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.

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.

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.

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.

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.

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

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.

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.

Effects of decreasing resolution on spectral and spatial information content in an agricultural area. [Pottawatmie study site, Iowa and Nebraska

NASA Technical Reports Server (NTRS)

1983-01-01

The effects of decreasing spatial resolution from 6 1/4 miles square to 50 miles square are described. The effects of increases in cell size is studied on; the mean and variance of spectral data; spatial trends; and vegetative index numbers. Information content changes on cadastral, vegetal, soil, water and physiographic information are summarized.

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.

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.

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...

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.

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.

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

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.

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.

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.

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.

Electric crosstalk impairs spatial resolution of multi-electrode arrays in retinal implants

NASA Astrophysics Data System (ADS)

Wilke, R. G. H.; Khalili Moghadam, G.; Lovell, N. H.; Suaning, G. J.; Dokos, S.

2011-08-01

Active multi-electrode arrays are used in vision prostheses, including optic nerve cuffs and cortical and retinal implants for stimulation of neural tissue. For retinal implants, arrays with up to 1500 electrodes are used in clinical trials. The ability to convey information with high spatial resolution is critical for these applications. To assess the extent to which spatial resolution is impaired by electric crosstalk, finite-element simulation of electric field distribution in a simplified passive tissue model of the retina is performed. The effects of electrode size, electrode spacing, distance to target cells, and electrode return configuration (monopolar, tripolar, hexagonal) on spatial resolution is investigated in the form of a mathematical model of electric field distribution. Results show that spatial resolution is impaired with increased distance from the electrode array to the target cells. This effect can be partly compensated by non-monopolar electrode configurations and larger electrode diameters, albeit at the expense of lower pixel densities due to larger covering areas by each stimulation electrode. In applications where multi-electrode arrays can be brought into close proximity to target cells, as presumably with epiretinal implants, smaller electrodes in monopolar configuration can provide the highest spatial resolution. However, if the implantation site is further from the target cells, as is the case in suprachoroidal approaches, hexagonally guarded electrode return configurations can convey higher spatial resolution. This paper was originally submitted for the special issue containing contributions from the Sixth Biennial Research Congress of The Eye and the Chip.

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.

Scaling effect of fraction of vegetation cover retrieved by algorithms based on linear mixture model

NASA Astrophysics Data System (ADS)

Obata, Kenta; Miura, Munenori; Yoshioka, Hiroki

2010-08-01

Differences in spatial resolution among sensors have been a source of error among satellite data products, known as a scaling effect. This study investigates the mechanism of the scaling effect on fraction of vegetation cover retrieved by a linear mixture model which employs NDVI as one of the constraints. The scaling effect is induced by the differences in texture, and the differences between the true endmember spectra and the endmember spectra assumed during retrievals. A mechanism of the scaling effect was analyzed by focusing on the monotonic behavior of spatially averaged FVC as a function of spatial resolution. The number of endmember is limited into two to proceed the investigation analytically. Although the spatially-averaged NDVI varies monotonically along with spatial resolution, the corresponding FVC values does not always vary monotonically. The conditions under which the averaged FVC varies monotonically for a certain sequence of spatial resolutions, were derived analytically. The increasing and decreasing trend of monotonic behavior can be predicted from the true and assumed endmember spectra of vegetation and non-vegetation classes regardless the distributions of the vegetation class within a fixed area. The results imply that the scaling effect on FVC is more complicated than that on NDVI, since, unlike NDVI, FVC becomes non-monotonic under a certain condition determined by the true and assumed endmember spectra.

The Effects of Spatial Resolution on Impervious Cover Classifications in Watersheds and Riparian Zones in Vermont

EPA Science Inventory

Impervious cover (roads, rooftops, etc.) is a known stressor on stream biota and habitat and is often used as an indicator for assessing the effects of urbanization on stream health. Understanding how spatial data resolution impacts estimates of impervious cover is important for ...

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

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.

Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.

2016-12-01

Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.

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.

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.

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...

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.

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

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

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.

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.

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.

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...

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

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.

Characterization and modelling of the spatially- and spectrally-varying point-spread function in hyperspectral imaging systems for computational correction of axial optical aberrations

NASA Astrophysics Data System (ADS)

Špiclin, Žiga; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2012-03-01

Spatial resolution of hyperspectral imaging systems can vary significantly due to axial optical aberrations that originate from wavelength-induced index-of-refraction variations of the imaging optics. For systems that have a broad spectral range, the spatial resolution will vary significantly both with respect to the acquisition wavelength and with respect to the spatial position within each spectral image. Variations of the spatial resolution can be effectively characterized as part of the calibration procedure by a local image-based estimation of the pointspread function (PSF) of the hyperspectral imaging system. The estimated PSF can then be used in the image deconvolution methods to improve the spatial resolution of the spectral images. We estimated the PSFs from the spectral images of a line grid geometric caliber. From individual line segments of the line grid, the PSF was obtained by a non-parametric estimation procedure that used an orthogonal series representation of the PSF. By using the non-parametric estimation procedure, the PSFs were estimated at different spatial positions and at different wavelengths. The variations of the spatial resolution were characterized by the radius and the fullwidth half-maximum of each PSF and by the modulation transfer function, computed from images of USAF1951 resolution target. The estimation and characterization of the PSFs and the image deconvolution based spatial resolution enhancement were tested on images obtained by a hyperspectral imaging system with an acousto-optic tunable filter in the visible spectral range. The results demonstrate that the spatial resolution of the acquired spectral images can be significantly improved using the estimated PSFs and image deconvolution methods.

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

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.

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

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.

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

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.

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

PubMed

Mishima, T; Kao, K C

1982-03-15

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

Breaking the acoustic diffraction limit via nonlinear effect and thermal confinement for potential deep-tissue high-resolution imaging

PubMed Central

Yuan, Baohong; Pei, Yanbo; Kandukuri, Jayanth

2013-01-01

Our recently developed ultrasound-switchable fluorescence (USF) imaging technique showed that it was feasible to conduct high-resolution fluorescence imaging in a centimeter-deep turbid medium. Because the spatial resolution of this technique highly depends on the ultrasound-induced temperature focal size (UTFS), minimization of UTFS becomes important for further improving the spatial resolution USF technique. In this study, we found that UTFS can be significantly reduced below the diffraction-limited acoustic intensity focal size via nonlinear acoustic effects and thermal confinement by appropriately controlling ultrasound power and exposure time, which can be potentially used for deep-tissue high-resolution imaging. PMID:23479498

Effects of daily, high spatial resolution a priori profiles of satellite-derived NOx emissions

NASA Astrophysics Data System (ADS)

Laughner, J.; Zare, A.; Cohen, R. C.

2016-12-01

The current generation of space-borne NO2 column observations provides a powerful method of constraining NOx emissions due to the spatial resolution and global coverage afforded by the Ozone Monitoring Instrument (OMI). The greater resolution available in next generation instruments such as TROPOMI and the capabilities of geosynchronous platforms TEMPO, Sentinel-4, and GEMS will provide even greater capabilities in this regard, but we must apply lessons learned from the current generation of retrieval algorithms to make the best use of these instruments. Here, we focus on the effect of the resolution of the a priori NO2 profiles used in the retrieval algorithms. We show that for an OMI retrieval, using daily high-resolution a priori profiles results in changes in the retrieved VCDs up to 40% when compared to a retrieval using monthly average profiles at the same resolution. Further, comparing a retrieval with daily high spatial resolution a priori profiles to a more standard one, we show that emissions derived increase by 100% when using the optimized retrieval.

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.

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.

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.

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.

Resolution convergence in cosmological hydrodynamical simulations using adaptive mesh refinement

NASA Astrophysics Data System (ADS)

Snaith, Owain N.; Park, Changbom; Kim, Juhan; Rosdahl, Joakim

2018-06-01

We have explored the evolution of gas distributions from cosmological simulations carried out using the RAMSES adaptive mesh refinement (AMR) code, to explore the effects of resolution on cosmological hydrodynamical simulations. It is vital to understand the effect of both the resolution of initial conditions (ICs) and the final resolution of the simulation. Lower initial resolution simulations tend to produce smaller numbers of low-mass structures. This will strongly affect the assembly history of objects, and has the same effect of simulating different cosmologies. The resolution of ICs is an important factor in simulations, even with a fixed maximum spatial resolution. The power spectrum of gas in simulations using AMR diverges strongly from the fixed grid approach - with more power on small scales in the AMR simulations - even at fixed physical resolution and also produces offsets in the star formation at specific epochs. This is because before certain times the upper grid levels are held back to maintain approximately fixed physical resolution, and to mimic the natural evolution of dark matter only simulations. Although the impact of hold-back falls with increasing spatial and IC resolutions, the offsets in the star formation remain down to a spatial resolution of 1 kpc. These offsets are of the order of 10-20 per cent, which is below the uncertainty in the implemented physics but are expected to affect the detailed properties of galaxies. We have implemented a new grid-hold-back approach to minimize the impact of hold-back on the star formation rate.

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.

Quantifying the effect of 3D spatial resolution on the accuracy of microstructural distributions

NASA Astrophysics Data System (ADS)

Loughnane, Gregory; Groeber, Michael; Uchic, Michael; Riley, Matthew; Shah, Megna; Srinivasan, Raghavan; Grandhi, Ramana

The choice of spatial resolution for experimentally-collected 3D microstructural data is often governed by general rules of thumb. For example, serial section experiments often strive to collect at least ten sections through the average feature-of-interest. However, the desire to collect high resolution data in 3D is greatly tempered by the exponential growth in collection times and data storage requirements. This paper explores the use of systematic down-sampling of synthetically-generated grain microstructures to examine the effect of resolution on the calculated distributions of microstructural descriptors such as grain size, number of nearest neighbors, aspect ratio, and Ω3.

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.

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.

High spatial resolution burn severity mapping of the New Jersey Pine Barrens with WorldView-3 near-infrared and shortwave infrared imagery

Treesearch

Timothy A. Warner; Nicholas S. Skowronski; Michael R. Gallagher

2017-01-01

The WorldView-3 (WV-3) sensor, launched in 2014, is the first highspatial resolution scanner to acquire imagery in the shortwave infrared (SWIR). A spectral ratio of the SWIR combined with the nearinfrared (NIR) can potentially provide an effective differentiation of wildfire burn severity. Previous high spatial resolution sensors were limited to data fromthe visible...

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.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

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

2013-04-01

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

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.

In-flight edge response measurements for high-spatial-resolution remote sensing systems

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Pagnutti, Mary A.; Ryan, Robert; Zanoni, Vickie

2002-09-01

In-flight measurements of spatial resolution were conducted as part of the NASA Scientific Data Purchase Verification and Validation process. Characterization included remote sensing image products with ground sample distance of 1 meter or less, such as those acquired with the panchromatic imager onboard the IKONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effects of both the image acquisition system and image post-processing. Spatial resolution was characterized by full width at half maximum of an edge-response-derived line spread function. The edge responses were analyzed using the tilted-edge technique that overcomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as tarps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. The effects of such factors as acquisition geometry, temporal variability, Modulation Transfer Function compensation, and ground sample distance on spatial resolution were investigated.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Iterative algorithm for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution

NASA Astrophysics Data System (ADS)

Quan, Haiyang; Wu, Fan; Hou, Xi

2015-10-01

New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Spatial and temporal resolution effects on urban catchments with different imperviousness degrees

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; van de Giesen, Nick C.

2015-04-01

One of the main problems in urban hydrological analysis is to measure the rainfall at urban scale with high resolution and use these measurements to model urban runoff processes to predict flows and reduce flood risk. With the aim of building a semi-distribute hydrological sewer model for an urban catchment, high resolution rainfall data are required as input. In this study, the sensitivity of hydrological response to high resolution precipitation data for hydrodynamic models at urban scale is evaluated with different combinations of spatial and temporal resolutions. The aim is to study sensitivity in relation to catchment characteristics, especially drainage area size, imperviousness degree and hydraulic properties such as special structures (weirs, pumping stations). Rainfall data of nine storms are considered with 4 different spatial resolutions (3000m, 1000m, 500m and 100m) combined with 4 different temporal resolutions (10min, 5min, 3min and 1min). The dual polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) provided the high resolution rainfall data of these rainfall events, used to improve the sewer model. The effects of spatial-temporal rainfall input resolution on response is studied in three Districts of Rotterdam (NL): Kralingen, Spaanse Polder and Centrum district. These catchments have different average drainage area size (from 2km2 to 7km2), and different general characteristics. Centrum district and Kralingen are, indeed, more various and include residential and commercial areas, big green areas and a small industrial area, while Spaanse Polder is a industrial area, densely urbanized, and presents a high percentage of imperviousness.

A COMPARISON OF ILLUMINATION GEOMETRY-BASED METHODS FOR TOPOGRAPHIC CORRECTION OF QUICKBIRD IMAGES OF AN UNDULANT AREA

USDA-ARS?s Scientific Manuscript database

The high spatial resolution of QuickBird satellite images makes it possible to show spatial variability at fine details. However, the effect of topography-induced illumination variations become more evident, even in moderately sloped areas. Based on a high resolution (1 m) digital elevation model ge...

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.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

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.

The effects of spatial sampling choices on MR temperature measurements.

PubMed

Todd, Nick; Vyas, Urvi; de Bever, Josh; Payne, Allison; Parker, Dennis L

2011-02-01

The purpose of this article is to quantify the effects that spatial sampling parameters have on the accuracy of magnetic resonance temperature measurements during high intensity focused ultrasound treatments. Spatial resolution and position of the sampling grid were considered using experimental and simulated data for two different types of high intensity focused ultrasound heating trajectories (a single point and a 4-mm circle) with maximum measured temperature and thermal dose volume as the metrics. It is demonstrated that measurement accuracy is related to the curvature of the temperature distribution, where regions with larger spatial second derivatives require higher resolution. The location of the sampling grid relative temperature distribution has a significant effect on the measured values. When imaging at 1.0 × 1.0 × 3.0 mm(3) resolution, the measured values for maximum temperature and volume dosed to 240 cumulative equivalent minutes (CEM) or greater varied by 17% and 33%, respectively, for the single-point heating case, and by 5% and 18%, respectively, for the 4-mm circle heating case. Accurate measurement of the maximum temperature required imaging at 1.0 × 1.0 × 3.0 mm(3) resolution for the single-point heating case and 2.0 × 2.0 × 5.0 mm(3) resolution for the 4-mm circle heating case. Copyright © 2010 Wiley-Liss, Inc.

Spatial resolution enhancement of terrestrial features using deconvolved SSM/I microwave brightness temperatures

NASA Technical Reports Server (NTRS)

Farrar, Michael R.; Smith, Eric A.

1992-01-01

A method for enhancing the 19, 22, and 37 GHz measurements of the SSM/I (Special Sensor Microwave/Imager) to the spatial resolution and sampling density of the high resolution 85-GHz channel is presented. An objective technique for specifying the tuning parameter, which balances the tradeoff between resolution and noise, is developed in terms of maximizing cross-channel correlations. Various validation procedures are performed to demonstrate the effectiveness of the method, which hopefully will provide researchers with a valuable tool in multispectral applications of satellite radiometer data.

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.

Cross-correlation photothermal optical coherence tomography with high effective resolution.

PubMed

Tang, Peijun; Liu, Shaojie; Chen, Junbo; Yuan, Zhiling; Xie, Bingkai; Zhou, Jianhua; Tang, Zhilie

2017-12-01

We developed a cross-correlation photothermal optical coherence tomography (CC-PTOCT) system for photothermal imaging with high lateral and axial resolution. The CC-PTOCT system consists of a phase-sensitive OCT system, a modulated pumping laser, and a digital cross-correlator. The pumping laser was used to induce the photothermal effect in the sample, causing a slight phase modulation of the OCT signals. A spatial phase differentiation method was employed to reduce phase accumulation. The noise brought by the phase differentiation method and the strong background noise were suppressed efficiently by the cross-correlator, which was utilized to extract the photothermal signals from the modulated signals. Combining the cross-correlation technique with spatial phase differentiation can improve both lateral and axial resolution of the PTOCT imaging system. Clear photothermal images of blood capillaries of a mouse ear in vivo were successfully obtained with high lateral and axial resolution. The experimental results demonstrated that this system can enhance the effective transverse resolution, effective depth resolution, and contrast of the PTOCT image effectively, aiding the ongoing development of the accurate 3D functional imaging.

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.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

High resolution simulations of aerosol microphysics in a global and regionally nested chemical transport model

NASA Astrophysics Data System (ADS)

Adams, P. J.; Marks, M.

2015-12-01

The aerosol indirect effect is the largest source of forcing uncertainty in current climate models. This effect arises from the influence of aerosols on the reflective properties and lifetimes of clouds, and its magnitude depends on how many particles can serve as cloud droplet formation sites. Assessing levels of this subset of particles (cloud condensation nuclei, or CCN) requires knowledge of aerosol levels and their global distribution, size distributions, and composition. A key tool necessary to advance our understanding of CCN is the use of global aerosol microphysical models, which simulate the processes that control aerosol size distributions: nucleation, condensation/evaporation, and coagulation. Previous studies have found important differences in CO (Chen, D. et al., 2009) and ozone (Jang, J., 1995) modeled at different spatial resolutions, and it is reasonable to believe that short-lived, spatially-variable aerosol species will be similarly - or more - susceptible to model resolution effects. The goal of this study is to determine how CCN levels and spatial distributions change as simulations are run at higher spatial resolution - specifically, to evaluate how sensitive the model is to grid size, and how this affects comparisons against observations. Higher resolution simulations are necessary supports for model/measurement synergy. Simulations were performed using the global chemical transport model GEOS-Chem (v9-02). The years 2008 and 2009 were simulated at 4ox5o and 2ox2.5o globally and at 0.5ox0.667o over Europe and North America. Results were evaluated against surface-based particle size distribution measurements from the European Supersites for Atmospheric Aerosol Research project. The fine-resolution model simulates more spatial and temporal variability in ultrafine levels, and better resolves topography. Results suggest that the coarse model predicts systematically lower ultrafine levels than does the fine-resolution model. Significant differences are also evident with respect to model-measurement comparisons, and will be discussed.

The effect of spatial resolution on water scarcity estimates in Australia

NASA Astrophysics Data System (ADS)

Gevaert, Anouk; Veldkamp, Ted; van Dijk, Albert; Ward, Philip

2017-04-01

Water scarcity is an important global issue with severe socio-economic consequences, and its occurrence is likely to increase in many regions due to population growth, economic development and climate change. This has prompted a number of global and regional studies to identify areas that are vulnerable to water scarcity and to determine how this vulnerability will change in the future. A drawback of these studies, however, is that they typically have coarse spatial resolutions. Here, we studied the effect of increasing the spatial resolution of water scarcity estimates in Australia, and the Murray-Darling Basin in particular. This was achieved by calculating the water stress index (WSI), an indicator showing the ratio of water use to water availability, at 0.5 and 0.05 degree resolution for the period 1990-2010. Monthly water availability data were based on outputs of the Australian Water Resources Assessment Landscape model (AWRA-L), which was run at both spatial resolutions and at a daily time scale. Water use information was obtained from a monthly 0.5 degree global dataset that distinguishes between water consumption for irrigation, livestock, industrial and domestic uses. The data were downscaled to 0.05 degree by dividing the sectoral water uses over the areas covered by relevant land use types using a high resolution ( 0.5km) land use dataset. The monthly WSIs at high and low resolution were then used to evaluate differences in the patterns of water scarcity frequency and intensity. In this way, we assess to what extent increasing the spatial resolution can improve the identification of vulnerable areas and thereby assist in the development of strategies to lower this vulnerability. The results of this study provide insight into the scalability of water scarcity estimates and the added value of high resolution water scarcity information in water resources management.

Taheri-Saramad x-ray detector (TSXD): a novel high spatial resolution x-ray imager based on ZnO nano scintillator wires in polycarbonate membrane.

PubMed

Taheri, A; Saramad, S; Ghalenoei, S; Setayeshi, S

2014-01-01

A novel x-ray imager based on ZnO nanowires is designed and fabricated. The proposed architecture is based on scintillation properties of ZnO nanostructures in a polycarbonate track-etched membrane. Because of higher refractive index of ZnO nanowire compared to the membrane, the nanowire acts as an optical fiber that prevents the generated optical photons to spread inside the detector. This effect improves the spatial resolution of the imager. The detection quantum efficiency and spatial resolution of the fabricated imager are 11% and <6.8 μm, respectively.

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 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

Identification of mosquito larval habitats in high resolution satellite data

NASA Astrophysics Data System (ADS)

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

2003-09-01

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

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.

