to the upwind and downwind behavior of the input wind forcing. The significant wave height is more sensitive to the meteorological forcing, exhibited by greater ensemble spread throughout the simulation. It is important that the land mask, seen by the meteorological model, is representative of the geography of the coastal estuary as resolved by the hydrodynamic model. As long as the temporal resolution of the wind field captures the bulk characteristics of the frontal passage, computational resources should be focused so as to ensure that the meteorological model resolves the spatial complexities, such as the land-water interface, that drive the land use responsible for dynamic downscaling of the winds.

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.

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.

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.

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.

Desertification in the south Junggar Basin, 2000-2009: Part I. Spatial analysis and indicator retrieval

NASA Astrophysics Data System (ADS)

Jiang, Miao; Lin, Yi

2018-07-01

Desertification is a serious environmental problem that threatens ecological balance and society sustainability, and pursuit of efficient techniques for its monitoring is always highlighted. Compared to in-situ investigation, remote sensing (RS) has proved to be an efficient solution plan, particularly for large covers, whereas previous RS-based studies mostly focused on proposal and validation of various indicators for different scenarios. To comprehensively reflect desertification and project its trend, this study attempted to develop a new comprehensive RS information model, with the scenario for test deployed at the south Junggar Basin, China in the last decade (2000-2009). The premise of establishing such a model, however, is not simple, involving selection of RS images with appropriate spatial resolutions and uniform retrievals of indicators with high accuracies. To handle these fundamental problems, this Part I compared the merits and faults of MODIS and TM images in desertification characterization, by making spatial analyses including land cover patch- and pixel-scale analyses and land attribute semi-variance and scale-agreement analyses. After the MODIS images with the resolution of 250 m were identified to be the appropriate choice, multiple representative indicators including NDVI, fraction of vegetation cover, land surface temperature, albedo and soil moisture that relate to different aspects of desertification processes were uniformly retrieved by using their individual effective algorithms and downscaling. Tests showed the spatial analyses did help in ensuring the premise of the whole study and the retrievals of indicators were reliable. The contributions are of fundamental implications for improving RS-based desertification analysis and have created a firm foundation for developing a RS information model in Part II.

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.

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

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.

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.

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

High resolution remote sensing information identification for characterizing uranium mineralization setting in Namibia

NASA Astrophysics Data System (ADS)

Zhang, Jie-Lin; Wang, Jun-hu; Zhou, Mi; Huang, Yan-ju; Xuan, Yan-xiu; Wu, Ding

2011-11-01

The modern Earth Observation System (EOS) technology takes important role in the uranium geological exploration, and high resolution remote sensing as one of key parts of EOS is vital to characterize spectral and spatial information of uranium mineralization factors. Utilizing satellite high spatial resolution and hyperspectral remote sensing data (QuickBird, Radarsat2, ASTER), field spectral measurement (ASD data) and geological survey, this paper established the spectral identification characteristics of uranium mineralization factors including six different types of alaskite, lower and upper marble of Rössing formation, dolerite, alkali metasomatism, hematization and chloritization in the central zone of Damara Orogen, Namibia. Moreover, adopted the texture information identification technology, the geographical distribution zones of ore-controlling faults and boundaries between the different strata were delineated. Based on above approaches, the remote sensing geological anomaly information and image interpretation signs of uranium mineralization factors were extracted, the metallogenic conditions were evaluated, and the prospective areas have been predicted.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

SYMPOSIUM ON MULTIMODALITY CARDIOVASCULAR MOLECULAR IMAGING IMAGING TECHNOLOGY - PART 2

PubMed Central

de Kemp, Robert A.; Epstein, Frederick H.; Catana, Ciprian; Tsui, Benjamin M.W.; Ritman, Erik L.

2013-01-01

Rationale The ability to trace or identify specific molecules within a specific anatomic location provides insight into metabolic pathways, tissue components and tracing of solute transport mechanisms. With the increasing use of small animals for research such imaging must have sufficiently high spatial resolution to allow anatomic localization as well as sufficient specificity and sensitivity to provide an accurate description of the molecular distribution and concentration. Methods Imaging methods based on electromagnetic radiation, such as PET, SPECT, MRI and CT, are increasingly applicable due to recent advances in novel scanner hardware, image reconstruction software and availability of novel molecules which have enhanced sensitivity in these methodologies. Results Micro-PET has been advanced by development of detector arrays that provide higher resolution and positron emitting elements that allow new molecular tracers to be labeled. Micro-MRI has been improved in terms of spatial resolution and sensitivity by increased magnet field strength and development of special purpose coils and associated scan protocols. Of particular interest is the associated ability to image local mechanical function and solute transport processes which can be directly related to the molecular information. This is further strengthened by the synergistic integration of the PET with MRI. Micro-SPECT has been improved by use of coded aperture imaging approaches as well as image reconstruction algorithms which can better deal with the photon limited scan data. The limited spatial resolution can be partially overcome by integrating the SPECT with CT. Micro-CT by itself provides exquisite spatial resolution of anatomy, but recent developments of high spatial resolution photon counting and spectrally-sensitive imaging arrays, combined with x-ray optical devices, have promise for actual molecular identification by virtue of the chemical bond lengths of molecules, especially of bio-polymers. Conclusion With the increasing use of small animals for evaluating new clinical imaging techniques as well as providing increased insights into patho-physiological phenomena, the availability of improved detection systems, scanning protocols and associated software, the repertoire of molecular imaging is greatly increased in sensitivity and specificity. PMID:20457793

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.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

DTIC Science & Technology

1990-12-01

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

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

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

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

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

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Williamson, H. Dawn

1988-01-01

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

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

NASA Astrophysics Data System (ADS)

Zhou, J.; Ding, L.

2017-12-01

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

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

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

DTIC Science & Technology

2007-03-01

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

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.

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.

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

PubMed

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

2018-01-01

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

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

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

2018-01-01

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

Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

NASA Technical Reports Server (NTRS)

Yang, Wenli; Pham, Long; Zhao, Peisheng; Kempler, Steve; Wei, Jennifer

2016-01-01

Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

Coastal circulation and sediment dynamics in Hanalei Bay, Kauai. Part I: Measurements of waves, currents, temperature, salinity and turbidity : June - August, 2005

USGS Publications Warehouse

Storlazzi, Curt D.; Presto, M. Kathy; Logan, Joshua B.; Field, Michael E.

2006-01-01

Introduction: High-resolution measurements of waves, currents, water levels, temperature, salinity and turbidity were made in Hanalei Bay, northern Kauai, Hawaii, during the summer of 2005 to better understand coastal circulation and sediment dynamics in coral reef habitats. A series of bottom-mounted instrument packages were deployed in water depths of 10 m or less to collect long-term, high-resolution measurements of waves, currents, water levels, temperature, salinity and turbidity. These data were supplemented with a series of vertical instrument casts to characterize the vertical and spatial variability in water column properties within the bay. The purpose of these measurements was to collect hydrographic data to learn how waves, currents and water column properties vary spatially and temporally in an embayment that hosts a nearshore coral reef ecosystem adjacent to a major river drainage. These measurements support the ongoing process studies being conducted as part of the U.S. Geological Survey (USGS) Coastal and Marine Geology Program's Coral Reef Project; the ultimate goal is to better understand the transport mechanisms of sediment, larvae, pollutants and other particles in coral reef settings. This report, the first part in a series, describes data acquisition, processing and analysis.

Towards Understanding the Contribution of Waterbodies to the Methane Emissions of a Permafrost Landscape on a Regional Scale - A Case Study from the Mackenzie Delta, Canada

NASA Astrophysics Data System (ADS)

Kohnert, K.; Juhls, B.; Muster, S.; Antonova, S.; Serafimovich, A.; Sachs, T.

2017-12-01

Waterbodies in the arctic permafrost zone are considered a major source of the greenhouse gas methane (CH4). However, the spatio-temporal variability of CH4 fluxes from waterbodies complicates spatial extrapolation of CH4 measurements at individual waterbodies. Therefore, the contribution of CH4 emissions from different waterbody types to the CH4 budget of the arctic permafrost zone has not yet been well constrained. To approach this problem, our study aimed i) at understanding if there are correlations between waterbodies and CH4 fluxes on a larger spatial extent containing several waterbodies and ii) at quantifying the influence of the spatial resolution of CH4 flux data on potential relations. Our two study areas of 1000 km² each are located in the northern and central part of the Mackenzie Delta, arctic Canada. We classified the waterbodies using maps from the circum-arctic Permafrost Region Pond and Lake Database (PeRL) based on TerraSAR-X data with a spatial resolution of 2.5 m x 2.5 m. We used the backscatter signals of Sentinel-1 data to determine whether or not waterbodies were freezing to the bottom to divide them into the two classes "deep" (> 2 m depth) and "shallow" (< 2 m depth). The CH4 flux map with a spatial resolution of 100 m x 100 m was calculated from data derived via the eddy-covariance technique from two aircraft campaigns in July 2012 and 2013. We coarsened the resolution of the CH4 flux map manually, to analyze if different spatial resolutions of CH4 flux data have an effect on the relation between waterbody characteristics (coverage, number, depth, size) and CH4 flux. We found that in both study areas, there was no correlation at any spatial resolution between the area fraction covered with water and the CH4 flux at a significance level of α = 0.05. We did not find consistent correlations or patterns between the number, size or depth of waterbodies and the CH4 flux in the two study areas. While there was no significant correlation in the central study area, in the northern study area a higher number of small or shallow waterbodies slightly increased the CH4 flux, whereas deep waterbodies decreased the CH4 flux. Our results indicate that waterbodies in permafrost landscapes do not necessarily act as significant CH4 emission hotspots on a regional scale containing both waterbodies and wetlands.

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.

A review of spatial downscaling of satellite remotely sensed soil moisture

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Merlin, Olivier; Verhoest, Niko E. C.

2017-06-01

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.

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.

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).

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

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

High-Resolution Urban Greenery Mapping for Micro-Climate Modelling Based on 3d City Models

NASA Astrophysics Data System (ADS)

Hofierka, J.; Gallay, M.; Kaňuk, J.; Šupinský, J.; Šašak, J.

2017-10-01

Urban greenery has various positive micro-climate effects including mitigation of heat islands. The primary root of heat islands in cities is in absorption of solar radiation by the mass of building structures, roads and other solid materials. The absorbed heat is subsequently re-radiated into the surroundings and increases ambient temperatures. The vegetation can stop and absorb most of incoming solar radiation mostly via the photosynthesis and evapotranspiration process. However, vegetation in mild climate of Europe manifests considerable annual seasonality which can also contribute to the seasonal change in the cooling effect of the vegetation on the urban climate. Modern methods of high-resolution mapping and new generations of sensors have brought opportunity to record the dynamics of urban greenery in a high resolution in spatial, spectral, and temporal domains. In this paper, we use the case study of the city of Košice in Eastern Slovakia to demonstrate the methodology of 3D mapping and modelling the urban greenery during one vegetation season in 2016. The purpose of this monitoring is to capture 3D effects of urban greenery on spatial distribution of solar radiation in urban environment. Terrestrial laser scanning was conducted on four selected sites within Košice in ultra-high spatial resolution. The entire study area, which included these four smaller sites, comprised 4 km2 of the central part of the city was flown within a single airborne lidar and photogrammetric mission to capture the upper parts of buildings and vegetation. The acquired airborne data were used to generate a 3D city model and the time series of terrestrial lidar data were integrated with the 3D city model. The results show that the terrestrial and airborne laser scanning techniques can be effectively used to monitor seasonal changes in foliage of trees in order to assess the transmissivity of the canopy for microclimate modelling.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

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

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

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

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

PubMed Central

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

2015-01-01

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

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

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

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

2014-10-07

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

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

PubMed

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

2015-01-01

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

Morphodynamics of a tidal ridge system in the southwestern Yellow Sea: HF radar study

NASA Astrophysics Data System (ADS)

Zhong, Yao-Zhao; Li, Yan; Wu, Xiong-Bin; Gao, Shu; Zhou, Tao; Wang, Ya Ping; Gao, Jian-Hua

2018-06-01

A radial tidal ridge system is present throughout the coastal waters of the southwestern Yellow Sea (China) with varied and complicated ridges and channels between them. A newly designed ground-wave high-frequency (HF radar), with full-coverage and high spatial-temporal resolution, was employed in this study to measure the surface currents and bathymetric features correlated wave celerity in the study area from July 17 to August 6, 2011. We found that the spatial distribution pattern of the tidal channels is generally stable with periodic adjustments during a spring-neap tidal cycle and with higher degree of spatial orderliness from neap to spring tides than from spring to neap tides; the nearshore part of the channels is most stable in lateral, the middle part is relatively lateral unstable, and the offshore part changes complicatedly; flood-dominated channels and ebb-dominated ridges are identified using HF radar signals. The horizontal Kelvin number (Keh) is workable in lateral stability evaluation. This study reveals the potential of HF radar in morphodynamic studies on shallow coastal waters.

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

A merged surface reflectance product from the Landsat and Sentinel-2 Missions

NASA Astrophysics Data System (ADS)

Vermote, E.; Claverie, M.; Masek, J. G.; Becker-Reshef, I.; Justice, C. O.

2013-12-01

This project is aimed at producing a merged surface product from the Landsat and Sentinel-2 missions to ultimately achieve high temporal coverage (~2 days repeat cycle) at high spatial resolution (20-60m). The goal is to achieve a seamless/consistent stream of surface reflectance data from the different sensors. The first part of this presentation discusses the basic requirements of such a product and the necessary processing steps: mainly calibration, atmospheric corrections, BRDF effect corrections, spectral band pass adjustments and gridding. We demonstrate the performance of those different corrections by using MODIS and VIIRS (Climate Modeling Grid at 0.05deg) data globally as well as Formosat-2 (8m spatial resolution) data (one crop site in South of France where 105 scenes were acquired during 2006-2010). The consistency of the surface reflectance product from MODIS and Formosat-2 ranges from 6 to 8% relative depending on the spectral bands (Green to NIR) with a bias between 2% (NIR) to 5% (green), which is acceptable given the cumulated limitation in cross-calibration, atmospheric correction and BRDF correction. The second part is devoted to the simulation of the merged Landsat and Sentinel-2 mission by using Landsat-7, LDCM (early) and SPOT-4 Take 5 dataset. SPOT-4 Take 5 dataset is a collection of 42 sites distributed globally and systematically acquired by SPOT-4 HRV every 5 days during the decommissioning phase of the SPOT4 mission (February-May 2013). Finally, the benefits of such a merged surface reflectance at high spatial and temporal resolution are discussed within the context of the agricultural monitoring, in particular in the perspective of the GEOGLAM (Global Earth Observation for Global Land Agriculture Monitoring) project.

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

NASA Technical Reports Server (NTRS)

Sadowski, F. E.; Sarno, J. E.

1976-01-01

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

Constructing a WISE High Resolution Galaxy Atlas

NASA Technical Reports Server (NTRS)

Jarrett, T. H.; Masci, F.; Tsai, C. W.; Petty, S.; Cluver, M.; Assef, Roberto J.; Benford, D.; Blain, A.; Bridge, C.; Donoso, E.;

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.

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.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

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

Morton, April M; McManamay, Ryan A; Nagle, Nicholas N

Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may thereforemore » not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.« less

Developpement D'un Modele Climatique Regional: Fizr Simulation des Conditions de Janvier de la Cote Ouest Nord Americaine

NASA Astrophysics Data System (ADS)

Goyette, Stephane

1995-11-01

Le sujet de cette these concerne la modelisation numerique du climat regional. L'objectif principal de l'exercice est de developper un modele climatique regional ayant les capacites de simuler des phenomenes de meso-echelle spatiale. Notre domaine d'etude se situe sur la Cote Ouest nord americaine. Ce dernier a retenu notre attention a cause de la complexite du relief et de son controle sur le climat. Les raisons qui motivent cette etude sont multiples: d'une part, nous ne pouvons pas augmenter, en pratique, la faible resolution spatiale des modeles de la circulation generale de l'atmosphere (MCG) sans augmenter a outrance les couts d'integration et, d'autre part, la gestion de l'environnement exige de plus en plus de donnees climatiques regionales determinees avec une meilleure resolution spatiale. Jusqu'alors, les MCG constituaient les modeles les plus estimes pour leurs aptitudes a simuler le climat ainsi que les changements climatiques mondiaux. Toutefois, les phenomenes climatiques de fine echelle echappent encore aux MCG a cause de leur faible resolution spatiale. De plus, les repercussions socio-economiques des modifications possibles des climats sont etroitement liees a des phenomenes imperceptibles par les MCG actuels. Afin de circonvenir certains problemes inherents a la resolution, une approche pratique vise a prendre un domaine spatial limite d'un MCG et a y imbriquer un autre modele numerique possedant, lui, un maillage de haute resolution spatiale. Ce processus d'imbrication implique alors une nouvelle simulation numerique. Cette "retro-simulation" est guidee dans le domaine restreint a partir de pieces d'informations fournies par le MCG et forcee par des mecanismes pris en charge uniquement par le modele imbrique. Ainsi, afin de raffiner la precision spatiale des previsions climatiques de grande echelle, nous developpons ici un modele numerique appele FIZR, permettant d'obtenir de l'information climatique regionale valide a la fine echelle spatiale. Cette nouvelle gamme de modeles-interpolateurs imbriques qualifies d'"intelligents" fait partie de la famille des modeles dits "pilotes". L'hypothese directrice de notre etude est fondee sur la supposition que le climat de fine echelle est souvent gouverne par des forcages provenant de la surface plutot que par des transports atmospheriques de grande echelle spatiale. La technique que nous proposons vise donc a guider FIZR par la Dynamique echantillonnee d'un MCG et de la forcer par la Physique du MCG ainsi que par un forcage orographique de meso-echelle, en chacun des noeuds de la grille fine de calculs. Afin de valider la robustesse et la justesse de notre modele climatique regional, nous avons choisi la region de la Cote Ouest du continent nord americain. Elle est notamment caracterisee par une distribution geographique des precipitations et des temperatures fortement influencee par le relief sous-jacent. Les resultats d'une simulation d'un mois de janvier avec FIZR demontrent que nous pouvons simuler des champs de precipitations et de temperatures au niveau de l'abri beaucoup plus pres des observations climatiques comparativement a ceux simules a partir d'un MCG. Ces performances sont manifestement attribuees au forcage orographique de meso-echelle de meme qu'aux caracteristiques de surface determinees a fine echelle. Un modele similaire a FIZR peut, en principe, etre implante sur l'importe quel MCG, donc, tout organisme de recherche implique en modelisation numerique mondiale de grande echelle pourra se doter d'un el outil de regionalisation.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

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

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

NASA Astrophysics Data System (ADS)

Wiggins, B. B.; deSouza, Z. O.; Vadas, J.; Alexander, A.; Hudan, S.; deSouza, R. T.

2017-11-01

A second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

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.

Impairments in Precision, Rather than Spatial Strategy, Characterize Performance on the Virtual Morris Water Maze: A Case Study

PubMed Central

Kolarik, Branden S.; Shahlaie, Kiarash; Hassan, Abdul; Borders, Alyssa A.; Kaufman, Kyle C.; Gurkoff, Gene; Yonelinas, Andy P.; Ekstrom, Arne D.

2015-01-01

Damage to the medial temporal lobes produces profound amnesia, greatly impairing the ability of patients to learn about new associations and events. While studies in rodents suggest a strong link between damage to the hippocampus and the ability to navigate using distal landmarks in a spatial environment, the connection between navigation and memory in humans remains less clear. Past studies on human navigation have provided mixed findings about whether patients with damage to the medial temporal lobes can successfully acquire and navigate new spatial environments, possibly due, in part, to issues related to patient demographics and characterization of medial temporal lobe damage. Here, we report findings from a young, high functioning patient who suffered severe medial temporal lobe damage. Although the patient is densely amnestic, her ability to acquire and utilize new, but coarse, spatial “maps” appears largely intact. Specifically, a novel computational analysis focused on the precision of her spatial search revealed a significant deficit in spatial precision rather than spatial search strategy. These findings argue that an intact hippocampus in humans is not necessary for representing multiple external landmarks during spatial navigation of new environments. We suggest instead that the human hippocampus may store and represent complex high-resolution bindings of features in the environment as part of a larger role in perception, memory, and navigation. PMID:26593960

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

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.

Experimental Estimation of CLASP Spatial Resolution: Results of the Instrument's Optical Alignment

NASA Technical Reports Server (NTRS)

Giono, Gabrial; Katsukawa, Yukio; Ishikawa, Ryoko; Narukage, Noriyuki; Bando, Takamasa; Kano, Ryohei; Suematsu, Yoshinori; Kobayashi, Ken; Winebarger, Amy; Auchere, Frederic

2015-01-01

The Chromospheric Lyman-Alpha SpectroPolarimeter (CLASP) is a sounding-rocket experiment currently being built at the National Astronomical Observatory of Japan. This instrument aims to probe for the first time the magnetic field strength and orientation in the solar upper-chromosphere and lower-transition region. CLASP will measure the polarization of the Lyman-Alpha line (121.6nm) with an unprecedented accuracy, and derive the magnetic field information through the Hanle effect. Although polarization accuracy and spectral resolution are crucial for the Hanle effect detection, spatial resolution is also important to get reliable context image via the slit-jaw camera. As spatial resolution is directly related with the alignment of optics, it is also a good way of ensuring the alignment of the instrument to meet the scientific requirement. This poster will detail the experiments carried out to align CLASP's optics (telescope and spectrograph), as both part of the instrument were aligned separately. The telescope was aligned in double-pass mode, and a laser interferometer (He-Ne) was used to measure the telescope's wavefront error (WFE). The secondary mirror tilt and position were adjusted to remove comas and defocus aberrations from the WFE. Effect of gravity on the WFE measurement was estimated and the final WFE derived in zero-g condition for CLASP telescope will be presented. In addition, an estimation of the spot shape and size derived from the final WFE will also be shown. The spectrograph was aligned with a custom procedure: because Ly-??light is absorbed by air, the spectrograph's off-axis parabolic mirrors were aligned in Visible Light (VL) using a custom-made VL grating instead of the flight Ly-? grating. Results of the alignment in Visible Light will be shown and the spot shape recorded with CCDs at various position along the slit will be displayed. Results from both alignment experiment will be compared to the design requirement, and will be combined in order to estimate CLASP spatial resolution after its alignment in visible light.

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

PubMed

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

2015-10-01

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color. © The Author 2014. Published by Oxford University Press.

The spatial resolution of silicon-based electron detectors in beta-autoradiography.

PubMed

Cabello, Jorge; Wells, Kevin

2010-03-21

Thin tissue autoradiography is an imaging modality where ex-vivo tissue sections are placed in direct contact with autoradiographic film. These tissue sections contain a radiolabelled ligand bound to a specific biomolecule under study. This radioligand emits beta - or beta+ particles ionizing silver halide crystals in the film. High spatial resolution autoradiograms are obtained using low energy radioisotopes, such as (3)H where an intrinsic 0.1-1 microm spatial resolution can be achieved. Several digital alternatives have been presented over the past few years to replace conventional film but their spatial resolution has yet to equal film, although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film. It will be shown in this work how pixel size is a critical parameter for achieving high spatial resolution for low energy uncollimated beta imaging. In this work we also examine the confounding factors impeding silicon-based technologies with respect to spatial resolution. The study considers charge diffusion in silicon and detector noise, and this is applied to a range of radioisotopes typically used in autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested.

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

Scaduto, DA; Hu, Y-H; Zhao, W

Purpose: Spatial resolution in digital breast tomosynthesis (DBT) is affected by inherent/binned detector resolution, oblique entry of x-rays, and focal spot size/motion; the limited angular range further limits spatial resolution in the depth-direction. While DBT is being widely adopted clinically, imaging performance metrics and quality control protocols have not been standardized. AAPM Task Group 245 on Tomosynthesis Quality Control has been formed to address this deficiency. Methods: Methods of measuring spatial resolution are evaluated using two prototype quality control phantoms for DBT. Spatial resolution in the detector plane is measured in projection and reconstruction domains using edge-spread function (ESF), point-spreadmore » function (PSF) and modulation transfer function (MTF). Spatial resolution in the depth-direction and effective slice thickness are measured in the reconstruction domain using slice sensitivity profile (SSP) and artifact spread function (ASF). An oversampled PSF in the depth-direction is measured using a 50 µm angulated tungsten wire, from which the MTF is computed. Object-dependent PSF is derived and compared with ASF. Sensitivity of these measurements to phantom positioning, imaging conditions and reconstruction algorithms is evaluated. Results are compared from systems of varying acquisition geometry (9–25 projections over 15–60°). Dependence of measurements on feature size is investigated. Results: Measurements of spatial resolution using PSF and LSF are shown to depend on feature size; depth-direction spatial resolution measurements are shown to similarly depend on feature size for ASF, though deconvolution with an object function removes feature size-dependence. A slanted wire may be used to measure oversampled PSFs, from which MTFs may be computed for both in-plane and depth-direction resolution. Conclusion: Spatial resolution measured using PSF is object-independent with sufficiently small object; MTF is object-independent. Depth-direction spatial resolution may be measured directly using MTF or indirectly using ASF or SSP as surrogate measurements. While MTF is object-independent, it is invalid for nonlinear reconstructions.« less

Spatial and temporal remote sensing data fusion for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

The suite of available remote sensing instruments varies widely in terms of sensor characteristics, spatial resolution and acquisition frequency. For example, the Moderate-resolution Imaging Spectroradiometer (MODIS) provides daily global observations at 250m to 1km spatial resolution. While imagery...

Development of a large-area Multigap RPC with adequate spatial resolution for muon tomography

NASA Astrophysics Data System (ADS)

Wang, J.; Wang, Y.; Wang, X.; Zeng, M.; Xie, B.; Han, D.; Lyu, P.; Wang, F.; Li, Y.

2016-11-01

We study the performance of a large-area 2-D Multigap Resistive Plate Chamber (MRPC) designed for muon tomography with high spatial resolution. An efficiency up to 98% and a spatial resolution of around 270 μ m are obtained in cosmic ray and X-ray tests. The performance of the MRPC is also investigated for two working gases: standard gas and pure Freon. The result shows that the MRPC working in pure Freon can provide higher efficiency and better spatial resolution.

Improving ground-penetrating radar data in sedimentary rocks using deterministic deconvolution

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.; Byrnes, A.P.

2003-01-01

Resolution is key to confidently identifying unique geologic features using ground-penetrating radar (GPR) data. Source wavelet "ringing" (related to bandwidth) in a GPR section limits resolution because of wavelet interference, and can smear reflections in time and/or space. The resultant potential for misinterpretation limits the usefulness of GPR. Deconvolution offers the ability to compress the source wavelet and improve temporal resolution. Unlike statistical deconvolution, deterministic deconvolution is mathematically simple and stable while providing the highest possible resolution because it uses the source wavelet unique to the specific radar equipment. Source wavelets generated in, transmitted through and acquired from air allow successful application of deterministic approaches to wavelet suppression. We demonstrate the validity of using a source wavelet acquired in air as the operator for deterministic deconvolution in a field application using "400-MHz" antennas at a quarry site characterized by interbedded carbonates with shale partings. We collected GPR data on a bench adjacent to cleanly exposed quarry faces in which we placed conductive rods to provide conclusive groundtruth for this approach to deconvolution. The best deconvolution results, which are confirmed by the conductive rods for the 400-MHz antenna tests, were observed for wavelets acquired when the transmitter and receiver were separated by 0.3 m. Applying deterministic deconvolution to GPR data collected in sedimentary strata at our study site resulted in an improvement in resolution (50%) and improved spatial location (0.10-0.15 m) of geologic features compared to the same data processed without deterministic deconvolution. The effectiveness of deterministic deconvolution for increased resolution and spatial accuracy of specific geologic features is further demonstrated by comparing results of deconvolved data with nondeconvolved data acquired along a 30-m transect immediately adjacent to a fresh quarry face. The results at this site support using deterministic deconvolution, which incorporates the GPR instrument's unique source wavelet, as a standard part of routine GPR data processing. ?? 2003 Elsevier B.V. All rights reserved.

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

2012-01-01

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

Some effects of finite spatial resolution on skin friction measurements in turbulent boundary layers

NASA Technical Reports Server (NTRS)

Westphal, Russell V.

1988-01-01

The effects of finite spatial resolution often cause serious errors in measurements in turbulent boundary layers, with particularly large effects for measurements of fluctuating skin friction and velocities within the sublayer. However, classical analyses of finite spatial resolution effects have generally not accounted for the substantial inhomogeneity and anisotropy of near-wall turbulence. The present study has made use of results from recent computational simulations of wall-bounded turbulent flows to examine spatial resolution effects for measurements made at a wall using both single-sensor probes and those employing two sensing volumes in a V shape. Results are presented to show the effects of finite spatial resolution on a variety of quantitites deduced from the skin friction field.

Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes

USGS Publications Warehouse

Davies, Ashley G.; Keszthelyi, Laszlo P.; McEwen, Alfred S.

2011-01-01

We have analysed high-spatial-resolution and high-temporal-resolution temperature measurements of the active lava lake at Erta'Ale volcano, Ethiopia, to derive requirements for measuring eruption temperatures at Io's volcanoes. Lava lakes are particularly attractive targets because they are persistent in activity and large, often with ongoing lava fountain activity that exposes lava at near-eruption temperature. Using infrared thermography, we find that extracting useful temperature estimates from remote-sensing data requires (a) high spatial resolution to isolate lava fountains from adjacent cooler lava and (b) rapid acquisition of multi-color data. Because existing spacecraft data of Io's volcanoes do not meet these criteria, it is particularly important to design future instruments so that they will be able to collect such data. Near-simultaneous data at more than two relatively short wavelengths (shorter than 1 μm) are needed to constrain eruption temperatures. Resolving parts of the lava lake or fountains that are near the eruption temperature is also essential, and we provide a rough estimate of the required image scale.

Combined Exact-Repeat and Geodetic Mission Altimetry for High-Resolution Empirical Tide Mapping

NASA Astrophysics Data System (ADS)

Zaron, E. D.

2014-12-01

The configuration of present and historical exact-repeat mission (ERM) altimeter ground tracks determines the maximum resolution of empirical tidal maps obtained with ERM data. Although the mode-1 baroclinic tide is resolvable at mid-latitudes in the open ocean, the ability to detect baroclinic and barotropic tides near islands and complex coastlines is limited, in part, by ERM track density. In order to obtain higher resolution maps, the possibility of combining ERM and geodetic mission (GM) altimetry is considered, using a combination of spatial thin-plate splines and temporal harmonic analysis. Given the present spatial and temporal distribution of GM missions, it is found that GM data can contribute to resolving tidal features smaller than 75 km, provided the signal amplitude is greater than about 1 cm. Uncertainties in the mean sea surface and environmental corrections are significant components of the GM error budget, and methods to optimize data selection and along-track filtering are still being optimized. Application to two regions, Monterey Bay and Luzon Strait, finds evidence for complex tidal fields in agreement with independent observations and modeling studies.

Examining nanoparticle assemblies using high spatial resolution x-ray microtomography

NASA Astrophysics Data System (ADS)

Jenneson, P. M.; Luggar, R. D.; Morton, E. J.; Gundogdu, O.; Tüzün, U.

2004-09-01

An experimental system has been designed to examine the assembly of nanoparticles in a variety of process engineering applications. These applications include the harvesting from solutions of nanoparticles into green parts, and the subsequent sintering into finished components. The system is based on an x-ray microtomography with a spatial resolution down to 5μm. The theoretical limitations in x-ray imaging are considered to allow experimental optimization. A standard nondestructive evaluation type apparatus with a small focal-spot x-ray tube, high-resolution complementary metal oxide semiconductor flat-panel pixellated detector, and a mechanical rotational stage is used to image the static systems. Dynamic sintering processes are imaged using the same x-ray source and detector but a custom rotational stage which is contained in an environmental chamber where the temperature, atmospheric pressure, and compaction force can be controlled. Three-dimensional tomographic data sets are presented here for samples from the pharmaceutical, nutraceutical, biotechnology, and nanoparticle handling industries and show the microscopic features and defects which can be resolved with the system.

Inspecting Friction Stir Welding using Electromagnetic Probes

NASA Technical Reports Server (NTRS)

Kinchen, David G.

2004-01-01

A report describes the use of advanced electromagnetic probes to measure the dimensions, the spatial distribution of electrical conductivity, and related other properties of friction stir welds (FSWs) between parts made of the same or different aluminum alloy(s). The probes are of the type described in in another Tech Brief. To recapitulate: A probe of this type is essentially an eddy-current probe that includes a primary (driver) winding that meanders and multiple secondary (sensing) windings that meander along the primary winding. Electrical conductivity is commonly used as a measure of heat treatment and tempering of aluminum alloys, but prior to the development of these probes, the inadequate sensitivity and limited accuracy of electrical-conductivity probes precluded such use on FSWs between different aluminum alloys, and the resolution of those probes was inadequate for measurement of FSW dimensions with positions and metallurgical properties. In contrast, the present probes afford adequate accuracy and spatial resolution for the purposes of measuring the dimensions of FSW welds and correlating spatially varying electrical conductivities with metallurgical properties, including surface defects.