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.

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

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.

Eddy Fluxes and Sensitivity of the Water Cycle to Spatial Resolution in Idealized Regional Aquaplanet Model Simulations

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

Hagos, Samson M.; Leung, Lai-Yung R.; Gustafson, William I.

2014-02-28

A multi-scale moisture budget analysis is used to identify the mechanisms responsible for the sensitivity of the water cycle to spatial resolution using idealized regional aquaplanet simulations. In the higher resolution simulations, moisture transport by eddies fluxes dry the boundary layer enhancing evaporation and precipitation. This effect of eddies, which is underestimated by the physics parameterizations in the low-resolution simulations, is found to be responsible for the sensitivity of the water cycle both directly, and through its upscale effect, on the mean circulation. Correlations among moisture transport by eddies at adjacent ranges of scales provides the potential for reducing thismore » sensitivity by representing the unresolved eddies by their marginally resolved counterparts.« less

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.

The influence of focal spot blooming on high-contrast spatial resolution in CT imaging.

PubMed

Grimes, Joshua; Duan, Xinhui; Yu, Lifeng; Halaweish, Ahmed F; Haag, Nicole; Leng, Shuai; McCollough, Cynthia

2015-10-01

The objective of this work was to investigate focal spot blooming effects on the spatial resolution of CT images and to evaluate an x-ray tube that uses dynamic focal spot control for minimizing focal spot blooming. The influence of increasing tube current at a fixed tube potential of 80 kV on high-contrast spatial resolution of seven different CT scanner models (scanners A-G), including one scanner that uses dynamic focal spot control to reduce focal spot blooming (scanner A), was evaluated. Spatial resolution was assessed using a wire phantom for the modulation transfer function (MTF) calculation and a copper disc phantom for measuring the slice sensitivity profile (SSP). The impact of varying the tube potential was investigated on two scanner models (scanners A and B) by measuring the MTF and SSP and also by using the resolution bar pattern module of the ACR CT phantom. The phantoms were scanned at 70-150 kV on scanner A and 80-140 kV on scanner B, with tube currents from 100 mA up to the maximum tube current available on each scanner. The images were reconstructed using a slice thickness of 0.6 mm with both smooth and sharp kernels. Additionally, focal spot size at varying tube potentials and currents was directly measured using pinhole and slit camera techniques. Evaluation of the MTF and SSP data from the 7 CT scanner models evaluated demonstrated decreased focal spot blooming for newer scanners, as evidenced by decreasing deviations in MTF and SSP as tube current varied. For scanners A and B, where focal spot blooming effects as a function of tube potential were assessed, the spatial resolution variation in the axial plane was much smaller on scanner A compared to scanner B as tube potential and current changed. On scanner A, the 50% MTF never decreased by more than 2% from the 50% MTF measured at 100 mA. On scanner B, the 50% MTF decreased by as much as 19% from the 50% MTF measured at 100 mA. Assessments of the SSP, the bar patterns in the ACR phantom and the pinhole and slit camera measurements were consistent with the MTF calculations. Focal spot blooming has a noticeable effect on spatial resolution in CT imaging. The focal spot shaping technology of scanner A greatly reduced blooming effects.

The feasibility study on 3-dimensional fluorescent x-ray computed tomography using the pinhole effect for biomedical applications.

PubMed

Sunaguchi, Naoki; Yuasa, Tetsuya; Hyodo, Kazuyuki; Zeniya, Tsutomu

2013-01-01

We propose a 3-dimensional fluorescent x-ray computed tomography (CT) pinhole collimator, aimed at providing molecular imaging with quantifiable measures and sub-millimeter spatial resolution. In this study, we demonstrate the feasibility of this concept and investigate imaging properties such as spatial resolution, contrast resolution and quantifiable measures, by imaging physical phantoms using a preliminary imaging system developed with monochromatic synchrotron x rays constructed at the BLNE-7A experimental line at KEK, Japan.

Four-dimensional ultrafast electron microscopy of phase transitions

PubMed Central

Grinolds, Michael S.; Lobastov, Vladimir A.; Weissenrieder, Jonas; Zewail, Ahmed H.

2006-01-01

Reported here is direct imaging (and diffraction) by using 4D ultrafast electron microscopy (UEM) with combined spatial and temporal resolutions. In the first phase of UEM, it was possible to obtain snapshot images by using timed, single-electron packets; each packet is free of space–charge effects. Here, we demonstrate the ability to obtain sequences of snapshots (“movies”) with atomic-scale spatial resolution and ultrashort temporal resolution. Specifically, it is shown that ultrafast metal–insulator phase transitions can be studied with these achieved spatial and temporal resolutions. The diffraction (atomic scale) and images (nanometer scale) we obtained manifest the structural phase transition with its characteristic hysteresis, and the time scale involved (100 fs) is now studied by directly monitoring coordinates of the atoms themselves. PMID:17130445

Limitation of Liquid Crystal on Silicon Spatial Light Modular for Holographic Three-dimensional Displays

NASA Technical Reports Server (NTRS)

Wang, Xinghua; Wang, Bin; Bos, Philip J.; Anderson, James E.; Kujawinska, Malgorzata; Pouch, John; Miranda, Feliz

2004-01-01

In a 3-D display system based on an opto-electronic reconstruction of a digitally recorded hologram, the field of view of such a system is limited by the spatial resolution of the liquid crystal on silicon (LCOS) spatial light modular (SLM) used to perform the opto-electronic reconstruction. In this article, the special resolution limitation of LCOS SLM associated with the fringe field effect and interpixel coupling is determined by the liquid crystal detector simulation and the Finite Difference Time Domain (FDTD) simulation. The diffraction efficiency loss associated with the imperfection in the phase profile is studied with an example of opto-electronic reconstruction of an amplitude object. A high spatial resolution LCOS SLM with a wide reconstruction angle is proposed.

Combined effects of levels of protection and environmental variables at different spatial resolutions on fish assemblages in a marine protected area.

PubMed

Claudet, Joachim; García-Charton, José Antonio; Lenfant, Philippe

2011-02-01

The links between species-environment relations and species' responses to protection are unclear, but the objectives of marine protected areas (MPAs) are most likely to be achieved when those relations are known and inform MPA design. The components of a species' habitat vary with the spatial resolution of the area considered. We characterized areas at two resolutions: 250 m(2) (transect) and approximately 30,000 m(2) (seascape). We considered three categories of environmental variables: substrate type, bottom complexity, and depth. We sought to determine at which resolution habitat characteristics were a better predictor of abundance and species composition of fishes and whether the relations with environmental variables at either resolution affected species' responses to protection. Habitat features accounted for a larger proportion of spatial variation in species composition and abundances than differences in protection status. This spatial variation was explained best by habitat characteristics at the seascape level than at the transect level. Species' responses to protected areas were specific to particular seascape characteristics, primarily depth, and bottom complexity. Our method may be useful for prioritizing marine areas for protection, designing MPAs, and monitoring their effectiveness. It identified areas that provided natural shelter, areas acting as buffer zones, and areas where fish species were most responsive to protection. The identification of such areas is necessary for cost-effective establishment and monitoring of MPAs. ©2010 Society for Conservation Biology.

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.

[Examination of upper abdominal region in high spatial resolution diffusion-weighted imaging using 3-Tesla MRI].

PubMed

Terada, Masaki; Matsushita, Hiroki; Oosugi, Masanori; Inoue, Kazuyasu; Yaegashi, Taku; Anma, Takeshi

2009-03-20

The advantage of the higher signal-to-noise ratio (SNR) of 3-Tesla magnetic resonance imaging (3-Tesla) has the possibility of contributing to the improvement of high spatial resolution without causing image deterioration. In this study, we compared SNR and the apparent diffusion coefficient (ADC) value with 3-Tesla as the condition in the diffusion-weighted image (DWI) parameter of the 1.5-Tesla magnetic resonance imaging (1.5-Tesla) and we examined the high spatial resolution images in the imaging method [respiratory-triggering (RT) method and breath free (BF) method] and artifact (motion and zebra) in the upper abdominal region of DWI at 3-Tesla. We have optimized scan parameters based on phantom and in vivo study. As a result, 3-Tesla was able to obtain about 1.5 times SNR in comparison with the 1.5-Tesla, ADC value had few differences. Moreover, the RT method was effective in correcting the influence of respiratory movement in comparison with the BF method, and image improvement by the effective acquisition of SNR and reduction of the artifact were provided. Thus, DWI of upper abdominal region was a useful sequence for the high spatial resolution in 3-Tesla.

Spatial attention does improve temporal discrimination.

PubMed

Chica, Ana B; Christie, John

2009-02-01

It has recently been stated that exogenous attention impairs temporal-resolution tasks (Hein, Rolke, & Ulrich, 2006; Rolke, Dinkelbach, Hein, & Ulrich, 2008; Yeshurun, 2004; Yeshurun & Levy, 2003). In comparisons of performance on spatially cued trials versus neutral cued trials, the results have suggested that spatial attention decreases temporal resolution. However, when performance on cued and uncued trials has been compared in order to equate for cue salience, typically speed-accuracy trade-offs (SATs) have been observed, making the interpretation of the results difficult. In the present experiments, we aimed at studying the effect of spatial attention in temporal resolution while using a procedure to control for SATs. We controlled reaction times (RTs) by constraining the time to respond, so that response decisions would be made within comparable time windows. The results revealed that when RT was controlled, performance was impaired for cued trials as compared with neutral trials, replicating previous findings. However, when cued and uncued trials were compared, performance was actually improved for cued trials as compared with uncued trials. These results suggest that SAT effects may have played an important role in the previous studies, because when they were controlled and measured, the results reversed, revealing that exogenous attention does improve performance on temporal-resolution tasks.

Effect of Temporal and Spatial Rainfall Resolution on HSPF Predictive Performance and Parameter Estimation

EPA Science Inventory

Watershed scale rainfall‐runoff models are used for environmental management and regulatory modeling applications, but their effectiveness are limited by predictive uncertainties associated with model input data. This study evaluated the effect of temporal and spatial rainfall re...

Experimental criteria for the determination of fractal parameters of premixed turbulent flames

NASA Astrophysics Data System (ADS)

Shepherd, I. G.; Cheng, Robert K.; Talbot, L.

1992-10-01

The influence of spatial resolution, digitization noise, the number of records used for averaging, and the method of analysis on the determination of the fractal parameters of a high Damköhler number, methane/air, premixed, turbulent stagnation-point flame are investigated in this paper. The flow exit velocity was 5 m/s and the turbulent Reynolds number was 70 based on a integral scale of 3 mm and a turbulent intensity of 7%. The light source was a copper vapor laser which delivered 20 nsecs, 5 mJ pulses at 4 kHz and the tomographic cross-sections of the flame were recorded by a high speed movie camera. The spatial resolution of the images is 155 × 121 μm/pixel with a field of view of 50 × 65 mm. The stepping caliper technique for obtaining the fractal parameters is found to give the clearest indication of the cutoffs and the effects of noise. It is necessary to ensemble average the results from more than 25 statistically independent images to reduce sufficiently the scatter in the fractal parameters. The effects of reduced spatial resolution on fractal plots are estimated by artificial degradation of the resolution of the digitized flame boundaries. The effect of pixel resolution, an apparent increase in flame length below the inner scale rolloff, appears in the fractal plots when the measurent scale is less than approximately twice the pixel resolution. Although a clearer determination of fractal parameters is obtained by local averaging of the flame boundaries which removes digitization noise, at low spatial resolution this technique can reduce the fractal dimension. The degree of fractal isotropy of the flame surface can have a significant effect on the estimation of the flame surface area and hence burning rate from two-dimensional images. To estimate this isotropy a determination of the outer cutoff is required and three-dimensional measurements are probably also necessary.

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.

Measurement of in situ sulfur isotopes by laser ablation multi-collector ICPMS: opening Pandora’s Box

USGS Publications Warehouse

Ridley, William I.; Pribil, Michael; Koenig, Alan E.; Slack, John F.

2015-01-01

Laser ablation multi-collector ICPMS is a modern tool for in situ measurement of S isotopes. Advantages of the technique are speed of analysis and relatively minor matrix effects combined with spatial resolution sufficient for many applications. The main disadvantage is a more destructive sampling mechanism relative to the ion microprobe technique. Recent advances in instrumentation allow precise measurement with spatial resolutions down to 25 microns. We describe specific examples from economic geology where increased spatial resolution has greatly expanded insights into the sources and evolution of fluids that cause mineralization and illuminated genetic relations between individual deposits in single mineral districts.

Resolution of spatial and temporal visual attention in infants with fragile X syndrome.

PubMed

Farzin, Faraz; Rivera, Susan M; Whitney, David

2011-11-01

Fragile X syndrome is the most common cause of inherited intellectual impairment and the most common single-gene cause of autism. Individuals with fragile X syndrome present with a neurobehavioural phenotype that includes selective deficits in spatiotemporal visual perception associated with neural processing in frontal-parietal networks of the brain. The goal of the current study was to examine whether reduced resolution of spatial and/or temporal visual attention may underlie perceptual deficits related to fragile X syndrome. Eye tracking was used to psychophysically measure the limits of spatial and temporal attention in infants with fragile X syndrome and age-matched neurotypically developing infants. Results from these experiments revealed that infants with fragile X syndrome experience drastically reduced resolution of temporal attention in a genetic dose-sensitive manner, but have a spatial resolution of attention that is not impaired. Coarse temporal attention could have significant knock-on effects for the development of perceptual, cognitive and motor abilities in individuals with the disorder.

Resolution of spatial and temporal visual attention in infants with fragile X syndrome

PubMed Central

Rivera, Susan M.; Whitney, David

2011-01-01

Fragile X syndrome is the most common cause of inherited intellectual impairment and the most common single-gene cause of autism. Individuals with fragile X syndrome present with a neurobehavioural phenotype that includes selective deficits in spatiotemporal visual perception associated with neural processing in frontal–parietal networks of the brain. The goal of the current study was to examine whether reduced resolution of spatial and/or temporal visual attention may underlie perceptual deficits related to fragile X syndrome. Eye tracking was used to psychophysically measure the limits of spatial and temporal attention in infants with fragile X syndrome and age-matched neurotypically developing infants. Results from these experiments revealed that infants with fragile X syndrome experience drastically reduced resolution of temporal attention in a genetic dose-sensitive manner, but have a spatial resolution of attention that is not impaired. Coarse temporal attention could have significant knock-on effects for the development of perceptual, cognitive and motor abilities in individuals with the disorder. PMID:22075522

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

PubMed

Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

2016-11-28

We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

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.

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.

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.

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.

Science and Technology Text Mining: Near-Earth Space

DTIC Science & Technology

2003-07-21

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

Estimating the effective spatial resolution of an AVHRR time series

USGS Publications Warehouse

Meyer, D.J.

1996-01-01

A method is proposed to estimate the spatial degradation of geometrically rectified AVHRR data resulting from misregistration and off-nadir viewing, and to infer the cumulative effect of these degradations over time. Misregistrations are measured using high resolution imagery as a geometric reference, and pixel sizes are computed directly from satellite zenith angles. The influence or neighbouring features on a nominal 1 km by 1 km pixel over a given site is estimated from the above information, and expressed as a spatial distribution whose spatial frequency response is used to define an effective field-of-view (EFOV) for a time series. In a demonstration of the technique applied to images from the Conterminous U.S. AVHRR data set, an EFOV of 3·1km in the east-west dimension and 19 km in the north-south dimension was estimated for a time series accumulated over a grasslands test site.

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.

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 New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

Electro-optical design of a long slit streak tube

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

USGS Publications Warehouse

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

2013-01-01

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

Design and performance of a high spatial resolution, time-of-flight PET detector

PubMed Central

Krishnamoorthy, Srilalan; LeGeyt, Benjamin; Werner, Matthew E.; Kaul, Madhuri; Newcomer, F. M.; Karp, Joel S.; Surti, Suleman

2014-01-01

This paper describes the design and performance of a high spatial resolution PET detector with time-of-flight capabilities. With an emphasis on high spatial resolution and sensitivity, we initially evaluated the performance of several 1.5 × 1.5 and 2.0 × 2.0 mm2 and 12–15 mm long LYSO crystals read out by several appropriately sized PMTs. Experiments to evaluate the impact of reflector on detector performance were performed and the final detector consisted of a 32 × 32 array of 1.5 × 1.5 × 15 mm3 LYSO crystals packed with a diffuse reflector and read out by a single Hamamatsu 64 channel multi-anode PMT. Such a design made it compact, modular and offered a cost-effective solution to obtaining excellent energy and timing resolution. To minimize the number of readout signals, a compact front-end readout electronics that summed anode signals along each of the orthogonal directions was also developed. Experimental evaluation of detector performance demonstrates clear discrimination of the crystals within the detector. An average energy resolution (FWHM) of 12.7 ± 2.6% and average coincidence timing resolution (FWHM) of 348 ps was measured, demonstrating suitability for use in the development of a high spatial resolution time-of-flight scanner for dedicated breast PET imaging. PMID:25246711

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.

Limits of a spatial resolution of the cascaded GEM based detectors

NASA Astrophysics Data System (ADS)

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

2017-06-01

Spatial resolution of tracking detectors based on GEM cascades is determined in the simulation and measured. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing taking into account diffusion, gas amplification fluctuations, the distribution of signals over readout electrodes, electronics noise and particular algorithm of final coordinate calculation (centre-of-gravity algorithm). The simulation demonstrates that the minimum of the spatial resolution of about 10-20 μm can be achieved with a gas mixture of Ar-CO2 (75%-25%) at a strip pitch in the range from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 70-100 μm at a pitch of 450-500 μm. The reasons of such behavior are discussed and corresponding hypothesis is tested. Particularly, the effect of electron cloud modification due to a GEM operation is considered using the ANSYS and Garfield++ simulation programs. The detection efficiency and spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at BINP are measured at the extracted beam facility of the VEPP-4M collider. One-coordinate resolution of two detectors for the DEUTERON facility is measured with a 2 GeV electron beam. The determined values of the detectors' spatial resolution is equal to 46.6 ± 0.1 μm and 38.5 ± 0.2 μm for orthogonal tracks in two detectors, respectively.

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.

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

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.

SPATIAL PATTERNS OF WATER QUALITY AND PLANKTON FROM HIGH-RESOLUTION CONTINUOUS IN SITU SENSING ALONG A 537-KM NEARSHORE TRANSECT OF WESTERN LAKE SUPERIOR, 2004

EPA Science Inventory

A demonstration that the adaptation of electronic instrumentation and towed survey strategies are effective in providing rapid, spatially extensive, and cost effective data for assessment of the Great Lakes.

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.

Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data

PubMed Central

Matej, Samuel; Li, Yusheng; Panetta, Joseph; Karp, Joel S.; Surti, Suleman

2016-01-01

The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake bias in the reconstructed image, the second one with the spatially variant and accurate PSF shape model is also able to ameliorate the spatially variant deformation effects to provide consistent uptake results independent of the lesion location within the FOV. PMID:27812222

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

PubMed

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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.

Topographic correction realization based on the CBERS-02B image

NASA Astrophysics Data System (ADS)

Qin, Hui-ping; Yi, Wei-ning; Fang, Yong-hua

2011-08-01

The special topography of mountain terrain will induce the retrieval distortion in same species and surface spectral lines. In order to improve the research accuracy of topographic surface characteristic, many researchers have focused on topographic correction. Topographic correction methods can be statistical-empirical model or physical model, in which the methods based on the digital elevation model data are most popular. Restricted by spatial resolution, previous model mostly corrected topographic effect based on Landsat TM image, whose spatial resolution is 30 meter that can be easily achieved from internet or calculated from digital map. Some researchers have also done topographic correction based on high spatial resolution images, such as Quickbird and Ikonos, but there is little correlative research on the topographic correction of CBERS-02B image. In this study, liao-ning mountain terrain was taken as the objective. The digital elevation model data was interpolated to 2.36 meter by 15 meter original digital elevation model one meter by one meter. The C correction, SCS+C correction, Minnaert correction and Ekstrand-r were executed to correct the topographic effect. Then the corrected results were achieved and compared. The images corrected with C correction, SCS+C correction, Minnaert correction and Ekstrand-r were compared, and the scatter diagrams between image digital number and cosine of solar incidence angel with respect to surface normal were shown. The mean value, standard variance, slope of scatter diagram, and separation factor were statistically calculated. The analysed result shows that the shadow is weakened in corrected images than the original images, and the three-dimensional affect is removed. The absolute slope of fitting lines in scatter diagram is minished. Minnaert correction method has the most effective result. These demonstrate that the former correction methods can be successfully adapted to CBERS-02B images. The DEM data can be interpolated step by step to get the corresponding spatial resolution approximately for the condition that high spatial resolution elevation data is hard to get.