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

The Analysis of Burrows Recognition Accuracy in XINJIANG'S Pasture Area Based on Uav Visible Images with Different Spatial Resolution

NASA Astrophysics Data System (ADS)

Sun, D.; Zheng, J. H.; Ma, T.; Chen, J. J.; Li, X.

2018-04-01

The rodent disaster is one of the main biological disasters in grassland in northern Xinjiang. The eating and digging behaviors will cause the destruction of ground vegetation, which seriously affected the development of animal husbandry and grassland ecological security. UAV low altitude remote sensing, as an emerging technique with high spatial resolution, can effectively recognize the burrows. However, how to select the appropriate spatial resolution to monitor the calamity of the rodent disaster is the first problem we need to pay attention to. The purpose of this study is to explore the optimal spatial scale on identification of the burrows by evaluating the impact of different spatial resolution for the burrows identification accuracy. In this study, we shoot burrows from different flight heights to obtain visible images of different spatial resolution. Then an object-oriented method is used to identify the caves, and we also evaluate the accuracy of the classification. We found that the highest classification accuracy of holes, the average has reached more than 80 %. At the altitude of 24 m and the spatial resolution of 1cm, the accuracy of the classification is the highest We have created a unique and effective way to identify burrows by using UAVs visible images. We draw the following conclusion: the best spatial resolution of burrows recognition is 1 cm using DJI PHANTOM-3 UAV, and the improvement of spatial resolution does not necessarily lead to the improvement of classification accuracy. This study lays the foundation for future research and can be extended to similar studies elsewhere.

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

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

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch; Zaidi, Habib; Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailedmore » investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.« less

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

Wiley, J.C.

The author describes a general `hp` finite element method with adaptive grids. The code was based on the work of Oden, et al. The term `hp` refers to the method of spatial refinement (h), in conjunction with the order of polynomials used as a part of the finite element discretization (p). This finite element code seems to handle well the different mesh grid sizes occuring between abuted grids with different resolutions.

Measuring radiant emissions from entire prescribed fires with ground, airborne and satellite sensors - RxCADRE 2012

Treesearch

Matthew B. Dickinson; Andrew T. Hudak; Thomas Zajkowski; E. Louise Loudermilk; Wilfrid Schroeder; Luke Ellison; Robert L. Kremens; William Holley; Otto Martinez; Alexander Paxton; Benjamin C. Bright; Joseph O' Brien; Ben Hornsby; Charles Ichoku; Jason Faulring; Aaron Gerace; David Peterson; Joseph Mauceri

2016-01-01

Characterising radiation from wildland fires is an important focus of fire science because radiation relates directly to the combustion process and can be measured across a wide range of spatial extents and resolutions. As part of a more comprehensive set of measurements collected during the 2012 Prescribed Fire Combustion and Atmospheric Dynamics Research (RxCADRE)...

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

VizieR Online Data Catalog: H2CO production in HD 163296 (Carney+)

NASA Astrophysics Data System (ADS)

Carney, M. T.; Hogerheijde, M. R.; Loomis, R. A.; Salinas, V. N.; Oberg, K. I.; Qi, C.; Wilner, D. J.

2017-07-01

The FITS files contain data cubes for H2CO(30 H2CO(322-221), H2CO(321-220), C18O(2-1), and a 2D image of the 1.3mm continuum. The observations were taken with the Atacama Large Millimeter/submillimeter Array (ALMA). The formaldehyde and 1.3mm continuum data have a spatial resolution of 0.5". The C18O(2-1) data is part of the ALMA Science Verification data set released for HD 163296, with an angular resolution of 0.8". (2 data files).

Nepal and Papua Airborne Gravity Surveys

NASA Astrophysics Data System (ADS)

Olesen, A. V.; Forsberg, R.; Kasenda, F.; Einarsson, I.; Manandhar, N.

2011-12-01

Airborne gravimetry offers a fast and economic way to cover vast areas and it allows access to otherwise difficult accessible areas like mountains, jungles and the near coastal zone. It has the potential to deliver high resolution and bias free data that may bridge the spectral gap between global satellite gravity models and the high resolution gravity information embedded in digital terrain models. DTU Space has for more than a decade done airborne gravity surveys in many parts of the world. Most surveys were done with a LaCoste & Romberg S-meter updated for airborne use. This instrument has proven to deliver near bias free data when properly processed. A Chekan AM gravimeter was recently added to the airborne gravity mapping system and will potentially enhance the spatial resolution and the robustness of the system. This paper will focus on results from two recent surveys over Nepal, flown in December 2010, and over Papua (eastern Indonesia), flown in May and June 2011. Both surveys were flown with the new double gravimeter setup and initial assessment of system performance indicates improved spatial resolution compared to the single gravimeter system. Comparison to EGM08 and to the most recent GOCE models highlights the impact of the new airborne gravity data in both cases. A newly computed geoid model for Nepal based on the airborne data allows for a more precise definition of the height of Mt. Everest in a global height system. This geoid model suggests that the height of Mt. Everest should be increased by approximately 1 meter. The paper will also briefly discuss system setup and will highlight a few essential processing steps that ensure that bias problems are minimized and spatial resolution enhanced.

A forestry GIS-based study on evaluating the potential of imaging spectroscopy in mapping forest land fertility

NASA Astrophysics Data System (ADS)

Mõttus, Matti; Takala, Tuure

2014-12-01

Fertility, or the availability of nutrients and water, controls forest productivity. It affects its carbon sequestration, and thus the forest's effect on climate, as well as its commercial value. Although the availability of nutrients cannot be measured directly using remote sensing methods, fertility alters several vegetation traits detectable from the reflectance spectra of the forest stand, including its pigment content and water stress. However, forest reflectance is also influenced by other factors, such as species composition and stand age. Here, we present a case study demonstrating how data obtained using imaging spectroscopy is correlated with site fertility. The study was carried out in Hyytiälä, Finland, in the southern boreal forest zone. We used a database of state-owned forest stands including basic forestry variables and a site fertility index. To test the suitability of imaging spectroscopy with different spatial and spectral resolutions for site fertility mapping, we performed two airborne acquisitions using different sensor configurations. First, the sensor was flown at a high altitude with high spectral resolution resulting in a pixel size in the order of a tree crown. Next, the same area was flown to provide reflectance data with sub-meter spatial resolution. However, to maintain usable signal-to-noise ratios, several spectral channels inside the sensor were combined, thus reducing spectral resolution. We correlated a number of narrowband vegetation indices (describing canopy biochemical composition, structure, and photosynthetic activity) on site fertility. Overall, site fertility had a significant influence on the vegetation indices but the strength of the correlation depended on dominant species. We found that high spatial resolution data calculated from the spectra of sunlit parts of tree crowns had the strongest correlation with site fertility.

Sea Ice Pressure Ridge Height Distributions for the Arctic Ocean in Winter, Just Prior to Melt

NASA Astrophysics Data System (ADS)

Duncan, K.; Farrell, S. L.; Richter-Menge, J.; Hutchings, J.; Dominguez, R.; Connor, L. N.

2016-12-01

Pressure ridges are one of the most dominant morphological features of the Arctic sea ice pack. An impediment to navigation, pressure ridges are also of climatological interest since they impact the mass, energy and momentum transfer budgets for the Arctic Ocean. Understanding the regional and seasonal distributions of ridge sail heights, and their variability, is important for quantifying total sea ice mass, and for improved treatment of sea ice dynamics in high-resolution numerical models. Observations of sail heights from airborne and ship-based platforms have been documented in previous studies, however studies with both high spatial and temporal resolution, across multiple regions of the Arctic, are only recently possible with the advent of dedicated airborne surveys of the Arctic Ocean. In this study we present results from the high-resolution Digital Mapping System (DMS), flown as part of NASA's Operation IceBridge missions. We use DMS imagery to calculate ridge sail heights, derived from the shadows they cast combined with the solar elevation angle and the known pixel size of each image. Our analyses describe sea ice conditions at the end of winter, during the months of March and April, over a period spanning seven years, from 2010 to 2016. The high spatial resolution (0.1m) and temporal extent (seven years) of the DMS data set provides, for the first time, the full sail-height distributions of both first-year and multi-year sea ice. We present the inter-annual variability in sail height distributions for both the Central Arctic and the Beaufort and Chukchi Seas. We validate our results via comparison with spatially coincident high-resolution SAR imagery and airborne laser altimeter elevations.

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.

How Cities Breathe: Ground-Referenced, Airborne Hyperspectral Imaging Precursor Measurements To Space-Based Monitoring

NASA Technical Reports Server (NTRS)

Leifer, Ira; Tratt, David; Quattrochi, Dale; Bovensmann, Heinrich; Gerilowski, Konstantin; Buchwitz, Michael; Burrows, John

2013-01-01

Methane's (CH4) large global warming potential (Shindell et al., 2012) and likely increasing future emissions due to global warming feedbacks emphasize its importance to anthropogenic greenhouse warming (IPCC, 2007). Furthermore, CH4 regulation has far greater near-term climate change mitigation potential versus carbon dioxide CO2, the other major anthropogenic Greenhouse Gas (GHG) (Shindell et al., 2009). Uncertainties in CH4 budgets arise from the poor state of knowledge of CH4 sources - in part from a lack of sufficiently accurate assessments of the temporal and spatial emissions and controlling factors of highly variable anthropogenic and natural CH4 surface fluxes (IPCC, 2007) and the lack of global-scale (satellite) data at sufficiently high spatial resolution to resolve sources. Many important methane (and other trace gases) sources arise from urban and mega-urban landscapes where anthropogenic activities are centered - most of humanity lives in urban areas. Studying these complex landscape tapestries is challenged by a wide and varied range of activities at small spatial scale, and difficulty in obtaining up-to-date landuse data in the developed world - a key desire of policy makers towards development of effective regulations. In the developing world, challenges are multiplied with additional political access challenges. As high spatial resolution satellite and airborne data has become available, activity mapping applications have blossomed - i.e., Google maps; however, tap a minute fraction of remote sensing capabilities due to limited (three band) spectral information. Next generation approaches that incorporate high spatial resolution hyperspectral and ultraspectral data will allow detangling of the highly heterogeneous usage megacity patterns by providing diagnostic identification of chemical composition from solids (refs) to gases (refs). To properly enable these next generation technologies for megacity include atmospheric radiative transfer modeling the complex and often aerosol laden, humid, urban microclimates, atmospheric transport and profile monitoring, spatial resolution, temporal cycles (diurnal and seasonal which involve interactions with the surrounding environment diurnal and seasonal cycles) and representative measurement approaches given traffic realities. Promising approaches incorporate contemporaneous airborne remote sensing and in situ measurements, nocturnal surface surveys, with ground station measurement

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

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

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

Techniques for studying gravity waves and turbulence: Vertical wind speed power spectra from the troposphere and stratosphere obtained under light wind conditions

NASA Technical Reports Server (NTRS)

Ecklund, W. L.; Balsley, B. B.; Crochet, M.; Carter, D. A.; Riddle, A. C.; Garello, R.

1983-01-01

A joint France/U.S. experiment was conducted near the mouth of the Rhone river in southern France as part of the ALPEX program. This experiment used 3 vertically directed 50 MHz radars separated by 4 to 6 km. The main purpose of this experiment was to study the spatial characteristics of gravity waves. The good height resolution (750 meters) and time resolution (1 minute) and the continuous operation over many weeks have yielded high resolution vertical wind speed power spectra under a variety of synoptic conditions. Vertical spectra obtained during very quiet (low wind) conditions in the troposphere and lower stratosphere from a single site are presented.

Super-resolution optical microscopy for studying membrane structure and dynamics.

PubMed

Sezgin, Erdinc

2017-07-12

Investigation of cell membrane structure and dynamics requires high spatial and temporal resolution. The spatial resolution of conventional light microscopy is limited due to the diffraction of light. However, recent developments in microscopy enabled us to access the nano-scale regime spatially, thus to elucidate the nanoscopic structures in the cellular membranes. In this review, we will explain the resolution limit, address the working principles of the most commonly used super-resolution microscopy techniques and summarise their recent applications in the biomembrane field.

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

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.

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge.

PubMed

Hernández, Jaime; Núñez, Ignacia; Bacigalupo, Antonella; Cattan, Pedro E

2013-05-31

Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study's methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases.

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge

PubMed Central

2013-01-01

Background Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Methods Vector’s locations were obtained with a rural householders’ survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. Results The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. Conclusions The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. PMID:23724993

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

USGS Publications Warehouse

Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

2014-01-01

Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE PAGES

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei; ...

2017-05-11

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

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

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method

NASA Astrophysics Data System (ADS)

Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.

2017-02-01

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

Stride search: A general algorithm for storm detection in high-resolution climate data

DOE PAGES

Bosler, Peter A.; Roesler, Erika L.; Taylor, Mark A.; ...

2016-04-13

This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclonemore » detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.« less

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

NASA Technical Reports Server (NTRS)

Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.

1992-01-01

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Spatial resolution of a spherical x-ray crystal spectrometer at various magnifications

DOE PAGES

Gao, Lan; Hill, K. W.; Bitter, M.; ...

2016-08-23

Here, a high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ 2 rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystalmore » (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications ( M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Emotional cues enhance the attentional effects on spatial and temporal resolution.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-12-01

In the present study, we demonstrated that the emotional significance of a spatial cue enhances the effect of covert attention on spatial and temporal resolution (i.e., our ability to discriminate small spatial details and fast temporal flicker). Our results indicated that fearful face cues, as compared with neutral face cues, enhanced the attentional benefits in spatial resolution but also enhanced the attentional deficits in temporal resolution. Furthermore, we observed that the overall magnitudes of individuals' attentional effects correlated strongly with the magnitude of the emotion × attention interaction effect. Combined, these findings provide strong support for the idea that emotion enhances the strength of a cue's attentional response.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Teuling, Adriaan J.; Torfs, Paul J. J. F.; Uijlenhoet, Remko; Mizukami, Naoki; Clark, Martyn P.

2016-03-01

A meta-analysis on 192 peer-reviewed articles reporting on applications of the variable infiltration capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, L. A.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.; Mizukami, N.; Clark, M. P.

2015-12-01

A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

Estimation of wind regime from combination of RCM and NWP data in the Gulf of Riga (Baltic Sea)

NASA Astrophysics Data System (ADS)

Sile, T.; Sennikovs, J.; Bethers, U.

2012-04-01

Gulf of Riga is a semi-enclosed gulf located in the Eastern part of the Baltic Sea. Reliable wind climate data is crucial for the development of wind energy. The objective of this study is to create high resolution wind parameter datasets for the Gulf of Riga using climate and numerical weather prediction (NWP) models as an alternative to methods that rely on observations with the expectation of benefit from comparing different approaches. The models used for the estimation of the wind regime are an ensemble of Regional Climate Models (RCM, ENSEMBLES, 23 runs are considered) and high resolution NWP data. Future projections provided by RCM are of interest however their spatial resolution is unsatisfactory. We describe a method of spatial refinement of RCM data using NWP data to resolve small scale features. We apply the method of RCM bias correction (Sennikovs and Bethers, 2009) previously used for temperature and precipitation to wind data and use NWP data instead of observations. The refinement function is calculated using contemporary climate (1981- 2010) and later applied to RCM near future (2021 - 2050) projections to produce a dataset with the same resolution as NWP data. This method corrects for RCM biases that were shown to be present in the initial analysis and inter-model statistical analysis was carried out to estimate uncertainty. Using the datasets produced by this method the current and future projections of wind speed and wind energy density are calculated. Acknowledgments: This research is part of the GORWIND (The Gulf of Riga as a Resource for Wind Energy) project (EU34711). The ENSEMBLES data used in this work was funded by the EU FP6 Integrated Project ENSEMBLES (Contract number 505539) whose support is gratefully acknowledged.

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

PubMed Central

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A.; Bandera, Antonio

2016-01-01

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. PMID:27898029

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid.

PubMed

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A; Bandera, Antonio

2016-11-26

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms.

Monitoring African savanna water use and water stress from local to regional scale: supporting rangeland management (pilot experience in Kruger National Park, South Africa).

NASA Astrophysics Data System (ADS)

Andreu, Ana; Dube, Timothy; Nieto, Hector; González-Dugo, Maria P.; Hülsmann, Stephan

2017-04-01

Drought periods and erratic rainfall patterns across large parts of Africa result in water-limited environments like savannas, highly sensitive to land management practices and changes in climate. Over the Southern part of the continent, savannas are key productive landscapes supporting livestock, crops and rural livelihoods. Monitoring water use and the natural vegetation stress over these semi-arid complex ecosystems can support rangeland management, to maintain long-term productivity. However, the precision/resolution/accuracy of the information required for management will differ at each scale: farm-local (e.g. evaluating the effect of management practices, livestock densities, crop production and grazing), to watershed (e.g. evaluating the effect of fire, detection of vulnerable areas) and regional (e.g. early prediction of drought). To overcome these constrains, TIGER project 401 combines two approaches that take advantage of different conceptual and operational capabilities of Earth Observation data sources. Sentinel 2 high spatial (10 m) and temporal ( 5 days) resolution VIS/NIR images are used for a continuous monitoring of vegetation cover and unstressed evapotranspiration (ET - using Kc-FAO56 method). This methodology will provide the required resolution for farm-local scales, tracking separately the seasonal variations of each canopy layer growth (grass and trees). Meanwhile, lower spatial resolution (1 km) MODIS thermal data allow to determine a regional water stress index (ratio between actual ET, estimated using Two Source Energy Balance-TSEB, and potential ET), supporting the detection of vulnerable areas. The model framework was tested and validated over savanna-type experimental areas (Skukuza & Malopeni), and later applied over the whole Kruger National Park during 2015-2016.

Imaging of spatial distributions of the millimeter wave intensity by using visible continuum radiation from a discharge in a Cs–Xe mixture. Part I: Review of the method and its fundamentals

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

Gitlin, M. S., E-mail: gitlin@appl.sci-nnov.ru

The first part of the review is presented which is dedicated to the time-resolved method of imaging and measuring the spatial distribution of the intensity of millimeter waves by using visible continuum (VC) emitted by the positive column (PC) of a dc discharge in a mixture of cesium vapor with xenon. The review focuses on the operating principles, fundamentals, and applications of this new technique. The design of the discharge tube and experimental setup used to create a wide homogeneous plasma slab with the help of the Cs–Xe discharge at a gas pressure of 45 Torr are described. The millimeter-wavemore » effects on the plasma slab are studied experimentally. The mechanism of microwave-induced variations in the VC brightness and the causes of violation of the local relation between the VC brightness and the intensity of millimeter waves are discussed. Experiments on the imaging of the field patterns of horn antennas and quasi-optical beams demonstrate that this technique can be used for good-quality imaging of millimeter-wave beams in the entire millimeter-wavelength band. The method has a microsecond temporal resolution and a spatial resolution of about 2 mm. Energy sensitivities of about 10 μJ/cm{sup 2} in the Ka-band and about 200 μJ/cm{sup 2} in the D-band have been demonstrated.« less

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Spatial resolution limits for the isotropic-3D PET detector X’tal cube

NASA Astrophysics Data System (ADS)

Yoshida, Eiji; Tashima, Hideaki; Hirano, Yoshiyuki; Inadama, Naoko; Nishikido, Fumihiko; Murayama, Hideo; Yamaya, Taiga

2013-11-01

Positron emission tomography (PET) has become a popular imaging method in metabolism, neuroscience, and molecular imaging. For dedicated human brain and small animal PET scanners, high spatial resolution is needed to visualize small objects. To improve the spatial resolution, we are developing the X’tal cube, which is our new PET detector to achieve isotropic 3D positioning detectability. We have shown that the X’tal cube can achieve 1 mm3 uniform crystal identification performance with the Anger-type calculation even at the block edges. We plan to develop the X’tal cube with even smaller 3D grids for sub-millimeter crystal identification. In this work, we investigate spatial resolution of a PET scanner based on the X’tal cube using Monte Carlo simulations for predicting resolution performance in smaller 3D grids. For spatial resolution evaluation, a point source emitting 511 keV photons was simulated by GATE for all physical processes involved in emission and interaction of positrons. We simulated two types of animal PET scanners. The first PET scanner had a detector ring 14.6 cm in diameter composed of 18 detectors. The second PET scanner had a detector ring 7.8 cm in diameter composed of 12 detectors. After the GATE simulations, we converted the interacting 3D position information to digitalized positions for realistic segmented crystals. We simulated several X’tal cubes with cubic crystals from (0.5 mm)3 to (2 mm)3 in size. Also, for evaluating the effect of DOI resolution, we simulated several X’tal cubes with crystal thickness from (0.5 mm)3 to (9 mm)3. We showed that sub-millimeter spatial resolution was possible using cubic crystals smaller than (1.0 mm)3 even with the assumed physical processes. Also, the weighted average spatial resolutions of both PET scanners with (0.5 mm)3 cubic crystals were 0.53 mm (14.6 cm ring diameter) and 0.48 mm (7.8 cm ring diameter). For the 7.8 cm ring diameter, spatial resolution with 0.5×0.5×1.0 mm3 crystals was improved 39% relative to the (1 mm)3 cubic crystals. On the other hand, spatial resolution with (0.5 mm)3 cubic crystals was improved 47% relative to the (1 mm)3 cubic crystals. The X’tal cube promises better spatial resolution for the 3D crystal block with isotropic resolution.

Rocket measurements of electron density irregularities during MAC/SINE

NASA Technical Reports Server (NTRS)

Ulwick, J. C.

1989-01-01

Four Super Arcas rockets were launched at the Andoya Rocket Range, Norway, as part of the MAC/SINE campaign to measure electron density irregularities with high spatial resolution in the cold summer polar mesosphere. They were launched as part of two salvos: the turbulent/gravity wave salvo (3 rockets) and the EISCAT/SOUSY radar salvo (one rocket). In both salvos meteorological rockets, measuring temperature and winds, were also launched and the SOUSY radar, located near the launch site, measured mesospheric turbulence. Electron density irregularities and strong gradients were measured by the rocket probes in the region of most intense backscatter observed by the radar. The electron density profiles (8 to 4 on ascent and 4 on descent) show very different characteristics in the peak scattering region and show marked spatial and temporal variability. These data are intercompared and discussed.

Geo-PET: A novel generic organ-pet for small animal organs and tissues

NASA Astrophysics Data System (ADS)

Sensoy, Levent

Reconstructed tomographic image resolution of small animal PET imaging systems is improving with advances in radiation detector development. However the trend towards higher resolution systems has come with an increase in price and system complexity. Recent developments in the area of solid-state photomultiplication devices like silicon photomultiplier arrays (SPMA) are creating opportunities for new high performance tools for PET scanner design. Imaging of excised small animal organs and tissues has been used as part of post-mortem studies in order to gain detailed, high-resolution anatomical information on sacrificed animals. However, this kind of ex-vivo specimen imaging has largely been limited to ultra-high resolution muCT. The inherent limitations to PET resolution have, to date, excluded PET imaging from these ex-vivo imaging studies. In this work, we leverage the diminishing physical size of current generation SPMA designs to create a very small, simple, and high-resolution prototype detector system targeting ex-vivo tomographic imaging of small animal organs and tissues. We investigate sensitivity, spatial resolution, and the reconstructed image quality of a prototype small animal PET scanner designed specifically for imaging of excised murine tissue and organs. We aim to demonstrate that a cost-effective silicon photomultiplier (SiPM) array based design with thin crystals (2 mm) to minimize depth of interaction errors might be able to achieve sub-millimeter resolution. We hypothesize that the substantial decrease in sensitivity associated with the thin crystals can be compensated for with increased solid angle detection, longer acquisitions, higher activity and wider acceptance energy windows (due to minimal scatter from excised organs). The constructed system has a functional field of view (FoV) of 40 mm diameter, which is adequate for most small animal specimen studies. We perform both analytical (3D-FBP) and iterative (ML-EM) methods in order to reconstruct tomographic images. Results demonstrate good agreement between the simulation and the prototype. Our detector system with pixelated crystals is able to separate small objects as close as 1.25 mm apart, whereas spatial resolution converges to the theoretical limit of 1.6 mm (half the size of the smallest detecting element), which is to comparable to the spatial resolution of the existing commercial small animal PET systems. Better system spatial resolution is achievable with new generation SiPM detector boards with 1 mm x 1 mm cell dimensions. We demonstrate through Monte Carlo simulations that it is possible to achieve sub-millimeter spatial image resolution (0.7 mm for our scanner) in complex objects using monolithic crystals and exploiting the light-sharing mechanism among the neighboring detector cells. Results also suggest that scanner (or object) rotation minimizes artifacts arising from poor angular sampling, which is even more significant in smaller PET designs as the gaps between the sensitive regions of the detector have a more exaggerated effect on the overall reconstructed image quality when the design is more compact. Sensitivity of the system, on the other hand, can be doubled by adding two additional detector heads resulting in a, fully closed, 4? geometry.

Spatial Soliton Interactions for Photonic Switching. Part I

DTIC Science & Technology

2000-03-07

technique , a fully vectorial, first-order nonlinear wave equation that consistently includes terms two -orders beyond the slowly-varying amplitude , slowly...by using two tunable mode-locked Er-doped fiber lasers ," in Conference on Optical Fiber Communications, OSA Technical Digest Series, vol. 4, 1994...instead, based on optical logic gates. In addition, optical logic could be used for contention resolution, real-time encryption /decryption, and other

Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

NASA Astrophysics Data System (ADS)

Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

2017-12-01

Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.

Spatial resolution limitation of liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

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

2004-10-01

The effect of fringing electric fields in a liquid crystal (LC) Optical Phased Array (OPA), also referred to as a spatial light modulator (SLM), is a governing factor that determines the diffraction efficiency (DE) of the LC OPA for high resolution spatial phase modulation. In this article, the fringing field effect in a high resolution LC OPA is studied by accurate modeling the DE of the LC blazed gratings by LC director simulation and Finite Difference Time Domain (FDTD) simulation. Influence factors that contribute significantly to the DE are discussed. Such results provide fundamental understanding for high resolution LC devices.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

NASA Technical Reports Server (NTRS)

Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.

2013-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Regional Specific Evidence for Memory-Load Dependent Activity in the Dorsal Subiculum and the Lateral Entorhinal Cortex

PubMed Central

Ku, Shih-pi; Nakamura, Nozomu H.; Maingret, Nicolas; Mahnke, Liv; Yoshida, Motoharu; Sauvage, Magdalena M.

2017-01-01

The subiculum and the lateral entorhinal cortex (LEC) are the main output areas of the hippocampus which contribute to spatial and non-spatial memory. The proximal part of the subiculum (bordering CA1) receives heavy projections from the perirhinal cortex and the distal part of CA1 (bordering the subiculum), both known for their ties to object recognition memory. However, the extent to which the proximal subiculum contributes to non-spatial memory is still unclear. Comparatively, the involvement of the LEC in non-spatial information processing is quite well known. However, very few studies have investigated its role within the frame of memory function. Thus, it is not known whether its contribution depends on memory load. In addition, the deep layers of the EC have been shown to be predictive of subsequent memory performance, but not its superficial layers. Hence, here we tested the extent to which the proximal part of the subiculum and the superficial and deep layers of the LEC contribute to non-spatial memory, and whether this contribution depends on the memory load of the task. To do so, we imaged brain activity at cellular resolution in these areas in rats performing a delayed nonmatch to sample task based on odors with two different memory loads (5 or 10 odors). This imaging technique is based on the detection of the RNA of the immediate-early gene Arc, which is especially tied to synaptic plasticity and behavioral demands, and is commonly used to map activity in the medial temporal lobe. We report for the first time that the proximal part of the subiculum is recruited in a memory-load dependent manner and the deep layers of the LEC engaged under high memory load conditions during the retrieval of non-spatial memory, thus shedding light on the specific networks contributing to non-spatial memory retrieval. PMID:28790897

Regional Specific Evidence for Memory-Load Dependent Activity in the Dorsal Subiculum and the Lateral Entorhinal Cortex.

PubMed

Ku, Shih-Pi; Nakamura, Nozomu H; Maingret, Nicolas; Mahnke, Liv; Yoshida, Motoharu; Sauvage, Magdalena M

2017-01-01

The subiculum and the lateral entorhinal cortex (LEC) are the main output areas of the hippocampus which contribute to spatial and non-spatial memory. The proximal part of the subiculum (bordering CA1) receives heavy projections from the perirhinal cortex and the distal part of CA1 (bordering the subiculum), both known for their ties to object recognition memory. However, the extent to which the proximal subiculum contributes to non-spatial memory is still unclear. Comparatively, the involvement of the LEC in non-spatial information processing is quite well known. However, very few studies have investigated its role within the frame of memory function. Thus, it is not known whether its contribution depends on memory load. In addition, the deep layers of the EC have been shown to be predictive of subsequent memory performance, but not its superficial layers. Hence, here we tested the extent to which the proximal part of the subiculum and the superficial and deep layers of the LEC contribute to non-spatial memory, and whether this contribution depends on the memory load of the task. To do so, we imaged brain activity at cellular resolution in these areas in rats performing a delayed nonmatch to sample task based on odors with two different memory loads (5 or 10 odors). This imaging technique is based on the detection of the RNA of the immediate-early gene Arc , which is especially tied to synaptic plasticity and behavioral demands, and is commonly used to map activity in the medial temporal lobe. We report for the first time that the proximal part of the subiculum is recruited in a memory-load dependent manner and the deep layers of the LEC engaged under high memory load conditions during the retrieval of non-spatial memory, thus shedding light on the specific networks contributing to non-spatial memory retrieval.

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

Multi-class geospatial object detection and geographic image classification based on collection of part detectors

NASA Astrophysics Data System (ADS)

Cheng, Gong; Han, Junwei; Zhou, Peicheng; Guo, Lei

2014-12-01

The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of a set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learn a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

Advanced Extraction of Spatial Information from High Resolution Satellite Data

NASA Astrophysics Data System (ADS)

Pour, T.; Burian, J.; Miřijovský, J.

2016-06-01

In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

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

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

The spatial resolution of a rotating gamma camera tomographic facility.

PubMed

Webb, S; Flower, M A; Ott, R J; Leach, M O; Inamdar, R

1983-12-01

An important feature determining the spatial resolution in transverse sections reconstructed by convolution and back-projection is the frequency filter corresponding to the convolution kernel. Equations have been derived giving the theoretical spatial resolution, for a perfect detector and noise-free data, using four filter functions. Experiments have shown that physical constraints will always limit the resolution that can be achieved with a given system. The experiments indicate that the region of the frequency spectrum between KN/2 and KN where KN is the Nyquist frequency does not contribute significantly to resolution. In order to investigate the physical effect of these filter functions, the spatial resolution of reconstructed images obtained with a GE 400T rotating gamma camera has been measured. The results obtained serve as an aid to choosing appropriate reconstruction filters for use with a rotating gamma camera system.

A high time and spatial resolution MRPC designed for muon tomography

NASA Astrophysics Data System (ADS)

Shi, L.; Wang, Y.; Huang, X.; Wang, X.; Zhu, W.; Li, Y.; Cheng, J.

2014-12-01

A prototype of cosmic muon scattering tomography system has been set up in Tsinghua University in Beijing. Multi-gap Resistive Plate Chamber (MRPC) is used in the system to get the muon tracks. Compared with other detectors, MRPC can not only provide the track but also the Time of Flight (ToF) between two detectors which can estimate the energy of particles. To get a more accurate track and higher efficiency of the tomography system, a new type of high time and two-dimensional spatial resolution MRPC has been developed. A series of experiments have been done to measure the efficiency, time resolution and spatial resolution. The results show that the efficiency can reach 95% and its time resolution is around 65 ps. The cluster size is around 4 and the spatial resolution can reach 200 μ m.

150-μm Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images.

PubMed

Leng, Shuai; Rajendran, Kishore; Gong, Hao; Zhou, Wei; Halaweish, Ahmed F; Henning, Andre; Kappler, Steffen; Baer, Matthias; Fletcher, Joel G; McCollough, Cynthia H

2018-05-28

The aims of this study were to quantitatively assess two new scan modes on a photon-counting detector computed tomography system, each designed to maximize spatial resolution, and to qualitatively demonstrate potential clinical impact using patient data. This Health Insurance Portability Act-compliant study was approved by our institutional review board. Two high-spatial-resolution scan modes (Sharp and UHR) were evaluated using phantoms to quantify spatial resolution and image noise, and results were compared with the standard mode (Macro). Patients were scanned using a conventional energy-integrating detector scanner and the photon-counting detector scanner using the same radiation dose. In first patient images, anatomic details were qualitatively evaluated to demonstrate potential clinical impact. Sharp and UHR modes had a 69% and 87% improvement in in-plane spatial resolution, respectively, compared with Macro mode (10% modulation-translation-function values of 16.05, 17.69, and 9.48 lp/cm, respectively). The cutoff spatial frequency of the UHR mode (32.4 lp/cm) corresponded to a limiting spatial resolution of 150 μm. The full-width-at-half-maximum values of the section sensitivity profiles were 0.41, 0.44, and 0.67 mm for the thinnest image thickness for each mode (0.25, 0.25, and 0.5 mm, respectively). At the same in-plane spatial resolution, Sharp and UHR images had up to 15% lower noise than Macro images. Patient images acquired in Sharp mode demonstrated better delineation of fine anatomic structures compared with Macro mode images. Phantom studies demonstrated superior resolution and noise properties for the Sharp and UHR modes relative to the standard Macro mode and patient images demonstrated the potential benefit of these scan modes for clinical practice.