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Gas scintillation glass GEM detector for high-resolution X-ray imaging and CT

NASA Astrophysics Data System (ADS)

Fujiwara, T.; Mitsuya, Y.; Fushie, T.; Murata, K.; Kawamura, A.; Koishikawa, A.; Toyokawa, H.; Takahashi, H.

2017-04-01

A high-spatial-resolution X-ray-imaging gaseous detector has been developed with a single high-gas-gain glass gas electron multiplier (G-GEM), scintillation gas, and optical camera. High-resolution X-ray imaging of soft elements is performed with a spatial resolution of 281 μm rms and an effective area of 100×100 mm. In addition, high-resolution X-ray 3D computed tomography (CT) is successfully demonstrated with the gaseous detector. It shows high sensitivity to low-energy X-rays, which results in high-contrast radiographs of objects containing elements with low atomic numbers. In addition, the high yield of scintillation light enables fast X-ray imaging, which is an advantage for constructing CT images with low-energy X-rays.

Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Kenward, T.; Lettenmaier, D. P.

1997-01-01

The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

The Effect Of Pixel Size On The Detection Rate Of Early Pulmonary Sarcoidosis In Digital Chest Radiographic Systems

NASA Astrophysics Data System (ADS)

MacMahon, Heber; Vyborny, Carl; Powell, Gregory; Doi, Kunio; Metz, Charles E.

1984-08-01

In digital radiography the pixel size used determines the potential spatial resolution of the system. The need for spatial resolution varies depending on the subject matter imaged. In many areas, including the chest, the minimum spatial resolution requirements have not been determined. Sarcoidosis is a disease which frequently causes subtle interstitial infiltrates in the lungs. As the initial step in an investigation designed to determine the minimum pixel size required in digital chest radiographic systems, we have studied 1 mm pixel digitized images on patients with early pulmonary sarcoidosis. The results of this preliminary study suggest that neither mild interstitial pulmonary infiltrates nor other abnormalities such as pneumothoraces may be detected reliably with 1 mm pixel digital images.

Physical effects of mechanical design parameters on photon sensitivity and spatial resolution performance of a breast-dedicated PET system.

PubMed

Spanoudaki, V C; Lau, F W Y; Vandenbroucke, A; Levin, C S

2010-11-01

This study aims to address design considerations of a high resolution, high sensitivity positron emission tomography scanner dedicated to breast imaging. The methodology uses a detailed Monte Carlo model of the system structures to obtain a quantitative evaluation of several performance parameters. Special focus was given to the effect of dense mechanical structures designed to provide mechanical robustness and thermal regulation to the minuscule and temperature sensitive detectors. For the energies of interest around the photopeak (450-700 keV energy window), the simulation results predict a 6.5% reduction in the single photon detection efficiency and a 12.5% reduction in the coincidence photon detection efficiency in the case that the mechanical structures are interspersed between the detectors. However for lower energies, a substantial increase in the number of detected events (approximately 14% and 7% for singles at a 100-200 keV energy window and coincidences at a lower energy threshold of 100 keV, respectively) was observed with the presence of these structures due to backscatter. The number of photon events that involve multiple interactions in various crystal elements is also affected by the presence of the structures. For photon events involving multiple interactions among various crystal elements, the coincidence photon sensitivity is reduced by as much as 20% for a point source at the center of the field of view. There is no observable effect on the intrinsic and the reconstructed spatial resolution and spatial resolution uniformity. Mechanical structures can have a considerable effect on system sensitivity, especially for systems processing multi-interaction photon events. This effect, however, does not impact the spatial resolution. Various mechanical structure designs are currently under evaluation in order to achieve optimum trade-off between temperature stability, accurate detector positioning, and minimum influence on system performance.

Physical effects of mechanical design parameters on photon sensitivity and spatial resolution performance of a breast-dedicated PET system

PubMed Central

Spanoudaki, V. C.; Lau, F. W. Y.; Vandenbroucke, A.; Levin, C. S.

2010-01-01

Purpose: This study aims to address design considerations of a high resolution, high sensitivity positron emission tomography scanner dedicated to breast imaging. Methods: The methodology uses a detailed Monte Carlo model of the system structures to obtain a quantitative evaluation of several performance parameters. Special focus was given to the effect of dense mechanical structures designed to provide mechanical robustness and thermal regulation to the minuscule and temperature sensitive detectors. Results: For the energies of interest around the photopeak (450–700 keV energy window), the simulation results predict a 6.5% reduction in the single photon detection efficiency and a 12.5% reduction in the coincidence photon detection efficiency in the case that the mechanical structures are interspersed between the detectors. However for lower energies, a substantial increase in the number of detected events (approximately 14% and 7% for singles at a 100–200 keV energy window and coincidences at a lower energy threshold of 100 keV, respectively) was observed with the presence of these structures due to backscatter. The number of photon events that involve multiple interactions in various crystal elements is also affected by the presence of the structures. For photon events involving multiple interactions among various crystal elements, the coincidence photon sensitivity is reduced by as much as 20% for a point source at the center of the field of view. There is no observable effect on the intrinsic and the reconstructed spatial resolution and spatial resolution uniformity. Conclusions: Mechanical structures can have a considerable effect on system sensitivity, especially for systems processing multi-interaction photon events. This effect, however, does not impact the spatial resolution. Various mechanical structure designs are currently under evaluation in order to achieve optimum trade-off between temperature stability, accurate detector positioning, and minimum influence on system performance. PMID:21158296

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

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.

Monitoring Cyanobacteria Bloom in Taihu Lake by High-Resolution Geostationary Satellite GF4

NASA Astrophysics Data System (ADS)

Liu, J.

2018-04-01

The high-resolution remote-sensing satellite, GF4 PMS, of China's geosynchronous earth orbit was successfully launched on December 29, 2015. Its high spatial resolution and high temporal resolution allow GF4 PMS to play a very important role in water environment monitoring, especially in the dynamic monitoring of lake and reservoir cyanobacteria blooms. As GF4 PMS has just been launched, there is still relatively little related research, and the practical application effect of GF4 PMS in the extraction of cyanobacteria blooms remains to be further tested. Therefore, in this study, the method and effect of GF4 PMS application in cyanobacteria bloom monitoring were studied in Taihu. It turned that GF4 PMS can be applied to the dynamic monitoring of the distribution of cyanobacteria blooms in Taihu, thereby finding the temporal and spatial variation of the distribution of cyanobacteria blooms.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Effects of finite spatial resolution on quantitative CBF images from dynamic PET

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

Phelps, M.E.; Huang, S.C.; Mahoney, D.K.

1985-05-01

The finite spatial resolution of PET causes the time-activity responses on pixels around the boundaries between gray and white matter regions to contain kinetic components from tissues of different CBF's. CBF values estimated from kinetics of such mixtures are underestimated because of the nonlinear relationship between the time-activity response and the estimated CBF. Computer simulation is used to investigate these effects on phantoms of circular structures and realistic brain slice in terms of object size and quantitative CBF values. The CBF image calculated is compared to the case of having resolution loss alone. Results show that the size of amore » high flow region in the CBF image is decreased while that of a low flow region is increased. For brain phantoms, the qualitative appearance of CBF images is not seriously affected, but the estimated CBF's are underestimated by 11 to 16 percent in local gray matter regions (of size 1 cm/sup 2/) with about 14 percent reduction in global CBF over the whole slice. It is concluded that the combined effect of finite spatial resolution and the nonlinearity in estimating CBF from dynamic PET is quite significant and must be considered in processing and interpreting quantitative CBF images.« less

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

PubMed

Wang, Haoyu; Miao, Yanwei; Zhou, Kun; Yu, Yanming; Bao, Shanglian; He, Qiang; Dai, Yongming; Xuan, Stephanie Y; Tarabishy, Bisher; Ye, Yongquan; Hu, Jiani

2010-09-01

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Correcting the effect of refraction and dispersion of light in FT-IR spectroscopic imaging in transmission through thick infrared windows.

PubMed

Chan, K L Andrew; Kazarian, Sergei G

2013-01-15

Transmission mode is one of the most common sampling methods for FT-IR spectroscopic imaging because the spectra obtained generally have a reasonable signal-to-noise ratio. However, dispersion and refraction of infrared light occurs when samples are sandwiched between infrared windows or placed underneath a layer of liquid. Dispersion and refraction cause infrared light to focus with different focal lengths depending on the wavelength (wavenumber) of the light. As a result, images obtained are in focus only at a particular wavenumber while they are defocused at other wavenumber values. In this work, a solution to correct this spread of focus by means of adding a lens on top of the infrared transparent window, such that a pseudo hemisphere is formed, has been investigated. Through this lens (or pseudo hemisphere), refraction of light is removed and the light across the spectral range has the same focal depth. Furthermore, the lens acts as a solid immersion objective and an increase of both magnification and spatial resolution (by 1.4 times) is demonstrated. The spatial resolution was investigated using an USAF resolution target, showing that the Rayleigh criterion can be achieved, as well as a sample with a sharp polymer interface to indicate the spatial resolution that can be expected in real samples. The reported approach was used to obtain chemical images of cross sections of cancer tissue and hair samples sandwiched between infrared windows showing the versatility and applicability of the method. In addition to the improved spatial resolution, the results reported herein also demonstrate that the lens can reduce the effect of scattering near the edges of tissue samples. The advantages of the presented approach, obtaining FT-IR spectroscopic images in transmission mode with the same focus across all wavenumber values and simultaneous improvement in spatial resolution, will have wide implications ranging from studies of live cells to sorption of drugs into tissues.

Effect of subaperture beamforming on phase coherence imaging.

PubMed

Hasegawa, Hideyuki; Kanai, Hiroshi

2014-11-01

High-frame-rate echocardiography using unfocused transmit beams and parallel receive beamforming is a promising method for evaluation of cardiac function, such as imaging of rapid propagation of vibration of the heart wall resulting from electrical stimulation of the myocardium. In this technique, high temporal resolution is realized at the expense of spatial resolution and contrast. The phase coherence factor has been developed to improve spatial resolution and contrast in ultrasonography. It evaluates the variance in phases of echo signals received by individual transducer elements after delay compensation, as in the conventional delay-andsum beamforming process. However, the phase coherence factor suppresses speckle echoes because phases of speckle echoes fluctuate as a result of interference of echoes. In the present study, the receiving aperture was divided into several subapertures, and conventional delay-and-sum beamforming was performed with respect to each subaperture to suppress echoes from scatterers except for that at a focal point. After subaperture beamforming, the phase coherence factor was obtained from beamformed RF signals from respective subapertures. By means of this procedure, undesirable echoes, which can interfere with the echo from a focal point, can be suppressed by subaperture beamforming, and the suppression of the phase coherence factor resulting from phase fluctuation caused by such interference can be avoided. In the present study, the effect of subaperture beamforming in high-frame-rate echocardiography with the phase coherence factor was evaluated using a phantom. By applying subaperture beamforming, the average intensity of speckle echoes from a diffuse scattering medium was significantly higher (-39.9 dB) than that obtained without subaperture beamforming (-48.7 dB). As for spatial resolution, the width at half-maximum of the lateral echo amplitude profile obtained without the phase coherence factor was 1.06 mm. By using the phase coherence factor, spatial resolution was improved significantly, and subaperture beamforming achieved a better spatial resolution of 0.75 mm than that of 0.78 mm obtained without subaperture beamforming.

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.

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

A High-Resolution Aerosol Retrieval Method for Urban Areas Using MISR Data

NASA Astrophysics Data System (ADS)

Moon, T.; Wang, Y.; Liu, Y.; Yu, B.

2012-12-01

Satellite-retrieved Aerosol Optical Depth (AOD) can provide a cost-effective way to monitor particulate air pollution without using expensive ground measurement sensors. One of the current state-of-the-art AOD retrieval method is NASA's Multi-angle Imaging SpectroRadiometer (MISR) operational algorithm, which has the spatial resolution of 17.6 km x 17.6 km. While the MISR baseline scheme already leads to exciting research opportunities to study particle compositions at regional scale, its spatial resolution is too coarse for analyzing urban areas where the AOD level has stronger spatial variations. We develop a novel high-resolution AOD retrieval algorithm that still uses MISR's radiance observations but has the resolution of 4.4km x 4.4km. We achieve the high resolution AOD retrieval by implementing a hierarchical Bayesian model and Monte-Carlo Markov Chain (MCMC) inference method. Our algorithm not only improves the spatial resolution, but also extends the coverage of AOD retrieval and provides with additional composition information of aerosol components that contribute to the AOD. We validate our method using the recent NASA's DISCOVER-AQ mission data, which contains the ground measured AOD values for Washington DC and Baltimore area. The validation result shows that, compared to the operational MISR retrievals, our scheme has 41.1% more AOD retrieval coverage for the DISCOVER-AQ data points and 24.2% improvement in mean-squared error (MSE) with respect to the AERONET ground measurements.

Estimating Carbon Storage and Sequestration by Urban Trees at Multiple Spatial Resolutions

NASA Astrophysics Data System (ADS)

Wu, J.; Tran, A.; Liao, A.

2010-12-01

Urban forests are an important component of urban-suburban environments. Urban trees provide not only a full range of social and psychological benefits to city dwellers, but also valuable ecosystem services to communities, such as removing atmospheric carbon dioxide, improving air quality, and reducing storm water runoff. There is an urgent need for developing strategic conservation plans for environmentally sustainable urban-suburban development based on the scientific understanding of the extent and function of urban forests. However, several challenges remain to accurately quantify various environmental benefits provided by urban trees, among which is to deal with the effect of changing spatial resolution and/or scale. In this study, we intended to examine the uncertainties of carbon storage and sequestration associated with the tree canopy coverage of different spatial resolutions. Multi-source satellite imagery data were acquired for the City of Fullerton, located in Orange County of California. The tree canopy coverage of the study area was classified at three spatial resolutions, ranging from 30 m (Landsat-5 Thematic Mapper), 15 m (Advanced Spaceborne Thermal Emission and Reflection Radiometer), to 2.5 m (QuickBird). We calculated the amount of carbon stored in the trees represented on the individual tree coverage maps and the annual carbon taken up by the trees with a model (i.e., CITYgreen) developed by the U.S. Forest Service. The results indicate that urban trees account for significant proportions of land cover in the study area even with the low spatial resolution data. The estimated carbon fixation benefits vary greatly depending on the details of land use and land cover classification. The extrapolation of estimation from the fine-resolution stand-level to the low-resolution landscape-scale will likely not preserve reasonable accuracy.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

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

LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

NASA Astrophysics Data System (ADS)

Li, Yusheng; Matej, Samuel; Karp, Joel S.; Metzler, Scott D.

2015-01-01

Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which can have significant implications in preclinical and clinical ROI imaging applications.

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

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

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

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

1991-01-01

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

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.

Impacting the effect of fMRI noise through hardware and acquisition choices - Implications for controlling false positive rates.

PubMed

Wald, Lawrence L; Polimeni, Jonathan R

2017-07-01

We review the components of time-series noise in fMRI experiments and the effect of image acquisition parameters on the noise. In addition to helping determine the total amount of signal and noise (and thus temporal SNR), the acquisition parameters have been shown to be critical in determining the ratio of thermal to physiological induced noise components in the time series. Although limited attention has been given to this latter metric, we show that it determines the degree of spatial correlations seen in the time-series noise. The spatially correlations of the physiological noise component are well known, but recent studies have shown that they can lead to a higher than expected false-positive rate in cluster-wise inference based on parametric statistical methods used by many researchers. Based on understanding the effect of acquisition parameters on the noise mixture, we propose several acquisition strategies that might be helpful reducing this elevated false-positive rate, such as moving to high spatial resolution or using highly-accelerated acquisitions where thermal sources dominate. We suggest that the spatial noise correlations at the root of the inflated false-positive rate problem can be limited with these strategies, and the well-behaved spatial auto-correlation functions (ACFs) assumed by the conventional statistical methods are retained if the high resolution data is smoothed to conventional resolutions. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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

PubMed

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Cone-beam micro computed tomography dedicated to the breast.

PubMed

Sarno, Antonio; Mettivier, Giovanni; Di Lillo, Francesca; Cesarelli, Mario; Bifulco, Paolo; Russo, Paolo

2016-12-01

We developed a scanner for micro computed tomography dedicated to the breast (BµCT) with a high resolution flat-panel detector and a microfocus X-ray tube. We evaluated the system spatial resolution via the 3D modulation transfer function (MTF). In addition to conventional absorption-based X-ray imaging, such a prototype showed capabilities for propagation-based phase-contrast and related edge enhancement effects in 3D imaging. The system limiting spatial resolution is 6.2mm -1 (MTF at 10%) in the vertical direction and 3.8mm -1 in the radial direction, values which compare favorably with the spatial resolution reached by mini focus breast CT scanners of other groups. The BµCT scanner was able to detect both microcalcification clusters and masses in an anthropomorphic breast phantom at a dose comparable to that of two-view mammography. The use of a breast holder is proposed in order to have 1-2min long scan times without breast motion artifacts. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Design and commissioning of an aberration-corrected ultrafast spin-polarized low energy electron microscope with multiple electron sources.

PubMed

Wan, Weishi; Yu, Lei; Zhu, Lin; Yang, Xiaodong; Wei, Zheng; Liu, Jefferson Zhe; Feng, Jun; Kunze, Kai; Schaff, Oliver; Tromp, Ruud; Tang, Wen-Xin

2017-03-01

We describe the design and commissioning of a novel aberration-corrected low energy electron microscope (AC-LEEM). A third magnetic prism array (MPA) is added to the standard AC-LEEM with two prism arrays, allowing the incorporation of an ultrafast spin-polarized electron source alongside the standard cold field emission electron source, without degrading spatial resolution. The high degree of symmetries of the AC-LEEM are utilized while we design the electron optics of the ultrafast spin-polarized electron source, so as to minimize the deleterious effect of time broadening, while maintaining full control of electron spin. A spatial resolution of 2nm and temporal resolution of 10ps (ps) are expected in the future time resolved aberration-corrected spin-polarized LEEM (TR-AC-SPLEEM). The commissioning of the three-prism AC-LEEM has been successfully finished with the cold field emission source, with a spatial resolution below 2nm. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial resolution measurements of the advanced radiographic capability x-ray imaging system at energies relevant to Compton radiography

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

Hall, G. N.; Izumi, N.; Landen, O. L.

2016-08-03

Compton radiography provides a means to measure the integrity, ρR and symmetry of the DT fuel in an inertial confinement fusion implosion near peak compression. Upcoming experiments at the National Ignition Facility will use the ARC (Advanced Radiography Capability) laser to drive backlighter sources for Compton radiography experiments, and will use the newly commissioned AXIS (ARC X-ray Imaging System) instrument as the detector. AXIS uses a dual-MCP (micro channel plate) to provide gating and high DQE at the 40–200keV x-ray range required for Compton radiography, but introduces many effects that contribute to the spatial resolution. Here, experiments were performed atmore » energies relevant to Compton radiography to begin characterization of the spatial resolution of the AXIS diagnostic.« less

Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

NASA Astrophysics Data System (ADS)

Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

2018-04-01

Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

Virtual strain gage size study

DOE PAGES

Reu, Phillip L.

2015-09-22

DIC is a non-linear low-pass spatial filtering operation; whether we consider the effect of the subset and shape function, the strain window used in the strain calculation, of other post-processing of the results, each decision will impact the spatial resolution, of the measurement. More fundamentally, the speckle size limits, the spatial resolution by dictating the smallest possible subset. After this decision the processing settings are controlled by the allowable noise level balanced by possible bias errors created by the data filtering. This article describes a process to determine optimum DIC software settings to determine if the peak displacements or strainsmore » are being found.« less

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.

FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

Treesearch

Russell A. Parsons

2006-01-01

Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...

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.