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Multi-Resolution Analysis of MODIS and ASTER Satellite Data for Water Classification

DTIC Science & Technology

2006-09-01

spectral bands, but also with different pixel resolutions . The overall goal... the total water surface. Due to the constraint that high spatial resolution satellite images are low temporal resolution , one needs a reliable method...at 15 m resolution , were processed. We used MODIS reflectance data from MOD02 Level 1B data. Even the spatial resolution of the 1240 nm

Definition of the Spatial Resolution of X-Ray Microanalysis in Thin Foils

NASA Technical Reports Server (NTRS)

Williams, D. B.; Michael, J. R.; Goldstein, J. I.; Romig, A. D., Jr.

1992-01-01

The spatial resolution of X-ray microanalysis in thin foils is defined in terms of the incident electron beam diameter and the average beam broadening. The beam diameter is defined as the full width tenth maximum of a Gaussian intensity distribution. The spatial resolution is calculated by a convolution of the beam diameter and the average beam broadening. This definition of the spatial resolution can be related simply to experimental measurements of composition profiles across interphase interfaces. Monte Carlo calculations using a high-speed parallel supercomputer show good agreement with this definition of the spatial resolution and calculations based on this definition. The agreement is good over a range of specimen thicknesses and atomic number, but is poor when excessive beam tailing distorts the assumed Gaussian electron intensity distributions. Beam tailing occurs in low-Z materials because of fast secondary electrons and in high-Z materials because of plural scattering.

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

Krishnan, Venkat; Cole, Wesley

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Use of UAS remote sensing data to estimate crop ET at high spatial resolution

USDA-ARS?s Scientific Manuscript database

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

Sub-millimetre DOI detector based on monolithic LYSO and digital SiPM for a dedicated small-animal PET system.

PubMed

Marcinkowski, Radosław; Mollet, Pieter; Van Holen, Roel; Vandenberghe, Stefaan

2016-03-07

The mouse model is widely used in a vast range of biomedical and preclinical studies. Thanks to the ability to detect and quantify biological processes at the molecular level in vivo, PET has become a well-established tool in these investigations. However, the need to visualize and quantify radiopharmaceuticals in anatomic structures of millimetre or less requires good spatial resolution and sensitivity from small-animal PET imaging systems.In previous work we have presented a proof-of-concept of a dedicated high-resolution small-animal PET scanner based on thin monolithic scintillator crystals and Digital Photon Counter photosensor. The combination of thin monolithic crystals and MLE positioning algorithm resulted in an excellent spatial resolution of 0.7 mm uniform in the entire field of view (FOV). However, the limitation of the scanner was its low sensitivity due to small thickness of the lutetium-yttrium oxyorthosilicate (LYSO) crystals (2 mm).Here we present an improved detector design for a small-animal PET system that simultaneously achieves higher sensitivity and sustains a sub-millimetre spatial resolution. The proposed detector consists of a 5 mm thick monolithic LYSO crystal optically coupled to a Digital Photon Counter. Mean nearest neighbour (MNN) positioning combined with depth of interaction (DOI) decoding was employed to achieve sub-millimetre spatial resolution. To evaluate detector performance the intrinsic spatial resolution, energy resolution and coincidence resolving time (CRT) were measured. The average intrinsic spatial resolution of the detector was 0.60 mm full-width-at-half-maximum (FWHM). A DOI resolution of 1.66 mm was achieved. The energy resolution was 23% FWHM at 511 keV and CRT of 529 ps were measured. The improved detector design overcomes the sensitivity limitation of the previous design by increasing the nominal sensitivity of the detector block and retains an excellent intrinsic spatial resolution.

The robustness of T2 value as a trabecular structural index at multiple spatial resolutions of 7 Tesla MRI.

PubMed

Lee, D K; Song, Y K; Park, B W; Cho, H P; Yeom, J S; Cho, G; Cho, H

2018-04-15

To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. The effects of MRI resolutions to T 2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T 2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T 2 and T2* were measured by degrading spatial resolutions on a 7 T system. In the defatted trabecular experiment, both T 2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm 3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| < 0.50) at spatial resolutions of 250 and 500 µm 3 . The correlations for T2* rapidly dropped ( |r| < 0.50) at a spatial resolution of 500 µm 3 , whereas those for T 2 remained consistently high ( |r| > 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm 3 , 2 minutes) T 2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm 3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). T 2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain. © 2018 International Society for Magnetic Resonance in Medicine.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

NASA Astrophysics Data System (ADS)

Gong, Kuang; Cherry, Simon R.; Qi, Jinyi

2016-03-01

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

High Efficiency Multi-shot Interleaved Spiral-In/Out Acquisition for High Resolution BOLD fMRI

PubMed Central

Jung, Youngkyoo; Samsonov, Alexey A.; Liu, Thomas T.; Buracas, Giedrius T.

2012-01-01

Growing demand for high spatial resolution BOLD functional MRI faces a challenge of the spatial resolution vs. coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in-out trajectory is preferred over spiral-in due to increased BOLD signal CNR and higher acquisition efficiency than that of spiral-out or non-interleaved spiral in/out trajectories (1), but to date applicability of the multi-shot interleaved spiral in-out for high spatial resolution imaging has not been studied. Herein we propose multi-shot interleaved spiral in-out acquisition and investigate its applicability for high spatial resolution BOLD fMRI. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2* decay, off-resonance and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in-out pulse sequence yields high BOLD CNR images at in-plane resolution below 1x1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multi-shot interleaved spiral in-out acquisition is a promising technique for high spatial resolution BOLD fMRI applications. PMID:23023395

Imaging Mass Spectrometry on the Nanoscale with Cluster Ion Beams

PubMed Central

2015-01-01

Imaging with cluster secondary ion mass spectrometry (SIMS) is reaching a mature level of development. Using a variety of molecular ion projectiles to stimulate desorption, 3-dimensional imaging with the selectivity of mass spectrometry can now be achieved with submicrometer spatial resolution and <10 nm depth resolution. In this Perspective, stock is taken regarding what it will require to routinely achieve these remarkable properties. Issues include the chemical nature of the projectile, topography formation, differential erosion rates, and perhaps most importantly, ionization efficiency. Shortcomings of existing instrumentation are also noted. Speculation about how to successfully resolve these issues is a key part of the discussion. PMID:25458665

Space-resolved measurements of neutrons and ions emitted by a plasma focus

NASA Astrophysics Data System (ADS)

Jaeger, U.

1980-05-01

Space-resolved measurements of neutrons and of accelerated charged particles emitted by a plasma focus device are presented. The neutron source was measured with one and two dimensional paraffin collimators. The spatial resolution is 5 mn along the axis and the radius, with a time resolution of 10 ns. In order to make quantitative statements about the neutron yield, neutron scattering, absorption, and nuclear reactions were taken into account. Part of the neutron measurement was carried out together with time and space resolved measurements of the electron density to study possible correlations between n sub e and y sub n.

The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI.

PubMed

Molloy, Erin K; Meyerand, Mary E; Birn, Rasmus M

2014-02-01

Functional MRI blood oxygen level-dependent (BOLD) signal changes can be subtle, motivating the use of imaging parameters and processing strategies that maximize the temporal signal-to-noise ratio (tSNR) and thus the detection power of neuronal activity-induced fluctuations. Previous studies have shown that acquiring data at higher spatial resolutions results in greater percent BOLD signal changes, and furthermore that spatially smoothing higher resolution fMRI data improves tSNR beyond that of data originally acquired at a lower resolution. However, higher resolution images come at the cost of increased acquisition time, and the number of image volumes also influences detectability. The goal of our study is to determine how the detection power of neuronally induced BOLD fluctuations acquired at higher spatial resolutions and then spatially smoothed compares to data acquired at the lower resolutions with the same imaging duration. The number of time points acquired during a given amount of imaging time is a practical consideration given the limited ability of certain populations to lie still in the MRI scanner. We compare acquisitions at three different in-plane spatial resolutions (3.50×3.50mm(2), 2.33×2.33mm(2), 1.75×1.75mm(2)) in terms of their tSNR, contrast-to-noise ratio, and the power to detect both task-related activation and resting-state functional connectivity. The impact of SENSE acceleration, which speeds up acquisition time increasing the number of images collected, is also evaluated. Our results show that after spatially smoothing the data to the same intrinsic resolution, lower resolution acquisitions have a slightly higher detection power of task-activation in some, but not all, brain areas. There were no significant differences in functional connectivity as a function of resolution after smoothing. Similarly, the reduced tSNR of fMRI data acquired with a SENSE factor of 2 is offset by the greater number of images acquired, resulting in few significant differences in detection power of either functional activation or connectivity after spatial smoothing. © 2013.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

A Comparison of Spatial and Spectral Image Resolution for Mapping Invasive Plants in Coastal California

NASA Astrophysics Data System (ADS)

Underwood, Emma C.; Ustin, Susan L.; Ramirez, Carlos M.

2007-01-01

We explored the potential of detecting three target invasive species: iceplant ( Carpobrotus edulis), jubata grass ( Cortaderia jubata), and blue gum ( Eucalyptus globulus) at Vandenberg Air Force Base, California. We compared the accuracy of mapping six communities (intact coastal scrub, iceplant invaded coastal scrub, iceplant invaded chaparral, jubata grass invaded chaparral, blue gum invaded chaparral, and intact chaparral) using four images with different combinations of spatial and spectral resolution: hyperspectral AVIRIS imagery (174 wavebands, 4 m spatial resolution), spatially degraded AVIRIS (174 bands, 30 m), spectrally degraded AVIRIS (6 bands, 4 m), and both spatially and spectrally degraded AVIRIS (6 bands, 30 m, i.e., simulated Landsat ETM data). Overall success rates for classifying the six classes was 75% (kappa 0.7) using full resolution AVIRIS, 58% (kappa 0.5) for the spatially degraded AVIRIS, 42% (kappa 0.3) for the spectrally degraded AVIRIS, and 37% (kappa 0.3) for the spatially and spectrally degraded AVIRIS. A true Landsat ETM image was also classified to illustrate that the results from the simulated ETM data were representative, which provided an accuracy of 50% (kappa 0.4). Mapping accuracies using different resolution images are evaluated in the context of community heterogeneity (species richness, diversity, and percent species cover). Findings illustrate that higher mapping accuracies are achieved with images possessing high spectral resolution, thus capturing information across the visible and reflected infrared solar spectrum. Understanding the tradeoffs in spectral and spatial resolution can assist land managers in deciding the most appropriate imagery with respect to target invasives and community characteristics.

Error Estimation in an Optimal Interpolation Scheme for High Spatial and Temporal Resolution SST Analyses

NASA Technical Reports Server (NTRS)

Rigney, Matt; Jedlovec, Gary; LaFontaine, Frank; Shafer, Jaclyn

2010-01-01

Heat and moisture exchange between ocean surface and atmosphere plays an integral role in short-term, regional NWP. Current SST products lack both spatial and temporal resolution to accurately capture small-scale features that affect heat and moisture flux. NASA satellite is used to produce high spatial and temporal resolution SST analysis using an OI technique.

Instrumentation in molecular imaging.

PubMed

Wells, R Glenn

2016-12-01

In vivo molecular imaging is a challenging task and no single type of imaging system provides an ideal solution. Nuclear medicine techniques like SPECT and PET provide excellent sensitivity but have poor spatial resolution. Optical imaging has excellent sensitivity and spatial resolution, but light photons interact strongly with tissues and so only small animals and targets near the surface can be accurately visualized. CT and MRI have exquisite spatial resolution, but greatly reduced sensitivity. To overcome the limitations of individual modalities, molecular imaging systems often combine individual cameras together, for example, merging nuclear medicine cameras with CT or MRI to allow the visualization of molecular processes with both high sensitivity and high spatial resolution.

Microdome-gooved Gd(2)O(2)S:Tb scintillator for flexible and high resolution digital radiography.

PubMed

Jung, Phill Gu; Lee, Chi Hoon; Bae, Kong Myeong; Lee, Jae Min; Lee, Sang Min; Lim, Chang Hwy; Yun, Seungman; Kim, Ho Kyung; Ko, Jong Soo

2010-07-05

A flexible microdome-grooved Gd(2)O(2)S:Tb scintillator is simulated, fabricated, and characterized for digital radiography applications. According to Monte Carlo simulation results, the dome-grooved structure has a high spatial resolution, which is verified by X-ray image performance of the scintillator. The proposed scintillator has lower X-ray sensitivity than a nonstructured scintillator but almost two times higher spatial resolution at high spatial frequency. Through evaluation of the X-ray performance of the fabricated scintillators, we confirm that the microdome-grooved scintillator can be applied to next-generation flexible digital radiography systems requiring high spatial resolution.

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

2016-05-01

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Impaired temporal, not just spatial, resolution in amblyopia.

PubMed

Spang, Karoline; Fahle, Manfred

2009-11-01

In amblyopia, neuronal deficits deteriorate spatial vision including visual acuity, possibly because of a lack of use-dependent fine-tuning of afferents to the visual cortex during infancy; but temporal processing may deteriorate as well. Temporal, rather than spatial, resolution was investigated in patients with amblyopia by means of a task based on time-defined figure-ground segregation. Patients had to indicate the quadrant of the visual field where a purely time-defined square appeared. The results showed a clear decrease in temporal resolution of patients' amblyopic eyes compared with the dominant eyes in this task. The extent of this decrease in figure-ground segregation based on time of motion onset only loosely correlated with the decrease in spatial resolution and spanned a smaller range than did the spatial loss. Control experiments with artificially induced blur in normal observers confirmed that the decrease in temporal resolution was not simply due to the acuity loss. Amblyopia not only decreases spatial resolution, but also temporal factors such as time-based figure-ground segregation, even at high stimulus contrasts. This finding suggests that the realm of neuronal processes that may be disturbed in amblyopia is larger than originally thought.

Spatial Resolution and Refractive Index Contrast of Resonant Photonic Crystal Surfaces for Biosensing

PubMed Central

Triggs, G. J.; Fischer, M.; Stellinga, D.; Scullion, M. G.; Evans, G. J. O.; Krauss, T. F.

2015-01-01

By depositing a resolution test pattern on top of a Si3N4 photonic crystal resonant surface, we have measured the dependence of spatial resolution on refractive index contrast Δn. Our experimental results and finite-difference time-domain (FDTD) simulations at different refractive index contrasts show that the spatial resolution of our device reduces with reduced contrast, which is an important consideration in biosensing, where the contrast may be of order 10−2. We also compare 1-D and 2-D gratings, taking into account different incidence polarizations, leading to a better understanding of the excitation and propagation of the resonant modes in these structures, as well as how this contributes to the spatial resolution. At Δn = 0.077, we observe resolutions of 2 and 6 μm parallel to and perpendicular to the grooves of a 1-D grating, respectively, and show that for polarized illumination of a 2-D grating, resolution remains asymmetrical. Illumination of a 2-D grating at 45° results in symmetric resolution. At very low index contrast, the resolution worsens dramatically, particularly for Δn < 0.01, where we observe a resolution exceeding 10 μm for our device. In addition, we measure a reduction in the resonance linewidth as the index contrast becomes lower, corresponding to a longer resonant mode propagation length in the structure and contributing to the change in spatial resolution. PMID:26356353

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes

USGS Publications Warehouse

Davies, A.G.; Keszthelyi, L.; McEwen, A.S.

2011-01-01

We have analysed high-spatial-resolution and high-temporal-resolution temperature measurements of the active lava lake at Erta'Ale volcano, Ethiopia, to derive requirements for measuring eruption temperatures at Io's volcanoes. Lava lakes are particularly attractive targets because they are persistent in activity and large, often with ongoing lava fountain activity that exposes lava at near-eruption temperature. Using infrared thermography, we find that extracting useful temperature estimates from remote-sensing data requires (a) high spatial resolution to isolate lava fountains from adjacent cooler lava and (b) rapid acquisition of multi-color data. Because existing spacecraft data of Io's volcanoes do not meet these criteria, it is particularly important to design future instruments so that they will be able to collect such data. Near-simultaneous data at more than two relatively short wavelengths (shorter than 1 ??m) are needed to constrain eruption temperatures. Resolving parts of the lava lake or fountains that are near the eruption temperature is also essential, and we provide a rough estimate of the required image scale. ?? 2011 by the American Geophysical Union.

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

MONET: multidimensional radiative cloud scene model

NASA Astrophysics Data System (ADS)

Chervet, Patrick

1999-12-01

All cloud fields exhibit variable structures (bulge) and heterogeneities in water distributions. With the development of multidimensional radiative models by the atmospheric community, it is now possible to describe horizontal heterogeneities of the cloud medium, to study these influences on radiative quantities. We have developed a complete radiative cloud scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative cloud scene from visible to infrared wavelengths for various viewing and solar conditions, different spatial scales, and various locations on the Earth. MONET is composed of two parts: a cloud medium generator (CSSM -- Cloud Scene Simulation Model) developed by the Air Force Research Laboratory, and a multidimensional radiative code (SHDOM -- Spherical Harmonic Discrete Ordinate Method) developed at the University of Colorado by Evans. MONET computes images for several scenario defined by user inputs: date, location, viewing angles, wavelength, spatial resolution, meteorological conditions (atmospheric profiles, cloud types)... For the same cloud scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on clouds or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various cloud types and spatial resolutions, and to determine specifications of new imaging sensor.

Spatial analysis of electricity demand patterns in Greece: Application of a GIS-based methodological framework

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

2016-04-01

We investigate various uses of electricity demand in Greece (agricultural, commercial, domestic, industrial use as well as use for public and municipal authorities and street lightning) and we examine their relation with variables such as population, total area, population density and the Gross Domestic Product. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the level of prefecture. We both visualize the results of the analysis and we perform cluster and outlier analysis using the Anselin local Moran's I statistic as well as hot spot analysis using the Getis-Ord Gi* statistic. The definition of the spatial patterns and relationships of the aforementioned variables in a GIS environment provides meaningful insight and better understanding of the regional development model in Greece and justifies the basis for an energy demand forecasting methodology. Acknowledgement: This research has been partly financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II: Reinforcement of the interdisciplinary and/ or inter-institutional research and innovation (CRESSENDO project; grant number 5145).

Climate Change Mitigation: Can the U.S. Intelligence Community Help?

DTIC Science & Technology

2013-06-01

satellite sensors to establish the concentration of atmospheric CO2 parts per million (ppm mole fraction) in samples collected at multiple...measurements. Spatial sampling density, the number of sensors or—in the case of satellite imagery the number and resolution of the images—likewise influences...Somewhat paradoxically, sensor accuracy from either remote ( satellites ) or in situ sensors is an important consideration, but it must also be evaluated

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

Sadowski, F. G.; Malila, W. A.; Sarno, J. E.; Nalepka, R. F.

1977-01-01

Inappropriate spatial resolution and corresponding data processing techniques may be major causes for non-optimal forest classification results frequently achieved from multispectral scanner (MSS) data. Procedures and results of empirical investigations are studied to determine the influence of MSS spatial resolution on the classification of forest features into levels of detail or hierarchies of information that might be appropriate for nationwide forest surveys and detailed in-place inventories. Two somewhat different, but related studies are presented. The first consisted of establishing classification accuracies for several hierarchies of features as spatial resolution was progressively coarsened from (2 meters) squared to (64 meters) squared. The second investigated the capabilities for specialized processing techniques to improve upon the results of conventional processing procedures for both coarse and fine resolution data.

Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.

2016-12-01

Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Dielectric Constant products: (the dielectric constant products are delivered together with soil moisture products, with the same averaging periods and generation frequency): maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation.

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

PubMed

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02 to 0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual dataset.

Simultaneous multiview capture and fusion improves spatial resolution in wide-field and light-sheet microscopy

PubMed Central

Wu, Yicong; Chandris, Panagiotis; Winter, Peter W.; Kim, Edward Y.; Jaumouillé, Valentin; Kumar, Abhishek; Guo, Min; Leung, Jacqueline M.; Smith, Corey; Rey-Suarez, Ivan; Liu, Huafeng; Waterman, Clare M.; Ramamurthi, Kumaran S.; La Riviere, Patrick J.; Shroff, Hari

2016-01-01

Most fluorescence microscopes are inefficient, collecting only a small fraction of the emitted light at any instant. Besides wasting valuable signal, this inefficiency also reduces spatial resolution and causes imaging volumes to exhibit significant resolution anisotropy. We describe microscopic and computational techniques that address these problems by simultaneously capturing and subsequently fusing and deconvolving multiple specimen views. Unlike previous methods that serially capture multiple views, our approach improves spatial resolution without introducing any additional illumination dose or compromising temporal resolution relative to conventional imaging. When applying our methods to single-view wide-field or dual-view light-sheet microscopy, we achieve a twofold improvement in volumetric resolution (~235 nm × 235 nm × 340 nm) as demonstrated on a variety of samples including microtubules in Toxoplasma gondii, SpoVM in sporulating Bacillus subtilis, and multiple protein distributions and organelles in eukaryotic cells. In every case, spatial resolution is improved with no drawback by harnessing previously unused fluorescence. PMID:27761486

The Effect of Spatial and Temporal Resolution of Cine Phase Contrast MRI on Wall Shear Stress and Oscillatory Shear Index Assessment

PubMed Central

Gijsen, Frank J.; Marquering, Henk; van Ooij, Pim; vanBavel, Ed; Wentzel, Jolanda J.; Nederveen, Aart J.

2016-01-01

Introduction Wall shear stress (WSS) and oscillatory shear index (OSI) are associated with atherosclerotic disease. Both parameters are derived from blood velocities, which can be measured with phase-contrast MRI (PC-MRI). Limitations in spatiotemporal resolution of PC-MRI are known to affect these measurements. Our aim was to investigate the effect of spatiotemporal resolution using a carotid artery phantom. Methods A carotid artery phantom was connected to a flow set-up supplying pulsatile flow. MRI measurement planes were placed at the common carotid artery (CCA) and internal carotid artery (ICA). Two-dimensional PC-MRI measurements were performed with thirty different spatiotemporal resolution settings. The MRI flow measurement was validated with ultrasound probe measurements. Mean flow, peak flow, flow waveform, WSS and OSI were compared for these spatiotemporal resolutions using regression analysis. The slopes of the regression lines were reported in %/mm and %/100ms. The distribution of low and high WSS and OSI was compared between different spatiotemporal resolutions. Results The mean PC-MRI CCA flow (2.5±0.2mL/s) agreed with the ultrasound probe measurements (2.7±0.02mL/s). Mean flow (mL/s) depended only on spatial resolution (CCA:-13%/mm, ICA:-49%/mm). Peak flow (mL/s) depended on both spatial (CCA:-13%/mm, ICA:-17%/mm) and temporal resolution (CCA:-19%/100ms, ICA:-24%/100ms). Mean WSS (Pa) was in inverse relationship only with spatial resolution (CCA:-19%/mm, ICA:-33%/mm). OSI was dependent on spatial resolution for CCA (-26%/mm) and temporal resolution for ICA (-16%/100ms). The regions of low and high WSS and OSI matched for most of the spatiotemporal resolutions (CCA:30/30, ICA:28/30 cases for WSS; CCA:23/30, ICA:29/30 cases for OSI). Conclusion We show that both mean flow and mean WSS are independent of temporal resolution. Peak flow and OSI are dependent on both spatial and temporal resolution. However, the magnitude of mean and peak flow, WSS and OSI, and the spatial distribution of OSI and WSS did not exhibit a strong dependency on spatiotemporal resolution. PMID:27669568

Zonal wavefront sensing with enhanced spatial resolution.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2016-12-01

In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.

The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme

USGS Publications Warehouse

Townshend, J.R.G.; Justice, C.O.; Skole, D.; Malingreau, J.-P.; Cihlar, J.; Teillet, P.; Sadowski, F.; Ruttenberg, S.

1994-01-01

Examination of the scientific priorities for the International Geosphere Biosphere Programme (IGBP) reveals a requirement for global land data sets in several of its Core Projects. These data sets need to be at several space and time scales. Requirements are demonstrated for the regular acquisition of data at spatial resolutions of 1 km and finer and at high temporal frequencies. Global daily data at a resolution of approximately 1 km are sensed by the Advanced Very High Resolution Radiometer (AVHRR), but they have not been available in a single archive. It is proposed, that a global data set of the land surface is created from remotely sensed data from the AVHRR to support a number of IGBP's projects. This data set should have a spatial resolution of 1 km and should be generated at least once every 10 days for the entire globe. The minimum length of record should be a year, and ideally a system should be put in place which leads to the continuous acquisition of 1 km data to provide a base line data set prior to the Earth Observing System (EOS) towards the end of the decade. Because of the high cloud cover in many parts of the world, it is necessary to plan for the collection of data from every orbit. Substantial effort will be required in the preprocessing of the data set involving radiometric calibration, atmospheric correction, geometric correction and temporal compositing, to make it suitable for the extraction of information.

Evolution and enabling capabilities of spatially resolved techniques for the characterization of heterogeneously catalyzed reactions

DOE PAGES

Morgan, Kevin; Touitou, Jamal; Choi, Jae -Soon; ...

2016-01-15

The development and optimization of catalysts and catalytic processes requires knowledge of reaction kinetics and mechanisms. In traditional catalyst kinetic characterization, the gas composition is known at the inlet, and the exit flow is measured to determine changes in concentration. As such, the progression of the chemistry within the catalyst is not known. Technological advances in electromagnetic and physical probes have made visualizing the evolution of the chemistry within catalyst samples a reality, as part of a methodology commonly known as spatial resolution. Herein, we discuss and evaluate the development of spatially resolved techniques, including the evolutions and achievements ofmore » this growing area of catalytic research. The impact of such techniques is discussed in terms of the invasiveness of physical probes on catalytic systems, as well as how experimentally obtained spatial profiles can be used in conjunction with kinetic modeling. Moreover, some aims and aspirations for further evolution of spatially resolved techniques are considered.« less

Preclinical Whole-body Fluorescence Imaging: Review of Instruments, Methods and Applications

PubMed Central

Leblond, Frederic; Davis, Scott C.; Valdés, Pablo A.; Pogue, Brain W.

2013-01-01

Fluorescence sampling of cellular function is widely used in all aspects of biology, allowing the visualization of cellular and sub-cellular biological processes with spatial resolutions in the range from nanometers up to centimeters. Imaging of fluorescence in vivo has become the most commonly used radiological tool in all pre-clinical work. In the last decade, full-body pre-clinical imaging systems have emerged with a wide range of utilities and niche application areas. The range of fluorescent probes that can be excited in the visible to near-infrared part of the electromagnetic spectrum continues to expand, with the most value for in vivo use being beyond the 630 nm wavelength, because the absorption of light sharply decreases. Whole-body in vivo fluorescence imaging has not yet reached a state of maturity that allows its routine use in the scope of large-scale pre-clinical studies. This is in part due to an incomplete understanding of what the actual fundamental capabilities and limitations of this imaging modality are. However, progress is continuously being made in research laboratories pushing the limits of the approach to consistently improve its performance in terms of spatial resolution, sensitivity and quantification. This paper reviews this imaging technology with a particular emphasis on its potential uses and limitations, the required instrumentation, and the possible imaging geometries and applications. A detailed account of the main commercially available systems is provided as well as some perspective relating to the future of the technology development. Although the vast majority of applications of in vivo small animal imaging are based on epi-illumination planar imaging, the future success of the method relies heavily on the design of novel imaging systems based on state-of-the-art optical technology used in conjunction with high spatial resolution structural modalities such as MRI, CT or ultra-sound. PMID:20031443

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

NASA Astrophysics Data System (ADS)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between -0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from -4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ˜ ±5 % of the total mortality across Europe.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Generating High-Temporal and Spatial Resolution TIR Image Data

NASA Astrophysics Data System (ADS)

Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

2017-09-01

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data

NASA Astrophysics Data System (ADS)

Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.

2017-12-01

Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture.

PubMed

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M; Torres-Rua, Alfonso; McKee, Mac

2017-09-14

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from "AggieAir", an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture

PubMed Central

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M.; McKee, Mac

2017-01-01

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products. PMID:28906428

Calibration of Fuji BAS-SR type imaging plate as high spatial resolution x-ray radiography recorder

NASA Astrophysics Data System (ADS)

Yan, Ji; Zheng, Jianhua; Zhang, Xing; Chen, Li; Wei, Minxi

2017-05-01

Image Plates as x-ray recorder have advantages including reusable, high dynamic range, large active area, and so on. In this work, Fuji BAS-SR type image plate combined with BAS-5000 scanner is calibrated. The fade rates of Image Plates has been measured using x-ray diffractometric in different room temperature; the spectral response of Image Plates has been measured using 241Am radioactive sealed source and fitting with linear model; the spatial resolution of Image Plates has been measured using micro-focus x-ray tube. The results show that Image Plates has an exponent decade curve and double absorption edge response curve. The spatial resolution of Image Plates with 25μ/50μ scanner resolution is 6.5lp/mm, 11.9lp/mm respectively and gold grid radiography is collected with 80lp/mm spatial resolution using SR-type Image Plates. BAS-SR type Image Plates can do high spatial resolution and quantitative radiographic works. It can be widely used in High energy density physics (HEDP), inertial confinement fusion (ICF) and laboratory astronomy physics.

Simulations of the temporal and spatial resolution for a compact time-resolved electron diffractometer

NASA Astrophysics Data System (ADS)

Robinson, Matthew S.; Lane, Paul D.; Wann, Derek A.

2016-02-01

A novel compact electron gun for use in time-resolved gas electron diffraction experiments has recently been designed and commissioned. In this paper we present and discuss the extensive simulations that were performed to underpin the design in terms of the spatial and temporal qualities of the pulsed electron beam created by the ionisation of a gold photocathode using a femtosecond laser. The response of the electron pulses to a solenoid lens used to focus the electron beam has also been studied. The simulated results show that focussing the electron beam affects the overall spatial and temporal resolution of the experiment in a variety of ways, and that factors that improve the resolution of one parameter can often have a negative effect on the other. A balance must, therefore, be achieved between spatial and temporal resolution. The optimal experimental time resolution for the apparatus is predicted to be 416 fs for studies of gas-phase species, while the predicted spatial resolution of better than 2 nm-1 compares well with traditional time-averaged electron diffraction set-ups.

Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

PubMed Central

Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

2018-01-01

Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

Spatial information is preferentially processed by the distal part of CA3: implication for memory retrieval.

PubMed

Flasbeck, Vera; Atucha, Erika; Nakamura, Nozomu H; Yoshida, Motoharu; Sauvage, Magdalena M

2018-07-16

For the past decades, CA3 was considered as a single functional entity. However, strong differences between the proximal (close to the dentate gyrus) and the distal (close to CA2) parts of CA3 in terms of connectivity patterns, gene expression and electrophysiological properties suggest that it is not the case. We recently showed that proximal CA3 (together with distal CA1) preferentially deals with non-spatial information [1]. In contrast to proximal CA3, distal CA3 mainly receives and predominantly projects to spatially tuned areas. Here, we tested if distal CA3 preferentially processes spatial information, which would suggest a segregation of the spatial information along the proximodistal axis of CA3. We used a high-resolution imaging technique based on the detection of the expression of the immediate-early gene Arc, commonly used to map activity in the medial temporal lobe. We showed that distal CA3 is strongly recruited in a newly designed delayed nonmatching-to-location task with high memory demands in rats, while proximal CA3 is not. These results indicate a functional segregation of CA3 that mirrors the one reported in CA1, and suggest the existence of a distal CA3- proximal CA1 spatial subnetwork. These findings bring further evidence for the existence of 'specialized' spatial and non-spatial subnetworks segregated along the proximodistal axis of the hippocampus and put forward the 'segregated' view of information processing in the hippocampus as a reasonable alternative to the well-accepted 'integrated' view, according to which spatial and non-spatial information are systematically integrated in the hippocampus to form episodic memory. Copyright © 2018. Published by Elsevier B.V.

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.

An optical wavefront sensor based on a double layer microlens array.

PubMed

Lin, Vinna; Wei, Hsiang-Chun; Hsieh, Hsin-Ta; Su, Guo-Dung John

2011-01-01

In order to determine light aberrations, Shack-Hartmann optical wavefront sensors make use of microlens arrays (MLA) to divide the incident light into small parts and focus them onto image planes. In this paper, we present the design and fabrication of long focal length MLA with various shapes and arrangements based on a double layer structure for optical wavefront sensing applications. A longer focal length MLA could provide high sensitivity in determining the average slope across each microlens under a given wavefront, and spatial resolution of a wavefront sensor is increased by numbers of microlenses across a detector. In order to extend focal length, we used polydimethysiloxane (PDMS) above MLA on a glass substrate. Because of small refractive index difference between PDMS and MLA interface (UV-resin), the incident light is less refracted and focused in further distance. Other specific focal lengths could also be realized by modifying the refractive index difference without changing the MLA size. Thus, the wavefront sensor could be improved with better sensitivity and higher spatial resolution.

Nanoscale chemical mapping of laser-solubilized silk

NASA Astrophysics Data System (ADS)

Ryu, Meguya; Kobayashi, Hanae; Balčytis, Armandas; Wang, Xuewen; Vongsvivut, Jitraporn; Li, Jingliang; Urayama, Norio; Mizeikis, Vygantas; Tobin, Mark; Juodkazis, Saulius; Morikawa, Junko

2017-11-01

A water soluble amorphous form of silk was made by ultra-short laser pulse irradiation and detected by nanoscale IR mapping. An optical absorption-induced nanoscale surface expansion was probed to yield the spectral response of silk at IR molecular fingerprinting wavelengths with a high  ˜ 20 nm spatial resolution defined by the tip of the probe. Silk microtomed sections of 1-5 μm in thickness were prepared for nanoscale spectroscopy and a laser was used to induce amorphisation. Comparison of silk absorbance measurements carried out by table-top and synchrotron Fourier transform IR spectroscopy proved that chemical imaging obtained at high spatial resolution and specificity (able to discriminate between amorphous and crystalline silk) is reliably achieved by nanoscale IR. Differences in absorbance and spectral line-shapes of the bands are related to the different sensitivity of the applied methods to real and imaginary parts of permittivity. A nanoscale material characterization by combining synchrotron IR radiation and nano-IR is discussed.

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.

Infrared and Raman Microscopy in Cell Biology

PubMed Central

Matthäus, Christian; Bird, Benjamin; Miljković, Miloš; Chernenko, Tatyana; Romeo, Melissa; Diem, Max

2009-01-01

This chapter presents novel microscopic methods to monitor cell biological processes of live or fixed cells without the use of any dye, stains, or other contrast agent. These methods are based on spectral techniques that detect inherent spectroscopic properties of biochemical constituents of cells, or parts thereof. Two different modalities have been developed for this task. One of them is infrared micro-spectroscopy, in which an average snapshot of a cell’s biochemical composition is collected at a spatial resolution of typically 25 mm. This technique, which is extremely sensitive and can collect such a snapshot in fractions of a second, is particularly suited for studying gross biochemical changes. The other technique, Raman microscopy (also known as Raman micro-spectroscopy), is ideally suited to study variations of cellular composition on the scale of subcellular organelles, since its spatial resolution is as good as that of fluorescence microscopy. Both techniques exhibit the fingerprint sensitivity of vibrational spectroscopy toward biochemical composition, and can be used to follow a variety of cellular processes. PMID:19118679

ROTI monitoring with reference to the International LOFAR Telescope

NASA Astrophysics Data System (ADS)

Kotulak, Kacper; Froń, Adam; Krankowski, Andrzej

2017-04-01

Interferometric networks operating on relatively long baselines, such as LOFAR (approx. baseline of 1500km) are one of the important scientific users of ionosphere monitoring products. Simultaneous observations of the radiosource from the different interferometric stations with such distance between can be distracted by the ionospheric medium in different ways, as signal would cross ionospheric regions with different ionization level. The main objective of presented work is to introduce ionospheric fluctuation product (ROT and ROTI maps), which will complement the main ILT dedicated product - high spatial and temporal resolution ionospheric maps (ILTG). Presented ROT/ROTI product is prepared basing on the real-time EUREF Permanent Network GNSS observations and generated with similar assumptions as ILTG products - one degree by one degree in spatial and one hour in temporal resolution. Presented product will be a part of the ILT ionospheric service planned for the nearest future. The presentation briefly presents the ROT and ROTI obtaining methodology as well as first results.

Fly's Eye GLM Simulator Preliminary Validation Analysis

NASA Astrophysics Data System (ADS)

Quick, M. G.; Christian, H. J., Jr.; Blakeslee, R. J.; Stewart, M. F.; Corredor, D.; Podgorny, S.

2017-12-01

As part of the validation effort for the Geostationary Lightning Mapper (GLM) an airborne radiometer array has been fabricated to observe lightning optical emission through the cloud top. The Fly's Eye GLM Simulator (FEGS) is a multi-spectral, photo-electric radiometer array with a nominal spatial resolution of 2 x 2 km and spatial footprint of 10 x 10 km at cloud top. A main 25 pixel array observes the 777.4 nm oxygen emission triplet using an optical passband filter with a 10 nm FWHM, a sampling rate of 100 kHz, and 16 bit resolution. From March to May of 2017 FEGS was flown on the NASA ER-2 high altitude aircraft during the GOES-R Validation Flight Campaign. Optical signatures of lightning were observed during a variety of thunderstorm scenarios while coincident measurements were obtained by GLM and ground based antennae networks. This presentation will describe the preliminary analysis of the FEGS dataset in the context of GLM validation.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

Fabrication and characterization of a 0.5-mm lutetium oxyorthosilicate detector array for high-resolution PET applications.

PubMed

Stickel, Jennifer R; Qi, Jinyi; Cherry, Simon R

2007-01-01

With the increasing use of in vivo imaging in mouse models of disease, there are many interesting applications that demand imaging of organs and tissues with submillimeter resolution. Though there are other contributing factors, the spatial resolution in small-animal PET is still largely determined by the detector pixel dimensions. In this work, a pair of lutetium oxyorthosilicate (LSO) arrays with 0.5-mm pixels was coupled to multichannel photomultiplier tubes and evaluated for use as high-resolution PET detectors. Flood histograms demonstrated that most crystals were clearly identifiable. Energy resolution varied from 22% to 38%. The coincidence timing resolution was 1.42-ns full width at half maximum (FWHM). The intrinsic spatial resolution was 0.68-mm FWHM as measured with a 30-gauge needle filled with (18)F. The improvement in spatial resolution in a tomographic setting is demonstrated using images of a line source phantom reconstructed with filtered backprojection and compared with images obtained from 2 dedicated small-animal PET scanners. Finally, a projection image of the mouse foot is shown to demonstrate the application of these 0.5-mm LSO detectors to a biologic task. A pair of highly pixelated LSO detections has been constructed and characterized for use as high-spatial-resolution PET detectors. It appears that small-animal PET systems capable of a FWHM spatial resolution of 600 microm or less are feasible and should be pursued.

Characterization of spatial and spectral resolution of a rotating prism chromotomographic hyperspectral imager

NASA Astrophysics Data System (ADS)

Bostick, Randall L.; Perram, Glen P.; Tuttle, Ronald

2009-05-01

The Air Force Institute of Technology (AFIT) has built a rotating prism chromotomographic hyperspectral imager (CTI) with the goal of extending the technology to exploit spatially extended sources with quickly varying (> 10 Hz) phenomenology, such as bomb detonations and muzzle flashes. This technology collects successive frames of 2-D data dispersed at different angles multiplexing spatial and spectral information which can then be used to reconstruct any arbitrary spectral plane(s). In this paper, the design of the AFIT instrument is described and then tested against a spectral target with near point source spatial characteristics to measure spectral and spatial resolution. It will be shown that, in theory, the spectral and spatial resolution in the 3-D spectral image cube is the nearly the same as a simple prism spectrograph with the same design. However, error in the knowledge of the prism linear dispersion at the detector array as a function of wavelength and projection angle will degrade resolution without further corrections. With minimal correction for error and use of a simple shift-and-add reconstruction algorithm, the CTI is able to produce a spatial resolution of about 2 mm in the object plane (234 μrad IFOV) and is limited by chromatic aberration. A spectral resolution of less than 1nm at shorter wavelengths is shown, limited primarily by prism dispersion.

High resolution modeling in urban hydrology: comparison between two modeling approaches and their sensitivity to high rainfall variability

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Bompard, Philippe; Schertzer, Daniel

2015-04-01

Urban water management is becoming increasingly complex, due to the rapid increase of impervious areas, and the potential effects of climate change. The large amount of water generated in a very short period of time and the limited capacity of sewer systems increase the vulnerability of urban environments to flooding risk and make it necessary to implement specific devices in order to handle the volume of water generated. This complex situation in urban environments makes the use of hydrological models as well as the implementation of more accurate and reliable tools for flow and rainfall measurements essential for a good pluvial network management, the use of decision support tools such as real-time radar forecasting system, the developpement of general public communication and warning systems, and the implementation of management strategy participate on limiting the flood damages. The very high spatial variability characteristic of urban environments makes it necessary to integrate the variability of physical properties and precipitation at fine scales in modeling processes, suggesting a high resolution modeling approach. In this paper we suggest a comparison between two modeling approaches and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The first model used in this study is CANOE, which is a semi-distributed model widely used in France by practitioners for urban hydrology and urban water management. Two configurations of this model are be used in this study, the first one integrate 9 sub-catchments with sizes range from (1ha to 76ha), in the second configuration, the spatial resolution of this model has been improved with 45 sub-catchments with sizes range from (1ha to 14ha), the aim is to see how the semi-distributed model resolution affects it sensitivity to rainfall variability. The second model is Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Multi-Hydro has been set up at two resolutions, 10m and 5m. The validation of these two models is performed using 5 rainfall events that occurred between 2010 and 2013. Radar data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. Raingauge and flow measurements data comes from the General Council of Val-de-Marne County. In this validation part, the hydrological responses given by two models and the different configurations are compared to flow measurements. It appears that CANOE gives better results than Multi-Hydro model, especially when using raingauge data. For some events, we noticed that model responses given when using raingauge and radar data are different, suggesting a sign of sensitivity to the spatial variability of rainfall. 10 high-resolution rainfall events are used in the second part to study the sensitivity of each modeling approach to high rainfall variability. Radar data was available at four spatial resolutions (100, 200, 500 and 1000m) and two temporal resolutions (1min and 5min), for each event, two rainfall directions (parallel and perpendicular) are used, meaning that 16 hydrological responses are simulated for each event and the variability within it analyzed. First results suggest that the fully distributed model is more sensitive to high rainfall variability than the semi-distributed one, the increase of both hydrological model spatial resolution improves their sensitivity to rainfall variability. This study highlights some technical challenges facing the high-resolution modeling, especially the difficulty to obtain reliable input data at an acceptable resolution and also the high computation time noticed particularly for the semi-distributed model making it difficult to use it in real time. The authors greatly acknowledge partial financial support from the project RainGain (http://www.raingain.eu) of the EU Interreg program.

High Spatial Resolution Thermal Satellite Technologies

NASA Technical Reports Server (NTRS)

Ryan, Robert

2003-01-01

This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.

Improved spatial resolution in PET scanners using sampling techniques

PubMed Central

Surti, Suleman; Scheuermann, Ryan; Werner, Matthew E.; Karp, Joel S.

2009-01-01

Increased focus towards improved detector spatial resolution in PET has led to the use of smaller crystals in some form of light sharing detector design. In this work we evaluate two sampling techniques that can be applied during calibrations for pixelated detector designs in order to improve the reconstructed spatial resolution. The inter-crystal positioning technique utilizes sub-sampling in the crystal flood map to better sample the Compton scatter events in the detector. The Compton scatter rejection technique, on the other hand, rejects those events that are located further from individual crystal centers in the flood map. We performed Monte Carlo simulations followed by measurements on two whole-body scanners for point source data. The simulations and measurements were performed for scanners using scintillators with Zeff ranging from 46.9 to 63 for LaBr3 and LYSO, respectively. Our results show that near the center of the scanner, inter-crystal positioning technique leads to a gain of about 0.5-mm in reconstructed spatial resolution (FWHM) for both scanner designs. In a small animal LYSO scanner the resolution improves from 1.9-mm to 1.6-mm with the inter-crystal technique. The Compton scatter rejection technique shows higher gains in spatial resolution but at the cost of reduction in scanner sensitivity. The inter-crystal positioning technique represents a modest acquisition software modification for an improvement in spatial resolution, but at a cost of potentially longer data correction and reconstruction times. The Compton scatter rejection technique, while also requiring a modest acquisition software change with no increased data correction and reconstruction times, will be useful in applications where the scanner sensitivity is very high and larger improvements in spatial resolution are desirable. PMID:19779586

Examination of elevation dependency in observed and projected temperature change in the Upper Indus Basin and Western Himalaya

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Forsythe, N. D.; Blenkinsop, S.; Archer, D.; Hardy, A.; Janes, T.; Jones, R. G.; Holderness, T.

2013-12-01

We present results of two distinct, complementary analyses to assess evidence of elevation dependency in temperature change in the UIB (Karakoram, Eastern Hindu Kush) and wider WH. The first analysis component examines historical remotely-sensed land surface temperature (LST) from the second and third generation of the Advanced Very High Resolution Radiometer (AVHRR/2, AVHRR/3) instrument flown on NOAA satellite platforms since the mid-1980s through present day. The high spatial resolution (<4km) from AVHRR instrument enables precise consideration of the relationship between estimated LST and surface topography. The LST data product was developed as part of initiative to produce continuous time-series for key remotely sensed spatial products (LST, snow covered area, cloud cover, NDVI) extending as far back into the historical record as feasible. Context for the AVHRR LST data product is provided by results of bias assessment and validation procedures against both available local observations, both manned and automatic weather stations. Local observations provide meaningful validation and bias assessment of the vertical gradients found in the AVHRR LST as the elevation range from the lowest manned meteorological station (at 1460m asl) to the highest automatic weather station (4733m asl) covers much of the key range yielding runoff from seasonal snowmelt. Furthermore the common available record period of these stations (1995 to 2007) enables assessment not only of the AVHRR LST but also performance comparisons with the more recent MODIS LST data product. A range of spatial aggregations (from minor tributary catchments to primary basin headwaters) is performed to assess regional homogeneity and identify potential latitudinal or longitudinal gradients in elevation dependency. The second analysis component investigates elevation dependency, including its uncertainty, in projected temperature change trajectories in the downscaling of a seventeen member Global Climate Model (GCM) perturbed physics ensemble (PPE) of transient (130-year) simulations using a moderate resolution (25km) regional climate model (RCM). The GCM ensemble is the17-member QUMP (Quantifying Uncertainty in Model Projections) ensemble and the downscaling is done using HadRM3P, part of the PRECIS regional climate modelling system. Both the RCM and GCMs are models developed the UK Met Office Hadley Centre and are based on the HadCM3 GCM. Use of the multi-member PPE enables quantification of uncertainty in projected temperature change while the spatial resolution of RCM improves insight into the role of elevation in projected rates of change. Furthermore comparison with the results of the remote sensing analysis component - considered to provide an 'observed climatology' - permits evaluation of individual ensemble members with regards to biases in spatial gradients in temperature as well timing and magnitude of annual cycles.

imVisIR - a new tool for high resolution soil characterisation

NASA Astrophysics Data System (ADS)

Steffens, Markus; Buddenbaum, Henning

2014-05-01

The physical and chemical heterogeneities of soils are the source of a vast functional diversity of soil properties in a multitude of spatial domains. But many studies do not consider the spatial variability of soil types, diagnostic horizons and properties. These lateral and vertical heterogeneities of soils or soil horizons are mostly neglected due to the limitations in the available soil data and missing techniques to gather the information. We present an imaging technique that enables the spatially accurate, high resolution assessment (63×63 µm2 per pixel) of complete soil profiles consisting of mineral and organic horizons. We used a stainless steel box (100×100×300 mm3) to sample various soil types and a hyperspectral camera to record the bidirectional reflectance of the large undisturbed soil samples in the visible and near infrared (Vis-NIR) part of the electromagnetic spectrum (400-1000 nm in 160 spectral bands). Various statistical, geostatistical and image processing tools were used to 1) assess the spatial variability of the soil profile as a whole; 2) classify diagnostic horizons; 3) extrapolate elemental concentrations of small sampling areas to the complete image and calculate high resolution chemometric maps of up to five elements (C, N, Al, Fe, Mn); and 4) derive maps of the chemical composition of soil organic matter. Imaging Vis-NIR (imVisIR) has the potential to significantly improve soil classification, assessment of elemental budgets and balances and the understanding of soil forming processes and mechanisms. It will help to identify areas of interest for techniques working on smaller scales and enable the upscaling and referencing of this information to the complete pedon.

Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

NASA Astrophysics Data System (ADS)

Li, Linlin; Vrieling, Anton; Skidmore, Andrew; Wang, Tiejun; Turak, Eren

2018-04-01

Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30 m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10 years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our method was not only effective for mapping permanent water fraction, but also in accurately capturing temporal fluctuations of surface water. Based on this good performance, we produced surface water fraction maps at 16-day interval for the 2000-2015 MODIS archive. Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling

NASA Astrophysics Data System (ADS)

Sasai, T.; Murakami, K.; Kato, S.; Matsunaga, T.; Saigusa, N.; Hiraki, K.

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. However, most studies, which aimed at the estimation of carbon exchanges between ecosystem and atmosphere, 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. 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. In this study, we show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. As methodology for computing the exchanges, we 1) developed a global 1km-grid climate and satellite dataset based on the approach in Setoyama and Sasai (2013); 2) used the satellite-driven biosphere model (Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data: BEAMS) (Sasai et al., 2005, 2007, 2011); 3) simulated the carbon exchanges by using the new dataset and BEAMS by the use of a supercomputer that includes 1280 CPU and 320 GPGPU cores (GOSAT RCF of NIES). As a result, we could develop a global uniform system for realistically estimating terrestrial carbon exchange, and evaluate net ecosystem production in each community level; leading to obtain highly detailed understanding of terrestrial carbon exchanges.

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

Gao, Lan; Hill, K. W.; Bitter, M.

Here, a high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ 2 rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystalmore » (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications ( M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Infrared atmospheric sounding interferometer correlation interferometry for the retrieval of atmospheric gases: the case of H2O and CO2.

PubMed

Grieco, Giuseppe; Masiello, Guido; Serio, Carmine; Jones, Roderic L; Mead, Mohammed I

2011-08-01

Correlation interferometry is a particular application of Fourier transform spectroscopy with partially scanned interferograms. Basically, it is a technique to obtain the difference between the spectra of atmospheric radiance at two diverse spectral resolutions. Although the technique could be exploited to design an appropriate correlation interferometer, in this paper we are concerned with the analytical aspects of the method and its application to high-spectral-resolution infrared observations in order to separate the emission of a given atmospheric gas from a spectral signal dominated by surface emission, such as in the case of satellite spectrometers operated in the nadir looking mode. The tool will be used to address some basic questions concerning the vertical spatial resolution of H2O and to develop an algorithm to retrieve the columnar amount of CO2. An application to complete interferograms from the Infrared Atmospheric Sounding Interferometer will be presented and discussed. For H2O, we have concluded that the vertical spatial resolution in the lower troposphere mostly depends on broad features associated with the spectrum, whereas for CO2, we have derived a technique capable of retrieving a CO2 columnar amount with accuracy of ≈±7 parts per million by volume at the level of each single field of view.

Evaluating Hyperspectral Imaging of Wetland Vegetation as a Tool for Detecting Estuarine Nutrient Enrichment

DTIC Science & Technology

2008-05-01

the vegetation’s uptake of water column nutrients produces a spectral response; and 3) the spectral and spatial resolutions ...analysis. This allowed us to evaluate these assumptions at the landscape level, by using the high spectral and spatial resolution of the hyperspectral... spatial resolution (2.5 m pixels) HyMap hyperspectral imagery of the entire wetland. After using a hand-held spectrometer to characterize

Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.

DOSoReMI.hu: collection of countrywide DSM products partly according to GSM.net specifications, partly driven by specific user demands

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2017-04-01

Due to former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. In traditional soil mapping the creation of a new map was troublesome and laborious. As a consequence, robust maps were elaborated and rather the demands were fitted to the available map products. Until recently spatial soil information demands have been serviced with the available datasets either in their actual form or after certain specific and often enforced, thematic and spatial inference. Considerable imperfection may occur in the accuracy and reliability of the map products, since there might be significant discrepancies between the available data and the expected information. The DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project was started intentionally for the renewal of the national soil spatial infrastructure in Hungary. During our activities we have significantly extended the potential, how soil information requirements could be satisfied. Soil property, soil type as well as functional soil maps were targeted. The set of the applied digital soil mapping techniques has been gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Soil property maps have been compiled partly according to GSM.net specifications, partly by slightly or more strictly changing some of their predefined parameters (depth intervals, pixel size, property etc.) according to the specific demands on the final products. The elaborated primary maps were further processed, since even DOSoReMI.hu intended to take steps for the regionalization of higher level soil information (processes, functions, and services) involving crop models in the spatial modelling. The framework of DOSoReMI.hu also provides opportunity for the elaboration of goal specific soil maps, with the prescription of the parameters (thematic, resolution, accuracy, reliability etc.) characterizing the map product. As a result, unique digital soil map products (in a more general meaning) were elaborated regionalizing specific soil (related) features, which were never mapped before, even nationally with high ( 1 ha) spatial resolution. Based upon the collected experiences, the full range of GSM.net products were also targeted. The web publishing of the results was also elaborated creating a proper WMS environment. Our paper will present the resulted national maps furthermore some conclusions drawn from the experiences.] Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA) under Grant K105167 and AGRARKLÍMA.2 VKSZ_12-1-2013-0034.

Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

NASA Astrophysics Data System (ADS)

Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

2014-11-01

Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.

Improving spectral resolution in spatial encoding dimension of single-scan nuclear magnetic resonance 2D spin echo correlated spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Liangjie; Wei, Zhiliang; Yang, Jian; Lin, Yanqin; Chen, Zhong

2014-11-01

The spatial encoding technique can be used to accelerate the acquisition of multi-dimensional nuclear magnetic resonance spectra. However, with this technique, we have to make trade-offs between the spectral width and the resolution in the spatial encoding dimension (F1 dimension), resulting in the difficulty of covering large spectral widths while preserving acceptable resolutions for spatial encoding spectra. In this study, a selective shifting method is proposed to overcome the aforementioned drawback. This method is capable of narrowing spectral widths and improving spectral resolutions in spatial encoding dimensions by selectively shifting certain peaks in spectra of the ultrafast version of spin echo correlated spectroscopy (UFSECSY). This method can also serve as a powerful tool to obtain high-resolution correlated spectra in inhomogeneous magnetic fields for its resistance to any inhomogeneity in the F1 dimension inherited from UFSECSY. Theoretical derivations and experiments have been carried out to demonstrate performances of the proposed method. Results show that the spectral width in spatial encoding dimension can be reduced by shortening distances between cross peaks and axial peaks with the proposed method and the expected resolution improvement can be achieved. Finally, the shifting-absent spectrum can be recovered readily by post-processing.

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Sympathy for the Devil: Detailing the Effects of Planning-Unit Size, Thematic Resolution of Reef Classes, and Socioeconomic Costs on Spatial Priorities for Marine Conservation

PubMed Central

Pressey, Robert L.; Weeks, Rebecca; Andréfouët, Serge; Moloney, James

2016-01-01

Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors—planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs—on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs. PMID:27829042

Sympathy for the Devil: Detailing the Effects of Planning-Unit Size, Thematic Resolution of Reef Classes, and Socioeconomic Costs on Spatial Priorities for Marine Conservation.

PubMed

Cheok, Jessica; Pressey, Robert L; Weeks, Rebecca; Andréfouët, Serge; Moloney, James

2016-01-01

Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors-planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs-on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs.

Investigation of spatial resolution improvement by use of a mouth-insert detector in the helmet PET scanner.

PubMed

Ahmed, Abdella M; Tashima, Hideaki; Yamaya, Taiga

2018-03-01

The dominant factor limiting the intrinsic spatial resolution of a positron emission tomography (PET) system is the size of the crystal elements in the detector. To increase sensitivity and achieve high spatial resolution, it is essential to use advanced depth-of-interaction (DOI) detectors and arrange them close to the subject. The DOI detectors help maintain high spatial resolution by mitigating the parallax error caused by the thickness of the scintillator near the peripheral regions of the field-of-view. As an optimal geometry for a brain PET scanner, with high sensitivity and spatial resolution, we proposed and developed the helmet-chin PET scanner using 54 four-layered DOI detectors consisting of a 16 × 16 × 4 array of GSOZ scintillator crystals with dimensions of 2.8 × 2.8 × 7.5 mm 3 . All the detectors used in the helmet-chin PET scanner had the same spatial resolution. In this study, we conducted a feasibility study of a new add-on detector arrangement for the helmet PET scanner by replacing the chin detector with a segmented crystal cube, having high spatial resolution in all directions, which can be placed inside the mouth. The crystal cube (which we have named the mouth-insert detector) has an array of 20 × 20 × 20 LYSO crystal segments with dimensions of 1 × 1 × 1 mm 3 . Thus, the scanner is formed by the combination of the helmet and mouth-insert detectors, and is referred to as the helmet-mouth-insert PET scanner. The results show that the helmet-mouth-insert PET scanner has comparable sensitivity and improved spatial resolution near the center of the hemisphere, compared to the helmet-chin PET scanner.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Developing a CCD camera with high spatial resolution for RIXS in the soft X-ray range

NASA Astrophysics Data System (ADS)

Soman, M. R.; Hall, D. J.; Tutt, J. H.; Murray, N. J.; Holland, A. D.; Schmitt, T.; Raabe, J.; Schmitt, B.

2013-12-01

The Super Advanced X-ray Emission Spectrometer (SAXES) at the Swiss Light Source contains a high resolution Charge-Coupled Device (CCD) camera used for Resonant Inelastic X-ray Scattering (RIXS). Using the current CCD-based camera system, the energy-dispersive spectrometer has an energy resolution (E/ΔE) of approximately 12,000 at 930 eV. A recent study predicted that through an upgrade to the grating and camera system, the energy resolution could be improved by a factor of 2. In order to achieve this goal in the spectral domain, the spatial resolution of the CCD must be improved to better than 5 μm from the current 24 μm spatial resolution (FWHM). The 400 eV-1600 eV energy X-rays detected by this spectrometer primarily interact within the field free region of the CCD, producing electron clouds which will diffuse isotropically until they reach the depleted region and buried channel. This diffusion of the charge leads to events which are split across several pixels. Through the analysis of the charge distribution across the pixels, various centroiding techniques can be used to pinpoint the spatial location of the X-ray interaction to the sub-pixel level, greatly improving the spatial resolution achieved. Using the PolLux soft X-ray microspectroscopy endstation at the Swiss Light Source, a beam of X-rays of energies from 200 eV to 1400 eV can be focused down to a spot size of approximately 20 nm. Scanning this spot across the 16 μm square pixels allows the sub-pixel response to be investigated. Previous work has demonstrated the potential improvement in spatial resolution achievable by centroiding events in a standard CCD. An Electron-Multiplying CCD (EM-CCD) has been used to improve the signal to effective readout noise ratio achieved resulting in a worst-case spatial resolution measurement of 4.5±0.2 μm and 3.9±0.1 μm at 530 eV and 680 eV respectively. A method is described that allows the contribution of the X-ray spot size to be deconvolved from these worst-case resolution measurements, estimating the spatial resolution to be approximately 3.5 μm and 3.0 μm at 530 eV and 680 eV, well below the resolution limit of 5 μm required to improve the spectral resolution by a factor of 2.

Coarse climate change projections for species living in a fine-scaled world.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-01-01

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change. © 2016 John Wiley & Sons Ltd.

Changes in precipitation isotope-climate relationships from temporal grouping and aggregation of weekly-resolved USNIP data: impacts on paleoclimate and environmental applications

NASA Astrophysics Data System (ADS)

Akers, P. D.; Welker, J. M.

2015-12-01

Spatial variations in precipitation isotopes have been the focus of much recent research, but relatively less work has explored changes at various temporal scales. This is partly because most spatially-diverse and long-term isotope databases are offered at a monthly resolution, while daily or event-level records are spatially and temporally limited by cost and logistics. A subset of 25 United States Network for Isotopes in Precipitation (USNIP) sites with weekly-resolution in the east-central United States was analyzed for site-specific relationships between δ18O and δD (the local meteoric water line/LMWL), δ18O and surface temperature, and δ18O and precipitation amount. Weekly data were then aggregated into monthly and seasonal data to examine the effect of aggregation on correlation and slope values for each of the relationships. Generally, increasing aggregation improved correlations (>25% for some sites) due to a reduced effect of extreme values, but estimates on regression variable error increased (>100%) because of reduced sample sizes. Aggregation resulted in small, but significant drops (5-25%) in relationship slope values for some sites. Weekly data were also grouped by month and season to explore changes in relationships throughout the year. Significant subannual variability exists in slope values and correlations even for sites with very strong overall correlations. LMWL slopes are highest in winter and lowest in summer, while the δ18O-surface temperature relationship is strongest in spring. Despite these overall trends, a high level of month-to-month and season-to-season variability is the norm for these sites. Researchers blindly applying overall relationships drawn from monthly-resolved databases to paleoclimate or environmental research risk assuming these relationships apply at all temporal resolutions. When possible, researchers should match the temporal resolution used to calculate an isotopic relationship with the temporal resolution of their applied proxy.

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Development and Characterization of a Dither-Based Super-Resolution Reconstruction Method for Fiber Imaging Arrays

NASA Astrophysics Data System (ADS)

Languirand, Eric Robert

Chemical imaging is an important tool for providing insight into function, role, and spatial distribution of analytes. This thesis describes the use of imaging fiber bundles (IFB) for super-resolution reconstruction using surface enhanced Raman scattering (SERS) showing improvement in resolution with arrayed bundles for the first time. Additionally this thesis describes characteristics of the IFB with regards to cross-talk as a function of aperture size. The first part of this thesis characterizes the IFB for both tapered and untapered bundles in terms of cross-talk. Cross-talk is defined as the amount of light leaking from a central fiber element in the imaging fiber bundle to surrounding fiber elements. To make this measurement ubiquitous for all imaging bundles, quantum dots were employed. Untapered and tapered IFB possess cross-talk of 2% or less, with fiber elements down to 32nm. The second part of this thesis employs a super resolution reconstruction algorithm using projection onto convex sets for resolution improvement. When using IFB arrays, the point spread function (PSF) of the array can be known accurately if the fiber elements over fill the pixel detector array. Therefore, the use of the known PSF compared to a general blurring kernel was evaluated. Relative increases in resolution of 12% and 2% at the 95% confidence level are found, when compared to a reference image, for the general blurring kernel and PSF, respectively. The third part of this thesis shows for the first time the use of SERS with a dithered IFB array coupled with super-resolution reconstruction. The resolution improvement across a step-edge is shown to be approximately 20% when compared to a reference image. This provides an additional means of increasing the resolution of fiber bundles beyond that of just tapering. Furthermore, this provides a new avenue for nanoscale imaging using these bundles. Lastly, synthetic data with varying degrees of signal-to-noise (S/N) were employed to explore the relationship S/N has with the reconstruction process. It is generally shown that increasing the number images used in the reconstruction process and increasing the S/N will improve the reconstruction providing larger increases in resolution.

The moderate resolution imaging spectrometer (MODIS) science and data system requirements

NASA Technical Reports Server (NTRS)

Ardanuy, Philip E.; Han, Daesoo; Salomonson, Vincent V.

1991-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) has been designated as a facility instrument on the first NASA polar orbiting platform as part of the Earth Observing System (EOS) and is scheduled for launch in the late 1990s. The near-global daily coverage of MODIS, combined with its continuous operation, broad spectral coverage, and relatively high spatial resolution, makes it central to the objectives of EOS. The development, implementation, production, and validation of the core MODIS data products define a set of functional, performance, and operational requirements on the data system that operate between the sensor measurements and the data products supplied to the user community. The science requirements guiding the processing of MODIS data are reviewed, and the aspects of an operations concept for the production of data products from MODIS for use by the scientific community are discussed.

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T

2013-08-01

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.

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.

Visual resolution and contrast sensitivity in two benthic sharks.

PubMed

Ryan, Laura A; Hart, Nathan S; Collin, Shaun P; Hemmi, Jan M

2016-12-15

Sharks have long been described as having 'poor' vision. They are cone monochromats and anatomical estimates suggest they have low spatial resolution. However, there are no direct behavioural measurements of spatial resolution or contrast sensitivity. This study estimates contrast sensitivity and spatial resolution of two species of benthic sharks, the Port Jackson shark, Heterodontus portusjacksoni, and the brown-banded bamboo shark, Chiloscyllium punctatum, by recording eye movements in response to optokinetic stimuli. Both species tracked moving low spatial frequency gratings with weak but consistent eye movements. Eye movements ceased at 0.38 cycles per degree, even for high contrasts, suggesting low spatial resolution. However, at lower spatial frequencies, eye movements were elicited by low contrast gratings, 1.3% and 2.9% contrast in H portusjacksoni and C. punctatum, respectively. Contrast sensitivity was higher than in other vertebrates with a similar spatial resolving power, which may reflect an adaptation to the relatively low contrast encountered in aquatic environments. Optokinetic gain was consistently low and neither species stabilised the gratings on their retina. To check whether restraining the animals affected their optokinetic responses, we also analysed eye movements in free-swimming C. punctatum We found no eye movements that could compensate for body rotations, suggesting that vision may pass through phases of stabilisation and blur during swimming. As C. punctatum is a sedentary benthic species, gaze stabilisation during swimming may not be essential. Our results suggest that vision in sharks is not 'poor' as previously suggested, but optimised for contrast detection rather than spatial resolution. © 2016. Published by The Company of Biologists Ltd.

Study of spatial resolution of coordinate detectors based on Gas Electron Multipliers

NASA Astrophysics Data System (ADS)

Kudryavtsev, V. N.; Maltsev, T. V.; Shekhtman, L. I.