Applications of high resolution rainfall radar data to quantify water temperature dynamics in urban catchments

NASA Astrophysics Data System (ADS)

Croghan, Danny; Van Loon, Anne; Bradley, Chris; Sadler, Jon; Hannnah, David

2017-04-01

Studies relating rainfall events to river water quality are frequently hindered by the lack of high resolution rainfall data. Local studies are particularly vulnerable due to the spatial variability of precipitation, whilst studies in urban environments require precipitation data at high spatial and temporal resolutions. The use of point-source data makes identifying causal effects of storms on water quality problematic and can lead to erroneous interpretations. High spatial and temporal resolution rainfall radar data offers great potential to address these issues. Here we use rainfall radar data with a 1km spatial resolution and 5 minute temporal resolution sourced from the UK Met Office Nimrod system to study the effects of storm events on water temperature (WTemp) in Birmingham, UK. 28 WTemp loggers were placed over 3 catchments on a rural-urban land use gradient to identify trends in WTemp during extreme events within urban environments. Using GIS, the catchment associated with each logger was estimated, and 5 min. rainfall totals and intensities were produced for each sub-catchment. Comparisons of rainfall radar data to meteorological stations in the same grid cell revealed the high accuracy of rainfall radar data in our catchments (<5% difference for studied months). The rainfall radar data revealed substantial differences in rainfall quantity between the three adjacent catchments. The most urban catchment generally received more rainfall, with this effect greatest in the highest intensity storms, suggesting the possibility of urban heat island effects on precipitation dynamics within the catchment. Rainfall radar data provided more accurate sub-catchment rainfall totals allowing better modelled estimates of storm flow, whilst spatial fluctuations in both discharge and WTemp can be simply related to precipitation intensity. Storm flow inputs for each sub-catchment were estimated and linked to changes in WTemp. WTemp showed substantial fluctuations (>1 °C) over short durations (<30 minutes) during storm events in urbanised sub-catchments, however WTemp recovery times were more prolonged. Use of the rainfall radar data allowed increased accuracy in estimates of storm flow timings and rainfall quantities at each sub-catchment, from which the impact of storm flow on WTemp could be quantified. We are currently using the radar data to derive thresholds for rainfall amount and intensity at which these storm deviations occur for each logger, from which the relative effects of land use and other catchment characteristics in each sub-catchment can be assessed. Our use of the rainfall radar data calls into question the validity of using station based data for small scale studies, particularly in urban areas, with high variation apparent in rainfall intensity both spatially and temporally. Variation was particularly high within the heavily urbanised catchment. For water quality studies, high resolution rainfall radar can be implemented to increase the reliability of interpretations of the response of water quality variables to storm water inputs in urban catchments.

Longitudinal spatial coherence gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination

NASA Astrophysics Data System (ADS)

Mehta, Dalip Singh; Ahmad, Azeem; Dubey, Vishesh; Singh, Veena; Butola, Ankit; Mohanty, Tonmoy; Nandi, Sreyankar

2018-02-01

We report longitudinal spatial coherence (LSC) gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination using laser as a light source. To accomplish this a pseudo thermal light source was synthesized by passing laser beams through an optical system, which is basically a speckle reduction system with combined effect of spatial, temporal, angular and polarisation diversity. The longitudinal spatial coherence length of such light was significantly reduced by synthesizing a pseudo thermal source with the combined effect of spatial, angular and temporal diversity. This results in a low spatially coherent (i.e., broad angular frequency spectrum) light source with narrow temporal frequency spectrum. Light from such a pseudo thermal light source was passed through an interference microscope with varying magnification, such as, 10X and 50X. The interference microscope was used for full-field OCT imaging of multilayer objects and topography of industrial objects. Experimental results of optical sectioning of multilayer biological objects with high axial-resolution less than 10μm was achieved which is comparable to broadband white light source. The synthesized light source with reduced speckles having uniform illumination on the sample, which can be very useful for fluorescence microscopy as well as quantitative phase microscopy with less phase noise. The present system does not require any dispersion compensation optical system for biological samples as a highly monochromatic light source is used.

High cognitive reserve is associated with a reduced age-related deficit in spatial conflict resolution

PubMed Central

Puccioni, Olga; Vallesi, Antonino

2012-01-01

Several studies support the existence of a specific age-related difficulty in suppressing potentially distracting information. The aim of the present study is to investigate whether spatial conflict resolution is selectively affected by aging. The way aging affects individuals could be modulated by many factors determined by the socieconomic status: we investigated whether factors such as cognitive reserve (CR) and years of education may play a compensatory role against age-related deficits in the spatial domain. A spatial Stroop task with no feature repetitions was administered to a sample of 17 non-demented older adults (69–79 years-old) and 18 younger controls (18–34 years-old) matched for gender and years of education. The two age groups were also administered with measures of intelligence and CR. The overall spatial Stroop effect did not differ according to age, neither for speed nor for accuracy. The two age groups equally showed sequential effects for congruent trials: reduced response times (RTs) if another congruent trial preceded them, and accuracy at ceiling. For incongruent trials, older adults, but not younger controls, were influenced by congruency of trialn−1, since RTs increased with preceding congruent trials. Interestingly, such an age-related modulation negatively correlated with CR. These findings suggest that spatial conflict resolution in aging is predominantly affected by general slowing, rather than by a more specific deficit. However, a high level of CR seems to play a compensatory role for both factors. PMID:23248595

Visually Lossless JPEG 2000 for Remote Image Browsing

PubMed Central

Oh, Han; Bilgin, Ali; Marcellin, Michael

2017-01-01

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of (spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting (multiple) quantization step sizes into a single JPEG2000 codestream. This codestream is JPEG2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG2000 Interactive Protocol (JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results. PMID:28748112

High-resolution measurements of the spatial and temporal evolution of megagauss magnetic fields created in intense short-pulse laser-plasma interactions

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

Chatterjee, Gourab, E-mail: gourab@tifr.res.in; Singh, Prashant Kumar; Adak, Amitava

A pump-probe polarimetric technique is demonstrated, which provides a complete, temporally and spatially resolved mapping of the megagauss magnetic fields generated in intense short-pulse laser-plasma interactions. A normally incident time-delayed probe pulse reflected from its critical surface undergoes a change in its ellipticity according to the magneto-optic Cotton-Mouton effect due to the azimuthal nature of the ambient self-generated megagauss magnetic fields. The temporal resolution of the magnetic field mapping is typically of the order of the pulsewidth, limited by the laser intensity contrast, whereas a spatial resolution of a few μm is achieved by this optical technique. High-harmonics of themore » probe can be employed to penetrate deeper into the plasma to even near-solid densities. The spatial and temporal evolution of the megagauss magnetic fields at the target front as well as at the target rear are presented. The μm-scale resolution of the magnetic field mapping provides valuable information on the filamentary instabilities at the target front, whereas probing the target rear mirrors the highly complex fast electron transport in intense laser-plasma interactions.« less

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

Effect of horizontal resolution on meteorology and air-quality prediction with a regional scale model

NASA Astrophysics Data System (ADS)

Varghese, Saji; Langmann, Baerbel; Ceburnis, Darius; O'Dowd, Colin D.

2011-08-01

Horizontal resolution sensitivity can significantly contribute to the uncertainty in predictions of meteorology and air-quality from a regional climate model. In the study presented here, a state-of-the-art regional scale atmospheric climate-chemistry-aerosol model REMOTE is used to understand the influence of spatial model resolutions of 1.0°, 0.5° and 0.25° on predicted meteorological and aerosol parameters for June 2003 for the European domain comprising North-east Atlantic and Western Europe. Model precipitation appears to improve with resolution while wind speed has shown best results for 0.25° resolution for most of the stations compared with ECAD data. Low root mean square error and spatial bias for surface pressure, precipitation and surface temperature show that the model is very reliable. Spatial and temporal variation in black carbon, primary organic carbon, sea-salt and sulphate concentrations and their burden are presented. In most cases, chemical species concentrations at the surface show no particular trend or improvement with increase in resolution. There has been a pronounced influence of horizontal resolution on the vertical distribution pattern of some aerosol species. Some of these effects are due to the improvement in topographical details, flow characteristics and associated vertical and horizontal dynamic processes. The different sink processes have contributed very differently to the various aerosol species in terms of deposition (wet and dry) and sedimentation which are strongly linked to the meteorological processes. Overall, considering the performance of meteorological parameters and chemical species concentrations, a horizontal model resolution of 0.5° is suggested to achieve reasonable results within the limitations of this model.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance.

PubMed

Li, Ke; Garrett, John; Ge, Yongshuai; Chen, Guang-Hong

2014-07-01

Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDIvol =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo(®), GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d'. (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

[The optimizing design and experiment for a MOEMS micro-mirror spectrometer].

PubMed

Mo, Xiang-xia; Wen, Zhi-yu; Zhang, Zhi-hai; Guo, Yuan-jun

2011-12-01

A MOEMS micro-mirror spectrometer, which uses micro-mirror as a light switch so that spectrum can be detected by a single detector, has the advantages of transforming DC into AC, applying Hadamard transform optics without additional template, high pixel resolution and low cost. In this spectrometer, the vital problem is the conflict between the scales of slit and the light intensity. Hence, in order to improve the resolution of this spectrometer, the present paper gives the analysis of the new effects caused by micro structure, and optimal values of the key factors. Firstly, the effects of diffraction limitation, spatial sample rate and curved slit image on the resolution of the spectrum were proposed. Then, the results were simulated; the key values were tested on the micro mirror spectrometer. Finally, taking all these three effects into account, this micro system was optimized. With a scale of 70 mm x 130 mm, decreasing the height of the image at the plane of micro mirror can not diminish the influence of curved slit image in the spectrum; under the demand of spatial sample rate, the resolution must be twice over the pixel resolution; only if the width of the slit is 1.818 microm and the pixel resolution is 2.2786 microm can the spectrometer have the best performance.

A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

2016-05-01

Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a range of plant development stages. Overall, STEM-LAI represents an effective downscaling and temporal enhancement mechanism that predicts in-situ measured LAI better than estimates derived through linear interpolation between Landsat acquisitions. This is particularly true when the in-situ measurement date is greater than 10 days from the nearest Landsat acquisition, with prediction errors reduced by up to 50%. With a streamlined and completely automated processing interface, STEM-LAI represents a flexible tool for LAI disaggregation in space and time that is adaptable to different land cover types, landscape heterogeneities, and cloud cover conditions.

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

USDA-ARS?s Scientific Manuscript database

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

Effects of model spatial resolution on ecohydrologic predictions and their sensitivity to inter-annual climate variability

Treesearch

Kyongho Son; Christina Tague; Carolyn Hunsaker

2016-01-01

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates...

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.

Sensitivity, accuracy, and precision issues in opto-electronic holography based on fiber optics and high-spatial- and high-digitial-resolution cameras

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Yokum, Jeffrey S.; Pryputniewicz, Ryszard J.

2002-06-01

Sensitivity, accuracy, and precision characteristics in quantitative optical metrology techniques, and specifically in optoelectronic holography based on fiber optics and high-spatial and high-digital resolution cameras, are discussed in this paper. It is shown that sensitivity, accuracy, and precision dependent on both, the effective determination of optical phase and the effective characterization of the illumination-observation conditions. Sensitivity, accuracy, and precision are investigated with the aid of National Institute of Standards and Technology (NIST) traceable gages, demonstrating the applicability of quantitative optical metrology techniques to satisfy constantly increasing needs for the study and development of emerging technologies.

Laser Doppler detection systems for gas velocity measurement.

PubMed

Huffaker, R M

1970-05-01

The velocity of gas flow has been remotely measured using a technique which involves the coherent detection of scattered laser radiation from small particles suspended in the fluid utilizing the doppler effect. Suitable instrumentation for the study of wind tunnel type and atmospheric flows are described. Mainly for reasons of spatial resolution, a function of the laser wavelength, the wind tunnel system utilizes an argon laser operating at 0.5 micro. The relaxed spatial resolution requirement of atmospheric applications allows the use of a carbon dioxide laser, which has superior performance at a wavelength of 10.6 micro, a deduction made from signal-to-noise ratio considerations. Theoretical design considerations are given which consider Mie scattering predictions, two-phase flow effects, photomixing fundamentals, laser selection, spatial resolution, and spectral broadening effects. Preliminary experimental investigations using the instrumentation are detailed. The velocity profile of the flow field generated by a 1.27-cm diam subsonic jet was investigated, and the result compared favorably with a hot wire investigation conducted in the same jet. Measurements of wind velocity at a range of 50 m have also shown the considerable promise of the atmospheric system.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

LPE grown LSO:Tb scintillator films for high-resolution X-ray imaging applications at synchrotron light sources

NASA Astrophysics Data System (ADS)

Cecilia, A.; Rack, A.; Douissard, P.-A.; Martin, T.; Dos Santos Rolo, T.; Vagovič, P.; Hamann, E.; van de Kamp, T.; Riedel, A.; Fiederle, M.; Baumbach, T.

2011-08-01

Within the project ScinTAX of the 6th framework program (FP6) of the European Commission (SCINTAX—STRP 033 427) we have developed a new thin single crystal scintillator for high-resolution X-ray imaging. The scintillator is based on a Tb-doped Lu2SiO5 (LSO) film epitaxially grown on an adapted substrate. The high density, effective atomic number and light yield of the scintillating LSO significantly improves the efficiency of the X-ray imaging detectors currently used in synchrotron micro-imaging applications. In this work we present the characterization of the scintillating LSO films in terms of their spatial resolution performance and we provide two examples of high spatial and high temporal resolution applications.

ICA-based artefact and accelerated fMRI acquisition for improved Resting State Network imaging

PubMed Central

Griffanti, Ludovica; Salimi-Khorshidi, Gholamreza; Beckmann, Christian F.; Auerbach, Edward J.; Douaud, Gwenaëlle; Sexton, Claire E.; Zsoldos, Enikő; Ebmeier, Klaus P; Filippini, Nicola; Mackay, Clare E.; Moeller, Steen; Xu, Junqian; Yacoub, Essa; Baselli, Giuseppe; Ugurbil, Kamil; Miller, Karla L.; Smith, Stephen M.

2014-01-01

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB’s ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures were assessed using timeseries (amplitude and spectra), network matrix and spatial map analyses. For timeseries and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses. PMID:24657355

ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging.

PubMed

Griffanti, Ludovica; Salimi-Khorshidi, Gholamreza; Beckmann, Christian F; Auerbach, Edward J; Douaud, Gwenaëlle; Sexton, Claire E; Zsoldos, Enikő; Ebmeier, Klaus P; Filippini, Nicola; Mackay, Clare E; Moeller, Steen; Xu, Junqian; Yacoub, Essa; Baselli, Giuseppe; Ugurbil, Kamil; Miller, Karla L; Smith, Stephen M

2014-07-15

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB's ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures was assessed using time series (amplitude and spectra), network matrix and spatial map analyses. For time series and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses. Copyright © 2014 Elsevier Inc. All rights reserved.

Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm

NASA Astrophysics Data System (ADS)

Ying, Changsheng; Zhao, Peng; Li, Ye

2018-01-01

The intensified charge-coupled device (ICCD) is widely used in the field of low-light-level (LLL) imaging. The LLL images captured by ICCD suffer from low spatial resolution and contrast, and the target details can hardly be recognized. Super-resolution (SR) reconstruction of LLL images captured by ICCDs is a challenging issue. The dispersion in the double-proximity-focused image intensifier is the main factor that leads to a reduction in image resolution and contrast. We divide the integration time into subintervals that are short enough to get photon images, so the overlapping effect and overstacking effect of dispersion can be eliminated. We propose an SR reconstruction algorithm based on iterative projection photon localization. In the iterative process, the photon image is sliced by projection planes, and photons are screened under the constraints of regularity. The accurate position information of the incident photons in the reconstructed SR image is obtained by the weighted centroids calculation. The experimental results show that the spatial resolution and contrast of our SR image are significantly improved.

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.

Tip-enhanced near-field Raman spectroscopy with a scanning tunneling microscope and side-illumination optics.

PubMed

Yi, K J; He, X N; Zhou, Y S; Xiong, W; Lu, Y F

2008-07-01

Conventional Raman spectroscopy (RS) suffers from low spatial resolution and low detection sensitivity due to the optical diffraction limit and small interaction cross sections. It has been reported that a highly localized and significantly enhanced electromagnetic field could be generated in the proximity of a metallic tip illuminated by a laser beam. In this study, a tip-enhanced RS system was developed to both improve the resolution and enhance the detection sensitivity using the tip-enhanced near-field effects. This instrument, by combining RS with a scanning tunneling microscope and side-illumination optics, demonstrated significant enhancement on both optical sensitivity and spatial resolution using either silver (Ag)-coated tungsten (W) tips or gold (Au) tips. The sensitivity improvement was verified by observing the enhancement effects on silicon (Si) substrates. Lateral resolution was verified to be below 100 nm by mapping Ag nanostructures. By deploying the depolarization technique, an apparent enhancement of 175% on Si substrates was achieved. Furthermore, the developed instrument features fast and reliable optical alignment, versatile sample adaptability, and effective suppression of far-field signals.

Agricultural Land Use mapping by multi-sensor approach for hydrological water quality monitoring

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Kodes, Vit

2010-05-01

The main objective of this study is to demonstrate potential of operational use of the high and medium resolution remote sensing data for hydrological water quality monitoring by mapping agriculture intensity and crop structures. In particular use of remote sensing mapping for optimization of pesticide monitoring. The agricultural mapping task is tackled by means of medium spatial and high temporal resolution ESA Envisat MERIS FR images together with single high spatial resolution IRS AWiFS image covering the whole area of interest (the Czech Republic). High resolution data (e.g. SPOT, ALOS, Landsat) are often used for agricultural land use classification, but usually only at regional or local level due to data availability and financial constraints. AWiFS data (nominal spatial resolution 56 m) due to the wide satellite swath seems to be more suitable for use at national level. Nevertheless, one of the critical issues for such a classification is to have sufficient image acquisitions over the whole vegetation period to describe crop development in appropriate way. ESA MERIS middle-resolution data were used in several studies for crop classification. The high temporal and also spectral resolution of MERIS data has indisputable advantage for crop classification. However, spatial resolution of 300 m results in mixture signal in a single pixel. AWiFS-MERIS data synergy brings new perspectives in agricultural Land Use mapping. Also, the developed methodology procedure is fully compatible with future use of ESA (GMES) Sentinel satellite images. The applied methodology of hybrid multi-sensor approach consists of these main stages: a/ parcel segmentation and spectral pre-classification of high resolution image (AWiFS); b/ ingestion of middle resolution (MERIS) vegetation spectro-temporal features; c/ vegetation signatures unmixing; and d/ semantic object-oriented classification of vegetation classes into final classification scheme. These crop groups were selected to be classified: winter crops, spring crops, oilseed rape, legumes, summer and other crops. This study highlights operational potentials of high temporal full resolution MERIS images in agricultural land use monitoring. Practical application of this methodology is foreseen, among others, in the water quality monitoring. Effective pesticide monitoring relies also on spatial distribution of applied pesticides, which can be derived from crop - plant protection product relationship. Knowledge of areas with predominant occurrence of specific crop based on remote sensing data described above can be used for a forecast of probable plant protection product application, thus cost-effective pesticide monitoring. The remote sensing data used on a continuous basis can be used in other long-term water management issues and provide valuable data for decision makers. Acknowledgement: Authors acknowledge the financial support of the Ministry of Education, Youth and Sports of the Czech Republic (grants No. 2B06095 and No. MSM 6046070901). The study was also supported by ESA CAT-1 (ref. 4358) and SOSI projects (Spatial Observation Services and Infrastructure; ref. GSTP-RTDA-EOPG-SW-08-0004).

Compact three-dimensional super-resolution system based on fluorescence emission difference microscopy

NASA Astrophysics Data System (ADS)

Zhu, Dazhao; Chen, Youhua; Fang, Yue; Hussain, Anwar; Kuang, Cuifang; Zhou, Xiaoxu; Xu, Yingke; Liu, Xu

2017-12-01

A compact microscope system for three-dimensional (3-D) super-resolution imaging is presented. The super-resolution capability of the system is based on a size-reduced effective 3-D point spread function generated through the fluorescence emission difference (FED) method. The appropriate polarization direction distribution and manipulation allows the panel active area of the spatial light modulator to be fully utilized. This allows simultaneous modulation of the incident light by two kinds of phase masks to be performed with a single spatial light modulator in order to generate a 3-D negative spot. The system is more compact than standard 3-D FED systems while maintaining all the advantages of 3-D FED microscopy. The experimental results demonstrated the improvement in 3-D resolution by nearly 1.7 times and 1.6 times compared to the classic confocal resolution in the lateral and axial directions, respectively.

Investigation of LANDSAT follow-on thematic mapper spatial, radiometric and spectral resolution

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Morgenstern, J. P.; Kent, E. R.; Erickson, J. D.

1976-01-01

The author has identified the following significant results. Fine resolution M7 multispectral scanner data collected during the Corn Blight Watch Experiment in 1971 served as the basis for this study. Different locations and times of year were studied. Definite improvement using 30-40 meter spatial resolution over present LANDSAT 1 resolution and over 50-60 meter resolution was observed, using crop area mensuration as the measure. Simulation studies carried out to extrapolate the empirical results to a range of field size distributions confirmed this effect, showing the improvement to be most pronounced for field sizes of 1-4 hectares. Radiometric sensitivity study showed significant degradation of crop classification accuracy immediately upon relaxation from the nominally specified values of 0.5% noise equivalent reflectance. This was especially the case for data which were spectrally similar such as that collected early in the growing season and also when attempting to accomplish crop stress detection.