2017-02-01

Spatial resolution of GEM-based tracking detectors is determined in the simulation and measured in the experiments. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting of atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing with accounting of diffusion, gas amplification fluctuations, distribution of signals on readout electrodes, electronics noise and particular algorithm of final coordinate calculation (center of gravity). The simulation demonstrates that the minimum of spatial resolution of about 10 μm can be achieved with a gas mixture of Ar -CO2 (75-25 %) at a strips pitch from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 80-100 μm at a pitch of 460-500 μm. Spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at the VEPP-3 storage ring is measured at the extracted beam facility of the VEPP-4 M collider. One-coordinate resolution of the DEUTERON detector is measured with electron beam of 500 MeV, 1 GeV and 3.5 GeV energies. The determined value of spatial resolution varies in the range from approximately 35 μm to 50 μm for orthogonal tracks in the experiments.

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

NASA Astrophysics Data System (ADS)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Long-Duration Environmentally-Adaptive Autonomous Rigorous Naval Systems

DTIC Science & Technology

2015-09-30

equations). The accuracy of the DO level-set equations for solving the governing stochastic level-set reachability fronts was first verified in part by...reachable set contours computed by DO and MC. We see that it is less than the spatial resolution used, indicating our DO solutions are accurate. We solved ...the interior of the sensors’ reachable sets, all the physically impossible trajectories are immediately ruled out. However, this approach is myopic

Shift focal spot X-ray tube to the imposition anode under long exposure

NASA Astrophysics Data System (ADS)

Obodovskiy, A. V.; Bessonov, V. B.; Larionov, I. A.

2018-02-01

X-ray non-destructive testing is an integral part of any modern industrial production. Microfocus X-ray sources make it possible to obtain projected images with an increased spatial resolution by using a direct geometric magnification during the survey. On the basis of the St. Petersburg State Electrotechnical University staff of the department of electronic devices and equipment has been designed model of microfocus X-ray computed tomography.

Effects of configural processing on the perceptual spatial resolution for face features.

PubMed

Namdar, Gal; Avidan, Galia; Ganel, Tzvi

2015-11-01

Configural processing governs human perception across various domains, including face perception. An established marker of configural face perception is the face inversion effect, in which performance is typically better for upright compared to inverted faces. In two experiments, we tested whether configural processing could influence basic visual abilities such as perceptual spatial resolution (i.e., the ability to detect spatial visual changes). Face-related perceptual spatial resolution was assessed by measuring the just noticeable difference (JND) to subtle positional changes between specific features in upright and inverted faces. The results revealed robust inversion effect for spatial sensitivity to configural-based changes, such as the distance between the mouth and the nose, or the distance between the eyes and the nose. Critically, spatial resolution for face features within the region of the eyes (e.g., the interocular distance between the eyes) was not affected by inversion, suggesting that the eye region operates as a separate 'gestalt' unit which is relatively immune to manipulations that would normally hamper configural processing. Together these findings suggest that face orientation modulates fundamental psychophysical abilities including spatial resolution. Furthermore, they indicate that classic psychophysical methods can be used as a valid measure of configural face processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Super resolution PLIF demonstrated in turbulent jet flows seeded with I2

NASA Astrophysics Data System (ADS)

Xu, Wenjiang; Liu, Ning; Ma, Lin

2018-05-01

Planar laser induced fluorescence (PLIF) represents an indispensable tool for flow and flame imaging. However, the PLIF technique suffers from limited spatial resolution or blurring in many situations, which restricts its applicability and capability. This work describes a new method, named SR-PLIF (super-resolution PLIF), to overcome these limitations and enhance the capability of PLIF. The method uses PLIF images captured simultaneously from two (or more) orientations to reconstruct a final PLIF image with resolution enhanced or blurring removed. This paper reports the development of the reconstruction algorithm, and the experimental demonstration of the SR-PLIF method both with controlled samples and with turbulent flows seeded with iodine vapor. Using controlled samples with two cameras, the spatial resolution in the best case was improved from 0.06 mm in the projections to 0.03 mm in the SR image, in terms of the spreading width of a sharp edge. With turbulent flows, an image sharpness measure was developed to quantify the spatial resolution, and SR reconstruction with two cameras can effectively improve the spatial resolution compared to the projections in terms of the sharpness measure.

Spatial entanglement patterns and Einstein-Podolsky-Rosen steering in Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Fadel, Matteo; Zibold, Tilman; Décamps, Boris; Treutlein, Philipp

2018-04-01

Many-particle entanglement is a fundamental concept of quantum physics that still presents conceptual challenges. Although nonclassical states of atomic ensembles were used to enhance measurement precision in quantum metrology, the notion of entanglement in these systems was debated because the correlations among the indistinguishable atoms were witnessed by collective measurements only. Here, we use high-resolution imaging to directly measure the spin correlations between spatially separated parts of a spin-squeezed Bose-Einstein condensate. We observe entanglement that is strong enough for Einstein-Podolsky-Rosen steering: We can predict measurement outcomes for noncommuting observables in one spatial region on the basis of corresponding measurements in another region with an inferred uncertainty product below the Heisenberg uncertainty bound. This method could be exploited for entanglement-enhanced imaging of electromagnetic field distributions and quantum information tasks.

Four-Photon Imaging with Thermal Light

NASA Astrophysics Data System (ADS)

Wen, Feng; Xue, Xinxin; Zhang, Xun; Yuan, Chenzhi; Sun, Jia; Song, Jianping; Zhang, Yanpeng

2014-10-01

In a near-field four-photon correlation measurement, ghost imaging with classical incoherent light is investigated. By applying the Klyshko advanced-wave picture, we consider the properties of four-photon spatial correlation and find that the fourth-order spatial correlation function can be decomposed into multiple lower-order correlation functions. On the basis of the spatial correlation properties, a proof-of-principle four-photon ghost imaging is proposed, and the effect of each part in a fourth-order correlation function on imaging is also analyzed. In addition, the similarities and differences among ghost imaging by fourth-, second-, and third-order correlations are also discussed. It is shown that the contrast and visibility of fourth-order correlated imaging are improved significantly, while the resolution is unchanged. Such studies can be very useful in better understanding multi photon interference and multi-channel correlation imaging.

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

DOE PAGES

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.; ...

2016-02-05

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

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

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

Web and Desktop Applications for ALMA Science Verification Data

NASA Astrophysics Data System (ADS)

Shirasaki, Y.; Kawasaki, W.; Eguchi, S.; Komiya, Y.; Kosugi, G.; Ohishi, M.; Mizumoto, Y.

2013-10-01

ALMA is the largest radio telescope operating in Chile, and it is expected to produce 200 TB of data every year. Even a data cube obtained for a single source can exceed 1 TB. It is, therefore, crucial to reduce the size of data transmitted through the Internet by doing a cutout of a part of a data cube and/or reducing the spatial/frequency resolution before transferring the data. To specify the cutout region or required resolution, one needs to overview the whole of the data without transferring the large data cube. For this purpose, we developed two applications for quick-looking ALMA data cube, ALMA Web QL and Desktop Viewer (Vissage).

Imaging Mass Spectrometry on the Nanoscale with Cluster Ion Beams

DOE PAGES

Winograd, Nicholas

2014-12-02

Imaging with cluster secondary ion mass spectrometry (SIMS) is reaching a mature level of development. When, using a variety of molecular ion projectiles to stimulate desorption, 3-dimensional imaging with the selectivity of mass spectrometry can now be achieved with submicrometer spatial resolution and <10 nm depth resolution. In this Perspective, stock is taken regarding what it will require to routinely achieve these remarkable properties. Some issues include the chemical nature of the projectile, topography formation, differential erosion rates, and perhaps most importantly, ionization efficiency. Shortcomings of existing instrumentation are also noted. One key part of this discussion involves speculation onmore » how best to resolve these issues.« less

Imaging Mass Spectrometry on the Nanoscale with Cluster Ion Beams

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

Winograd, Nicholas

Imaging with cluster secondary ion mass spectrometry (SIMS) is reaching a mature level of development. When, using a variety of molecular ion projectiles to stimulate desorption, 3-dimensional imaging with the selectivity of mass spectrometry can now be achieved with submicrometer spatial resolution and <10 nm depth resolution. In this Perspective, stock is taken regarding what it will require to routinely achieve these remarkable properties. Some issues include the chemical nature of the projectile, topography formation, differential erosion rates, and perhaps most importantly, ionization efficiency. Shortcomings of existing instrumentation are also noted. One key part of this discussion involves speculation onmore » how best to resolve these issues.« less

Effects of CT resolution and radiodensity threshold on the CFD evaluation of nasal airflow.

PubMed

Quadrio, Maurizio; Pipolo, Carlotta; Corti, Stefano; Messina, Francesco; Pesci, Chiara; Saibene, Alberto M; Zampini, Samuele; Felisati, Giovanni

2016-03-01

The article focuses on the robustness of a CFD-based procedure for the quantitative evaluation of the nasal airflow. CFD ability to yield robust results with respect to the unavoidable procedural and modeling inaccuracies must be demonstrated to allow this tool to become part of the clinical practice in this field. The present article specifically addresses the sensitivity of the CFD procedure to the spatial resolution of the available CT scans, as well as to the choice of the segmentation level of the CT images. We found no critical problems concerning these issues; nevertheless, the choice of the segmentation level is potentially delicate if carried out by an untrained operator.

Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

NASA Astrophysics Data System (ADS)

Hester, David Barry

The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the cost of high resolution imagery continues to decline, this research makes an important contribution to this exciting era in the science of remote sensing.

Integrating Eddy Covariance, Penman-Monteith and METRIC based Evapotranspiration estimates to generate high resolution space-time ET over the Brazos River Basin

NASA Astrophysics Data System (ADS)

Mbabazi, D.; Mohanty, B.; Gaur, N.

2017-12-01

Evapotranspiration (ET) is an important component of the water and energy balance and accounts for 60 -70% of precipitation losses. However, accurate estimates of ET are difficult to quantify at varying spatial and temporal scales. Eddy covariance methods estimate ET at high temporal resolutions but without capturing the spatial variation in ET within its footprint. On the other hand, remote sensing methods using Landsat imagery provide ET with high spatial resolution but low temporal resolution (16 days). In this study, we used both eddy covariance and remote sensing methods to generate high space-time resolution ET. Daily, monthly and seasonal ET estimates were obtained using the eddy covariance (EC) method, Penman-Monteith (PM) and Mapping Evapotranspiration with Internalized Calibration (METRIC) models to determine cotton and native prairie ET dynamics in the Brazos river basin characterized by varying hydro-climatic and geological gradients. Daily estimates of spatially distributed ET (30 m resolution) were generated using spatial autocorrelation and temporal interpolations between the EC flux variable footprints and METRIC ET for the 2016 and 2017 growing seasons. A comparison of the 2016 and 2017 preliminary daily ET estimates showed similar ET dynamics/trends among the EC, PM and METRIC methods, and 5-20% differences in seasonal ET estimates. This study will improve the spatial estimates of EC ET and temporal resolution of satellite derived ET thus providing better ET data for water use management.

Effects of finite hot-wire spatial resolution on turbulence statistics and velocity spectra in a round turbulent free jet

NASA Astrophysics Data System (ADS)

Sadeghi, Hamed; Lavoie, Philippe; Pollard, Andrew

2018-03-01

The effect of finite hot-wire spatial resolution on turbulence statistics and velocity spectra in a round turbulent free jet is investigated. To quantify spatial resolution effects, measurements were taken using a nano-scale thermal anemometry probe (NSTAP) and compared to results from conventional hot-wires with sensing lengths of l=0.5 and 1 mm. The NSTAP has a sensing length significantly smaller than the Kolmogorov length scale η for the present experimental conditions, whereas the sensing lengths for the conventional probes are larger than η. The spatial resolution is found to have a significant impact on the dissipation both on and off the jet centreline with the NSTAP results exceeding those obtained from the conventional probes. The resolution effects along the jet centreline are adequately predicted using a Wyngaard-type spectral technique (Wyngaard in J Sci Instr 1(2):1105-1108,1968), but additional attenuation on the measured turbulence quantities are observed off the centreline. The magnitude of this attenuation is a function of both the ratio of wire length to Kolmogorov length scale and the magnitude of the shear. The effect of spatial resolution is noted to have an impact on the power-law decay parameters for the turbulent kinetic energy that is computed. The effect of spatial filtering on the streamwise dissipation energy spectra is also considered. Empirical functions are proposed to estimate the effect of finite resolution, which take into account the mean shear.

Spatial resolution versus contrast trade-off enhancement in high-resolution surface plasmon resonance imaging (SPRI) by metal surface nanostructure design.

PubMed

Banville, Frederic A; Moreau, Julien; Sarkar, Mitradeep; Besbes, Mondher; Canva, Michael; Charette, Paul G

2018-04-16

Surface plasmon resonance imaging (SPRI) is an optical near-field method used for mapping the spatial distribution of chemical/physical perturbations above a metal surface without exogenous labeling. Currently, the majority of SPRI systems are used in microarray biosensing, requiring only modest spatial resolution. There is increasing interest in applying SPRI for label-free near-field imaging of biological cells to study cell/surface interactions. However, the required resolution (sub-µm) greatly exceeds what current systems can deliver. Indeed, the attenuation length of surface plasmon polaritons (SPP) severely limits resolution along one axis, typically to tens of µm. Strategies to date for improving spatial resolution result in a commensurate deterioration in other imaging parameters. Unlike the smooth metal surfaces used in SPRI that support purely propagating surface modes, nanostructured metal surfaces support "hybrid" SPP modes that share attributes from both propagating and localized modes. We show that these hybrid modes are especially well-suited to high-resolution imaging and demonstrate how the nanostructure geometry can be designed to achieve sub-µm resolution while mitigating the imaging parameter trade-off according to an application-specific optimum.

Two-photon imaging of spatially extended neuronal network dynamics with high temporal resolution.

PubMed

Lillis, Kyle P; Eng, Alfred; White, John A; Mertz, Jerome

2008-07-30

We describe a simple two-photon fluorescence imaging strategy, called targeted path scanning (TPS), to monitor the dynamics of spatially extended neuronal networks with high spatiotemporal resolution. Our strategy combines the advantages of mirror-based scanning, minimized dead time, ease of implementation, and compatibility with high-resolution low-magnification objectives. To demonstrate the performance of TPS, we monitor the calcium dynamics distributed across an entire juvenile rat hippocampus (>1.5mm), at scan rates of 100 Hz, with single cell resolution and single action potential sensitivity. Our strategy for fast, efficient two-photon microscopy over spatially extended regions provides a particularly attractive solution for monitoring neuronal population activity in thick tissue, without sacrificing the signal-to-noise ratio or high spatial resolution associated with standard two-photon microscopy. Finally, we provide the code to make our technique generally available.

High Resolution Tissue Imaging Using the Single-probe Mass Spectrometry under Ambient Conditions

NASA Astrophysics Data System (ADS)

Rao, Wei; Pan, Ning; Yang, Zhibo

2015-06-01

Ambient mass spectrometry imaging (MSI) is an emerging field with great potential for the detailed spatial analysis of biological samples with minimal pretreatment. We have developed a miniaturized sampling and ionization device, the Single-probe, which uses in-situ surface micro-extraction to achieve high detection sensitivity and spatial resolution during MSI experiments. The Single-probe was coupled to a Thermo LTQ Orbitrap XL mass spectrometer and was able to create high spatial and high mass resolution MS images at 8 ± 2 and 8.5 μm on flat polycarbonate microscope slides and mouse kidney sections, respectively, which are among the highest resolutions available for ambient MSI techniques. Our proof-of-principle experiments indicate that the Single-probe MSI technique has the potential to obtain ambient MS images with very high spatial resolutions with minimal sample preparation, which opens the possibility for subcellular ambient tissue MSI to be performed in the future.

High Speed Computational Ghost Imaging via Spatial Sweeping

NASA Astrophysics Data System (ADS)

Wang, Yuwang; Liu, Yang; Suo, Jinli; Situ, Guohai; Qiao, Chang; Dai, Qionghai

2017-03-01

Computational ghost imaging (CGI) achieves single-pixel imaging by using a Spatial Light Modulator (SLM) to generate structured illuminations for spatially resolved information encoding. The imaging speed of CGI is limited by the modulation frequency of available SLMs, and sets back its practical applications. This paper proposes to bypass this limitation by trading off SLM’s redundant spatial resolution for multiplication of the modulation frequency. Specifically, a pair of galvanic mirrors sweeping across the high resolution SLM multiply the modulation frequency within the spatial resolution gap between SLM and the final reconstruction. A proof-of-principle setup with two middle end galvanic mirrors achieves ghost imaging as fast as 42 Hz at 80 × 80-pixel resolution, 5 times faster than state-of-the-arts, and holds potential for one magnitude further multiplication by hardware upgrading. Our approach brings a significant improvement in the imaging speed of ghost imaging and pushes ghost imaging towards practical applications.

Edge-Preserving Image Smoothing Constraint in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) of Hyperspectral Data.

PubMed

Hugelier, Siewert; Vitale, Raffaele; Ruckebusch, Cyril

2018-03-01

This article explores smoothing with edge-preserving properties as a spatial constraint for the resolution of hyperspectral images with multivariate curve resolution-alternating least squares (MCR-ALS). For each constrained component image (distribution map), irrelevant spatial details and noise are smoothed applying an L 1 - or L 0 -norm penalized least squares regression, highlighting in this way big changes in intensity of adjacent pixels. The feasibility of the constraint is demonstrated on three different case studies, in which the objects under investigation are spatially clearly defined, but have significant spectral overlap. This spectral overlap is detrimental for obtaining a good resolution and additional spatial information should be provided. The final results show that the spatial constraint enables better image (map) abstraction, artifact removal, and better interpretation of the results obtained, compared to a classical MCR-ALS analysis of hyperspectral images.

Introduction of digital soil mapping techniques for the nationwide regionalization of soil condition in Hungary; the first results of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Dobos, Endre

2014-05-01

Due to the former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfilled with these available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project (DOSoReMI.hu; Digital, Optimized, Soil Related Maps and Information in Hungary) we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied in Hungary. We started to compile digital soil related maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The spatial resolution of the targeted countrywide, digital, thematic maps is at least 1:50.000 (approx. 50-100 meter raster resolution). DOSoReMI.hu results are also planned to contribute to the European part of GSM.net products. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. In our paper we will present the first results. - Regression kriging (RK) has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matter content. In the course of RK-based mapping spatially segmented categorical information provided by the SMUs of Digital Kreybig Soil Information System (DKSIS) has been also used in the form of indicator variables. - Classification and regression trees (CART) were used to improve the spatial resolution of category-type soil maps (thematic downscaling), like genetic soil type and soil productivity maps. The approach was justified by the fact that certain thematic soil maps are not available in the required scale. Decision trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identified and expressed in decision rules made the creation of spatially refined maps possible with the aid of high resolution environmental auxiliary variables. Among these co-variables, a special role was played by larger scale spatial soil information with diverse attributes. As a next step, the testing of random forests for the same purposes has been started. - Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil (related) map. This suggests the opportunity of optimization. For the creation of an object specific soil (related) map with predefined parameters (resolution, accuracy, reliability etc.) one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). The first findings on the inclusion and joint usage of spatial soil data as well as on the consistency of various evaluations of the result maps will be also presented. Acknowledgement: Our work has been supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

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.

Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations.

PubMed

Van Steenkiste, Gwendolyn; Jeurissen, Ben; Veraart, Jelle; den Dekker, Arnold J; Parizel, Paul M; Poot, Dirk H J; Sijbers, Jan

2016-01-01

Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images. An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation. Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error. The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time. © 2015 Wiley Periodicals, Inc.

Camera system resolution and its influence on digital image correlation

DOE PAGES

Reu, Phillip L.; Sweatt, William; Miller, Timothy; ...

2014-09-21

Digital image correlation (DIC) uses images from a camera and lens system to make quantitative measurements of the shape, displacement, and strain of test objects. This increasingly popular method has had little research on the influence of the imaging system resolution on the DIC results. This paper investigates the entire imaging system and studies how both the camera and lens resolution influence the DIC results as a function of the system Modulation Transfer Function (MTF). It will show that when making spatial resolution decisions (including speckle size) the resolution limiting component should be considered. A consequence of the loss ofmore » spatial resolution is that the DIC uncertainties will be increased. This is demonstrated using both synthetic and experimental images with varying resolution. The loss of image resolution and DIC accuracy can be compensated for by increasing the subset size, or better, by increasing the speckle size. The speckle-size and spatial resolution are now a function of the lens resolution rather than the more typical assumption of the pixel size. The study will demonstrate the tradeoffs associated with limited lens resolution.« less

Attenuated total reflection-Fourier transform infrared imaging of large areas using inverted prism crystals and combining imaging and mapping.

PubMed

Chan, K L Andrew; Kazarian, Sergei G

2008-10-01

Attenuated total reflection-Fourier transform infrared (ATR-FT-IR) imaging is a very useful tool for capturing chemical images of various materials due to the simple sample preparation and the ability to measure wet samples or samples in an aqueous environment. However, the size of the array detector used for image acquisition is often limited and there is usually a trade off between spatial resolution and the field of view (FOV). The combination of mapping and imaging can be used to acquire images with a larger FOV without sacrificing spatial resolution. Previous attempts have demonstrated this using an infrared microscope and a Germanium hemispherical ATR crystal to achieve images of up to 2.5 mm x 2.5 mm but with varying spatial resolution and depth of penetration across the imaged area. In this paper, we demonstrate a combination of mapping and imaging with a different approach using an external optics housing for large ATR accessories and inverted ATR prisms to achieve ATR-FT-IR images with a large FOV and reasonable spatial resolution. The results have shown that a FOV of 10 mm x 14 mm can be obtained with a spatial resolution of approximately 40-60 microm when using an accessory that gives no magnification. A FOV of 1.3 mm x 1.3 mm can be obtained with spatial resolution of approximately 15-20 microm when using a diamond ATR imaging accessory with 4x magnification. No significant change in image quality such as spatial resolution or depth of penetration has been observed across the whole FOV with this method and the measurement time was approximately 15 minutes for an image consisting of 16 image tiles.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

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

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

The Use of Coarse Resolution Satellite Imagery to Predict Human Puumala Virus Epidemics in Sweden.

DTIC Science & Technology

1992-09-11

the adverse effects on NDVI data quality can occur in both the spatial and temporal dimension. In other words, a specific pixel value recorded in...are compared to the land-oriented systems.22 On the other hand, the very course spatial resolution has the advantage of greatly reducing the volume...necessary on the scale of individual fields, in which case LANDSAT-TM has higher spatial resolution ; and secondly, when specific

Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

NASA Astrophysics Data System (ADS)

Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

2015-10-01

The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

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.

Spatial Resolution, Grayscale, and Error Diffusion Trade-offs: Impact on Display System Design

NASA Technical Reports Server (NTRS)

Gille, Jennifer L. (Principal Investigator)

1996-01-01

We examine technology trade-offs related to grayscale resolution, spatial resolution, and error diffusion for tessellated display systems. We present new empirical results from our psychophysical study of these trade-offs and compare them to the predictions of a model of human vision.

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

Krishnan, Venkat; Cole, Wesley

This poster is based on the paper of the same name, presented at the IEEE Power & Energy Society General Meeting, July18, 2016. 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 solarmore » modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions - native resolution (134 BAs), state-level, and NERC 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

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

Gao, Lan, E-mail: lgao@pppl.gov; Hill, K. W.; Bitter, M.

A high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ{sub 2} rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystal (p)more » and crystal-to-detector (q) distances were varied to produce spatial magnifications (M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Simulation the spatial resolution of an X-ray imager based on zinc oxide nanowires in anodic aluminium oxide membrane by using MCNP and OPTICS Codes

NASA Astrophysics Data System (ADS)

Samarin, S. N.; Saramad, S.

2018-05-01

The spatial resolution of a detector is a very important parameter for x-ray imaging. A bulk scintillation detector because of spreading of light inside the scintillator does't have a good spatial resolution. The nanowire scintillators because of their wave guiding behavior can prevent the spreading of light and can improve the spatial resolution of traditional scintillation detectors. The zinc oxide (ZnO) scintillator nanowire, with its simple construction by electrochemical deposition in regular hexagonal structure of Aluminum oxide membrane has many advantages. The three dimensional absorption of X-ray energy in ZnO scintillator is simulated by a Monte Carlo transport code (MCNP). The transport, attenuation and scattering of the generated photons are simulated by a general-purpose scintillator light response simulation code (OPTICS). The results are compared with a previous publication which used a simulation code of the passage of particles through matter (Geant4). The results verify that this scintillator nanowire structure has a spatial resolution less than one micrometer.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

Automatic optical inspection of regular grid patterns with an inspection camera used below the Shannon-Nyquist criterion for optical resolution

NASA Astrophysics Data System (ADS)

Ferreira, Flávio P.; Forte, Paulo M. F.; Felgueiras, Paulo E. R.; Bret, Boris P. J.; Belsley, Michael S.; Nunes-Pereira, Eduardo J.

2017-02-01

An Automatic Optical Inspection (AOI) system for optical inspection of imaging devices used in automotive industry using an inspecting optics of lower spatial resolution than the device under inspection is described. This system is robust and with no moving parts. The cycle time is small. Its main advantage is that it is capable of detecting and quantifying defects in regular patterns, working below the Shannon-Nyquist criterion for optical resolution, using a single low resolution image sensor. It is easily scalable, which is an important advantage in industrial applications, since the same inspecting sensor can be reused for increasingly higher spatial resolutions of the devices to be inspected. The optical inspection is implemented with a notch multi-band Fourier filter, making the procedure especially fitted for regular patterns, like the ones that can be produced in image displays and Head Up Displays (HUDs). The regular patterns are used in production line only, for inspection purposes. For image displays, functional defects are detected at the level of a sub-image display grid element unit. Functional defects are the ones impairing the function of the display, and are preferred in AOI to the direct geometric imaging, since those are the ones directly related with the end-user experience. The shift in emphasis from geometric imaging to functional imaging is critical, since it is this that allows quantitative inspection, below Shannon-Nyquist. For HUDs, the functional detect detection addresses defects resulting from the combined effect of the image display and the image forming optics.

Hi-Res scan mode in clinical MDCT systems: Experimental assessment of spatial resolution performance

PubMed Central

Cruz-Bastida, Juan P.; Gomez-Cardona, Daniel; Li, Ke; Sun, Heyi; Hsieh, Jiang; Szczykutowicz, Timothy P.; Chen, Guang-Hong

2016-01-01

Purpose: The introduction of a High-Resolution (Hi-Res) scan mode and another associated option that combines Hi-Res mode with the so-called High Definition (HD) reconstruction kernels (referred to as a Hi-Res/HD mode in this paper) in some multi-detector CT (MDCT) systems offers new opportunities to increase spatial resolution for some clinical applications that demand high spatial resolution. The purpose of this work was to quantify the in-plane spatial resolution along both the radial direction and tangential direction for the Hi-Res and Hi-Res/HD scan modes at different off-center positions. Methods: A technique was introduced and validated to address the signal saturation problem encountered in the attempt to quantify spatial resolution for the Hi-Res and Hi-Res/HD scan modes. Using the proposed method, the modulation transfer functions (MTFs) of a 64-slice MDCT system (Discovery CT750 HD, GE Healthcare) equipped with both Hi-Res and Hi-Res/HD modes were measured using a metal bead at nine different off-centered positions (0–16 cm with a step size of 2 cm); at each position, both conventional scans and Hi-Res scans were performed. For each type of scan and position, 80 repeated acquisitions were performed to reduce noise induced uncertainties in the MTF measurements. A total of 15 reconstruction kernels, including eight conventional kernels and seven HD kernels, were used to reconstruct CT images of the bead. An ex vivo animal study consisting of a bone fracture model was performed to corroborate the MTF results, as the detection of this high-contrast and high frequency task is predominantly determined by spatial resolution. Images of this animal model generated by different scan modes and reconstruction kernels were qualitatively compared with the MTF results. Results: At the centered position, the use of Hi-Res mode resulted in a slight improvement in the MTF; each HD kernel generated higher spatial resolution than its counterpart conventional kernel. However, the MTF along the tangential direction of the scan field of view (SFOV) was significantly degraded at off-centered positions, yet the combined Hi-Res/HD mode reduced this azimuthal MTF degradation. Images of the animal bone fracture model confirmed the improved spatial resolution at the off-centered positions through the use of the Hi-Res mode and HD kernels. Conclusions: The Hi-Res/HD scan improve spatial resolution of MDCT systems at both centered and off-centered positions. PMID:27147351

Hi-Res scan mode in clinical MDCT systems: Experimental assessment of spatial resolution performance.

PubMed

Cruz-Bastida, Juan P; Gomez-Cardona, Daniel; Li, Ke; Sun, Heyi; Hsieh, Jiang; Szczykutowicz, Timothy P; Chen, Guang-Hong

2016-05-01

The introduction of a High-Resolution (Hi-Res) scan mode and another associated option that combines Hi-Res mode with the so-called High Definition (HD) reconstruction kernels (referred to as a Hi-Res/HD mode in this paper) in some multi-detector CT (MDCT) systems offers new opportunities to increase spatial resolution for some clinical applications that demand high spatial resolution. The purpose of this work was to quantify the in-plane spatial resolution along both the radial direction and tangential direction for the Hi-Res and Hi-Res/HD scan modes at different off-center positions. A technique was introduced and validated to address the signal saturation problem encountered in the attempt to quantify spatial resolution for the Hi-Res and Hi-Res/HD scan modes. Using the proposed method, the modulation transfer functions (MTFs) of a 64-slice MDCT system (Discovery CT750 HD, GE Healthcare) equipped with both Hi-Res and Hi-Res/HD modes were measured using a metal bead at nine different off-centered positions (0-16 cm with a step size of 2 cm); at each position, both conventional scans and Hi-Res scans were performed. For each type of scan and position, 80 repeated acquisitions were performed to reduce noise induced uncertainties in the MTF measurements. A total of 15 reconstruction kernels, including eight conventional kernels and seven HD kernels, were used to reconstruct CT images of the bead. An ex vivo animal study consisting of a bone fracture model was performed to corroborate the MTF results, as the detection of this high-contrast and high frequency task is predominantly determined by spatial resolution. Images of this animal model generated by different scan modes and reconstruction kernels were qualitatively compared with the MTF results. At the centered position, the use of Hi-Res mode resulted in a slight improvement in the MTF; each HD kernel generated higher spatial resolution than its counterpart conventional kernel. However, the MTF along the tangential direction of the scan field of view (SFOV) was significantly degraded at off-centered positions, yet the combined Hi-Res/HD mode reduced this azimuthal MTF degradation. Images of the animal bone fracture model confirmed the improved spatial resolution at the off-centered positions through the use of the Hi-Res mode and HD kernels. The Hi-Res/HD scan improve spatial resolution of MDCT systems at both centered and off-centered positions.

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

Monte Carlo-based assessment of the trade-off between spatial resolution, field-of-view and scattered radiation in the variable resolution X-ray CT scanner.

PubMed

Arabi, Hossein; Kamali Asl, Ali Reza; Ay, Mohammad Reza; Zaidi, Habib

2015-07-01

The purpose of this work is to evaluate the impact of optimization of magnification on performance parameters of the variable resolution X-ray (VRX) CT scanner. A realistic model based on an actual VRX CT scanner was implemented in the GATE Monte Carlo simulation platform. To evaluate the influence of system magnification, spatial resolution, field-of-view (FOV) and scatter-to-primary ratio of the scanner were estimated for both fixed and optimum object magnification at each detector rotation angle. Comparison and inference between these performance parameters were performed angle by angle to determine appropriate object position at each opening half angle. Optimization of magnification resulted in a trade-off between spatial resolution and FOV of the scanner at opening half angles of 90°-12°, where the spatial resolution increased up to 50% and the scatter-to-primary ratio decreased from 4.8% to 3.8% at a detector angle of about 90° for the same FOV and X-ray energy spectrum. The disadvantage of magnification optimization at these angles is the significant reduction of the FOV (up to 50%). Moreover, magnification optimization was definitely beneficial for opening half angles below 12° improving the spatial resolution from 7.5 cy/mm to 20 cy/mm. Meanwhile, the FOV increased by more than 50% at these angles. It can be concluded that optimization of magnification is essential for opening half angles below 12°. For opening half angles between 90° and 12°, the VRX CT scanner magnification should be set according to the desired spatial resolution and FOV. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Comparison of high resolution x-ray detectors with conventional FPDs using experimental MTFs and apodized aperture pixel design for reduced aliasing

NASA Astrophysics Data System (ADS)

Shankar, A.; Russ, M.; Vijayan, S.; Bednarek, D. R.; Rudin, S.