Development of a compact E ? B microchannel plate detector for beam imaging

DOE PAGES

Wiggins, B. B.; Singh, Varinderjit; Vadas, J.; ...

2017-06-17

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatialmore » resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.« less

Development of a compact E ? B microchannel plate detector for beam imaging

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

Wiggins, B. B.; Singh, Varinderjit; Vadas, J.

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatialmore » resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.« less

Model of diffusion-assisted direct laser writing by means of nanopolymerization in the presence of radical quencher

NASA Astrophysics Data System (ADS)

Pikulin, Alexander; Bityurin, Nikita; Sokolov, Viktor I.

2015-12-01

Diffusion-assisted direct laser writing (DA-DLW) by multiphoton polymerization has been recently shown to be one of the most promising methods for the high-resolution 3D nanofabrication [I. Sakellari, et al., ACS Nano 6, 2302 (2012)]. The improvement of the writing spatial resolution has been observed under certain conditions when the mobile radical quencher (polymerization inhibitor) is added to the photosensitive composition. In this work, we present a theoretical study of this method, focusing on the resolution capabilities and optimal writing parameters. The laser beam absorption in the polymerizable composition causes the localized depletion of the quencher molecules. If the quencher depletion is balanced by its diffusion from the outside of the focal volume, the quasi-stationary non-equillibrium concentration spatial profile with zero minimum can be obtained. The polymer is then effectively formed only in the domain where the quencher is depleted. The spatially-distributed quencher, in this case, has the effect similar to that of the vortex beam in STimulated Emission Microscopy (STED).

Model of diffusion-assisted direct laser writing by means of nanopolymerization in the presence of radical quencher

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

Pikulin, Alexander, E-mail: pikulin@ufp.appl.sci-nnov.ru; Bityurin, Nikita; Institute of Applied Physics of Russian Academy of Sciences, 46, Ul’yanov Str., Nizhniy Novgorod, 603950

Diffusion-assisted direct laser writing (DA-DLW) by multiphoton polymerization has been recently shown to be one of the most promising methods for the high-resolution 3D nanofabrication [I. Sakellari, et al., ACS Nano 6, 2302 (2012)]. The improvement of the writing spatial resolution has been observed under certain conditions when the mobile radical quencher (polymerization inhibitor) is added to the photosensitive composition. In this work, we present a theoretical study of this method, focusing on the resolution capabilities and optimal writing parameters. The laser beam absorption in the polymerizable composition causes the localized depletion of the quencher molecules. If the quencher depletionmore » is balanced by its diffusion from the outside of the focal volume, the quasi-stationary non-equillibrium concentration spatial profile with zero minimum can be obtained. The polymer is then effectively formed only in the domain where the quencher is depleted. The spatially-distributed quencher, in this case, has the effect similar to that of the vortex beam in STimulated Emission Microscopy (STED)« less

Hyperspectral retinal imaging with a spectrally tunable light source

NASA Astrophysics Data System (ADS)

Francis, Robert P.; Zuzak, Karel J.; Ufret-Vincenty, Rafael

2011-03-01

Hyperspectral retinal imaging can measure oxygenation and identify areas of ischemia in human patients, but the devices used by current researchers are inflexible in spatial and spectral resolution. We have developed a flexible research prototype consisting of a DLP®-based spectrally tunable light source coupled to a fundus camera to quickly explore the effects of spatial resolution, spectral resolution, and spectral range on hyperspectral imaging of the retina. The goal of this prototype is to (1) identify spectral and spatial regions of interest for early diagnosis of diseases such as glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR); and (2) define required specifications for commercial products. In this paper, we describe the challenges and advantages of using a spectrally tunable light source for hyperspectral retinal imaging, present clinical results of initial imaging sessions, and describe how this research can be leveraged into specifying a commercial product.

Matrix Sublimation/Recrystallization for Imaging Proteins by Mass Spectrometry at High Spatial Resolution

PubMed Central

Yang, Junhai; Caprioli, Richard M.

2011-01-01

We have employed matrix deposition by sublimation for protein image analysis on tissue sections using a hydration/recrystallization process that produces high quality MALDI mass spectra and high spatial resolution ion images. We systematically investigated different washing protocols, the effect of tissue section thickness, the amount of sublimated matrix per unit area and different recrystallization conditions. The results show that an organic solvent rinse followed by ethanol/water rinses substantially increased sensitivity for the detection of proteins. Both the thickness of tissue section and amount of sinapinic acid sublimated per unit area have optimal ranges for maximal protein signal intensity. Ion images of mouse and rat brain sections at 50, 20 and 10 µm spatial resolution are presented and are correlated with H&E stained optical images. For targeted analysis, histology directed imaging can be performed using this protocol where MS analysis and H&E staining are performed on the same section. PMID:21639088

Considering low-rank, sparse and gas-inflow effects constraints for accelerated pulmonary dynamic hyperpolarized 129Xe MRI

NASA Astrophysics Data System (ADS)

Xiao, Sa; Deng, He; Duan, Caohui; Xie, Junshuai; Zhang, Huiting; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2018-05-01

Dynamic hyperpolarized (HP) 129Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution.

Experimental flat-panel high-spatial-resolution volume CT of the temporal bone.

PubMed

Gupta, Rajiv; Bartling, Soenke H; Basu, Samit K; Ross, William R; Becker, Hartmut; Pfoh, Armin; Brady, Thomas; Curtin, Hugh D

2004-09-01

A CT scanner employing a digital flat-panel detector is capable of very high spatial resolution as compared with a multi-section CT (MSCT) scanner. Our purpose was to determine how well a prototypical volume CT (VCT) scanner with a flat-panel detector system defines fine structures in temporal bone. Four partially manipulated temporal-bone specimens were imaged by use of a prototypical cone-beam VCT scanner with a flat-panel detector system at an isometric resolution of 150 microm at the isocenter. These specimens were also depicted by state-of-the-art multisection CT (MSCT). Forty-two structures imaged by both scanners were qualitatively assessed and rated, and scores assigned to VCT findings were compared with those of MSCT. Qualitative assessment of anatomic structures, lesions, cochlear implants, and middle-ear hearing aids indicated that image quality was significantly better with VCT (P < .001). Structures near the spatial-resolution limit of MSCT (e.g., bony covering of the tympanic segment of the facial canal, the incudo-stapedial joint, the proximal vestibular aqueduct, the interscalar septum, and the modiolus) had higher contrast and less partial-volume effect with VCT. The flat-panel prototype provides better definition of fine osseous structures of temporal bone than that of currently available MSCT scanners. This study provides impetus for further research in increasing spatial resolution beyond that offered by the current state-of-the-art scanners.

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

GRACE Hydrological estimates for small basins: Evaluating processing approaches on the High Plains Aquifer, USA

NASA Astrophysics Data System (ADS)

Longuevergne, Laurent; Scanlon, Bridget R.; Wilson, Clark R.

2010-11-01

The Gravity Recovery and Climate Experiment (GRACE) satellites provide observations of water storage variation at regional scales. However, when focusing on a region of interest, limited spatial resolution and noise contamination can cause estimation bias and spatial leakage, problems that are exacerbated as the region of interest approaches the GRACE resolution limit of a few hundred km. Reliable estimates of water storage variations in small basins require compromises between competing needs for noise suppression and spatial resolution. The objective of this study was to quantitatively investigate processing methods and their impacts on bias, leakage, GRACE noise reduction, and estimated total error, allowing solution of the trade-offs. Among the methods tested is a recently developed concentration algorithm called spatiospectral localization, which optimizes the basin shape description, taking into account limited spatial resolution. This method is particularly suited to retrieval of basin-scale water storage variations and is effective for small basins. To increase confidence in derived methods, water storage variations were calculated for both CSR (Center for Space Research) and GRGS (Groupe de Recherche de Géodésie Spatiale) GRACE products, which employ different processing strategies. The processing techniques were tested on the intensively monitored High Plains Aquifer (450,000 km2 area), where application of the appropriate optimal processing method allowed retrieval of water storage variations over a portion of the aquifer as small as ˜200,000 km2.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Active Radiation Detectors for Use in Space Beyond Low Earth Orbit: Spatial and Energy Resolution Requirements and Methods for Heavy Ion Charge Classification

NASA Astrophysics Data System (ADS)

McBeth, Rafe A.

Space radiation exposure to astronauts will need to be carefully monitored on future missions beyond low earth orbit. NASA has proposed an updated radiation risk framework that takes into account a significant amount of radiobiological and heavy ion track structure information. These models require active radiation detection systems to measure the energy and ion charge Z. However, current radiation detection systems cannot meet these demands. The aim of this study was to investigate several topics that will help next generation detection systems meet the NASA objectives. Specifically, this work investigates the required spatial resolution to avoid coincident events in a detector, the effects of energy straggling and conversion of dose from silicon to water, and methods for ion identification (Z) using machine learning. The main results of this dissertation are as follows: 1. Spatial resolution on the order of 0.1 cm is required for active space radiation detectors to have high confidence in identifying individual particles, i.e., to eliminate coincident events. 2. Energy resolution of a detector system will be limited by energy straggling effects and the conversion of dose in silicon to dose in biological tissue (water). 3. Machine learning methods show strong promise for identification of ion charge (Z) with simple detector designs.

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

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.

The nature of giant clumps in distant galaxies probed by the anatomy of the cosmic snake

NASA Astrophysics Data System (ADS)

Cava, Antonio; Schaerer, Daniel; Richard, Johan; Pérez-González, Pablo G.; Dessauges-Zavadsky, Miroslava; Mayer, Lucio; Tamburello, Valentina

2018-01-01

Giant stellar clumps are ubiquitous in high-redshift galaxies1,2. They are thought to play an important role in the build-up of galactic bulges3 and as diagnostics of star formation feedback in galactic discs4. Hubble Space Telescope (HST) blank field imaging surveys have estimated that these clumps have masses of up to 109.5 M⊙ and linear sizes of ≳1 kpc5,6. Recently, gravitational lensing has also been used to get higher spatial resolution7-9. However, both recent lensed observations10,11 and models12,13 suggest that the clumps' properties may be overestimated by the limited resolution of standard imaging techniques. A definitive proof of this observational bias is nevertheless still missing. Here we investigate directly the effect of resolution on clump properties by analysing multiple gravitationally lensed images of the same galaxy at different spatial resolutions, down to 30 pc. We show that the typical mass and size of giant clumps, generally observed at 1 kpc resolution in high-redshift galaxies, are systematically overestimated. The high spatial resolution data, only enabled by strong gravitational lensing using currently available facilities, support smaller scales of clump formation by fragmentation of the galactic gas disk via gravitational instabilities.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

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

Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu; Garrett, John

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIRmore » (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.« less

High-resolution scanning precession electron diffraction: Alignment and spatial resolution.

PubMed

Barnard, Jonathan S; Johnstone, Duncan N; Midgley, Paul A

2017-03-01

Methods are presented for aligning the pivot point of a precessing electron probe in the scanning transmission electron microscope (STEM) and for assessing the spatial resolution in scanning precession electron diffraction (SPED) experiments. The alignment procedure is performed entirely in diffraction mode, minimising probe wander within the bright-field (BF) convergent beam electron diffraction (CBED) disk and is used to obtain high spatial resolution SPED maps. Through analysis of the power spectra of virtual bright-field images extracted from the SPED data, the precession-induced blur was measured as a function of precession angle. At low precession angles, SPED spatial resolution was limited by electronic noise in the scan coils; whereas at high precession angles SPED spatial resolution was limited by tilt-induced two-fold astigmatism caused by the positive spherical aberration of the probe-forming lens. Copyright © 2016 Elsevier B.V. All rights reserved.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

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.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

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.

Copper Decoration of Carbon Nanotubes and High Resolution Electron Microscopy

NASA Astrophysics Data System (ADS)

Probst, Camille

A new process of decorating carbon nanotubes with copper was developed for the fabrication of nanocomposite aluminum-nanotubes. The process consists of three stages: oxidation, activation and electroless copper plating on the nanotubes. The oxidation step was required to create chemical function on the nanotubes, essential for the activation step. Then, catalytic nanoparticles of tin-palladium were deposited on the tubes. Finally, during the electroless copper plating, copper particles with a size between 20 and 60 nm were uniformly deposited on the nanotubes surface. The reproducibility of the process was shown by using another type of carbon nanotube. The fabrication of nanocomposites aluminum-nanotubes was tested by aluminum vacuum infiltration. Although the infiltration of carbon nanotubes did not produce the expected results, an interesting electron microscopy sample was discovered during the process development: the activated carbon nanotubes. Secondly, scanning transmitted electron microscopy (STEM) imaging in SEM was analysed. The images were obtained with a new detector on the field emission scanning electron microscope (Hitachi S-4700). Various parameters were analysed with the use of two different samples: the activated carbon nanotubes (previously obtained) and gold-palladium nanodeposits. Influences of working distance, accelerating voltage or sample used on the spatial resolution of images obtained with SMART (Scanning Microscope Assessment and Resolution Testing) were analysed. An optimum working distance for the best spatial resolution related to the sample analysed was found for the imaging in STEM mode. Finally, relation between probe size and spatial resolution of backscattered electrons (BSE) images was studied. An image synthesis method was developed to generate the BSE images from backscattered electrons coefficients obtained with CASINO software. Spatial resolution of images was determined using SMART. The analysis shown that using a probe size smaller than the size of the observed object (sample features) does not improve the spatial resolution. In addition, the effects of the accelerating voltage, the current intensity and the sample geometry and composition were analysed.

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.

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

Depth-resolved mid-infrared photothermal imaging of living cells and organisms with submicrometer spatial resolution

PubMed Central

Zhang, Delong; Li, Chen; Zhang, Chi; Slipchenko, Mikhail N.; Eakins, Gregory; Cheng, Ji-Xin

2016-01-01

Chemical contrast has long been sought for label-free visualization of biomolecules and materials in complex living systems. Although infrared spectroscopic imaging has come a long way in this direction, it is thus far only applicable to dried tissues because of the strong infrared absorption by water. It also suffers from low spatial resolution due to long wavelengths and lacks optical sectioning capabilities. We overcome these limitations through sensing vibrational absorption–induced photothermal effect by a visible laser beam. Our mid-infrared photothermal (MIP) approach reached 10 μM detection sensitivity and submicrometer lateral spatial resolution. This performance has exceeded the diffraction limit of infrared microscopy and allowed label-free three-dimensional chemical imaging of live cells and organisms. Distributions of endogenous lipid and exogenous drug inside single cells were visualized. We further demonstrated in vivo MIP imaging of lipids and proteins in Caenorhabditis elegans. The reported MIP imaging technology promises broad applications from monitoring metabolic activities to high-resolution mapping of drug molecules in living systems, which are beyond the reach of current infrared microscopy. PMID:27704043

Depth-resolved mid-infrared photothermal imaging of living cells and organisms with submicrometer spatial resolution.

PubMed

Zhang, Delong; Li, Chen; Zhang, Chi; Slipchenko, Mikhail N; Eakins, Gregory; Cheng, Ji-Xin

2016-09-01

Chemical contrast has long been sought for label-free visualization of biomolecules and materials in complex living systems. Although infrared spectroscopic imaging has come a long way in this direction, it is thus far only applicable to dried tissues because of the strong infrared absorption by water. It also suffers from low spatial resolution due to long wavelengths and lacks optical sectioning capabilities. We overcome these limitations through sensing vibrational absorption-induced photothermal effect by a visible laser beam. Our mid-infrared photothermal (MIP) approach reached 10 μM detection sensitivity and submicrometer lateral spatial resolution. This performance has exceeded the diffraction limit of infrared microscopy and allowed label-free three-dimensional chemical imaging of live cells and organisms. Distributions of endogenous lipid and exogenous drug inside single cells were visualized. We further demonstrated in vivo MIP imaging of lipids and proteins in Caenorhabditis elegans . The reported MIP imaging technology promises broad applications from monitoring metabolic activities to high-resolution mapping of drug molecules in living systems, which are beyond the reach of current infrared microscopy.

High-resolution imaging of magnetic fields using scanning superconducting quantum interference device (SQUID) microscopy

NASA Astrophysics Data System (ADS)

Fong de Los Santos, Luis E.

Development of a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with sub-millimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensor is mounted in the tip of a sapphire rod and thermally anchored to the cryostat helium reservoir. A 25 mum sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows adjusting the sample-to-sensor spacing from the top of the Dewar. I have achieved a sensor-to-sample spacing of 100 mum, which could be maintained for periods of up to 4 weeks. Different SQUID sensor configurations are necessary to achieve the best combination of spatial resolution and field sensitivity for a given magnetic source. For imaging thin sections of geological samples, I used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80 mum, and achieved a field sensitivity of 1.5 pT/Hz1/2 and a magnetic moment sensitivity of 5.4 x 10-18 Am2/Hz1/2 at a sensor-to-sample spacing of 100 mum in the white noise region for frequencies above 100 Hz. Imaging action currents in cardiac tissue requires higher field sensitivity, which can only be achieved by compromising spatial resolution. I developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250 mum to 1 mm, and achieved sensitivities of 480 - 180 fT/Hz1/2 in the white noise region for frequencies above 100 Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

Emotion-induced trade-offs in spatiotemporal vision.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-05-01

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

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

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.

Chandra ACIS Sub-pixel Resolution

NASA Astrophysics Data System (ADS)

Kim, Dong-Woo; Anderson, C. S.; Mossman, A. E.; Allen, G. E.; Fabbiano, G.; Glotfelty, K. J.; Karovska, M.; Kashyap, V. L.; McDowell, J. C.

2011-05-01

We investigate how to achieve the best possible ACIS spatial resolution by binning in ACIS sub-pixel and applying an event repositioning algorithm after removing pixel-randomization from the pipeline data. We quantitatively assess the improvement in spatial resolution by (1) measuring point source sizes and (2) detecting faint point sources. The size of a bright (but no pile-up), on-axis point source can be reduced by about 20-30%. With the improve resolution, we detect 20% more faint sources when embedded on the extended, diffuse emission in a crowded field. We further discuss the false source rate of about 10% among the newly detected sources, using a few ultra-deep observations. We also find that the new algorithm does not introduce a grid structure by an aliasing effect for dithered observations and does not worsen the positional accuracy

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.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

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

2004-08-01

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

Combined Use of Satellite Observations with Urban Surface Characteristics to Estimate PM Concentrations by Employing Mixed-Effects Models

NASA Astrophysics Data System (ADS)

Beloconi, Anton; Benas, Nikolaos; Chrysoulakis, Nektarios; Kamarianakis, Yiannis

2015-11-01

Linear mixed effects models were developed for the estimation of the average daily Particulate Matter (PM) concentration spatial distribution over the area of Greater London (UK). Both fine (PM2.5) and coarse (PM10) concentrations were predicted for the 2002- 2012 time period, based on satellite data. The latter included Aerosol Optical Thickness (AOT) at 3×3 km spatial resolution, as well as the Surface Relative Humidity, Surface Temperature and K-Index derived from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. For a meaningful interpretation of the association among these variables, all data were homogenized with regard to spatial support and geographic projection, thus addressing the change of support problem and leading to a valid statistical inference. To this end, spatial (2D) and spatio- temporal (3D) kriging techniques were applied to in-situ particulate matter concentrations and the leave-one- station-out cross-validation was performed on a daily level to gauge the quality of the predictions. Satellite- derived covariates displayed clear seasonal patterns; in order to work with data which is stationary in mean, for each covariate, deviations from its estimated annual profiles were computed using nonlinear least squares and nonlinear absolute deviations. High-resolution land- cover and morphology static datasets were additionally incorporated in the analysis in order to catch the effects of nearby emission sources and sequestration sites. For pairwise comparisons of the particulate matter concentration means at distinct land-cover classes, the pairwise comparisons method for unequal sample sizes, known as Tukey's method, was performed. The use of satellite-derived products allowed better assessment of space-time interactions of PM, since these daily spatial measurements were able to capture differences in PM concentrations between grid cells, while the use of high- resolution land-cover and morphology static datasets allowed accounting for local industrial, domestic and traffic related air pollution. The developed methods are expected to fully exploit ESA's new Sentinel-3 observations to estimate spatial distributions of both PM10 and PM2.5 concentrations in arbitrary cities.

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.

Efficient space-time sampling with pixel-wise coded exposure for high-speed imaging.

PubMed

Liu, Dengyu; Gu, Jinwei; Hitomi, Yasunobu; Gupta, Mohit; Mitsunaga, Tomoo; Nayar, Shree K

2014-02-01

Cameras face a fundamental trade-off between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this trade-off without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing, and reconstructing the space-time volume to overcome this trade-off. Our approach has two important distinctions compared to previous works: 1) We achieve sparse representation of videos by learning an overcomplete dictionary on video patches, and 2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach, sampling function and sparse representation, by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a liquid crystal on silicon device. System characteristics such as field of view and modulation transfer function are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution.

Time of flight dependent linearity in diffuse imaging: how effective is it to evaluate the spatial resolution by measuring the edge response function?

PubMed

Ortiz-Rascón, E; Bruce, N C; Rodríguez-Rosales, A A; Garduño-Mejía, J

2016-03-01

We describe the behavior of linearity in diffuse imaging by evaluating the differences between time-resolved images produced by photons arriving at the detector at different times. Two approaches are considered: Monte Carlo simulations and experimental results. The images of two complete opaque bars embedded in a transparent or in a turbid medium with a slab geometry are analyzed; the optical properties of the turbid medium sample are close to those of breast tissue. A simple linearity test was designed involving a direct comparison between the intensity profile produced by two bars scanned at the same time and the intensity profile obtained by adding two profiles of each bar scanned one at a time. It is shown that the linearity improves substantially when short time of flight photons are used in the imaging process, but even then the nonlinear behavior prevails. As the edge response function (ERF) has been used widely for testing the spatial resolution in imaging systems, the main implication of a time dependent linearity is the weakness of the linearity assumption when evaluating the spatial resolution through the ERF in diffuse imaging systems, and the need to evaluate the spatial resolution by other methods.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

GATE simulation of a new design of pinhole SPECT system for small animal brain imaging

NASA Astrophysics Data System (ADS)

Uzun Ozsahin, D.; Bläckberg, L.; El Fakhri, G.; Sabet, H.

2017-01-01

Small animal SPECT imaging has gained an increased interest over the past decade since it is an excellent tool for developing new drugs and tracers. Therefore, there is a huge effort on the development of cost-effective SPECT detectors with high capabilities. The aim of this study is to simulate the performance characteristics of new designs for a cost effective, stationary SPECT system dedicated to small animal imaging with a focus on mice brain. The conceptual design of this SPECT system platform, Stationary Small Animal SSA-SPECT, is to use many pixelated CsI:TI detector modules with 0.4 mm × 0.4 mm pixels in order to achieve excellent intrinsic detector resolution where each module is backed by a single pinhole collimator with 0.3 mm hole diameter. In this work, we present the simulation results of four variations of the SSA-SPECT platform where the number of detector modules and FOV size is varied while keeping the detector size and collimator hole size constant. Using the NEMA NU-4 protocol, we performed spatial resolution, sensitivity, image quality simulations followed by a Derenzo-like phantom evaluation. The results suggest that all four SSA-SPECT systems can provide better than 0.063% system sensitivity and < 1.5 mm FWHM spatial resolution without resolution recovery or other correction techniques. Specifically, SSA-SPECT-1 showed a system sensitivity of 0.09% in combination with 1.1 mm FWHM spatial resolution.

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.

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates

EPA Science Inventory

The development of effective measures to stabilize atmospheric 22 CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strengt...

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

PubMed

Radogna, Raffaella; Verwilligen, Piet

2018-01-01

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

Femtosecond gas phase electron diffraction with MeV electrons.

PubMed

Yang, Jie; Guehr, Markus; Vecchione, Theodore; Robinson, Matthew S; Li, Renkai; Hartmann, Nick; Shen, Xiaozhe; Coffee, Ryan; Corbett, Jeff; Fry, Alan; Gaffney, Kelly; Gorkhover, Tais; Hast, Carsten; Jobe, Keith; Makasyuk, Igor; Reid, Alexander; Robinson, Joseph; Vetter, Sharon; Wang, Fenglin; Weathersby, Stephen; Yoneda, Charles; Wang, Xijie; Centurion, Martin

2016-12-16

We present results on ultrafast gas electron diffraction (UGED) experiments with femtosecond resolution using the MeV electron gun at SLAC National Accelerator Laboratory. UGED is a promising method to investigate molecular dynamics in the gas phase because electron pulses can probe the structure with a high spatial resolution. Until recently, however, it was not possible for UGED to reach the relevant timescale for the motion of the nuclei during a molecular reaction. Using MeV electron pulses has allowed us to overcome the main challenges in reaching femtosecond resolution, namely delivering short electron pulses on a gas target, overcoming the effect of velocity mismatch between pump laser pulses and the probe electron pulses, and maintaining a low timing jitter. At electron kinetic energies above 3 MeV, the velocity mismatch between laser and electron pulses becomes negligible. The relativistic electrons are also less susceptible to temporal broadening due to the Coulomb force. One of the challenges of diffraction with relativistic electrons is that the small de Broglie wavelength results in very small diffraction angles. In this paper we describe the new setup and its characterization, including capturing static diffraction patterns of molecules in the gas phase, finding time-zero with sub-picosecond accuracy and first time-resolved diffraction experiments. The new device can achieve a temporal resolution of 100 fs root-mean-square, and sub-angstrom spatial resolution. The collimation of the beam is sufficient to measure the diffraction pattern, and the transverse coherence is on the order of 2 nm. Currently, the temporal resolution is limited both by the pulse duration of the electron pulse on target and by the timing jitter, while the spatial resolution is limited by the average electron beam current and the signal-to-noise ratio of the detection system. We also discuss plans for improving both the temporal resolution and the spatial resolution.

Visualising landscape evolution: the effects of resolution on soil redistribution

NASA Astrophysics Data System (ADS)

Schoorl, Jeroen M.; Claessens, Lieven; (A) Veldkamp, Tom

2017-04-01

Landscape forming processes such as erosion by water, land sliding by water and gravity or ploughing by gravity, are closely related to resolution and land use changes. These processes may be controlled and influenced by multiple bio-physical and socio-economic driving factors, resulting in a complex multi-scale system. Consequently, land use changes should not be analysed in isolation without accounting for both on-site and off-site effects of these landscape processes in landscapes where water driven and or gravity driven processes are very active,. Especially the visualisation of these on- and off-site effects as a movie of evolving time series and changes is a potential valuable possibility in DEM modelling approaches. To investigate the interactions between land use, land use change, resolution of DEMs and landscape processes, a case study for the Álora region in southern Spain will presented, mainly as movies of modelling time-series, Starting from a baseline scenario of land use change, different levels of resolutions, interactions and feedbacks are added to the coupled LAPSUS model framework: Quantities and spatial patterns of both land use change and soil redistribution are compared between the baseline scenario without interactions and with each of the interaction mechanisms implemented consecutively. All as a function of spatial resolution. Keywords: LAPSUS; land use change; soil erosion, movie;

Effective resolution concepts for lidar observations

NASA Astrophysics Data System (ADS)

Iarlori, M.; Madonna, F.; Rizi, V.; Trickl, T.; Amodeo, A.

2015-12-01

Since its establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has provided, through its database, quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or high-spectral-resolution lidars). These coefficients are stored in terms of vertical profiles, and the EARLINET database also includes the details of the range resolution of the vertical profiles. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly acting as low-pass filters to reduce the high-frequency noise. Data filtering is described by the digital signal processing (DSP) theory as a convolution sum: each filtered signal output at a given range is the result of a linear combination of several signal input data samples (relative to different ranges from the lidar receiver), and this could be seen as a loss of range resolution of the output signal. Low-pass filtering always introduces distortions in the lidar profile shape. Thus, both the removal of high frequency, i.e., the removal of details up to a certain spatial extension, and the spatial distortion produce a reduction of the range resolution. This paper discusses the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved from lidar data. Large attention has been dedicated to providing an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

Super-resolution imaging by resonant tunneling in anisotropic acoustic metamaterials.

PubMed

Liu, Aiping; Zhou, Xiaoming; Huang, Guoliang; Hu, Gengkai

2012-10-01

The resonant tunneling effects that could result in complete transmission of evanescent waves are examined in acoustic metamaterials of anisotropic effective mass. The tunneling conditions are first derived for the metamaterials composed of classical mass-in-mass structures. It is found that the tunneling transmission occurs when the total length of metamaterials is an integral number of half-wavelengths of the periodic Bloch wave. Due to the local resonance of building units of metamaterials, the Bloch waves are spatially modulated within the periodic structures, leading to the resonant tunneling occurring in the low-frequency region. The metamaterial slab lens with anisotropic effective mass is designed by which the physics of resonant tunneling and the features for evanescent field manipulations are examined. The designed lens interacts with evanescent waves in the way of the propagating wavenumber weakly dependent on the spatial frequency of evanescent waves. Full-wave simulations validate the imaging performance of the proposed lens with the spatial resolution beyond the diffraction limit.

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

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

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.

Spatial variations of the Sr I 4607 Å scattering polarization peak

NASA Astrophysics Data System (ADS)

Bianda, M.; Berdyugina, S.; Gisler, D.; Ramelli, R.; Belluzzi, L.; Carlin, E. S.; Stenflo, J. O.; Berkefeld, T.

2018-06-01

Context. The scattering polarization signal observed in the photospheric Sr I 4607 Å line is expected to vary at granular spatial scales. This variation can be due to changes in the magnetic field intensity and orientation (Hanle effect), but also to spatial and temporal variations in the plasma properties. Measuring the spatial variation of such polarization signal would allow us to study the properties of the magnetic fields at subgranular scales, but observations are challenging since both high spatial resolution and high spectropolarimetric sensitivity are required. Aims: We aim to provide observational evidence of the polarization peak spatial variations, and to analyze the correlation they might have with granulation. Methods: Observations conjugating high spatial resolution and high spectropolarimetric precision were performed with the Zurich IMaging POLarimeter, ZIMPOL, at the GREGOR solar telescope, taking advantage of the adaptive optics system and the newly installed image derotator. Results: Spatial variations of the scattering polarization in the Sr I 4607 Å line are clearly observed. The spatial scale of these variations is comparable with the granular size. Small correlations between the polarization signal amplitude and the continuum intensity indicate that the polarization is higher at the center of granules than in the intergranular lanes.

A comparative verification of high resolution precipitation forecasts using model output statistics

NASA Astrophysics Data System (ADS)

van der Plas, Emiel; Schmeits, Maurice; Hooijman, Nicolien; Kok, Kees

2017-04-01

Verification of localized events such as precipitation has become even more challenging with the advent of high-resolution meso-scale numerical weather prediction (NWP). The realism of a forecast suggests that it should compare well against precipitation radar imagery with similar resolution, both spatially and temporally. Spatial verification methods solve some of the representativity issues that point verification gives rise to. In this study a verification strategy based on model output statistics is applied that aims to address both double penalty and resolution effects that are inherent to comparisons of NWP models with different resolutions. Using predictors based on spatial precipitation patterns around a set of stations, an extended logistic regression (ELR) equation is deduced, leading to a probability forecast distribution of precipitation for each NWP model, analysis and lead time. The ELR equations are derived for predictands based on areal calibrated radar precipitation and SYNOP observations. The aim is to extract maximum information from a series of precipitation forecasts, like a trained forecaster would. The method is applied to the non-hydrostatic model Harmonie (2.5 km resolution), Hirlam (11 km resolution) and the ECMWF model (16 km resolution), overall yielding similar Brier skill scores for the 3 post-processed models, but larger differences for individual lead times. Besides, the Fractions Skill Score is computed using the 3 deterministic forecasts, showing somewhat better skill for the Harmonie model. In other words, despite the realism of Harmonie precipitation forecasts, they only perform similarly or somewhat better than precipitation forecasts from the 2 lower resolution models, at least in the Netherlands.

Effect of climate data on simulated carbon and nitrogen balances for Europe

NASA Astrophysics Data System (ADS)

Blanke, Jan Hendrik; Lindeskog, Mats; Lindström, Johan; Lehsten, Veiko

2016-05-01

In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ-GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%-93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%-10.7% of the total variability followed by GCMs (0.3%-7.6%), RCPs (0%-6.3%), and downscaling methods (0.1%-4.6%). The higher-order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%-45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ-GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias-corrected, bilinearly interpolated CMIP5 projections.

Impacts of model spatial resolution on the vertical structure of convection in the tropics

NASA Astrophysics Data System (ADS)

Bui, Hien Xuan; Yu, Jia-Yuh; Chou, Chia

2018-02-01

This study examined the impacts of model horizontal resolution on vertical structures of convection in the tropics by performing sensitivity experiments with the NCAR CESM1. It was found that contributions to the total precipitation between top-heavy and bottom-heavy convection are different among various resolutions. A coarser resolution tends to produce a greater contribution from top-heavy convection and, as a result, stronger precipitation in the western Pacific ITCZ; while there is less contribution from bottom-heavy convection and weaker precipitation in the eastern Pacific ITCZ. In the western Pacific ITCZ, where the convection is dominated by a top-heavy structure, the stronger precipitation in coarser resolution experiments is due to changes in temperature and moisture profiles associated with a warmer environment (i.e., thermodynamical effect). In the eastern Pacific ITCZ, where the convection is dictated by a bottom-heavy structure, the stronger precipitation in finer resolution experiments comes from changes in convection structure (i.e., dynamic effect) which favors a greater contribution of bottom-heavy convection as the model resolution goes higher. The moisture budget analysis further suggested that the very different behavior in precipitation tendencies in response to model resolution changes between the western and eastern Pacific ITCZs are determined mainly by changes in convective structure rather than changes in convective strength. This study pointed out the importance of model spatial resolution in reproducing a reasonable contribution to the total precipitation between top-heavy and bottom-heavy structure of convection in the tropical Pacific ITCZs.

a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

NASA Astrophysics Data System (ADS)

Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.

2017-09-01

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

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.

High-Rate Capable Floating Strip Micromegas

NASA Astrophysics Data System (ADS)

Bortfeldt, Jonathan; Bender, Michael; Biebel, Otmar; Danger, Helge; Flierl, Bernhard; Hertenberger, Ralf; Lösel, Philipp; Moll, Samuel; Parodi, Katia; Rinaldi, Ilaria; Ruschke, Alexander; Zibell, André

2016-04-01

We report on the optimization of discharge insensitive floating strip Micromegas (MICRO-MEsh GASeous) detectors, fit for use in high-energy muon spectrometers. The suitability of these detectors for particle tracking is shown in high-background environments and at very high particle fluxes up to 60 MHz/cm2. Measurement and simulation of the microscopic discharge behavior have demonstrated the excellent discharge tolerance. A floating strip Micromegas with an active area of 48 cm × 50 cm with 1920 copper anode strips exhibits in 120 GeV pion beams a spatial resolution of 50 μm at detection efficiencies above 95%. Pulse height, spatial resolution and detection efficiency are homogeneous over the detector. Reconstruction of particle track inclination in a single detector plane is discussed, optimum angular resolutions below 5° are observed. Systematic deviations of this μTPC-method are fully understood. The reconstruction capabilities for minimum ionizing muons are investigated in a 6.4 cm × 6.4 cm floating strip Micromegas under intense background irradiation of the whole active area with 20 MeV protons at a rate of 550 kHz. The spatial resolution for muons is not distorted by space charge effects. A 6.4 cm × 6.4 cm floating strip Micromegas doublet with low material budget is investigated in highly ionizing proton and carbon ion beams at particle rates between 2 MHz and 2 GHz. Stable operation up to the highest rates is observed, spatial resolution, detection efficiencies, the multi-hit and high-rate capability are discussed.

Variations in optical coherence tomography resolution and uniformity: a multi-system performance comparison

PubMed Central

Fouad, Anthony; Pfefer, T. Joshua; Chen, Chao-Wei; Gong, Wei; Agrawal, Anant; Tomlins, Peter H.; Woolliams, Peter D.; Drezek, Rebekah A.; Chen, Yu

2014-01-01

Point spread function (PSF) phantoms based on unstructured distributions of sub-resolution particles in a transparent matrix have been demonstrated as a useful tool for evaluating resolution and its spatial variation across image volumes in optical coherence tomography (OCT) systems. Measurements based on PSF phantoms have the potential to become a standard test method for consistent, objective and quantitative inter-comparison of OCT system performance. Towards this end, we have evaluated three PSF phantoms and investigated their ability to compare the performance of four OCT systems. The phantoms are based on 260-nm-diameter gold nanoshells, 400-nm-diameter iron oxide particles and 1.5-micron-diameter silica particles. The OCT systems included spectral-domain and swept source systems in free-beam geometries as well as a time-domain system in both free-beam and fiberoptic probe geometries. Results indicated that iron oxide particles and gold nanoshells were most effective for measuring spatial variations in the magnitude and shape of PSFs across the image volume. The intensity of individual particles was also used to evaluate spatial variations in signal intensity uniformity. Significant system-to-system differences in resolution and signal intensity and their spatial variation were readily quantified. The phantoms proved useful for identification and characterization of irregularities such as astigmatism. Our multi-system results provide evidence of the practical utility of PSF-phantom-based test methods for quantitative inter-comparison of OCT system resolution and signal uniformity. PMID:25071949

Comparative analysis of Worldview-2 and Landsat 8 for coastal saltmarsh mapping accuracy assessment

NASA Astrophysics Data System (ADS)

Rasel, Sikdar M. M.; Chang, Hsing-Chung; Diti, Israt Jahan; Ralph, Tim; Saintilan, Neil

2016-05-01

Coastal saltmarsh and their constituent components and processes are of an interest scientifically due to their ecological function and services. However, heterogeneity and seasonal dynamic of the coastal wetland system makes it challenging to map saltmarshes with remotely sensed data. This study selected four important saltmarsh species Pragmitis australis, Sporobolus virginicus, Ficiona nodosa and Schoeloplectus sp. as well as a Mangrove and Pine tree species, Avecinia and Casuarina sp respectively. High Spatial Resolution Worldview-2 data and Coarse Spatial resolution Landsat 8 imagery were selected in this study. Among the selected vegetation types some patches ware fragmented and close to the spatial resolution of Worldview-2 data while and some patch were larger than the 30 meter resolution of Landsat 8 data. This study aims to test the effectiveness of different classifier for the imagery with various spatial and spectral resolutions. Three different classification algorithm, Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Artificial Neural Network (ANN) were tested and compared with their mapping accuracy of the results derived from both satellite imagery. For Worldview-2 data SVM was giving the higher overall accuracy (92.12%, kappa =0.90) followed by ANN (90.82%, Kappa 0.89) and MLC (90.55%, kappa = 0.88). For Landsat 8 data, MLC (82.04%) showed the highest classification accuracy comparing to SVM (77.31%) and ANN (75.23%). The producer accuracy of the classification results were also presented in the paper.

Prototype pre-clinical PET scanner with depth-of-interaction measurements using single-layer crystal array and single-ended readout

NASA Astrophysics Data System (ADS)

Lee, Min Sun; Kim, Kyeong Yun; Ko, Guen Bae; Lee, Jae Sung

2017-05-01

In this study, we developed a proof-of-concept prototype PET system using a pair of depth-of-interaction (DOI) PET detectors based on the proposed DOI-encoding method and digital silicon photomultiplier (dSiPM). Our novel cost-effective DOI measurement method is based on a triangular-shaped reflector that requires only a single-layer pixelated crystal and single-ended signal readout. The DOI detector consisted of an 18  ×  18 array of unpolished LYSO crystal (1.47  ×  1.47  ×  15 mm3) wrapped with triangular-shaped reflectors. The DOI information was encoded by depth-dependent light distribution tailored by the reflector geometry and DOI correction was performed using four-step depth calibration data and maximum-likelihood (ML) estimation. The detector pair and the object were placed on two motorized rotation stages to demonstrate 12-block ring PET geometry with 11.15 cm diameter. Spatial resolution was measured and phantom and animal imaging studies were performed to investigate imaging performance. All images were reconstructed with and without the DOI correction to examine the impact of our DOI measurement. The pair of dSiPM-based DOI PET detectors showed good physical performances respectively: 2.82 and 3.09 peak-to-valley ratios, 14.30% and 18.95% energy resolution, and 4.28 and 4.24 mm DOI resolution averaged over all crystals and all depths. A sub-millimeter spatial resolution was achieved at the center of the field of view (FOV). After applying ML-based DOI correction, maximum 36.92% improvement was achieved in the radial spatial resolution and a uniform resolution was observed within 5 cm of transverse PET FOV. We successfully acquired phantom and animal images with improved spatial resolution and contrast by using the DOI measurement. The proposed DOI-encoding method was successfully demonstrated in the system level and exhibited good performance, showing its feasibility for animal PET applications with high spatial resolution and sensitivity.