2017-03-01

Apodized Aperture Pixel (AAP) design, proposed by Ismailova et.al, is an alternative to the conventional pixel design. The advantages of AAP processing with a sinc filter in comparison with using other filters include non-degradation of MTF values and elimination of signal and noise aliasing, resulting in an increased performance at higher frequencies, approaching the Nyquist frequency. If high resolution small field-of-view (FOV) detectors with small pixels used during critical stages of Endovascular Image Guided Interventions (EIGIs) could also be extended to cover a full field-of-view typical of flat panel detectors (FPDs) and made to have larger effective pixels, then methods must be used to preserve the MTF over the frequency range up to the Nyquist frequency of the FPD while minimizing aliasing. In this work, we convolve the experimentally measured MTFs of an Microangiographic Fluoroscope (MAF) detector, (the MAF-CCD with 35μm pixels) and a High Resolution Fluoroscope (HRF) detector (HRF-CMOS50 with 49.5μm pixels) with the AAP filter and show the superiority of the results compared to MTFs resulting from moving average pixel binning and to the MTF of a standard FPD. The effect of using AAP is also shown in the spatial domain, when used to image an infinitely small point object. For detectors in neurovascular interventions, where high resolution is the priority during critical parts of the intervention, but full FOV with larger pixels are needed during less critical parts, AAP design provides an alternative to simple pixel binning while effectively eliminating signal and noise aliasing yet allowing the small FOV high resolution imaging to be maintained during critical parts of the EIGI.

Improvement of range spatial resolution of medical ultrasound imaging by element-domain signal processing

NASA Astrophysics Data System (ADS)

Hasegawa, Hideyuki

2017-07-01

The range spatial resolution is an important factor determining the image quality in ultrasonic imaging. The range spatial resolution in ultrasonic imaging depends on the ultrasonic pulse length, which is determined by the mechanical response of the piezoelectric element in an ultrasonic probe. To improve the range spatial resolution without replacing the transducer element, in the present study, methods based on maximum likelihood (ML) estimation and multiple signal classification (MUSIC) were proposed. The proposed methods were applied to echo signals received by individual transducer elements in an ultrasonic probe. The basic experimental results showed that the axial half maximum of the echo from a string phantom was improved from 0.21 mm (conventional method) to 0.086 mm (ML) and 0.094 mm (MUSIC).

Imaging cells and sub-cellular structures with ultrahigh resolution full-field X-ray microscopy.

PubMed

Chien, C C; Tseng, P Y; Chen, H H; Hua, T E; Chen, S T; Chen, Y Y; Leng, W H; Wang, C H; Hwu, Y; Yin, G C; Liang, K S; Chen, F R; Chu, Y S; Yeh, H I; Yang, Y C; Yang, C S; Zhang, G L; Je, J H; Margaritondo, G

2013-01-01

Our experimental results demonstrate that full-field hard-X-ray microscopy is finally able to investigate the internal structure of cells in tissues. This result was made possible by three main factors: the use of a coherent (synchrotron) source of X-rays, the exploitation of contrast mechanisms based on the real part of the refractive index and the magnification provided by high-resolution Fresnel zone-plate objectives. We specifically obtained high-quality microradiographs of human and mouse cells with 29 nm Rayleigh spatial resolution and verified that tomographic reconstruction could be implemented with a final resolution level suitable for subcellular features. We also demonstrated that a phase retrieval method based on a wave propagation algorithm could yield good subcellular images starting from a series of defocused microradiographs. The concluding discussion compares cellular and subcellular hard-X-ray microradiology with other techniques and evaluates its potential impact on biomedical research. Copyright © 2012 Elsevier Inc. All rights reserved.

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 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.

Spatiotemporal variability in biogenic gas dynamics in a subtropical peat soil at the laboratory scale is revealed using high-resolution ground-penetrating radar

NASA Astrophysics Data System (ADS)

Mustasaar, Mario; Comas, Xavier

2017-09-01

The importance of peatlands as sources of greenhouse gas emissions has been demonstrated in many studies during the last two decades. While most studies have shown the heterogeneous distribution of biogenic gas in peat soils at the field scale (sampling volumes in the order of meters), little information exists for submeter scales, particularly relevant to properly capture the dynamics of hot spots for gas accumulation and release when designing sampling routines with methods that use smaller (i.e., submeter) sampling volumes like flux chambers. In this study, ground-penetrating radar is used at the laboratory scale to evaluate biogenic gas dynamics at high spatial resolution (i.e., cm) in a peat monolith from the Everglades. The results indicate sharp changes (both spatially and temporally) in the dynamics of gas accumulation and release, representing hot spots for production and release of biogenic gases with surface areas ranging between 5 to 10 cm diameter and are associated with increases in porosity. Furthermore, changes in gas composition and inferred methane (CH4) and carbon dioxide (CO2) fluxes also displayed a high spatiotemporal variability associated with hot spots, resulting in CH4 and CO2 flux estimates showing differences up to 1 order of magnitude during the same day for different parts of the sample. This work follows on recent studies in the Everglades and questions the appropriateness of spatial and temporal scales of measurement when defining gas dynamics by showing how flux values may change both spatially and temporarily even when considering submeter spatial scales.

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

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)

MODIS Retrievals of Cloud Optical Thickness and Particle Radius

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Ackerman, S. A.; Gray, M.; Moody, E.; Arnold, G. T.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

Visualizing single molecules interacting with nuclear pore complexes by narrow-field epifluorescence microscopy

PubMed Central

Yang, Weidong; Musser, Siegfried M.

2008-01-01

The utility of single molecule fluorescence (SMF) for understanding biological reactions has been amply demonstrated by a diverse series of studies over the last decade. In large part, the molecules of interest have been limited to those within a small focal volume or near a surface to achieve the high sensitivity required for detecting the inherently weak signals arising from individual molecules. Consequently, the investigation of molecular behavior with high time and spatial resolution deep within cells using SMF has remained challenging. Recently, we demonstrated that narrow-field epifluorescence microscopy allows visualization of nucleocytoplasmic transport at the single cargo level. We describe here the methodological approach that yields 2 ms and ∼15 nm resolution for a stationary particle. The spatial resolution for a mobile particle is inherently worse, and depends on how fast the particle is moving. The signal-to-noise ratio is sufficiently high to directly measure the time a single cargo molecule spends interacting with the nuclear pore complex. Particle tracking analysis revealed that cargo molecules randomly diffuse within the nuclear pore complex, exiting as a result of a single rate-limiting step. We expect that narrow-field epifluorescence microscopy will be useful for elucidating other binding and trafficking events within cells. PMID:16879979

A multi-temporal fusion-based approach for land cover mapping in support of nuclear incident response

NASA Astrophysics Data System (ADS)

Sah, Shagan

An increasingly important application of remote sensing is to provide decision support during emergency response and disaster management efforts. Land cover maps constitute one such useful application product during disaster events; if generated rapidly after any disaster, such map products can contribute to the efficacy of the response effort. In light of recent nuclear incidents, e.g., after the earthquake/tsunami in Japan (2011), our research focuses on constructing rapid and accurate land cover maps of the impacted area in case of an accidental nuclear release. The methodology involves integration of results from two different approaches, namely coarse spatial resolution multi-temporal and fine spatial resolution imagery, to increase classification accuracy. Although advanced methods have been developed for classification using high spatial or temporal resolution imagery, only a limited amount of work has been done on fusion of these two remote sensing approaches. The presented methodology thus involves integration of classification results from two different remote sensing modalities in order to improve classification accuracy. The data used included RapidEye and MODIS scenes over the Nine Mile Point Nuclear Power Station in Oswego (New York, USA). The first step in the process was the construction of land cover maps from freely available, high temporal resolution, low spatial resolution MODIS imagery using a time-series approach. We used the variability in the temporal signatures among different land cover classes for classification. The time series-specific features were defined by various physical properties of a pixel, such as variation in vegetation cover and water content over time. The pixels were classified into four land cover classes - forest, urban, water, and vegetation - using Euclidean and Mahalanobis distance metrics. On the other hand, a high spatial resolution commercial satellite, such as RapidEye, can be tasked to capture images over the affected area in the case of a nuclear event. This imagery served as a second source of data to augment results from the time series approach. The classifications from the two approaches were integrated using an a posteriori probability-based fusion approach. This was done by establishing a relationship between the classes, obtained after classification of the two data sources. Despite the coarse spatial resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion-based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. This fusion thus contributed to classification accuracy refinement, with a few additional advantages, such as correction for cloud cover and providing for an approach that is robust against point-in-time seasonal anomalies, due to the inclusion of multi-temporal data. We concluded that this approach is capable of generating land cover maps of acceptable accuracy and rapid turnaround, which in turn can yield reliable estimates of crop acreage of a region. The final algorithm is part of an automated software tool, which can be used by emergency response personnel to generate a nuclear ingestion pathway information product within a few hours of data collection.

Conebeam CT of the head and neck, part 1: physical principles.

PubMed

Miracle, A C; Mukherji, S K

2009-06-01

Conebeam x-ray CT (CBCT) is a developing imaging technique designed to provide relatively low-dose high-spatial-resolution visualization of high-contrast structures in the head and neck and other anatomic areas. This first installment in a 2-part review will address the physical principles underlying CBCT imaging as it is used in dedicated head and neck scanners. Concepts related to CBCT acquisition geometry, flat panel detection, and image quality will be explored in detail. Particular emphasis will be placed on technical limitations to low-contrast detectability and radiation dose. Proposed methods of x-ray scatter reduction will also be discussed.

Lock-in imaging with synchronous digital mirror demodulation

NASA Astrophysics Data System (ADS)

Bush, Michael G.

2010-04-01

Lock-in imaging enables high contrast imaging in adverse conditions by exploiting a modulated light source and homodyne detection. We report results on a patent pending lock-in imaging system fabricated from commercial-off-theshelf parts utilizing standard cameras and a spatial light modulator. By leveraging the capabilities of standard parts we are able to present a low cost, high resolution, high sensitivity camera with applications in search and rescue, friend or foe identification (IFF), and covert surveillance. Different operating modes allow the same instrument to be utilized for dual band multispectral imaging or high dynamic range imaging, increasing the flexibility in different operational settings.

Using High Spatial Resolution to Improve BOLD fMRI Detection at 3T

PubMed Central

Claise, Béatrice; Jean, Betty

2015-01-01

For different functional magnetic resonance imaging experiments using blood oxygenation level-dependent (BOLD) contrast, the acquisition of T 2*-weighted scans at a high spatial resolution may be advantageous in terms of time-course signal-to-noise ratio and of BOLD sensitivity when the regions are prone to susceptibility artifacts. In this study, we explore this solution by examining how spatial resolution influences activations elicited when appetizing food pictures are viewed. Twenty subjects were imaged at 3 T with two different voxel volumes, 3.4 μl and 27 μl. Despite the diminution of brain coverage, we found that high-resolution acquisition led to a better detection of activations. Though known to suffer to different degrees from susceptibility artifacts, the activations detected by high spatial resolution were notably consistent with those reported in published activation likelihood estimation meta-analyses, corresponding to taste-responsive regions. Furthermore, these regions were found activated bilaterally, in contrast with previous findings. Both the reduction of partial volume effect, which improves BOLD contrast, and the mitigation of susceptibility artifact, which boosts the signal to noise ratio in certain regions, explained the better detection noted with high resolution. The present study provides further evidences that high spatial resolution is a valuable solution for human BOLD fMRI, especially for studying food-related stimuli. PMID:26550990

NuLat: 3D Event Reconstruction of a ROL Detector for Neutrino Detection and Background Rejection

NASA Astrophysics Data System (ADS)

Yokley, Zachary; NuLat Collaboration

2015-04-01

NuLat is a proposed very-short baseline reactor antineutrino experiment that employs a unique detector design, a Ragahavan Optical Lattice (ROL), developed for the LENS solar neutrino experiment. The 3D lattice provides high spatial and temporal resolution and allows for energy deposition in each voxel to be determined independently of other voxels, as well as the time sequence associated with each voxel energy deposition. This unique feature arises from two independent means to spatially locate energy deposits: via timing and via optical channeling. NuLat, the first application of a ROL detector targeting physics results, will measure the reactor antineutrino flux at very short baselines via inverse beta decay (IBD). The ROL design of NuLat makes possible the reconstruction of positron energy with little contamination due to the annihilation gammas which smear the positron energy resolution in a traditional detector. IBD events are cleanly tagged via temporal and spatial coincidence of neutron capture in the vertex voxel or nearest neighbors. This talk will present work on IBD event reconstruction in NuLat and its likely impact on sterile neutrino detection via operation in higher background locations enabled by its superior rejection of backgrounds. This research has been funded in part by the National Science Foundation on Award Numbers 1001394 and 1001078.

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

Bosler, Peter A.; Roesler, Erika L.; Taylor, Mark A.

This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclonemore » detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.« less

Investigation of Relationship between High-energy X-Ray Sources and Photospheric and Helioseismic Impacts of X1.8 Solar Flare of 2012 October 23

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

Sharykin, I. N.; Zimovets, I. V.; Kosovichev, A. G.

The X-class solar flare of 2012 October 23 generated continuum photospheric emission and a strong helioseismic wave (“sunquake”) that points to an intensive energy release in the dense part of the solar atmosphere. We study properties of the energy release with high temporal and spatial resolutions, using photospheric data from the Helioseismic Magnetic Imager (HMI) on board Solar Dynamics Observatory , and hard X-ray observations made by RHESSI . For this analysis we use level-1 HMI data (filtergrams), obtained by scanning the Fe i line (6731 Å) with the time cadence of ∼3.6 s and spatial resolution of ∼0.″5 permore » pixel. It is found that the photospheric disturbances caused by the flare spatially coincide with the region of hard X-ray emission but are delayed by ≲4 s. This delay is consistent with predictions of the flare hydrodynamics RADYN models. However, the models fail to explain the magnitude of variations observed by the HMI. The data indicate that the photospheric impact and helioseismic wave might be caused by the electron energy flux, which is substantially higher than that in the current flare radiative hydrodynamic models.« less

Variability of 4D flow parameters when subjected to changes in MRI acquisition parameters using a realistic thoracic aortic phantom.

PubMed

Montalba, Cristian; Urbina, Jesus; Sotelo, Julio; Andia, Marcelo E; Tejos, Cristian; Irarrazaval, Pablo; Hurtado, Daniel E; Valverde, Israel; Uribe, Sergio

2018-04-01

To assess the variability of peak flow, mean velocity, stroke volume, and wall shear stress measurements derived from 3D cine phase contrast (4D flow) sequences under different conditions of spatial and temporal resolutions. We performed controlled experiments using a thoracic aortic phantom. The phantom was connected to a pulsatile flow pump, which simulated nine physiological conditions. For each condition, 4D flow data were acquired with different spatial and temporal resolutions. The 2D cine phase contrast and 4D flow data with the highest available spatio-temporal resolution were considered as a reference for comparison purposes. When comparing 4D flow acquisitions (spatial and temporal resolution of 2.0 × 2.0 × 2.0 mm 3 and 40 ms, respectively) with 2D phase-contrast flow acquisitions, the underestimation of peak flow, mean velocity, and stroke volume were 10.5, 10 and 5%, respectively. However, the calculated wall shear stress showed an underestimation larger than 70% for the former acquisition, with respect to 4D flow, with spatial and temporal resolution of 1.0 × 1.0 × 1.0 mm 3 and 20 ms, respectively. Peak flow, mean velocity, and stroke volume from 4D flow data are more sensitive to changes of temporal than spatial resolution, as opposed to wall shear stress, which is more sensitive to changes in spatial resolution. Magn Reson Med 79:1882-1892, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

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.

The validity of flow approximations when simulating catchment-integrated flash floods

NASA Astrophysics Data System (ADS)

Bout, B.; Jetten, V. G.

2018-01-01

Within hydrological models, flow approximations are commonly used to reduce computation time. The validity of these approximations is strongly determined by flow height, flow velocity and the spatial resolution of the model. In this presentation, the validity and performance of the kinematic, diffusive and dynamic flow approximations are investigated for use in a catchment-based flood model. Particularly, the validity during flood events and for varying spatial resolutions is investigated. The OpenLISEM hydrological model is extended to implement both these flow approximations and channel flooding based on dynamic flow. The flow approximations are used to recreate measured discharge in three catchments, among which is the hydrograph of the 2003 flood event in the Fella river basin. Furthermore, spatial resolutions are varied for the flood simulation in order to investigate the influence of spatial resolution on these flow approximations. Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured discharge. Kinematic flow, which is commonly used in hydrological modelling, substantially over-estimates hydrological connectivity in the simulations with a spatial resolution of below 30 m. Since spatial resolutions of models have strongly increased over the past decades, usage of routed kinematic flow should be reconsidered. The combination of diffusive or dynamic overland flow and dynamic channel flooding provides high accuracy in recreating the 2003 Fella river flood event. Finally, in the case of flood events, spatial modelling of kinematic flow substantially over-estimates hydrological connectivity and flow concentration since pressure forces are removed, leading to significant errors.

GOW2.0: A global wave hindcast of high resolution

NASA Astrophysics Data System (ADS)

Menendez, Melisa; Perez, Jorge; Losada, Inigo

2016-04-01

The information provided by reconstructions of historical wind generated waves is of paramount importance for a variety of coastal and offshore purposes (e.g. risk assessment, design of costal structures and coastal management). Here, a new global wave hindcast (GOW2.0) is presented. This hindcast is an update of GOW1.0 (Reguero et al. 2012) motivated by the emergence of new settings and atmospheric information from reanalysis during recent years. GOW2.0 is based on version 4.18 of WaveWatch III numerical model (Tolman, 2014). Main features of the model set-up are the analysis and selection of recent source terms concerning wave generation and dissipation (Ardhuin et al. 2010, Zieger et al., 2015) and the implementation of obstruction grids to improve the modeling of wave shadowing effects in line with the approach described in Chawla and Tolman (2007). This has been complemented by a multigrid system and the use of the hourly wind and ice coverage from the Climate Forecast System Reanalysis, CFSR (30km spatial resolution approximately). The multigrid scheme consists of a series of "two-way" nested domains covering the whole ocean basins at a 0.5° spatial resolution and continental shelfs worldwide at a 0.25° spatial resolution. In addition, a technique to reconstruct wave 3D spectra for any grid-point is implemented from spectral partitioning information. A validation analysis of GOW2.0 outcomes has been undertaken considering wave spectral information from surface buoy stations and multi-mission satellite data for a spatial validation. GOW2.0 shows a substantial improvement over its predecessor for all the analyzed variables. In summary, GOW2.0 reconstructs historical wave spectral data and climate information from 1979 to present at hourly resolution providing higher spatial resolution over regions where local generated wind seas, bimodal-spectral behaviour and relevant swell transformations across the continental shelf are important. Ardhuin F, Rogers E, Babanin AV, et al (2010). Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation. J Phys Oceanogr. 2010;40(9):1917-1941. doi:10.1175/2010JPO4324.1. Chawla A, Tolman HL. Obstruction grids for spectral wave models. Ocean Model. 2008;22(1-2):12-25. doi:10.1016/j.ocemod.2008.01.003. Reguero BG, Menendez M, Mendez FJ, Minguez R, Losada IJ (2012). A Global Ocean Wave (GOW) calibrated reanalysis from 1948 onwards. Coastal Engineering, 65, 38-55. Tolman HL (2014). User manual and system documentation of WAVEWATCH III version 4.18. NOAA / NWS / NCEP / MMAB Tech Note. Zieger S, Babanin AV, Rogers WE, Young IR (2015). Observation-based source terms in the third-generation wave model WAVEWATCH. Ocean Modelling, 96, 2-25.

Characterizing tree canopy temperature heterogeneity using an unmanned aircraft-borne thermal imager

NASA Astrophysics Data System (ADS)

Messinger, M.; Powell, R.; Silman, M.; Wright, M.; Nicholson, W.

2013-12-01

Leaf temperature (Tleaf) is an important control on many physiological processes such as photosynthesis and respiration, is a key variable for characterizing canopy energy fluxes, and is a valuable metric for identifying plant water stress or disease. Traditional methods of Tleaf measurement involve either the use of thermocouples, a time and labor-intensive method that samples sparsely in space, or the use of air temperature (Tair) as a proxy measure, which can introduce inaccuracies due to near constant canopy-atmosphere energy flux. Thermal infrared (TIR) imagery provides an efficient means of collecting Tleaf for large areas. Existing satellite and aircraft-based TIR imagery is, however, limited by low spatial and/or temporal resolution, while crane-mounted camera systems have strictly limited spatial extents. Unmanned aerial systems (UAS) offer new opportunities to acquire high spatial and temporal resolution imagery on demand. Here, we demonstrate the feasibility of collecting tree canopy Tleaf data using a small multirotor UAS fitted with a high spatial resolution TIR imager. The goals of this pilot study were to a) characterize basic patterns of within crown Tleaf for 4 study species and b) identify trends in Tleaf between species with varying leaf morphologies and canopy structures. TIR imagery was acquired for individual tree crowns of 4 species common to the North Carolina Piedmont ecoregion (Quercus phellos, Pinus strobus, Liriodendron tulipifera, Magnolia grandiflora) in an urban park environment. Due to significantly above-average summer precipitation, we assumed that none of the sampled trees was limited by soil water availability. We flew the TIR imaging system over 3-4 individuals of each of the 4 target species on 3 separate days. Imagery of all individuals was collected within the same 2-hour period in the afternoon on all days. There was low wind and partly cloudy skies during imaging. Tair, relative humidity, and wind speed were recorded at each site. Emissivity was assumed to be 0.98 for all species. Acquired images had a pixel resolution of <3 cm and measurement accuracy of ×1° C. We found the UAS-borne TIR imaging system to be an effective tool for collection of high resolution canopy imagery. The system imaged all targeted crowns quickly and reliably, providing a viable alternative to current methods of canopy Tleaf measurement. Analysis of the imagery indicated significant variability in Tleaf both within and between crowns. We identified trends in Tleaf related to average leaf size, shape, and crown structural traits. These data on the heterogeneity of Tleaf can further our understanding of canopy-atmosphere energy exchange. This pilot study demonstrates the promise of UAS-borne TIR sensors for acquiring high spatial resolution imagery at the scale of individual tree crowns.

Towards a microchannel-based X-ray detector with two-dimensional spatial and time resolution and high dynamic range

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

Adams, Bernhard W.; Mane, Anil U.; Elam, Jeffrey W.

X-ray detectors that combine two-dimensional spatial resolution with a high time resolution are needed in numerous applications of synchrotron radiation. Most detectors with this combination of capabilities are based on semiconductor technology and are therefore limited in size. Furthermore, the time resolution is often realised through rapid time-gating of the acquisition, followed by a slower readout. Here, a detector technology is realised based on relatively inexpensive microchannel plates that uses GHz waveform sampling for a millimeter-scale spatial resolution and better than 100 ps time resolution. The technology is capable of continuous streaming of time- and location-tagged events at rates greatermore » than 10 7events per cm 2. Time-gating can be used for improved dynamic range.« less

Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy

NASA Astrophysics Data System (ADS)

Descloux, A.; Grußmayer, K. S.; Bostan, E.; Lukes, T.; Bouwens, A.; Sharipov, A.; Geissbuehler, S.; Mahul-Mellier, A.-L.; Lashuel, H. A.; Leutenegger, M.; Lasser, T.

2018-03-01

Super-resolution fluorescence microscopy provides unprecedented insight into cellular and subcellular structures. However, going `beyond the diffraction barrier' comes at a price, since most far-field super-resolution imaging techniques trade temporal for spatial super-resolution. We propose the combination of a novel label-free white light quantitative phase imaging with fluorescence to provide high-speed imaging and spatial super-resolution. The non-iterative phase retrieval relies on the acquisition of single images at each z-location and thus enables straightforward 3D phase imaging using a classical microscope. We realized multi-plane imaging using a customized prism for the simultaneous acquisition of eight planes. This allowed us to not only image live cells in 3D at up to 200 Hz, but also to integrate fluorescence super-resolution optical fluctuation imaging within the same optical instrument. The 4D microscope platform unifies the sensitivity and high temporal resolution of phase imaging with the specificity and high spatial resolution of fluorescence microscopy.

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

PubMed Central

Bishara, Waheb; Su, Ting-Wei; Coskun, Ahmet F.; Ozcan, Aydogan

2010-01-01

We demonstrate lensfree holographic microscopy on a chip to achieve ~0.6 µm spatial resolution corresponding to a numerical aperture of ~0.5 over a large field-of-view of ~24 mm2. By using partially coherent illumination from a large aperture (~50 µm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans. PMID:20588977

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.

Selective spatial enhancement: Attentional spotlight size impacts spatial but not temporal perception.

PubMed

Goodhew, Stephanie C; Shen, Elizabeth; Edwards, Mark

2016-08-01

An important but often neglected aspect of attention is how changes in the attentional spotlight size impact perception. The zoom-lens model predicts that a small ("focal") attentional spotlight enhances all aspects of perception relative to a larger ("diffuse" spotlight). However, based on the physiological properties of the two major classes of visual cells (magnocellular and parvocellular neurons) we predicted trade-offs in spatial and temporal acuity as a function of spotlight size. Contrary to both of these accounts, however, across two experiments we found that attentional spotlight size affected spatial acuity, such that spatial acuity was enhanced for a focal relative to a diffuse spotlight, whereas the same modulations in spotlight size had no impact on temporal acuity. This likely reflects the function of attention: to induce the high spatial resolution of the fovea in periphery, where spatial resolution is poor but temporal resolution is good. It is adaptive, therefore, for the attentional spotlight to enhance spatial acuity, whereas enhancing temporal acuity does not confer the same benefit.

Attentional enhancement of spatial resolution: linking behavioural and neurophysiological evidence

PubMed Central

Anton-Erxleben, Katharina; Carrasco, Marisa

2014-01-01

Attention allows us to select relevant sensory information for preferential processing. Behaviourally, it improves performance in various visual tasks. One prominent effect of attention is the modulation of performance in tasks that involve the visual system’s spatial resolution. Physiologically, attention modulates neuronal responses and alters the profile and position of receptive fields near the attended location. Here, we develop a hypothesis linking the behavioural and electrophysiological evidence. The proposed framework seeks to explain how these receptive field changes enhance the visual system’s effective spatial resolution and how the same mechanisms may also underlie attentional effects on the representation of spatial information. PMID:23422910

Downscaling soil moisture over regions that include multiple coarse-resolution grid cells

USDA-ARS?s Scientific Manuscript database

Many applications require soil moisture estimates over large spatial extents (30-300 km) and at fine-resolutions (10-30 m). Remote-sensing methods can provide soil moisture estimates over very large spatial extents (continental to global) at coarse resolutions (10-40 km), but their output must be d...

Urban cover mapping using digital, high-resolution aerial imagery

Treesearch

Soojeong Myeong; David J. Nowak; Paul F. Hopkins; Robert H. Brock

2003-01-01

High-spatial resolution digital color-infrared aerial imagery of Syracuse, NY was analyzed to test methods for developing land cover classifications for an urban area. Five cover types were mapped: tree/shrub, grass/herbaceous, bare soil, water and impervious surface. Challenges in high-spatial resolution imagery such as shadow effect and similarity in spectral...

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.

PubMed

Abatzoglou, John T; Dobrowski, Solomon Z; Parks, Sean A; Hegewisch, Katherine C

2018-01-09

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Development of Finer Spatial Resolution Optical Properties from MODIS

DTIC Science & Technology

2008-02-04

infrared (SWIR) channels at 1240 nm and 2130 run. The increased resolution spectral Rrs channels are input into bio-optical algorithms (Quasi...processes. Additionally, increased resolution is required for validation of ocean color products in coastal regions due to the shorter spatial scales of...with in situ Rrs data to determine the "best" method in coastal regimes. We demonstrate that finer resolution is required for validation of coastal

Data Descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Treesearch

John T. Abatzoglou; Solomon Z. Dobrowski; Sean A. Parks; Katherine C. Hegewisch

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from...

Magnetoacoustic Imaging of Electrical Conductivity of Biological Tissues at a Spatial Resolution Better than 2 mm

PubMed Central

Hu, Gang; He, Bin

2011-01-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an emerging approach for noninvasively imaging electrical impedance properties of biological tissues. The MAT-MI imaging system measures ultrasound waves generated by the Lorentz force, having been induced by magnetic stimulation, which is related to the electrical conductivity distribution in tissue samples. MAT-MI promises to provide fine spatial resolution for biological tissue imaging as compared to ultrasound resolution. In the present study, we first estimated the imaging spatial resolution by calculating the full width at half maximum (FWHM) of the system point spread function (PSF). The actual spatial resolution of our MAT-MI system was experimentally determined to be 1.51 mm by a parallel-line-source phantom with Rayleigh criterion. Reconstructed images made from tissue-mimicking gel phantoms, as well as animal tissue samples, were consistent with the morphological structures of the samples. The electrical conductivity value of the samples was determined directly by a calibrated four-electrode system. It has been demonstrated that MAT-MI is able to image the electrical impedance properties of biological tissues with better than 2 mm spatial resolution. These results suggest the potential of MAT-MI for application to early detection of small-size diseased tissues (e.g. small breast cancer). PMID:21858111

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

High-Definition Television (HDTV) Images for Earth Observations and Earth Science Applications

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Holland, S. Douglas; Runco, Susan K.; Pitts, David E.; Whitehead, Victor S.; Andrefouet, Serge M.

2000-01-01

As part of Detailed Test Objective 700-17A, astronauts acquired Earth observation images from orbit using a high-definition television (HDTV) camcorder, Here we provide a summary of qualitative findings following completion of tests during missions STS (Space Transport System)-93 and STS-99. We compared HDTV imagery stills to images taken using payload bay video cameras, Hasselblad film camera, and electronic still camera. We also evaluated the potential for motion video observations of changes in sunlight and the use of multi-aspect viewing to image aerosols. Spatial resolution and color quality are far superior in HDTV images compared to National Television Systems Committee (NTSC) video images. Thus, HDTV provides the first viable option for video-based remote sensing observations of Earth from orbit. Although under ideal conditions, HDTV images have less spatial resolution than medium-format film cameras, such as the Hasselblad, under some conditions on orbit, the HDTV image acquired compared favorably with the Hasselblad. Of particular note was the quality of color reproduction in the HDTV images HDTV and electronic still camera (ESC) were not compared with matched fields of view, and so spatial resolution could not be compared for the two image types. However, the color reproduction of the HDTV stills was truer than colors in the ESC images. As HDTV becomes the operational video standard for Space Shuttle and Space Station, HDTV has great potential as a source of Earth-observation data. Planning for the conversion from NTSC to HDTV video standards should include planning for Earth data archiving and distribution.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Spatial and Temporal Dynamics of Mass Mortalities in Oysters Is Influenced by Energetic Reserves and Food Quality

PubMed Central

Pernet, Fabrice; Lagarde, Franck; Jeannée, Nicolas; Daigle, Gaetan; Barret, Jean; Le Gall, Patrik; Quere, Claudie; D’orbcastel, Emmanuelle Roque

2014-01-01

Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality. PMID:24551106

Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation.

PubMed

Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

2017-01-27

Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

Spatial and temporal dynamics of mass mortalities in oysters is influenced by energetic reserves and food quality.

PubMed

Pernet, Fabrice; Lagarde, Franck; Jeannée, Nicolas; Daigle, Gaetan; Barret, Jean; Le Gall, Patrik; Quere, Claudie; D'orbcastel, Emmanuelle Roque

2014-01-01

Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality.

Shear behavior of thermoformed woven-textile thermoplastic prepregs: An analysis combining bias-extension test and X-ray microtomography

NASA Astrophysics Data System (ADS)

Gassoumi, M.; Rolland du Roscoat, S.; Casari, P.; Dumont, P. J. J.; Orgéas, L.; Jacquemin, F.

2017-10-01

Thermoforming allows the manufacture of structural parts for the automotive and aeronautical domains using long fiber thermoplastic prepregs with short cycle times. During this operation, several sheets of molten prepregs are stacked and subjected to large macroscale strains, mainly via in-plane shear, out-of-plane consolidation or dilatation, and bending of the fibrous reinforcement. These deformation modes and the related meso and microstructure evolutions are still poorly understood. However, they can drastically alter the end-use macroscale properties of fabricated parts. To better understand these phenomena, bias extension tests were performed using specimens made of several stacked layers of glass woven fabrics and polyamide matrix. The macroscale shear behavior of these prepregs was investigated at various temperatures. A multiscale analysis of deformed samples was performed using X-ray microtomography images of the deformed specimens acquired at two different spatial resolutions. The low-resolution images were used to analyze the deformation mechanisms and the structural characteristics of prepregs at the macroscale and bundle scales. It was possible to analyze the 3D shapes of deformed samples and, in particular, the spatial variations of their thickness so as to quantify the out-of-plane dilatancy or consolidation phenomena induced by the in-plane shear of prepregs. At a lower scale, the analysis of the high-resolution images showed that these mechanisms were accompanied by the growth of pores and the deformation of fiber bundles. The orientation of the fiber bundles and its through-thickness evolution were measured along the weft and warp directions in the deformed samples, allowing the relevance of geometrical models currently used to analyze bias extension tests to be discussed. Results can be used to enhance the current rheological models for the prediction of thermoforming of thermoplastic prepregs.