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

NASA Astrophysics Data System (ADS)

Chybicki, Andrzej; Łubniewski, Zbigniew

2017-09-01

Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth's environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR), using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdansk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255°C with correlation coefficient R equal to 0.828 and Bias = 0.557°C. For comparison, using the PBIM method, it was obtained RMSE = 2.832°C, R = 0.775 and Bias = 0.997°C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53°C on average, in the case of applying the proposed method than in the case of using the PBIM method.

Optimization of air gap for two-dimensional imaging system using synchrotron radiation

NASA Astrophysics Data System (ADS)

Zeniya, Tsutomu; Takeda, Tohoru; Yu, Quanwen; Hyodo, Kazuyuki; Yuasa, Tetsuya; Aiyoshi, Yuji; Hiranaka, Yukio; Itai, Yuji; Akatsuka, Takao

2000-11-01

Since synchrotron radiation (SR) has several excellent properties such as high brilliance, broad continuous energy spectrum and small divergence, we can obtain x-ray images with high contrast and high spatial resolution by using of SR. In 2D imaging using SR, air gap method is very effective to reduce the scatter contamination. However, to use air gap method, the geometrical effect of finite source size of SR must be considered because spatial resolution of image is degraded by air gap. For 2D x-ray imaging with SR, x-ray mammography was chosen to examine the effect of air gap method. We theoretically discussed the optimization of air gap distance suing effective scatter point source model proposed by Muntz, and executed experiment with a newly manufactured monochromator with asymmetrical reflection and an imaging plate.

Combining environment and health information systems for the assessment of atmospheric pollution on human health.

PubMed

Skouloudis, Andreas N; Kassomenos, Pavlos

2014-08-01

The use of emerging technologies for environmental monitoring with satellite and in-situ sensors have become essential instruments for assessing the impact of environmental pollution on human health, especially in areas that require high spatial and temporal resolution. This was until recently a rather difficult problem. Regrettably, with classical approaches the spatial resolution is frequently inadequate in reporting environmental causes and health effects in the same time scale. This work examines with new tools different levels of air-quality with sensor monitoring with the aim to associate those with severe health effects. The process established here facilitates the precise representation of human exposure with the population attributed in a fine spatial grid and taking into account environmental stressors of human exposure. These stressors can be monitored with innovative sensor units with a temporal resolution that accurately describes chronic and acute environmental burdens. The current understanding of the situation in densely populated areas can be properly analyzed, before commitments are made for reductions in total emissions as well as for assessing the effects of reduced trans-boundary fluxes. In addition, the data processed here with in-situ sensors can assist in establishing more effective regulatory policies for the protection of vulnerable population groups and the satellite monitoring instruments permit abatement strategies that are close to real-time over large geographical areas. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Midlatitude sporadic-E episodes viewed by L-band split-spectrum InSAR

NASA Astrophysics Data System (ADS)

Furuya, Masato; Suzuki, Takato; Maeda, Jun; Heki, Kosuke

2017-12-01

Sporadic-E (Es) is a layer of ionization that irregularly appears within the E region of the ionosphere and is known to generate an unusual propagation of very high frequency waves over long distances. The detailed spatial structure of Es remains unclear due to the limited spatial resolution in the conventional ionosonde observations. We detect midlatitude Es by interferometric synthetic aperture radar (InSAR), which can clarify the spatial structure of Es with unprecedented resolution. Moreover, we use the range split-spectrum method (SSM) to separate dispersive and nondispersive components in the InSAR image. While InSAR SSM largely succeeds in decomposing into dispersive and nondispersive signals, our results indicate that small-scale dispersive signals due to the total electron content anomalies are accompanied by nondispersive signals with similar spatial scale at the same locations. We also examine the effects of higher-order terms in the refractive index for dispersive media. Both of these detected Es episodes indicate that smaller-scale dispersive effects originate from higher-order effects. We interpret that the smaller-scale nondispersive signals could indicate the emergence of nitric oxide (NO) generated by the reactions of metals, Mg and Fe, with nitric oxide ion (NO+) during the Es.

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.

Visual attention: The past 25 years

PubMed Central

Carrasco, Marisa

2012-01-01

This review focuses on covert attention and how it alters early vision. I explain why attention is considered a selective process, the constructs of covert attention, spatial endogenous and exogenous attention, and feature-based attention. I explain how in the last 25 years research on attention has characterized the effects of covert attention on spatial filters and how attention influences the selection of stimuli of interest. This review includes the effects of spatial attention on discriminability and appearance in tasks mediated by contrast sensitivity and spatial resolution; the effects of feature-based attention on basic visual processes, and a comparison of the effects of spatial and feature-based attention. The emphasis of this review is on psychophysical studies, but relevant electrophysiological and neuroimaging studies and models regarding how and where neuronal responses are modulated are also discussed. PMID:21549742

Visual attention: the past 25 years.

PubMed

Carrasco, Marisa

2011-07-01

This review focuses on covert attention and how it alters early vision. I explain why attention is considered a selective process, the constructs of covert attention, spatial endogenous and exogenous attention, and feature-based attention. I explain how in the last 25 years research on attention has characterized the effects of covert attention on spatial filters and how attention influences the selection of stimuli of interest. This review includes the effects of spatial attention on discriminability and appearance in tasks mediated by contrast sensitivity and spatial resolution; the effects of feature-based attention on basic visual processes, and a comparison of the effects of spatial and feature-based attention. The emphasis of this review is on psychophysical studies, but relevant electrophysiological and neuroimaging studies and models regarding how and where neuronal responses are modulated are also discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effect of different thickness of material filter on Tc-99m spectra and performance parameters of gamma camera

NASA Astrophysics Data System (ADS)

Nazifah, A.; Norhanna, S.; Shah, S. I.; Zakaria, A.

2014-11-01

This study aimed to investigate the effects of material filter technique on Tc-99m spectra and performance parameters of Philip ADAC forte dual head gamma camera. Thickness of material filter was selected on the basis of percentage attenuation of various gamma ray energies by different thicknesses of zinc material. A cylindrical source tank of NEMA single photon emission computed tomography (SPECT) Triple Line Source Phantom filled with water and Tc-99m radionuclide injected was used for spectra, uniformity and sensitivity measurements. Vinyl plastic tube was used as a line source for spatial resolution. Images for uniformity were reconstructed by filtered back projection method. Butterworth filter of order 5 and cut off frequency 0.35 cycles/cm was selected. Chang's attenuation correction method was applied by selecting 0.13/cm linear attenuation coefficient. Count rate was decreased with material filter from the compton region of Tc-99m energy spectrum, also from the photopeak region. Spatial resolution was improved. However, uniformity of tomographic image was equivocal, and system volume sensitivity was reduced by material filter. Material filter improved system's spatial resolution. Therefore, the technique may be used for phantom studies to improve the image quality.

Resolution and quantification accuracy enhancement of functional delay and sum beamforming for three-dimensional acoustic source identification with solid spherical arrays

NASA Astrophysics Data System (ADS)

Chu, Zhigang; Yang, Yang; Shen, Linbang

2017-05-01

Functional delay and sum (FDAS) is a novel beamforming algorithm introduced for the three-dimensional (3D) acoustic source identification with solid spherical microphone arrays. Being capable of offering significantly attenuated sidelobes with a fast speed, the algorithm promises to play an important role in interior acoustic source identification. However, it presents some intrinsic imperfections, specifically poor spatial resolution and low quantification accuracy. This paper focuses on conquering these imperfections by ridge detection (RD) and deconvolution approach for the mapping of acoustic sources (DAMAS). The suggested methods are referred to as FDAS+RD and FDAS+RD+DAMAS. Both computer simulations and experiments are utilized to validate their effects. Several interesting conclusions have emerged: (1) FDAS+RD and FDAS+RD+DAMAS both can dramatically ameliorate FDAS's spatial resolution and at the same time inherit its advantages. (2) Compared to the conventional DAMAS, FDAS+RD+DAMAS enjoys the same super spatial resolution, stronger sidelobe attenuation capability and more than two hundred times faster speed. (3) FDAS+RD+DAMAS can effectively conquer FDAS's low quantification accuracy. Whether the focus distance is equal to the distance from the source to the array center or not, it can quantify the source average pressure contribution accurately. This study will be of great significance to the accurate and quick localization and quantification of acoustic sources in cabin environments.

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

Digital Fresnel reflection holography for high-resolution 3D near-wall flow measurement.

PubMed

Kumar, S Santosh; Hong, Jiarong

2018-05-14

We propose a novel backscatter holographic imaging system, as a compact and effective tool for 3D near-wall flow diagnostics at high resolutions, utilizing light reflected at the solid-liquid interface as a reference beam. The technique is fully calibrated, and is demonstrated in a densely seeded channel to achieve a spatial resolution of near-wall flows equivalent to or exceeding prior digital inline holographic measurements using local tracer seeding technique. Additionally, we examined the effects of seeding concentration and laser coherence on the measurement resolution and sample volume resolved, demonstrating the potential to manipulate sample domain by tuning the laser coherence profile.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Super-resolution reconstruction of MR image with a novel residual learning network algorithm

NASA Astrophysics Data System (ADS)

Shi, Jun; Liu, Qingping; Wang, Chaofeng; Zhang, Qi; Ying, Shihui; Xu, Haoyu

2018-04-01

Spatial resolution is one of the key parameters of magnetic resonance imaging (MRI). The image super-resolution (SR) technique offers an alternative approach to improve the spatial resolution of MRI due to its simplicity. Convolutional neural networks (CNN)-based SR algorithms have achieved state-of-the-art performance, in which the global residual learning (GRL) strategy is now commonly used due to its effectiveness for learning image details for SR. However, the partial loss of image details usually happens in a very deep network due to the degradation problem. In this work, we propose a novel residual learning-based SR algorithm for MRI, which combines both multi-scale GRL and shallow network block-based local residual learning (LRL). The proposed LRL module works effectively in capturing high-frequency details by learning local residuals. One simulated MRI dataset and two real MRI datasets have been used to evaluate our algorithm. The experimental results show that the proposed SR algorithm achieves superior performance to all of the other compared CNN-based SR algorithms in this work.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift.

PubMed

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

2017-04-01

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

Effect of combined digital imaging parameters on endodontic file measurements.

PubMed

de Oliveira, Matheus Lima; Pinto, Geraldo Camilo de Souza; Ambrosano, Glaucia Maria Bovi; Tosoni, Guilherme Monteiro

2012-10-01

This study assessed the effect of the combination of a dedicated endodontic filter, spatial resolution, and contrast resolution on the determination of endodontic file lengths. Forty extracted single-rooted teeth were x-rayed with K-files (ISO size 10 and 15) in the root canals. Images were acquired using the VistaScan system (Dürr Dental, Beitigheim-Bissingen, Germany) under different combining parameters of spatial resolution (10 and 25 line pairs per millimeter [lp/mm]) and contrast resolution (8- and 16-bit depths). Subsequently, a dedicated endodontic filter was applied on the 16-bit images, creating 2 additional parameters. Six observers measured the length of the endodontic files in the root canals using the software that accompanies the system. The mean values of the actual file lengths and the measurements of the radiographic images were submitted to 1-way analysis of variance and the Tukey test at a level of significance of 5%. The intraobserver reproducibility was assessed by the intraclass correlation coefficient. All combined image parameters showed excellent intraobserver agreement with intraclass correlation coefficient means higher than 0.98. The imaging parameter of 25 lp/mm and 16 bit associated with the use of the endodontic filter did not differ significantly from the actual file lengths when both file sizes were analyzed together or separately (P > .05). When the size 15 file was evaluated separately, only 8-bit images differed significantly from the actual file lengths (P ≤ .05). The combination of an endodontic filter with high spatial resolution and high contrast resolution is recommended for the determination of file lengths when using storage phosphor plates. Copyright © 2012 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

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.

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.

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

AAPM/RSNA physics tutorial for residents: physics of flat-panel fluoroscopy systems: Survey of modern fluoroscopy imaging: flat-panel detectors versus image intensifiers and more.

PubMed

Nickoloff, Edward Lee

2011-01-01

This article reviews the design and operation of both flat-panel detector (FPD) and image intensifier fluoroscopy systems. The different components of each imaging chain and their functions are explained and compared. FPD systems have multiple advantages such as a smaller size, extended dynamic range, no spatial distortion, and greater stability. However, FPD systems typically have the same spatial resolution for all fields of view (FOVs) and are prone to ghosting. Image intensifier systems have better spatial resolution with the use of smaller FOVs (magnification modes) and tend to be less expensive. However, the spatial resolution of image intensifier systems is limited by the television system to which they are coupled. Moreover, image intensifier systems are degraded by glare, vignetting, spatial distortions, and defocusing effects. FPD systems do not have these problems. Some recent innovations to fluoroscopy systems include automated filtration, pulsed fluoroscopy, automatic positioning, dose-area product meters, and improved automatic dose rate control programs. Operator-selectable features may affect both the patient radiation dose and image quality; these selectable features include dose level setting, the FOV employed, fluoroscopic pulse rates, geometric factors, display software settings, and methods to reduce the imaging time. © RSNA, 2011.

Photo-induced spatial modulation of THz waves: opportunities and limitations.

PubMed

Kannegulla, Akash; Shams, Md Itrat Bin; Liu, Lei; Cheng, Li-Jing

2015-12-14

Programmable conductive patterns created by photoexcitation of semiconductor substrates using digital light processing (DLP) provides a versatile approach for spatial and temporal modulation of THz waves. The reconfigurable nature of the technology has great potential in implementing several promising THz applications, such as THz beam steering, THz imaging or THz remote sensing, in a simple, cost-effective manner. In this paper, we provide physical insight about how the semiconducting materials, substrate dimension, optical illumination wavelength and illumination size impact the performance of THz modulation, including modulation depth, modulation speed and spatial resolution. The analysis establishes design guidelines for the development of photo-induced THz modulation technology. Evolved from the theoretical analysis, a new mesa array technology composed by a matrix of sub-THz wavelength structures is introduced to maximize both spatial resolution and modulation depth for THz modulation with low-power photoexcitation by prohibiting the lateral diffusion of photogenerated carriers.

Phase-based, high spatial resolution and distributed, static and dynamic strain sensing using Brillouin dynamic gratings in optical fibers.

PubMed

Bergman, Arik; Langer, Tomi; Tur, Moshe

2017-03-06

A novel technique combining Brillouin phase-shift measurements with Brillouin dynamic gratings (BDGs) reflectometry in polarization-maintaining fibers is presented here for the first time. While a direct measurement of the optical phase in standard BDG setups is impractical due to non-local phase contributions, their detrimental effect is reduced by ~4 orders of magnitude through the coherent addition of Stokes and anti-Stokes reflections from two counter-propagating BDGs in the fiber. The technique advantageously combines the high-spatial-resolution of BDGs reflectometry with the increased tolerance to optical power fluctuations of phasorial measurements, to enhance the performance of fiber-optic strain sensors. We demonstrate a distributed measurement (20cm spatial-resolution) of both static and dynamic (5kHz of vibrations at a sampling rate of 1MHz) strain fields acting on the fiber, in good agreement with theory and (for the static case) with the results of commercial reflectometers.

Assessing the spatial distribution of coral bleaching using small unmanned aerial systems

NASA Astrophysics Data System (ADS)

Levy, Joshua; Hunter, Cynthia; Lukacazyk, Trent; Franklin, Erik C.

2018-06-01

Small unmanned aerial systems (sUAS) are an affordable, effective complement to existing coral reef monitoring and assessment tools. sUAS provide repeatable low-altitude, high-resolution photogrammetry to address fundamental questions of spatial ecology and community dynamics for shallow coral reef ecosystems. Here, we qualitatively describe the use of sUAS to survey the spatial characteristics of coral cover and the distribution of coral bleaching across patch reefs in Kānéohe Bay, Hawaii, and address limitations and anticipated technology advancements within the field of UAS. Overlapping sub-decimeter low-altitude aerial reef imagery collected during the 2015 coral bleaching event was used to construct high-resolution reef image mosaics of coral bleaching responses on four Kānéohe Bay patch reefs, totaling 60,000 m2. Using sUAS imagery, we determined that paled, bleached and healthy corals on all four reefs were spatially clustered. Comparative analyses of data from sUAS imagery and in situ diver surveys found as much as 14% difference in coral cover values between survey methods, depending on the size of the reef and area surveyed. When comparing the abundance of unhealthy coral (paled and bleached) between sUAS and in situ diver surveys, we found differences in cover from 1 to 49%, depending on the depth of in situ surveys, the percent of reef area covered with sUAS surveys and patchiness of the bleaching response. This study demonstrates the effective use of sUAS surveys for assessing the spatial dynamics of coral bleaching at colony-scale resolutions across entire patch reefs and evaluates the complementarity of data from both sUAS and in situ diver surveys to more accurately characterize the spatial ecology of coral communities on reef flats and slopes.

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

2016-10-01

We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

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.

New learning based super-resolution: use of DWT and IGMRF prior.

PubMed

Gajjar, Prakash P; Joshi, Manjunath V

2010-05-01

In this paper, we propose a new learning-based approach for super-resolving an image captured at low spatial resolution. Given the low spatial resolution test image and a database consisting of low and high spatial resolution images, we obtain super-resolution for the test image. We first obtain an initial high-resolution (HR) estimate by learning the high-frequency details from the available database. A new discrete wavelet transform (DWT) based approach is proposed for learning that uses a set of low-resolution (LR) images and their corresponding HR versions. Since the super-resolution is an ill-posed problem, we obtain the final solution using a regularization framework. The LR image is modeled as the aliased and noisy version of the corresponding HR image, and the aliasing matrix entries are estimated using the test image and the initial HR estimate. The prior model for the super-resolved image is chosen as an Inhomogeneous Gaussian Markov random field (IGMRF) and the model parameters are estimated using the same initial HR estimate. A maximum a posteriori (MAP) estimation is used to arrive at the cost function which is minimized using a simple gradient descent approach. We demonstrate the effectiveness of the proposed approach by conducting the experiments on gray scale as well as on color images. The method is compared with the standard interpolation technique and also with existing learning-based approaches. The proposed approach can be used in applications such as wildlife sensor networks, remote surveillance where the memory, the transmission bandwidth, and the camera cost are the main constraints.

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.

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

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

PubMed

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

2015-01-01

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

Scale effects on the evapotranspiration estimation over a water-controlled Mediterranean ecosystem and its influence on hydrological modelling

NASA Astrophysics Data System (ADS)

Carpintero, Elisabet; González-Dugo, María P.; José Polo, María; Hain, Christopher; Nieto, Héctor; Gao, Feng; Andreu, Ana; Kustas, William; Anderson, Martha

2017-04-01

The integration of currently available satellite data into surface energy balance models can provide estimates of evapotranspiration (ET) with spatial and temporal resolutions determined by sensor characteristics. The use of data fusion techniques may increase the temporal resolution of these estimates using multiple satellites, providing a more frequent ET monitoring for hydrological purposes. The objective of this work is to analyze the effects of pixel resolution on the estimation of evapotranspiration using different remote sensing platforms, and to provide continuous monitoring of ET over a water-controlled ecosystem, the Holm oak savanna woodland known as dehesa. It is an agroforestry system with a complex canopy structure characterized by widely-spaced oak trees combined with crops, pasture and shrubs. The study was carried out during two years, 2013 and 2014, combining ET estimates at different spatial and temporal resolutions and applying data fusion techniques for a frequent monitoring of water use at fine spatial resolution. A global and daily ET product at 5 km resolution, developed with the ALEXI model using MODIS day-night temperature difference (Anderson et al., 2015a) was used as a starting point. The associated flux disaggregation scheme, DisALEXI (Norman et al., 2003), was later applied to constrain higher resolution ET from both MODIS and Landsat 7/8 images. The Climate Forecast System Reanalysis (CFSR) provided the meteorological data. Finally, a data fusion technique, the STARFM model (Gao et al., 2006), was applied to fuse MODIS and Landsat ET maps in order to obtain daily ET at 30 m resolution. These estimates were validated and analyzed at two different scales: at local scale over a dehesa experimental site and at watershed scale with a predominant Mediterranean oak savanna landscape, both located in Southern Spain. Local ET estimates from the modeling system were validated with measurements provided by an eddy covariance tower installed in the dehesa (38 ° 12 'N, 4 ° 17' W, 736 m a.s.l.). The results supported the ability of ALEXI/DisALEXI model to accurately estimate turbulent and radiative fluxes over this complex landscape, both at 1 Km and at 30 m spatial resolution. The application of the STARFM model gave significant improvement in capturing the spatio-temporal heterogeneity of ET over the different seasons, compared with traditional interpolation methods using MODIS and Landsat ET data. At basin scale, the physically-based distributed hydrological model WiMMed has been applied to evaluate ET estimates. This model focuses on the spatial interpolation of the meteorological variables and the physical modelling of the daily water balance at the cell and watershed scale, using daily streamflow rates measured at the watershed outlet for final comparison.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Snapshot hyperspectral fovea vision system (HyperVideo)

NASA Astrophysics Data System (ADS)

Kriesel, Jason; Scriven, Gordon; Gat, Nahum; Nagaraj, Sheela; Willson, Paul; Swaminathan, V.