Overlapping MALDI-Mass Spectrometry Imaging for In-Parallel MS and MS/MS Data Acquisition without Sacrificing Spatial Resolution

NASA Astrophysics Data System (ADS)

Hansen, Rebecca L.; Lee, Young Jin

2017-09-01

Metabolomics experiments require chemical identifications, often through MS/MS analysis. In mass spectrometry imaging (MSI), this necessitates running several serial tissue sections or using a multiplex data acquisition method. We have previously developed a multiplex MSI method to obtain MS and MS/MS data in a single experiment to acquire more chemical information in less data acquisition time. In this method, each raster step is composed of several spiral steps and each spiral step is used for a separate scan event (e.g., MS or MS/MS). One main limitation of this method is the loss of spatial resolution as the number of spiral steps increases, limiting its applicability for high-spatial resolution MSI. In this work, we demonstrate multiplex MS imaging is possible without sacrificing spatial resolution by the use of overlapping spiral steps, instead of spatially separated spiral steps as used in the previous work. Significant amounts of matrix and analytes are still left after multiple spectral acquisitions, especially with nanoparticle matrices, so that high quality MS and MS/MS data can be obtained on virtually the same tissue spot. This method was then applied to visualize metabolites and acquire their MS/MS spectra in maize leaf cross-sections at 10 μm spatial resolution. [Figure not available: see fulltext.

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

USDA-ARS?s Scientific Manuscript database

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified ...

Development of new family of wide-angle anamorphic lens with controlled distortion profile

NASA Astrophysics Data System (ADS)

Gauvin, Jonny; Doucet, Michel; Wang, Min; Thibault, Simon; Blanc, Benjamin

2005-08-01

It is well known that a fish-eye lens produces a circular image of the scene with a particular distortion profile. When using a fish-eye lens with a standard sensor (e.g. 1/3", 1/4",.), only a part of the rectangular detector area is used, leaving many pixels unused. We proposed a new approach to get enhanced resolution for panoramic imaging. In this paper, various arrangements of innovative 180-degree anamorphic wide-angle lens design are considered. Their performances as well as lens manufacturability are also discussed. The concept of the design is to use anamorphic optics to produce elliptical image that maximize pixel resolution in both axis. Furthermore, a non-linear distortion profile is also introduced to enhance spatial resolution for specific field angle. Typical applications such as panoramic photography, video conferencing, and homeland/transportation security are also presented.

Prospect of space-based interferometry at EUV and soft X-ray wavelengths

NASA Technical Reports Server (NTRS)

Welsh, Barry Y.; Chakrabarti, Supriya

1992-01-01

We review the current capabilities of high-resolution, spectroscopic, space-borne instrumentation available for both solar and stellar observations in the EUV and soft X-ray wavelength regimes, and describe the basic design of a compact, all-reflection interferometer based on the spatial heterodyne technique; this is capable of producing a resolving power (lambda/Delta-lambda) of about 20,000 in the 100-200 A region using presently available multilayer optical components. Such an instrument can be readily constructed with existing technology. Due to its small size and lack of moving parts, it is ideally suited to spaceborne applications. Based on best estimates of the efficiency of this instrument at soft X-ray wavelengths, we review the possible use of this high-resolution interferometer in obtaining high-resolution full-disk spectroscopy of the sun. We also discuss its possible use for observations of diffuse sources such as the EUV interstellar background radiation.

Using Multi-Temporal Imaging Spectroscopy Data to Detect Drought and Bark Beetle Related Conifer Mortality across the Central Sierra Nevada, California, USA

NASA Astrophysics Data System (ADS)

Tane, Z.; Ramirez, C.; Roberts, D. A.; Koltunov, A.; Sweeney, S.

2016-12-01

There is considerable scientific and public interest in the ongoing drought and bark beetle driven conifer mortality in the Central and Southern Sierra Nevada, the scale of which has not been seen previously in California's recorded history. Just before and during this mortality event (2013-2016), Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) data were acquired seasonally over part of the affected area as part of the HyspIRI Preparatory Mission. In this study, we used 11 AVIRIS flight lines from 8 seasonal flights (from spring 2013 to summer 2015) to detect conifer mortality. In addition to the standard pre-processing completed by NASA's Jet Propulsion Lab, AVIRIS images were co-registered and georeferenced between time steps and images were resampled to the spatial resolution and signal-to-noise ratio expected from the proposed HyspIRI satellite. We used summer 2015 high-spatial resolution WorldView-2 and WorldView-3 images from across the study area to collect training data from five scenes, and independent validation data from five additional scenes. A cover class map developed with a machine-learning algorithm, separated pixels into green conifer, red-attack conifer, and non-conifer dominant cover, yielding a high accuracy (above 85% accuracy on the independent validation data) in the tree mortality final map. Discussion will include the effects of temporal information and input dimensionality on classification accuracy, comparison with multi-spectral classification accuracy, the ecological and forest management implications of this work, incorporating 2016 AVIRS images to detect 2016 mortality, and future work in understanding the spatial patterns underlying the mortality.

Galileo Ultraviolet Spectrometer experiment

NASA Technical Reports Server (NTRS)

Hord, C. W.; Mcclintock, W. E.; Stewart, A. I. F.; Barth, C. A.; Esposito, L. W.; Thomas, G. E.; Sandel, B. R.; Hunten, D. M.; Broadfoot, A. L.; Shemansky, D. E.

1992-01-01

The Galileo ultraviolet spectrometer experiment uses data obtained by the Ultraviolet Spectrometer (UVS) mounted on the pointed orbiter scan platform and from the Extreme Ultraviolet Spectrometer (EUVS) mounted on the spinning part of the orbiter with the field of view perpendicular to the spin axis. The UVS is a Ebert-Fastie design that covers the range 113-432 nm with a wavelength resolution of 0.7 nm below 190 and 1.3 nm at longer wavelengths. The UVS spatial resolution is 0.4 deg x 0.1 deg for illuminated disk observations and 1 deg x 0.1 deg for limb geometries. The EUVS is a Voyager design objective grating spectrometer, modified to cover the wavelength range from 54 to 128 nm with wavelength resolution 3.5 nm for extended sources and 1.5 nm for point sources and spatial resolution of 0.87 deg x 0.17 deg. The EUVS instrument will follow up on the many Voyager UVS discoveries, particularly the sulfur and oxygen ion emissions in the Io torus and molecular and atomic hydrogen auroral and airglow emissions from Jupiter. The UVS will obtain spectra of emission, absorption, and scattering features in the unexplored, by spacecraft, 170-432 nm wavelength region. The UVS and EUVS instruments will provide a powerful instrument complement to investigate volatile escape and surface composition of the Galilean satellites, the Io plasma torus, micro- and macro-properties of the Jupiter clouds, and the composition structure and evolution of the Jupiter upper atmosphere.

Establishing resolution-improved NMR spectroscopy in high magnetic fields with unknown spatiotemporal variations

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

Zhang, Zhiyong; Cai, Shuhui; Zheng, Zhenyao

A half-century quest for higher magnetic fields has been an integral part of the progress undergone in the Nuclear Magnetic Resonance (NMR) study of materials’ structure and dynamics. Because 2D NMR relies on systematic changes in coherences’ phases as a function of an encoding time varied over a series of independent experiments, it generally cannot be applied in temporally unstable fields. This precludes most NMR methods from being used to characterize samples situated in hybrid or resistive magnets that are capable of achieving extremely high magnetic field strength. Recently, “ultrafast” NMR has been developed into an effective and widely applicablemore » methodology enabling the acquisition of a multidimensional NMR spectrum in a single scan; it can therefore be used to partially mitigate the effects of temporally varying magnetic fields. Nevertheless, the strong interference of fluctuating fields with the spatial encoding of ultrafast NMR still severely restricts measurement sensitivity and resolution. Here, we introduce a strategy for obtaining high resolution NMR spectra that exploits the immunity of intermolecular zero-quantum coherences (iZQCs) to field instabilities and inhomogeneities. The spatial encoding of iZQCs is combined with a J-modulated detection scheme that removes the influence of arbitrary field inhomogeneities during acquisition. This new method can acquire high-resolution one-dimensional NMR spectra in large inhomogeneous and fluctuating fields, and it is tested with fields experimentally modeled to mimic those of resistive and resistive-superconducting hybrid magnets.« less

A Sagnac Fourier spectrometer

DOE PAGES

Lenzner, Matthias; Diels, Jean -Claude

2017-03-09

A spectrometer based on a Sagnac interferometer, where one of the mirrors is replaced by a transmission grating, is introduced. Since the action of a transmission grating is reversible, both directions experience the same diffraction at a given wavelength. At the output, the crossed wavefronts are imaged onto a camera, where their Fizeau fringe pattern is recorded. Each spectral element produces a unique spatial frequency, hence the Fourier transform of the recorded interferogram contains the spectrum. Since the grating is tuned to place zero spatial frequency at a selected wavelength, the adjoining spectrum is heterodyned with respect to this wavelength.more » This spectrum can then be discriminated at a high spectral resolution from relatively low spatial frequencies. The spectrometer can be designed without moving parts for a relatively narrow spectral range or with a rotatable grating. As a result, the latter version bears the potential to be calibrated without a calibrated light source.« less

A Sagnac Fourier spectrometer

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

Lenzner, Matthias; Diels, Jean -Claude

A spectrometer based on a Sagnac interferometer, where one of the mirrors is replaced by a transmission grating, is introduced. Since the action of a transmission grating is reversible, both directions experience the same diffraction at a given wavelength. At the output, the crossed wavefronts are imaged onto a camera, where their Fizeau fringe pattern is recorded. Each spectral element produces a unique spatial frequency, hence the Fourier transform of the recorded interferogram contains the spectrum. Since the grating is tuned to place zero spatial frequency at a selected wavelength, the adjoining spectrum is heterodyned with respect to this wavelength.more » This spectrum can then be discriminated at a high spectral resolution from relatively low spatial frequencies. The spectrometer can be designed without moving parts for a relatively narrow spectral range or with a rotatable grating. As a result, the latter version bears the potential to be calibrated without a calibrated light source.« less

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.

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.

Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

NASA Astrophysics Data System (ADS)

Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

2018-01-01

We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

Spatially-controlled illumination with rescan confocal microscopy enhances image quality, resolution and reduces photodamage

NASA Astrophysics Data System (ADS)

Krishnaswami, Venkataraman; De Luca, Giulia M. R.; Breedijk, Ronald M. P.; Van Noorden, Cornelis J. F.; Manders, Erik M. M.; Hoebe, Ron A.

2017-02-01

Fluorescence microscopy is an important tool in biomedical imaging. An inherent trade-off lies between image quality and photodamage. Recently, we have introduced rescan confocal microscopy (RCM) that improves the lateral resolution of a confocal microscope down to 170 nm. Previously, we have demonstrated that with controlled-light exposure microscopy, spatial control of illumination reduces photodamage without compromising image quality. Here, we show that the combination of these two techniques leads to high resolution imaging with reduced photodamage without compromising image quality. Implementation of spatially-controlled illumination was carried out in RCM using a line scanning-based approach. Illumination is spatially-controlled for every line during imaging with the help of a prediction algorithm that estimates the spatial profile of the fluorescent specimen. The estimation is based on the information available from previously acquired line images. As a proof-of-principle, we show images of N1E-115 neuroblastoma cells, obtained by this new setup with reduced illumination dose, improved resolution and without compromising image quality.

The spatial resolving power of earth resources satellites: A review

NASA Technical Reports Server (NTRS)

Townshend, J. R. G.

1980-01-01

The significance of spatial resolving power on the utility of current and future Earth resources satellites is critically discussed and the relative merits of different approaches in defining and estimating spatial resolution are outlined. It is shown that choice of a particular measure of spatial resolution depends strongly on the particular needs of the user. Several experiments have simulated the capabilities of future satellite systems by degradation of aircraft images. Surprisingly, many of these indicated that improvements in resolution may lead to a reduction in the classification accuracy of land cover types using computer assisted methods. However, where the frequency of boundary pixels is high, the converse relationship is found. Use of imagery dependent upon visual interpretation is likely to benefit more consistently from higher resolutions. Extraction of information from images will depend upon several other factors apart from spatial resolving power: these include characteristics of the terrain being sensed, the image processing methods that are applied as well as certain sensor characteristics.

Combined Landsat-8 and Sentinel-2 Burned Area Mapping

NASA Astrophysics Data System (ADS)

Huang, H.; Roy, D. P.; Zhang, H.; Boschetti, L.; Yan, L.; Li, Z.

2017-12-01

Fire products derived from coarse spatial resolution satellite data have become an important source of information for the multiple user communities involved in fire science and applications. The advent of the MODIS on NASA's Terra and Aqua satellites enabled systematic production of 500m global burned area maps. There is, however, an unequivocal demand for systematically generated higher spatial resolution burned area products, in particular to examine the role of small-fires for various applications. Moderate spatial resolution contemporaneous satellite data from Landsat-8 and the Sentinel-2A and -2B sensors provide the opportunity for detailed spatial mapping of burned areas. Combined, these polar-orbiting systems provide 10m to 30m multi-spectral global coverage more than once every three days. This NASA funded research presents results to prototype a combined Landsat-8 Sentinel-2 burned area product. The Landsat-8 and Sentinel-2 pre-processing, the time-series burned area mapping algorithm, and preliminary results and validation using high spatial resolution commercial satellite data over Africa are presented.

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

An Optical Wavefront Sensor Based on a Double Layer Microlens Array

PubMed Central

Lin, Vinna; Wei, Hsiang-Chun; Hsieh, Hsin-Ta; Su, Guo-Dung John

2011-01-01

In order to determine light aberrations, Shack-Hartmann optical wavefront sensors make use of microlens arrays (MLA) to divide the incident light into small parts and focus them onto image planes. In this paper, we present the design and fabrication of long focal length MLA with various shapes and arrangements based on a double layer structure for optical wavefront sensing applications. A longer focal length MLA could provide high sensitivity in determining the average slope across each microlens under a given wavefront, and spatial resolution of a wavefront sensor is increased by numbers of microlenses across a detector. In order to extend focal length, we used polydimethysiloxane (PDMS) above MLA on a glass substrate. Because of small refractive index difference between PDMS and MLA interface (UV-resin), the incident light is less refracted and focused in further distance. Other specific focal lengths could also be realized by modifying the refractive index difference without changing the MLA size. Thus, the wavefront sensor could be improved with better sensitivity and higher spatial resolution. PMID:22346643

Geologic map and map database of parts of Marin, San Francisco, Alameda, Contra Costa, and Sonoma counties, California

USGS Publications Warehouse

Blake, M.C.; Jones, D.L.; Graymer, R.W.; digital database by Soule, Adam

2000-01-01

This digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (mageo.txt, mageo.pdf, or mageo.ps), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:62,500 or smaller general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (mageo.txt, mageo.pdf, or mageo.ps), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:62,500 or smaller.

HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling.

PubMed

Ross, C Wade; Prihodko, Lara; Anchang, Julius; Kumar, Sanath; Ji, Wenjie; Hanan, Niall P

2018-05-15

Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.

Miniature Spatial Heterodyne Raman Spectrometer with a Cell Phone Camera Detector.

PubMed

Barnett, Patrick D; Angel, S Michael

2017-05-01

A spatial heterodyne Raman spectrometer (SHRS) with millimeter-sized optics has been coupled with a standard cell phone camera as a detector for Raman measurements. The SHRS is a dispersive-based interferometer with no moving parts and the design is amenable to miniaturization while maintaining high resolution and large spectral range. In this paper, a SHRS with 2.5 mm diffraction gratings has been developed with 17.5 cm -1 theoretical spectral resolution. The footprint of the SHRS is orders of magnitude smaller than the footprint of charge-coupled device (CCD) detectors typically employed in Raman spectrometers, thus smaller detectors are being explored to shrink the entire spectrometer package. This paper describes the performance of a SHRS with 2.5 mm wide diffraction gratings and a cell phone camera detector, using only the cell phone's built-in optics to couple the output of the SHRS to the sensor. Raman spectra of a variety of samples measured with the cell phone are compared to measurements made using the same miniature SHRS with high-quality imaging optics and a high-quality, scientific-grade, thermoelectrically cooled CCD.

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

NASA Astrophysics Data System (ADS)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

USGS Publications Warehouse

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

2014-01-01

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

A neutron camera system for MAST.

PubMed

Cecconello, M; Turnyanskiy, M; Conroy, S; Ericsson, G; Ronchi, E; Sangaroon, S; Akers, R; Fitzgerald, I; Cullen, A; Weiszflog, M

2010-10-01

A prototype neutron camera has been developed and installed at MAST as part of a feasibility study for a multichord neutron camera system with the aim to measure the spatial and time resolved 2.45 MeV neutron emissivity profile. Liquid scintillators coupled to a fast digitizer are used for neutron/gamma ray digital pulse shape discrimination. The preliminary results obtained clearly show the capability of this diagnostic to measure neutron emissivity profiles with sufficient time resolution to study the effect of fast ion loss and redistribution due to magnetohydrodynamic activity. A minimum time resolution of 2 ms has been achieved with a modest 1.5 MW of neutral beam injection heating with a measured neutron count rate of a few 100 kHz.

First experiment on retrieval of tropospheric NO2 over polluted areas with 2.4-km spatial resolution basing on satellite spectral measurements

NASA Astrophysics Data System (ADS)

Postylyakov, Oleg V.; Borovski, Alexander N.; Makarenkov, Aleksandr A.

2017-11-01

Three satellites of the Resurs-P series (№1, №2, №3) aimed for remote sensing of the Earth began to operate in Russia in 2013-2016. Hyperspectral instruments GSA onboard Resurs-P perform routine imaging of the Earth surface in the spectral range of 400-1000 nm with the spectral resolution better than 10 nm and the spatial resolution of 30 m. In a special regime the GSA/Resurs-P may reach higher spectral resolution with the spatial resolution of 120 m and be used for retrieval of the tropospheric NO2 spatial distribution. We developed the first GSA/Resurs-P algorithm for the tropospheric NO2 retrieval and shortly analyze the first results for the most polluted Hebei province of China. The developed GSA/Resurs-P algorithm shows the spatial resolution of about 2.4 km for tropospheric NO2 pollution what significantly exceed resolution of other available now satellite instruments and considered as a target for future geostationary (GEO) missions for monitoring of tropospheric NO2 pollution. Differ to the currently operated low-Earth orbit (LEO) instruments, which may provide global distribution of NO2 every one or two days, GSA performs NO2 measurement on request. The precision of the NO2 measurements with 2.4 km resolution is about 2.5x1015 mol/cm2 (for DSCD) therefore it is recommended to use it for investigation of the tropospheric NO2 in polluted areas. Thus GSA/Resurs-P is the interesting and unique tool for NO2 pollution investigations and testing methods of interpretation of future high-resolution satellite data on pollutions and their emissions.

Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

NASA Astrophysics Data System (ADS)

Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.

2017-08-01

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

Comparing the imaging performance of computed super resolution and magnification tomosynthesis

NASA Astrophysics Data System (ADS)

Maidment, Tristan D.; Vent, Trevor L.; Ferris, William S.; Wurtele, David E.; Acciavatti, Raymond J.; Maidment, Andrew D. A.

2017-03-01

Computed super-resolution (SR) is a method of reconstructing images with pixels that are smaller than the detector element size; superior spatial resolution is achieved through the elimination of aliasing and alteration of the sampling function imposed by the reconstructed pixel aperture. By comparison, magnification mammography is a method of projection imaging that uses geometric magnification to increase spatial resolution. This study explores the development and application of magnification digital breast tomosynthesis (MDBT). Four different acquisition geometries are compared in terms of various image metrics. High-contrast spatial resolution was measured in various axes using a lead star pattern. A modified Defrise phantom was used to determine the low-frequency spatial resolution. An anthropomorphic phantom was used to simulate clinical imaging. Each experiment was conducted at three different magnifications: contact (1.04x), MAG1 (1.3x), and MAG2 (1.6x). All images were taken on our next generation tomosynthesis system, an in-house solution designed to optimize SR. It is demonstrated that both computed SR and MDBT (MAG1 and MAG2) provide improved spatial resolution over non-SR contact imaging. To achieve the highest resolution, SR and MDBT should be combined. However, MDBT is adversely affected by patient motion at higher magnifications. In addition, MDBT requires more radiation dose and delays diagnosis, since MDBT would be conducted upon recall. By comparison, SR can be conducted with the original screening data. In conclusion, this study demonstrates that computed SR and MDBT are both viable methods of imaging the breast.

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).

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

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

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

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.

Quality evaluation of pansharpened hyperspectral images generated using multispectral images

NASA Astrophysics Data System (ADS)

Matsuoka, Masayuki; Yoshioka, Hiroki

2012-11-01

Hyperspectral remote sensing can provide a smooth spectral curve of a target by using a set of higher spectral resolution detectors. The spatial resolution of the hyperspectral images, however, is generally much lower than that of multispectral images due to the lower energy of incident radiation. Pansharpening is an image-fusion technique that generates higher spatial resolution multispectral images by combining lower resolution multispectral images with higher resolution panchromatic images. In this study, higher resolution hyperspectral images were generated by pansharpening of simulated lower hyperspectral and higher multispectral data. Spectral and spatial qualities of pansharpened images, then, were accessed in relation to the spectral bands of multispectral images. Airborne hyperspectral data of AVIRIS was used in this study, and it was pansharpened using six methods. Quantitative evaluations of pansharpened image are achieved using two frequently used indices, ERGAS, and the Q index.

Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

PubMed

Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

2017-04-01

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

Long-Term Monitoring of Desert Land and Natural Resources and Application of Remote Sensing Technologies

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

Hamada, Yuki; Rollins, Katherine E.

2016-11-01

Monitoring environmental impacts over large, remote desert regions for long periods of time can be very costly. Remote sensing technologies present a promising monitoring tool because they entail the collection of spatially contiguous data, automated processing, and streamlined data analysis. This report provides a summary of remote sensing products and refinement of remote sensing data interpretation methodologies that were generated as part of the U.S. Department of the Interior Bureau of Land Management Solar Energy Program. In March 2015, a team of researchers from Argonne National Laboratory (Argonne) collected field data of vegetation and surface types from more than 5,000more » survey points within the eastern part of the Riverside East Solar Energy Zone (SEZ). Using the field data, remote sensing products that were generated in 2014 using very high spatial resolution (VHSR; 15 cm) multispectral aerial images were validated in order to evaluate potential refinements to the previous methodologies to improve the information extraction accuracy.« less

Resolution-enhanced Mapping Spectrometer

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Aubrun, J. N.; Rosenberg, W. J.; Roche, A. E.

1993-01-01

A familiar mapping spectrometer implementation utilizes two dimensional detector arrays with spectral dispersion along one direction and spatial along the other. Spectral images are formed by spatially scanning across the scene (i.e., push-broom scanning). For imaging grating and prism spectrometers, the slit is perpendicular to the spatial scan direction. For spectrometers utilizing linearly variable focal-plane-mounted filters the spatial scan direction is perpendicular to the direction of spectral variation. These spectrometers share the common limitation that the number of spectral resolution elements is given by the number of pixels along the spectral (or dispersive) direction. Resolution enhancement by first passing the light input to the spectrometer through a scanned etalon or Michelson is discussed. Thus, while a detector element is scanned through a spatial resolution element of the scene, it is also temporally sampled. The analysis for all the pixels in the dispersive direction is addressed. Several specific examples are discussed. The alternate use of a Michelson for the same enhancement purpose is also discussed. Suitable for weight constrained deep space missions, hardware systems were developed including actuators, sensor, and electronics such that low-resolution etalons with performance required for implementation would weigh less than one pound.

Neutron imaging with lithium indium diselenide: Surface properties, spatial resolution, and computed tomography

NASA Astrophysics Data System (ADS)

Lukosi, Eric D.; Herrera, Elan H.; Hamm, Daniel S.; Burger, Arnold; Stowe, Ashley C.

2017-11-01

An array of lithium indium diselenide (LISe) scintillators were investigated for application in neutron imaging. The sensors, varying in thickness and surface roughness, were tested using both reflective and anti-reflective mounting to an aluminum window. The spatial resolution of each LISe scintillator was calculated using the knife-edge test and a modulation transfer function analysis. It was found that the anti-reflective backing case yielded higher spatial resolutions by up to a factor of two over the reflective backing case despite a reduction in measured light yield by an average of 1.97. In most cases, the use of an anti-reflective backing resulted in a higher spatial resolution than the 50 μm-thick ZnS(Cu):6 LiF comparison scintillation screen. The effect of surface roughness was not directly correlated to measured light yield or observed spatial resolution, but weighting the reflective backing case by the random surface roughness revealed that a linear relationship exists between the fractional change (RB/ARB) of the two. Finally, the LISe scintillator array was used in neutron computed tomography to investigate the features of halyomorpha halys with the reflective and anti-reflective backing.

On the Importance of Spatial Resolution for Flap Side Edge Noise Prediction

NASA Technical Reports Server (NTRS)

Mineck, Raymond E.; Khorrami, Mehdi R.

2017-01-01

A spatial resolution study of flap tip flow and the effects on the farfield noise signature for an 18%-scale, semispan Gulfstream aircraft model are presented. The NASA FUN3D unstructured, compressible Navier-Stokes solver was used to perform the highly resolved, time-dependent, detached eddy simulations of the flow field associated with the flap for this high-fidelity aircraft model. Following our previous work on the same model, the latest computations were undertaken to determine the causes of deficiencies observed in our earlier predictions of the steady and unsteady surface pressures and off-surface flow field at the flap tip regions, in particular the outboard tip area, where the presence of a cavity at the side-edge produces very complex flow features and interactions. The present results show gradual improvement in steady loading at the outboard flap edge region with increasing spatial resolution, yielding more accurate fluctuating surface pressures, off-surface flow field, and farfield noise with improved high-frequency content when compared with wind tunnel measurements. The spatial resolution trends observed in the present study demonstrate that the deficiencies reported in our previous computations are mostly caused by inadequate spatial resolution and are not related to the turbulence model.

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Treesearch

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Spatial noise and threshold contrasts in LCD displays

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Krupinski, Elizabeth A.; Chawla, Amarpreet S.; Fan, Jiahua; Gandhi, Kunal

2003-05-01

This paper presents the results of initial physical and psycho-physical evaluations of the noise of high resolution LCDs. 5 LCDs were involved, having 4 different pixel structures. Spatial as well as temporal noise was physically measured with the aid of a high-performance CCD camera. Human contrast sensitivity in the presence of spatial noise was determined psycho-physically using periodic stimuli (square-wave patterns) as well as aperiodic stimuli (squares). For the measurements of the human contrast sensitivity, all LCDs were calibrated to the DICOM 14 Grayscale Standard Display Function (GSDF). The results demonstrate that spatial noise is the dominant noise in all LCDs, while temporal noise is insignificant and plays only a minor part. The magnitude of spatial noise of LCDs is in the range between that of CRTs with a P104 and that of CRTs with a P45. Of particular importance with respect to LCD noise is the contribution of the pixel structure to the Noise Power Spectrum, which shows up as sharp spikes at spatial frequencies beyond the LCDs" Nyquist frequency. The paper does not offer any clues about the importance of these spikes on the human contrast sensitivity.

Resolution modeling of dispersive imaging spectrometers

NASA Astrophysics Data System (ADS)

Silny, John F.

2017-08-01

This paper presents best practices for modeling the resolution of dispersive imaging spectrometers. The differences between sampling, width, and resolution are discussed. It is proposed that the spectral imaging community adopt a standard definition for resolution as the full-width at half maximum of the total line spread function. Resolution should be computed for each of the spectral, cross-scan spatial, and along-scan spatial/temporal dimensions separately. A physical optics resolution model is presented that incorporates the effects of slit diffraction and partial coherence, the result of which is a narrower slit image width and reduced radiometric throughput.

High-resolution infrared thermography for capturing wildland fire behaviour - RxCADRE 2012

Treesearch

Joseph J. O’Brien; E. Louise Loudermilk; Benjamin Hornsby; Andrew T. Hudak; Benjamin C. Bright; Matthew B. Dickinson; J. Kevin Hiers; Casey Teske; Roger D. Ottmar

2016-01-01

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at wide spatial extents and high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about fire effects and useful for examining patterns of fire spread. In this study we describe our...

CERES Search and Subset Tool

Atmospheric Science Data Center

2016-06-24

... data granules using a high resolution spatial metadata database and directly accessing the archived data granules. Subset results are ... data granules using a high resolution spatial metadata database and directly accessing the archived data granules. Subset results are ...

Optimization of the spatial resolution for the GE discovery PET/CT 710 by using NEMA NU 2-2007 standards

NASA Astrophysics Data System (ADS)

Yoon, Hyun Jin; Jeong, Young Jin; Son, Hye Joo; Kang, Do-Young; Hyun, Kyung-Yae; Lee, Min-Kyung

2015-01-01

The spatial resolution in positron emission tomography (PET) is fundamentally limited by the geometry of the detector element, the positron's recombination range with electrons, the acollinearity of the positron, the crystal decoding error, the penetration into the detector ring, and the reconstruction algorithms. In this paper, optimized parameters are suggested to produce high-resolution PET images by using an iterative reconstruction algorithm. A phantom with three point sources structured with three capillary tubes was prepared with an axial extension of less than 1 mm and was filled with 18F-fluorodeoxyglucose (18F-FDG) with concentrations above 200 MBq/cc. The performance measures of all the PET images were acquired according to the National Electrical Manufacturers Association (NEMA) NU 2-2007 standards procedures. The parameters for the iterative reconstruction were adjusted around the values recommended by General Electric GE, and the optimized values of the spatial resolution and the full width at half maximum (FWHM) or the full width at tenth of maximum (FWTM) values were found for the best PET resolution. The axial and the transverse spatial resolutions, according to the filtered back-projection (FBP) at 1 cm off-axis, were 4.81 and 4.48 mm, respectively. The axial and the transaxial spatial resolutions at 10 cm off-axis were 5.63 mm and 5.08 mm, respectively, and the trans-axial resolution at 10 cm was evaluated as the average of the radial and the tangential measurements. The recommended optimized parameters of the spatial resolution according to the NEMA phantom for the number of subsets, the number of iterations, and the Gaussian post-filter are 12, 3, and 3 mm for the iterative reconstruction VUE Point HD without the SharpIR algorithm (HD), and 12, 12, and 5.2 mm with SharpIR (HD.S), respectively, according to the Advantage Workstation Volume Share 5 (AW4.6). The performance measurements for the GE Discovery PET/CT 710 using the NEMA NU 2-2007 standards from our results will be helpful in the quantitative analysis of PET scanner images. The spatial resolution was modified more by using an improved algorithm such as HD.S, than by using HD and FBP. The use of the optimized parameters for iterative reconstructions is strongly recommended for qualitative images from the GE Discovery PET/CT 710 scanner.

A method for generating high resolution satellite image time series

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-10-01

There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation, environment and etc. applications.

Analysis of axial spatial resolution in a variable resolution x-ray cone beam CT (VRX-CBCT) system

NASA Astrophysics Data System (ADS)

Dahi, Bahram; Keyes, Gary S.; Rendon, David A.; DiBianca, Frank A.

2008-03-01

The Variable Resolution X-ray (VRX) technique has been successfully used in a Cone-Beam CT (CBCT) system to increase the spatial resolution of CT images in the transverse plane. This was achieved by tilting the Flat Panel Detector (FPD) to smaller vrx y angles in a VRX Cone Beam CT (VRX-CBCT) system. In this paper, the effect on the axial spatial resolution of CT images created by the VRX-CBCT system is examined at different vrx x angles, where vrx x is the tilting angle of the FPD about its x-axis. An amorphous silicon FPD with a CsI scintillator is coupled with a micro-focus x-ray tube to form a CBCT. The FPD is installed on a rotating frame that allows rotation of up to 90° about x and y axes of the FPD. There is no rotation about the z-axis (i.e. normal to the imaging surface). Tilting the FPD about its x-axis (i.e. decreasing the vrx x angle) reduces both the width of the line-spread function and the sampling distance by a factor of sin vrx x, thereby increasing the theoretical detector pre-sampling spatial resolution proportionately. This results in thinner CT slices that in turn help increase the axial spatial resolution of the CT images. An in-house phantom is used to measure the MTF of the reconstructed CT images at different vrx x angles.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

PubMed

Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

2015-01-01

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001). Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

The influence of spatial resolution on human health risk co-benefit estimates for global climate policy assessments.

PubMed

Shih, Hsiu-Ching; Crawford-Brown, Douglas; Ma, Hwong-wen

2015-03-15

Assessment of the ability of climate policies to produce desired improvements in public health through co-benefits of air pollution reduction can consume resources in both time and research funds. These resources increase significantly as the spatial resolution of models increases. In addition, the level of spatial detail available in macroeconomic models at the heart of climate policy assessments is much lower than that available in traditional human health risk modeling. It is therefore important to determine whether increasing spatial resolution considerably affects risk-based decisions; which kinds of decisions might be affected; and under what conditions they will be affected. Human health risk co-benefits from carbon emissions reductions that bring about concurrent reductions in Particulate Matter (PM10) emissions is therefore examined here at four levels of spatial resolution (Uniform Nation, Uniform Region, Uniform County/city, Health Risk Assessment) in a case study of Taiwan as one of the geographic regions of a global macroeceonomic model, with results that are representative of small, industrialized nations within that global model. A metric of human health risk mortality (YOLL, years of life lost in life expectancy) is compared under assessments ranging from a "uniform simulation" in which there is no spatial resolution of changes in ambient air concentration under a policy to a "highly spatially resolved simulation" (called here Health Risk Assessment). PM10 is chosen in this study as the indicator of air pollution for which risks are assessed due to its significance as a co-benefit of carbon emissions reductions within climate mitigation policy. For the policy examined, the four estimates of mortality in the entirety of Taiwan are 747 YOLL, 834 YOLL, 984 YOLL and 916 YOLL, under Uniform Taiwan, Uniform Region, Uniform County and Health Risk Assessment respectively; or differences of 18%, 9%, 7% if the HRA methodology is taken as the baseline. While these differences are small compared to uncertainties in health risk assessment more generally, the ranks of different regions and of emissions categories as the focus of regulatory efforts estimated at these four levels of spatial resolution are quite different. The results suggest that issues of risk equity within a nation might be missed by the lower levels of spatial resolution, suggesting that low resolution models are suited to calculating national cost-benefit ratios but not as suited to assessing co-benefits of climate policies reflecting intersubject variability in risk, or in identifying sub-national regions and emissions sectors on which to focus attention (although even here, the errors introduced by low spatial resolution are generally less than 40%). Copyright © 2014 Elsevier Ltd. All rights reserved.

The Effect of Magnetic Field on Positron Range and Spatial Resolution in an Integrated Whole-Body Time-Of-Flight PET/MRI System.

PubMed

Huang, Shih-Ying; Savic, Dragana; Yang, Jaewon; Shrestha, Uttam; Seo, Youngho

2014-11-01

Simultaneous imaging systems combining positron emission tomography (PET) and magnetic resonance imaging (MRI) have been actively investigated. A PET/MR imaging system (GE Healthcare) comprised of a time-of-flight (TOF) PET system utilizing silicon photomultipliers (SiPMs) and 3-tesla (3T) MRI was recently installed at our institution. The small-ring (60 cm diameter) TOF PET subsystem of this PET/MRI system can generate images with higher spatial resolution compared with conventional PET systems. We have examined theoretically and experimentally the effect of uniform magnetic fields on the spatial resolution for high-energy positron emitters. Positron emitters including 18 F, 124 I, and 68 Ga were simulated in water using the Geant4 Monte Carlo toolkit in the presence of a uniform magnetic field (0, 3, and 7 Tesla). The positron annihilation position was tracked to determine the 3D spatial distribution of the 511-keV gammy ray emission. The full-width at tenth maximum (FWTM) of the positron point spread function (PSF) was determined. Experimentally, 18 F and 68 Ga line source phantoms in air and water were imaged with an investigational PET/MRI system and a PET/CT system to investigate the effect of magnetic field on the spatial resolution of PET. The full-width half maximum (FWHM) of the line spread function (LSF) from the line source was determined as the system spatial resolution. Simulations and experimental results show that the in-plane spatial resolution was slightly improved at field strength as low as 3 Tesla, especially when resolving signal from high-energy positron emitters in the air-tissue boundary.

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

PubMed Central

Hu, Mao-Gui; Wang, Jin-Feng; Ge, Yong

2009-01-01

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics. PMID:22291530

Electron-Beam Mapping of Vibrational Modes with Nanometer Spatial Resolution.

PubMed

Dwyer, C; Aoki, T; Rez, P; Chang, S L Y; Lovejoy, T C; Krivanek, O L

2016-12-16

We demonstrate that a focused beam of high-energy electrons can be used to map the vibrational modes of a material with a spatial resolution of the order of one nanometer. Our demonstration is performed on boron nitride, a polar dielectric which gives rise to both localized and delocalized electron-vibrational scattering, either of which can be selected in our off-axial experimental geometry. Our experimental results are well supported by our calculations, and should reconcile current controversy regarding the spatial resolution achievable in vibrational mapping with focused electron beams.

Reconstructed Image Spatial Resolution of Multiple Coincidences Compton Imager

NASA Astrophysics Data System (ADS)

Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna

2010-02-01

We study the multiple coincidences Compton imager (MCCI) which is based on a simultaneous acquisition of several photons emitted in cascade from a single nuclear decay. Theoretically, this technique should provide a major improvement in localization of a single radioactive source as compared to a standard Compton camera. In this work, we investigated the performance and limitations of MCCI using Monte Carlo computer simulations. Spatial resolutions of the reconstructed point source have been studied as a function of the MCCI parameters, including geometrical dimensions and detector characteristics such as materials, energy and spatial resolutions.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

Highly efficient peptide separations in proteomics. Part 2: bi- and multidimensional liquid-based separation techniques.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Tuytten, Robin; Verleysen, Katleen; Kas, Koen; François, Isabelle; Sandra, Pat

2009-04-15

Multidimensional liquid-based separation techniques are described for maximizing the resolution of the enormous number of peptides generated upon tryptic digestion of proteomes, and hence, reduce the spatial and temporal complexity of the sample to a level that allows successful mass spectrometric analysis. This review complements the previous contribution on unidimensional high performance liquid chromatography (HPLC). Both chromatography and electrophoresis will be discussed albeit with reversed-phase HPLC (RPLC) as the final separation dimension prior to MS analysis.

MeV ion-induced movement of lattice disorder in single crystalline silicon

NASA Astrophysics Data System (ADS)

Sen, P.; Akhtar, J.; Russell, F. M.

2000-08-01

We provide experimental evidence for the transport of atomic disorder over large distances, in device grade single-crystalline silicon, following irradiation with 200 MeV silver ions. Pile-up of lattice defects or disorder is effected at predetermined locations, spatially separated from the irradiation site. These are revealed by STM scans with atomic resolution, of an intermediate region, spanning from irradiated to shadowed parts of the crystal surface. The experimental results are consistent with transport of disorder through breather-like intrinsic localised excitations.

Functional cardiac magnetic resonance microscopy

NASA Astrophysics Data System (ADS)

Brau, Anja Christina Sophie

2003-07-01

The study of small animal models of human cardiovascular disease is critical to our understanding of the origin, progression, and treatment of this pervasive disease. Complete analysis of disease pathophysiology in these animal models requires measuring structural and functional changes at the level of the whole heart---a task for which an appropriate non-invasive imaging method is needed. The purpose of this work was thus to develop an imaging technique to support in vivo characterization of cardiac structure and function in rat and mouse models of cardiovascular disease. Whereas clinical cardiac magnetic resonance imaging (MRI) provides accurate assessment of the human heart, the extension of cardiac MRI from humans to rodents presents several formidable scaling challenges. Acquiring images of the mouse heart with organ definition and fluidity of contraction comparable to that achieved in humans requires an increase in spatial resolution by a factor of 3000 and an increase in temporal resolution by a factor of ten. No single technical innovation can meet the demanding imaging requirements imposed by the small animal. A functional cardiac magnetic resonance microscopy technique was developed by integrating improvements in physiological control, imaging hardware, biological synchronization of imaging, and pulse sequence design to achieve high-quality images of the murine heart with high spatial and temporal resolution. The specific methods and results from three different sets of imaging experiments are presented: (1) 2D functional imaging in the rat with spatial resolution of 175 mum2 x 1 mm and temporal resolution of 10 ms; (2) 3D functional imaging in the rat with spatial resolution of 100 mum 2 x 500 mum and temporal resolution of 30 ms; and (3) 2D functional imaging in the mouse with spatial resolution down to 100 mum2 x 1 mm and temporal resolution of 10 ms. The cardiac microscopy technique presented here represents a novel collection of technologies capable of acquiring routine high-quality images of murine cardiac structure and function with minimal artifacts and markedly higher spatial resolution compared to conventional techniques. This work is poised to serve a valuable role in the evaluation of cardiovascular disease and should find broad application in studies ranging from basic pathophysiology to drug discovery.

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

Wu, Pei-Hsin; Chung, Hsiao-Wen; Tsai, Ping-Huei

Purpose: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm{sup 3} achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm{sup 3} voxel volume at 3.0 T. Methods: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations weremore » given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outerk-space data components. Results: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm{sup 3} to 0.43 × 0.43 × 2 mm{sup 3} has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. Conclusions: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.« less

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

Signatures of Penumbral Magnetic Fields at Very High Spatial Resolution

NASA Astrophysics Data System (ADS)

Langhans, K.

2006-12-01

Full Stokes spectro-polarimetry, together with refined techniques to interpret the measurements and continual modeling efforts, have improved our understanding of sunspot penumbrae in the last years. In spite of this progress, an improvement in the spatial resolution of the observations is clearly needed to establish in a more direct way the fine structure of the penumbra. The discovery of dark penumbral cores by tet{l3 Sc02} suggests that we are starting to resolve the fundamental scales of the penumbra. Spectro-polarimetric measurements that are sensitive to the magnetic field in both the photosphere and higher layers, and obtained at a spatial resolution approaching 0.1 arcsec, may therefore allow us to draw firm conclusions about the fine scale organization of penumbral magnetic fields. In this paper I will discuss recent polarization measurements at very high spatial resolution, trying to reconcile the different scenarios put forward to explain the structure of the penumbra.

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.

Super-resolution reconstruction of hyperspectral images.

PubMed

Akgun, Toygar; Altunbasak, Yucel; Mersereau, Russell M

2005-11-01

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.

Temporal and spatial resolution required for imaging myocardial function

NASA Astrophysics Data System (ADS)

Eusemann, Christian D.; Robb, Richard A.

2004-05-01

4-D functional analysis of myocardial mechanics is an area of significant interest and research in cardiology and vascular/interventional radiology. Current multidimensional analysis is limited by insufficient temporal resolution of x-ray and magnetic resonance based techniques, but recent improvements in system design holds hope for faster and higher resolution scans to improve images of moving structures allowing more accurate functional studies, such as in the heart. This paper provides a basis for the requisite temporal and spatial resolution for useful imaging during individual segments of the cardiac cycle. Multiple sample rates during systole and diastole are compared to determine an adequate sample frequency to reduce regional myocardial tracking errors. Concurrently, out-of-plane resolution has to be sufficiently high to minimize partial volume effect. Temporal resolution and out-of-plane spatial resolution are related factors that must be considered together. The data used for this study is a DSR dynamic volume image dataset with high temporal and spatial resolution using implanted fiducial markers to track myocardial motion. The results of this study suggest a reduced exposure and scan time for x-ray and magnetic resonance imaging methods, since a lower sample rate during systole is sufficient, whereas the period of rapid filling during diastole requires higher sampling. This could potentially reduce the cost of these procedures and allow higher patient throughput.

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.

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

Tiwari, K. C.; Arora, M.; Singh, D.

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Gamma-Ray Imager With High Spatial And Spectral Resolution

NASA Technical Reports Server (NTRS)

Callas, John L.; Varnell, Larry S.; Wheaton, William A.; Mahoney, William A.

1996-01-01

Gamma-ray instrument developed to enable both two-dimensional imaging at relatively high spatial resolution and spectroscopy at fractional-photon-energy resolution of about 10 to the negative 3rd power in photon-energy range from 10 keV to greater than 10 MeV. In its spectroscopic aspect, instrument enables identification of both narrow and weak gamma-ray spectral peaks.

High-resolution spatial modeling of daily weather elements for a catchment in the Oregon Cascade Mountains, United States

Treesearch

Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane

2007-01-01

High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...

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.

A maximum likelihood method for high resolution proton radiography/proton CT

NASA Astrophysics Data System (ADS)

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Portillo, Stephen K. N.; Beaulieu, Luc; Seco, Joao

2016-12-01

Multiple Coulomb scattering (MCS) is the largest contributor to blurring in proton imaging. In this work, we developed a maximum likelihood least squares estimator that improves proton radiography’s spatial resolution. The water equivalent thickness (WET) through projections defined from the source to the detector pixels were estimated such that they maximizes the likelihood of the energy loss of every proton crossing the volume. The length spent in each projection was calculated through the optimized cubic spline path estimate. The proton radiographies were produced using Geant4 simulations. Three phantoms were studied here: a slanted cube in a tank of water to measure 2D spatial resolution, a voxelized head phantom for clinical performance evaluation as well as a parametric Catphan phantom (CTP528) for 3D spatial resolution. Two proton beam configurations were used: a parallel and a conical beam. Proton beams of 200 and 330 MeV were simulated to acquire the radiography. Spatial resolution is increased from 2.44 lp cm-1 to 4.53 lp cm-1 in the 200 MeV beam and from 3.49 lp cm-1 to 5.76 lp cm-1 in the 330 MeV beam. Beam configurations do not affect the reconstructed spatial resolution as investigated between a radiography acquired with the parallel (3.49 lp cm-1 to 5.76 lp cm-1) or conical beam (from 3.49 lp cm-1 to 5.56 lp cm-1). The improved images were then used as input in a photon tomography algorithm. The proton CT reconstruction of the Catphan phantom shows high spatial resolution (from 2.79 to 5.55 lp cm-1 for the parallel beam and from 3.03 to 5.15 lp cm-1 for the conical beam) and the reconstruction of the head phantom, although qualitative, shows high contrast in the gradient region. The proposed formulation of the optimization demonstrates serious potential to increase the spatial resolution (up by 65 % ) in proton radiography and greatly accelerate proton computed tomography reconstruction.

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.

SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT

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

Collins-Fekete, C; Centre Hospitalier University de Quebec, Quebec, QC; Mass General Hospital

2016-06-15

Purpose: Multiple Coulomb scattering is the largest contributor to blurring in proton imaging. Here we tested a maximum likelihood least squares estimator (MLLSE) to improve the spatial resolution of proton radiography (pRad) and proton computed tomography (pCT). Methods: The object is discretized into voxels and the average relative stopping power through voxel columns defined from the source to the detector pixels is optimized such that it maximizes the likelihood of the proton energy loss. The length spent by individual protons in each column is calculated through an optimized cubic spline estimate. pRad images were first produced using Geant4 simulations. Anmore » anthropomorphic head phantom and the Catphan line-pair module for 3-D spatial resolution were studied and resulting images were analyzed. Both parallel and conical beam have been investigated for simulated pRad acquisition. Then, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Specific filters were applied on proton angle and energy loss data to remove proton histories that underwent nuclear interactions. The MTF10% (lp/mm) was used to evaluate and compare spatial resolution. Results: Numerical simulations showed improvement in the pRad spatial resolution for the parallel (2.75 to 6.71 lp/cm) and conical beam (3.08 to 5.83 lp/cm) reconstructed with the MLLSE compared to averaging detector pixel signals. For full tomographic reconstruction, the improved pRad were used as input into a simultaneous algebraic reconstruction algorithm. The Catphan pCT reconstruction based on the MLLSE-enhanced projection showed spatial resolution improvement for the parallel (2.83 to 5.86 lp/cm) and conical beam (3.03 to 5.15 lp/cm). The anthropomorphic head pCT displayed important contrast gains in high-gradient regions. Experimental results also demonstrated significant improvement in spatial resolution of the pediatric head radiography. Conclusion: The proposed MLLSE shows promising potential to increase the spatial resolution (up to 244%) in proton imaging.« less

A maximum likelihood method for high resolution proton radiography/proton CT.

PubMed

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Portillo, Stephen K N; Beaulieu, Luc; Seco, Joao

2016-12-07

Multiple Coulomb scattering (MCS) is the largest contributor to blurring in proton imaging. In this work, we developed a maximum likelihood least squares estimator that improves proton radiography's spatial resolution. The water equivalent thickness (WET) through projections defined from the source to the detector pixels were estimated such that they maximizes the likelihood of the energy loss of every proton crossing the volume. The length spent in each projection was calculated through the optimized cubic spline path estimate. The proton radiographies were produced using Geant4 simulations. Three phantoms were studied here: a slanted cube in a tank of water to measure 2D spatial resolution, a voxelized head phantom for clinical performance evaluation as well as a parametric Catphan phantom (CTP528) for 3D spatial resolution. Two proton beam configurations were used: a parallel and a conical beam. Proton beams of 200 and 330 MeV were simulated to acquire the radiography. Spatial resolution is increased from 2.44 lp cm -1 to 4.53 lp cm -1 in the 200 MeV beam and from 3.49 lp cm -1 to 5.76 lp cm -1 in the 330 MeV beam. Beam configurations do not affect the reconstructed spatial resolution as investigated between a radiography acquired with the parallel (3.49 lp cm -1 to 5.76 lp cm -1 ) or conical beam (from 3.49 lp cm -1 to 5.56 lp cm -1 ). The improved images were then used as input in a photon tomography algorithm. The proton CT reconstruction of the Catphan phantom shows high spatial resolution (from 2.79 to 5.55 lp cm -1 for the parallel beam and from 3.03 to 5.15 lp cm -1 for the conical beam) and the reconstruction of the head phantom, although qualitative, shows high contrast in the gradient region. The proposed formulation of the optimization demonstrates serious potential to increase the spatial resolution (up by 65[Formula: see text]) in proton radiography and greatly accelerate proton computed tomography reconstruction.

Spatial Classification of Orchards and Vineyards with High Spatial Resolution Panchromatic Imagery

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

Warner, Timothy; Steinmaus, Karen L.

2005-02-01

New high resolution single spectral band imagery offers the capability to conduct image classifications based on spatial patterns in imagery. A classification algorithm based on autocorrelation patterns was developed to automatically extract orchards and vineyards from satellite imagery. The algorithm was tested on IKONOS imagery over Granger, WA, which resulted in a classification accuracy of 95%.

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

NASA Astrophysics Data System (ADS)

Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

2018-02-01

The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

High-resolution maps of real and illusory tactile activation in primary somatosensory cortex in individual monkeys with functional magnetic resonance imaging and optical imaging.

PubMed

Chen, Li M; Turner, Gregory H; Friedman, Robert M; Zhang, Na; Gore, John C; Roe, Anna W; Avison, Malcolm J

2007-08-22

Although blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to explore human brain function, questions remain regarding the ultimate spatial resolution of positive BOLD fMRI, and indeed the extent to which functional maps revealed by positive BOLD correlate spatially with maps obtained with other high-spatial-resolution mapping techniques commonly used in animals, such as optical imaging of intrinsic signal (OIS) and single-unit electrophysiology. Here, we demonstrate that the positive BOLD signal at 9.4T can reveal the fine topography of individual fingerpads in single-condition activation maps in nonhuman primates. These digit maps are similar to maps obtained from the same animal using intrinsic optical imaging. Furthermore, BOLD fMRI reliably resolved submillimeter spatial shifts in activation in area 3b previously identified with OIS (Chen et al., 2003) as neural correlates of the "funneling illusion." These data demonstrate that at high field, high-spatial-resolution topographic maps can be achieved using the positive BOLD signal, weakening previous notions regarding the spatial specificity of the positive BOLD signal.

Influence of Scale Effect and Model Performance in Downscaling ASTER Land Surface Temperatures to a Very High Spatial Resolution in an Agricultural Area

NASA Astrophysics Data System (ADS)

Zhou, J.; Li, G.; Liu, S.; Zhan, W.; Zhang, X.

2015-12-01

At present land surface temperatures (LSTs) can be generated from thermal infrared remote sensing with spatial resolutions from ~100 m to tens of kilometers. However, LSTs with high spatial resolution, e.g. tens of meters, are still lack. The purpose of LST downscaling is to generate LSTs with finer spatial resolutions than their native spatial resolutions. The statistical linear or nonlinear regression models are most frequently used for LST downscaling. The basic assumption of these models is the scale-invariant relationships between LST and its descriptors, which is questioned but rare researches have been reported. In addition, few researches can be found for downscaling satellite LST or TIR data to a high spatial resolution, i.e. better than 100 m or even finer. The lack of LST with high spatial resolution cannot satisfy the requirements of applications such as evapotranspiration mapping at the field scale. By selecting a dynamically developing agricultural oasis as the study area, the aim of this study is to downscale the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSTs to 15 m, to satisfy the requirement of evapotranspiration mapping at the field scale. Twelve ASTER images from May to September in 2012, covering the entire growth stage of maize, were selected. Four statistical models were evaluated, including one global model, one piecewise model, and two local models. The influence from scale effect in downscaling LST was quantified. The downscaled LSTs are evaluated from accuracy and image quality. Results demonstrate that the influence from scale effect varies according to models and the maize growth stage. Significant influence about -4 K to 6 K existed at the early stage and weaker influence existed in the middle stage. When compared with the ground measured LSTs, the downscaled LSTs resulted from the global and local models yielded higher accuracies and better image qualities than the local models. In addition to the vegetation indices, the surface albedo is an important descriptor for downscaling LST through explaining its spatial variation induced by soil moisture.

Integrating flood modelling in a hydrological catchment model: flow approximations and spatial resolution.

NASA Astrophysics Data System (ADS)

van den Bout, Bastian; Jetten, Victor

2017-04-01

Within hydrological models, flow approximations are commonly used to reduce computation time. The validity of these approximations is strongly determined by flow height, flow velocity, the spatial resolution of the model, and by the manner in which flow routing is implemented. The assumptions of these approximations can furthermore limit emergent behavior, and influence flow behavior under space-time scaling. In this presentation, the validity and performance of the kinematic, diffusive and dynamic flow approximations are investigated for use in a catchment-based flood model. Particularly, the validity during flood events and for varying spatial resolutions is investigated. The OpenLISEM hydrological model is extended to implement these flow approximations and channel flooding based on dynamic flow. The kinematic routing uses a predefined converging flow network, the diffusive and dynamic routing uses a 2D flow solution over a DEM. The channel flow in all cases is a 1D kinematic wave approximation. The flow approximations are used to recreate measured discharge in three catchments of different size in China, Spain and Italy, among which is the hydrograph of the 2003 flood event in the Fella river basin (Italy). Furthermore, spatial resolutions are varied for the flood simulation in order to investigate the influence of spatial resolution on these flow approximations. Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured temporal variation of the discharge. Kinematic flow, which is commonly used in hydrological modelling, substantially over-estimates hydrological connectivity in the simulations with a spatial resolution of below 30 meters. Since spatial resolutions of models have strongly increased over the past decades, usage of routed kinematic flow should be reconsidered. In the case of flood events, spatial modelling of kinematic flow substantially over-estimates hydrological connectivity and flow concentration, leading to significant errors. The combination of diffusive or dynamic overland flow and dynamic channel flooding provides high accuracy in recreating the 2003 Fella river flood event. Finally, flow approximations substantially influenced the predictive potential of the (flash) flood model.

Silicon detectors for combined MR-PET and MR-SPECT imaging

NASA Astrophysics Data System (ADS)

Studen, A.; Brzezinski, K.; Chesi, E.; Cindro, V.; Clinthorne, N. H.; Cochran, E.; Grošičar, B.; Grkovski, M.; Honscheid, K.; Kagan, H.; Lacasta, C.; Llosa, G.; Mikuž, M.; Stankova, V.; Weilhammer, P.; Žontar, D.

2013-02-01

Silicon based devices can extend PET-MR and SPECT-MR imaging to applications, where their advantages in performance outweigh benefits of high statistical counts. Silicon is in many ways an excellent detector material with numerous advantages, among others: excellent energy and spatial resolution, mature processing technology, large signal to noise ratio, relatively low price, availability, versatility and malleability. The signal in silicon is also immune to effects of magnetic field at the level normally used in MR devices. Tests in fields up to 7 T were performed in a study to determine effects of magnetic field on positron range in a silicon PET device. The curvature of positron tracks in direction perpendicular to the field's orientation shortens the distance between emission and annihilation point of the positron. The effect can be fully appreciated for a rotation of the sample for a fixed field direction, compressing range in all dimensions. A popular Ga-68 source was used showing a factor of 2 improvement in image noise compared to zero field operation. There was also a little increase in noise as the reconstructed resolution varied between 2.5 and 1.5 mm. A speculative applications can be recognized in both emission modalities, SPECT and PET. Compton camera is a subspecies of SPECT, where a silicon based scatter as a MR compatible part could inserted into the MR bore and the secondary detector could operate in less constrained environment away from the magnet. Introducing a Compton camera also relaxes requirements of the radiotracers used, extending the range of conceivable photon energies beyond 140.5 keV of the Tc-99m. In PET, one could exploit the compressed sub-millimeter range of positrons in the magnetic field. To exploit the advantage, detectors with spatial resolution commensurate to the effect must be used with silicon being an excellent candidate. Measurements performed outside of the MR achieving spatial resolution below 1 mm are reported.

WaterWorld, a spatial hydrological model applied at scales from local to global: key challenges to local application

NASA Astrophysics Data System (ADS)

Burke, Sophia; Mulligan, Mark

2017-04-01

WaterWorld is a widely used spatial hydrological policy support system. The last user census indicates regular use by 1029 institutions across 141 countries. A key feature of WaterWorld since 2001 is that it comes pre-loaded with all of the required data for simulation anywhere in the world at a 1km or 1 ha resolution. This means that it can be easily used, without specialist technical ability, to examine baseline hydrology and the impacts of scenarios for change or management interventions to support policy formulation, hence its labelling as a policy support system. WaterWorld is parameterised by an extensive global gridded database of more than 600 variables, developed from many sources, since 1998, the so-called simTerra database. All of these data are available globally at 1km resolution and some variables (terrain, land cover, urban areas, water bodies) are available globally at 1ha resolution. If users have access to better data than is pre-loaded, they can upload their own data. WaterWorld is generally applied at the national or basin scale at 1km resolution, or locally (for areas of <10,000km2) at 1ha resolution, though continental (1km resolution) and global (10km resolution) applications are possible so it is a model with local to global applications. WaterWorld requires some 140 maps to run including monthly climate data, land cover and use, terrain, population, water bodies and more. Whilst publically-available terrain and land cover data are now well developed for local scale application, climate and land use data remain a challenge, with most global products being available at 1km or 10km resolution or worse, which is rather coarse for local application. As part of the EartH2Observe project we have used WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) at 1km resolution to provide an alternative input to WaterWorld's preloaded climate data. Here we examine the impacts of that on key hydrological outputs: water balance, water quality and outline the remaining challenges of using datasets like these for local scale application.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery

NASA Astrophysics Data System (ADS)

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms (R2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms ( R 2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

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.

First Time-Resolved Observations of Precipitation Structure and Storm Intensity with a Constellation of Smallsats (TROPICS) Mission Applications Workshop Summary Report

NASA Technical Reports Server (NTRS)

Zavodsky, B.; Dunion, J.; Blackwell, W.; Braun, S.; Velden, C.; Brennan, M.; Adler, R.

2017-01-01

The National Aeronautics and Space Administration (NASA) Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of SmallSats (TROPICS) mission is a constellation of state-of-the-science observing platforms that will measure temperature and humidity soundings and precipitation with spatial resolution comparable to current operational passive microwave sounders but with unprecedented temporal resolution. TROPICS is a cost-capped ($30 million) Venture-class mission funded by the NASA Earth Science Division (ESD) and led by principal investigator Dr. William Blackwell from the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The mission is comprised of a constellation of six, three-unit (3U) Cube-Sats (approximately 10 by 10 by 34 centimeters), each hosting a 12-channel passive microwave spectrometer based on the Micro-sized Microwave Atmospheric Satellite 2 (MicroMAS-2) developed at MIT LL. TROPICS will provide imagery at frequencies near 91 and 205 gigahertz, temperature sounding near 118 gigahertz, and moisture sounding near 183 gigahertz. Spatial resolution at nadir will be around 27 kilometers for temperature and 17 kilometers for moisture and precipitation with a swath width of approximately 2,000 kilometers. Both the spatial resolution and swath width are similar to the Advanced Technology Microwave Sounder (ATMS) that is being flown as part of the Suomi National Polar-Orbiting Partnership and will fly starting in 2017 on the National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS). In addition, TROPICS meets many of the requirements outlined in the 2007 Decadal Survey for the Precision and All-Weather Temperature and Humidity mission, which was originally envisioned as a microwave instrument in geostationary orbit. TROPICS enables temporal resolution similar to geostationary orbit but at a much lower cost, demonstrating a technology that could impact the design of future Earth-observing missions. The satellites for the TROPICS mission are slated for delivery to NASA in 2019 for launches planned no earlier than 2020. The primary mission objective of TROPICS is to relate temperature, humidity, and precipitation structure to the evolution of tropical cyclone (TC) intensity.

Satellite image time series simulation for environmental monitoring

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of costly high resolution data can be reduced as much as possible, and it presents an efficient solution with great cost performance to build up an economically operational monitoring service for environment, agriculture, forest, land use investigation, and other applications.

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

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2006-01-01

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Overview of Initial Results from CRISM

NASA Astrophysics Data System (ADS)

Seelos, F.; Murchie, S.; Mustard, J.; Pelkey, S.; Roach, L.; Elhmann, B.; Arvidson, R.; Wiseman, S.; Milliken, R.; CRISM Team

2007-05-01

The Mars Reconnaissance Orbiter (MRO) reached 100 days of primary science phase operations on February 15th, 2007. Over this time period, the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has acquired high spatial resolution hyperspectral observations and contextual multispectral survey data of type localities that record water-rock interaction through much of the geologic history of Mars. CRISM's primary science objectives are to characterize the mineralogical record of past aqueous environments and to monitor the contemporary spatial and seasonal distributions of volatiles in the surface-atmosphere system. These objectives are accomplished through an observation strategy that includes targeted data acquisition, atmospheric and seasonal monitoring, and global mapping. Targeted observations are acquired by gimbaling the instrument along-track to reduce apparent ground motion, resulting in a spatial resolution of 15-20 m/pixel in 544 wavelengths from 362 to 3920 nm. As a part of each targeted observation 10 additional spatially binned images are acquired at different atmospheric path lengths, creating an emission phase function (EPF) that allows surface-atmosphere separation in the analysis of the observed radiance. The atmospheric and seasonal monitoring campaigns consist of global grids of EPF measurements at regular Ls intervals. In CRISM's global mapping campaign, data are acquired in a push broom observing mode at a reduced spatial and spectral resolution of 200m/pxl and 72 selected spectral channels. Initial data analysis reveals evidence for environmental variability throughout Martian history. Noachian deposits exhibit diverse phyllosilicate mineralogy in a greater number of geologic units than previously recognized. Distinct mineralogic signatures are sometimes separated only by hundreds of meters, indicating variability in alteration environment or parent rock composition. Hesperian layered deposits exhibit strong vertical heterogeneity with different abundances and types of sulfate minerals, suggesting local environmental changes on short geologic timescales. The Amazonian north polar layered deposits exhibit complex vertical layering in the abundance and/or grain size of water ice. The underlying basal unit shows little evidence for ice except in restricted locations where the morphology is consistent with subsequent modification of the deposits by fluid flow. Multispectral mapping is nearly complete at the high northern latitudes and shows evidence for significant hydrated mineral content in portions of the basal unit.

Spatial resolution of a hard x-ray CCD detector.

PubMed

Seely, John F; Pereira, Nino R; Weber, Bruce V; Schumer, Joseph W; Apruzese, John P; Hudson, Lawrence T; Szabo, Csilla I; Boyer, Craig N; Skirlo, Scott

2010-08-10

The spatial resolution of an x-ray CCD detector was determined from the widths of the tungsten x-ray lines in the spectrum formed by a crystal spectrometer in the 58 to 70 keV energy range. The detector had 20 microm pixel, 1700 by 1200 pixel format, and a CsI x-ray conversion scintillator. The spectral lines from a megavolt x-ray generator were focused on the spectrometer's Rowland circle by a curved transmission crystal. The line shapes were Lorentzian with an average width after removal of the natural and instrumental line widths of 95 microm (4.75 pixels). A high spatial frequency background, primarily resulting from scattered gamma rays, was removed from the spectral image by Fourier analysis. The spectral lines, having low spatial frequency in the direction perpendicular to the dispersion, were enhanced by partially removing the Lorentzian line shape and by fitting Lorentzian curves to broad unresolved spectral features. This demonstrates the ability to improve the spectral resolution of hard x-ray spectra that are recorded by a CCD detector with well-characterized intrinsic spatial resolution.

Improved spatial resolution of luminescence images acquired with a silicon line scanning camera

NASA Astrophysics Data System (ADS)

Teal, Anthony; Mitchell, Bernhard; Juhl, Mattias K.

2018-04-01

Luminescence imaging is currently being used to provide spatially resolved defect in high volume silicon solar cell production. One option to obtain the high throughput required for on the fly detection is the use a silicon line scan cameras. However, when using a silicon based camera, the spatial resolution is reduced as a result of the weakly absorbed light scattering within the camera's chip. This paper address this issue by applying deconvolution from a measured point spread function. This paper extends the methods for determining the point spread function of a silicon area camera to a line scan camera with charge transfer. The improvement in resolution is quantified in the Fourier domain and in spatial domain on an image of a multicrystalline silicon brick. It is found that light spreading beyond the active sensor area is significant in line scan sensors, but can be corrected for through normalization of the point spread function. The application of this method improves the raw data, allowing effective detection of the spatial resolution of defects in manufacturing.

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.

Coherent x-ray diffraction imaging with nanofocused illumination.

PubMed

Schroer, C G; Boye, P; Feldkamp, J M; Patommel, J; Schropp, A; Schwab, A; Stephan, S; Burghammer, M; Schöder, S; Riekel, C

2008-08-29

Coherent x-ray diffraction imaging is an x-ray microscopy technique with the potential of reaching spatial resolutions well beyond the diffraction limits of x-ray microscopes based on optics. However, the available coherent dose at modern x-ray sources is limited, setting practical bounds on the spatial resolution of the technique. By focusing the available coherent flux onto the sample, the spatial resolution can be improved for radiation-hard specimens. A small gold particle (size <100 nm) was illuminated with a hard x-ray nanobeam (E=15.25 keV, beam dimensions approximately 100 x 100 nm2) and is reconstructed from its coherent diffraction pattern. A resolution of about 5 nm is achieved in 600 s exposure time.

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.