2012-06-01

The development and demonstration of a new snapshot hyperspectral sensor is described. The system is a significant extension of the four dimensional imaging spectrometer (4DIS) concept, which resolves all four dimensions of hyperspectral imaging data (2D spatial, spectral, and temporal) in real-time. The new sensor, dubbed "4×4DIS" uses a single fiber optic reformatter that feeds into four separate, miniature visible to near-infrared (VNIR) imaging spectrometers, providing significantly better spatial resolution than previous systems. Full data cubes are captured in each frame period without scanning, i.e., "HyperVideo". The current system operates up to 30 Hz (i.e., 30 cubes/s), has 300 spectral bands from 400 to 1100 nm (~2.4 nm resolution), and a spatial resolution of 44×40 pixels. An additional 1.4 Megapixel video camera provides scene context and effectively sharpens the spatial resolution of the hyperspectral data. Essentially, the 4×4DIS provides a 2D spatially resolved grid of 44×40 = 1760 separate spectral measurements every 33 ms, which is overlaid on the detailed spatial information provided by the context camera. The system can use a wide range of off-the-shelf lenses and can either be operated so that the fields of view match, or in a "spectral fovea" mode, in which the 4×4DIS system uses narrow field of view optics, and is cued by a wider field of view context camera. Unlike other hyperspectral snapshot schemes, which require intensive computations to deconvolve the data (e.g., Computed Tomographic Imaging Spectrometer), the 4×4DIS requires only a linear remapping, enabling real-time display and analysis. The system concept has a range of applications including biomedical imaging, missile defense, infrared counter measure (IRCM) threat characterization, and ground based remote sensing.

The scale dependence of optical diversity in a prairie ecosystem

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula.

PubMed

Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula

NASA Astrophysics Data System (ADS)

Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

A Sensitive Method for Examining Whole Cell Biochemical Composition in Single Cells of Filamentous Fungi using Synchrotron FTIR Spectromicroscopy

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

Konstantin,J.; Gough, K.; Julian, R.

2008-01-01

Cell function is related to cell composition. The asexual state of filamentous fungi (molds and mildews) has two main life cycle stages: vegetative hyphae for substrate colonization and nutrient acquisition, and asexual spores for survival and dispersal. Hyphal composition changes over a few tens of microns during growth and maturation; spores are different from hyphae. Most biochemical analyses are restricted to studying a few components at high spatial resolution (e.g. histochemistry) or many compounds at low spatial resolution (e.g. GC-MS). Synchrotron FTIR spectromicroscopy can be used to study fungal cell biology by fingerprinting varieties of carbohydrates, proteins, and lipids atmore » about 6 microm spatial resolution. FTIR can distinguish fungal species and changes during hyphal growth, and reveals that even fungi grown under optimal vs mildly stressed conditions exhibit dramatic biochemical changes without obvious morphological effects. Here we compare hypha and spore composition of two fungi, Neurospora and Rhizopus. There are clear biochemical changes when Neurospora hyphae commit to spore development, during spore maturation and following germination, many of which are consistent with results from molecular genetics, but have not been shown before at high spatial resolution. Rhizopus spores develop within a fluid-containing sporangium that becomes dry at maturity. Rhizopus spores had similar protein content and significantly more carbohydrate than the sporangial fluid, both of which are novel findings.« less

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Black hole mass measurement using molecular gas kinematics: what ALMA can do

NASA Astrophysics Data System (ADS)

Yoon, Ilsang

2017-04-01

We study the limits of the spatial and velocity resolution of radio interferometry to infer the mass of supermassive black holes (SMBHs) in galactic centres using the kinematics of circum-nuclear molecular gas, by considering the shapes of the galaxy surface brightness profile, signal-to-noise ratios (S/Ns) of the position-velocity diagram (PVD) and systematic errors due to the spatial and velocity structure of the molecular gas. We argue that for fixed galaxy stellar mass and SMBH mass, the spatial and velocity scales that need to be resolved increase and decrease, respectively, with decreasing Sérsic index of the galaxy surface brightness profile. We validate our arguments using simulated PVDs for varying beam size and velocity channel width. Furthermore, we consider the systematic effects on the inference of the SMBH mass by simulating PVDs including the spatial and velocity structure of the molecular gas, which demonstrates that their impacts are not significant for a PVD with good S/N unless the spatial and velocity scale associated with the systematic effects are comparable to or larger than the angular resolution and velocity channel width of the PVD from pure circular motion. Also, we caution that a bias in a galaxy surface brightness profile owing to the poor resolution of a galaxy photometric image can largely bias the SMBH mass by an order of magnitude. This study shows the promise and the limits of ALMA observations for measuring SMBH mass using molecular gas kinematics and provides a useful technical justification for an ALMA proposal with the science goal of measuring SMBH mass.

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

Effective resolution concepts for lidar observations

NASA Astrophysics Data System (ADS)

Iarlori, M.; Madonna, F.; Rizi, V.; Trickl, T.; Amodeo, A.

2015-05-01

Since its first establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has been devoted to providing, through its database, exclusively quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or High Spectral Resolution Lidars). As these coefficients are provided in terms of vertical profiles, EARLINET database must also include the details on the range resolution of the submitted data. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly working as low pass filters with the purpose of noise damping. Low pass filters are mathematically described by the Digital Signal Processing (DSP) theory as a convolution sum. As a consequence, this implies that each filter's output, at a given range (or time) in our case, will be the result of a linear combination of several lidar input data relative to different ranges (times) before and after the given range (time): a first hint of loss of resolution of the output signal. The application of filtering processes will also always distort the underlying true profile whose relevant features, like aerosol layers, will then be affected both in magnitude and in spatial extension. Thus, both the removal of noise and the spatial distortion of the true profile produce a reduction of the range resolution. This paper provides the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved starting from lidar data. Large attention has been addressed to provide an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE.

PubMed

Zaretskaya, Natalia; Fischl, Bruce; Reuter, Martin; Renvall, Ville; Polimeni, Jonathan R

2018-01-15

Recent advances in MR technology have enabled increased spatial resolution for routine functional and anatomical imaging, which has created demand for software tools that are able to process these data. The availability of high-resolution data also raises the question of whether higher resolution leads to substantial gains in accuracy of quantitative morphometric neuroimaging procedures, in particular the cortical surface reconstruction and cortical thickness estimation. In this study we adapted the FreeSurfer cortical surface reconstruction pipeline to process structural data at native submillimeter resolution. We then quantified the differences in surface placement between meshes generated from (0.75 mm) 3 isotropic resolution data acquired in 39 volunteers and the same data downsampled to the conventional 1 mm 3 voxel size. We find that when processed at native resolution, cortex is estimated to be thinner in most areas, but thicker around the Cingulate and the Calcarine sulci as well as in the posterior bank of the Central sulcus. Thickness differences are driven by two kinds of effects. First, the gray-white surface is found closer to the white matter, especially in cortical areas with high myelin content, and thus low contrast, such as the Calcarine and the Central sulci, causing local increases in thickness estimates. Second, the gray-CSF surface is placed more interiorly, especially in the deep sulci, contributing to local decreases in thickness estimates. We suggest that both effects are due to reduced partial volume effects at higher spatial resolution. Submillimeter voxel sizes can therefore provide improved accuracy for measuring cortical thickness. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

PubMed

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

2018-09-01

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

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.

Nonlinear ultrasonic imaging with X wave

NASA Astrophysics Data System (ADS)

Du, Hongwei; Lu, Wei; Feng, Huanqing

2009-10-01

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

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

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.

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

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

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.

Theory of a Quantum Scanning Microscope for Cold Atoms

NASA Astrophysics Data System (ADS)

Yang, D.; Laflamme, C.; Vasilyev, D. V.; Baranov, M. A.; Zoller, P.

2018-03-01

We propose and analyze a scanning microscope to monitor "live" the quantum dynamics of cold atoms in a cavity QED setup. The microscope measures the atomic density with subwavelength resolution via dispersive couplings to a cavity and homodyne detection within the framework of continuous measurement theory. We analyze two modes of operation. First, for a fixed focal point the microscope records the wave packet dynamics of atoms with time resolution set by the cavity lifetime. Second, a spatial scan of the microscope acts to map out the spatial density of stationary quantum states. Remarkably, in the latter case, for a good cavity limit, the microscope becomes an effective quantum nondemolition device, such that the spatial distribution of motional eigenstates can be measured backaction free in single scans, as an emergent quantum nondemolition measurement.

Theory of a Quantum Scanning Microscope for Cold Atoms.

PubMed

Yang, D; Laflamme, C; Vasilyev, D V; Baranov, M A; Zoller, P

2018-03-30

We propose and analyze a scanning microscope to monitor "live" the quantum dynamics of cold atoms in a cavity QED setup. The microscope measures the atomic density with subwavelength resolution via dispersive couplings to a cavity and homodyne detection within the framework of continuous measurement theory. We analyze two modes of operation. First, for a fixed focal point the microscope records the wave packet dynamics of atoms with time resolution set by the cavity lifetime. Second, a spatial scan of the microscope acts to map out the spatial density of stationary quantum states. Remarkably, in the latter case, for a good cavity limit, the microscope becomes an effective quantum nondemolition device, such that the spatial distribution of motional eigenstates can be measured backaction free in single scans, as an emergent quantum nondemolition measurement.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

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.

Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

2015-01-01

The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite

PubMed Central

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

2015-01-01

The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN usingimages of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN. PMID:26447470

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.

Effects of Drake Passage on a strongly eddying global ocean

NASA Astrophysics Data System (ADS)

Viebahn, Jan; von der Heydt, Anna S.; Dijkstra, Henk A.

2015-04-01

During the past 65 Million (Ma) years, Earth's climate has undergone a major change from warm 'greenhouse' to colder 'icehouse' conditions with extensive ice sheets in the polar regions of both hemispheres. The Eocene-Oligocene (~34 Ma) and Oligocene-Miocene (~23 Ma) boundaries reflect major transitions in Cenozoic global climate change. Proposed mechanisms of these transitions include reorganization of ocean circulation due to critical gateway opening/deepening, changes in atmospheric CO2-concentration, and feedback mechanisms related to land-ice formation. Drake Passage (DP) is an intensively studied gateway because it plays a central role in closing the transport pathways of heat and chemicals in the ocean. The climate response to a closed DP has been explored with a variety of general circulation models, however, all of these models employ low model-grid resolutions such that the effects of subgrid-scale fluctuations ('eddies') are parameterized. We present results of the first high-resolution (0.1° horizontally) realistic global ocean model simulation with a closed DP in which the eddy field is largely resolved. The simulation extends over more than 200 years such that the strong transient adjustment process is passed and a near-equilibrium ocean state is reached. The effects of DP are diagnosed by comparing with both an open DP high-resolution control simulation (of same length) and corresponding low-resolution simulations. By focussing on the heat/tracer transports we demonstrate that the results are twofold: Considering spatially integrated transports the overall response to a closed DP is well captured by low-resolution simulations. However, looking at the actual spatial distributions drastic differences appear between far-scattered high-resolution and laminar-uniform low-resolution fields. We conclude that sparse and highly localized tracer proxy observations have to be interpreted carefully with the help of high-resolution model simulations.

CdS nanorods/organic hybrid LED array and the piezo-phototronic effect of the device for pressure mapping.

PubMed

Bao, Rongrong; Wang, Chunfeng; Dong, Lin; Shen, Changyu; Zhao, Kun; Pan, Caofeng

2016-04-21

As widely applied in light-emitting diodes and optical devices, CdS has attracted the attention of many researchers due to its nonlinear properties and piezo-electronic effect. Here, we demonstrate a LED array composed of PSS and CdS nanorods and research the piezo-photonic effect of the array device. The emission intensity of the device depends on the electron-hole recombination at the interface of the p-n junction which can be adjusted using the piezo-phototronic effect and can be used to map the pressure applied on the surface of the device with spatial resolution as high as 1.5 μm. A flexible LED device array has been prepared using a CdS nanorod array on a Au/Cr/kapton substrate. This device may be used in the field of strain mapping using its high pressure spatial-resolution and flexibility.

Towards the Optimal Pixel Size of dem for Automatic Mapping of Landslide Areas

NASA Astrophysics Data System (ADS)

Pawłuszek, K.; Borkowski, A.; Tarolli, P.

2017-05-01

Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1 m, 2 m, 5 m and 10 m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1 m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5 m DEM-resolution for FFNN and 1 m DEM resolution for results. The best performance was found to be using 5 m DEM-resolution for FFNN and 1 m DEM resolution for ML classification.

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

PubMed Central

Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

2018-01-01

Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

PubMed

Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

2018-06-01

The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

Effects of Digitization and JPEG Compression on Land Cover Classification Using Astronaut-Acquired Orbital Photographs

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Webb, Edward L.; Evangelista, Arlene

2000-01-01

Studies that utilize astronaut-acquired orbital photographs for visual or digital classification require high-quality data to ensure accuracy. The majority of images available must be digitized from film and electronically transferred to scientific users. This study examined the effect of scanning spatial resolution (1200, 2400 pixels per inch [21.2 and 10.6 microns/pixel]), scanning density range option (Auto, Full) and compression ratio (non-lossy [TIFF], and lossy JPEG 10:1, 46:1, 83:1) on digital classification results of an orbital photograph from the NASA - Johnson Space Center archive. Qualitative results suggested that 1200 ppi was acceptable for visual interpretive uses for major land cover types. Moreover, Auto scanning density range was superior to Full density range. Quantitative assessment of the processing steps indicated that, while 2400 ppi scanning spatial resolution resulted in more classified polygons as well as a substantially greater proportion of polygons < 0.2 ha, overall agreement between 1200 ppi and 2400 ppi was quite high. JPEG compression up to approximately 46:1 also did not appear to have a major impact on quantitative classification characteristics. We conclude that both 1200 and 2400 ppi scanning resolutions are acceptable options for this level of land cover classification, as well as a compression ratio at or below approximately 46:1. Auto range density should always be used during scanning because it acquires more of the information from the film. The particular combination of scanning spatial resolution and compression level will require a case-by-case decision and will depend upon memory capabilities, analytical objectives and the spatial properties of the objects in the image.

Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Hayashi, Toshiyuki; Kato, Toshinori; Okada, Eiji

2004-06-01

Near-infrared (NIR) topography can obtain a topographical distribution of the activated region in the brain cortex. Near-infrared light is strongly scattered in the head, and the volume of tissue sampled by a source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. In this study, a one-dimensional distribution of absorption change in a head model is calculated by mapping and reconstruction methods to evaluate the effect of the image reconstruction algorithm and the interval of measurement points for topographic imaging on the accuracy of the topographic image. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The measurement points are one-dimensionally arranged on the surface of the model, and the distance between adjacent measurement points is varied from 4 mm to 28 mm. Small intervals of the measurement points improve the topographic image calculated by both the mapping and reconstruction methods. In the conventional mapping method, the limit of the spatial resolution depends upon the interval of the measurement points and spatial sensitivity profile for source-detector pairs. The reconstruction method has advantages over the mapping method which improve the results of one-dimensional analysis when the interval of measurement points is less than 12 mm. The effect of overlapping of spatial sensitivity profiles indicates that the reconstruction method may be effective to improve the spatial resolution of a two-dimensional reconstruction of topographic image obtained with larger interval of measurement points. Near-infrared topography with the reconstruction method potentially obtains an accurate distribution of absorption change in the brain even if the size of absorption change is less than 10 mm.

Constraining regional scale carbon budgets at the US West Coast using a high-resolution atmospheric inverse modeling approach

NASA Astrophysics Data System (ADS)

Goeckede, M.; Michalak, A. M.; Vickers, D.; Turner, D.; Law, B.

2009-04-01

The study presented is embedded within the NACP (North American Carbon Program) West Coast project ORCA2, which aims at determining the regional carbon balance of the US states Oregon, California and Washington. Our work specifically focuses on the effect of disturbance history and climate variability, aiming at improving our understanding of e.g. drought stress and stand age on carbon sources and sinks in complex terrain with fine-scale variability in land cover types. The ORCA2 atmospheric inverse modeling approach has been set up to capture flux variability on the regional scale at high temporal and spatial resolution. Atmospheric transport is simulated coupling the mesoscale model WRF (Weather Research and Forecast) with the STILT (Stochastic Time Inverted Lagrangian Transport) footprint model. This setup allows identifying sources and sinks that influence atmospheric observations with highly resolved mass transport fields and realistic turbulent mixing. Terrestrial biosphere carbon fluxes are simulated at spatial resolutions of up to 1km and subdaily timesteps, considering effects of ecoregion, land cover type and disturbance regime on the carbon budgets. Our approach assimilates high-precision atmospheric CO2 concentration measurements and eddy-covariance data from several sites throughout the model domain, as well as high-resolution remote sensing products (e.g. LandSat, MODIS) and interpolated surface meteorology (DayMet, SOGS, PRISM). We present top-down modeling results that have been optimized using Bayesian inversion, reflecting the information on regional scale carbon processes provided by the network of high-precision CO2 observations. We address the level of detail (e.g. spatial and temporal resolution) that can be resolved by top-down modeling on the regional scale, given the uncertainties introduced by various sources for model-data mismatch. Our results demonstrate the importance of accurate modeling of carbon-water coupling, with the representation of water availability and drought stress playing a dominant role to capture spatially variable CO2 exchange rates in a region characterized by strong climatic gradients.

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 wavefront control of high-power laser systems

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

Brase, J; Brown, C; Carrano, C

1999-07-08

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

Impacts of rainfall spatial variability on hydrogeological response

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

NASA Technical Reports Server (NTRS)

Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.

2006-01-01

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

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

Spatial resolution of pace mapping of idiopathic ventricular tachycardia/ectopy originating in the right ventricular outflow tract.

PubMed

Bogun, Frank; Taj, Majid; Ting, Michael; Kim, Hyungjin Myra; Reich, Stephen; Good, Eric; Jongnarangsin, Krit; Chugh, Aman; Pelosi, Frank; Oral, Hakan; Morady, Fred

2008-03-01

Pace mapping has been used to identify the site of origin of focal ventricular arrhythmias. The spatial resolution of pace mapping has not been adequately quantified using currently available three-dimensional mapping systems. The purpose of this study was to determine the spatial resolution of pace mapping in patients with idiopathic ventricular tachycardia or premature ventricular contractions originating in the right ventricular outflow tract. In 16 patients with idiopathic ventricular tachycardia/ectopy from the right ventricular outflow tract, comparisons and classifications of pace maps were performed by two observers (good pace map: match >10/12 leads; inadequate pace map: match < or =10/12 leads) and a customized MATLAB 6.0 program (assessing correlation coefficient and normalized root mean square of the difference (nRMSd) between test and template signals). With an electroanatomic mapping system, the correlation coefficient of each pace map was correlated with the distance between the pacing site and the effective ablation site. The endocardial area within the 10-ms activation isochrone was measured. The ablation procedure was effective in all patients. Sites with good pace maps had a higher correlation coefficient and lower nRMSd than sites with inadequate pace maps (correlation coefficient: 0.96 +/- 0.03 vs 0.76 +/- 0.18, P <.0001; nRMSd: 0.41 +/- 0.16 vs 0.89 +/- 0.39, P <.0001). Using receiver operating characteristic curves, appropriate cutoff values were >0.94 for correlation coefficient (sensitivity 81%, specificity 89%) and < or =0.54 for nRMSd (sensitivity 76%, specificity 80%). Good pace maps were located a mean of 7.3 +/- 5.0 mm from the effective ablation site and had a mean activation time of -24 +/- 7 ms. However, in 3 (18%) of 16 patients, the best pace map was inadequate at the effective ablation site, with an endocardial activation time at these sites of -25 +/- 12 ms. Pace maps with correlation coefficient > or =0.94 were confined to an area of 1.8 +/- 0.6 cm2. The 10-ms isochrone measured 1.2 +/- 0.7 cm2. The spatial resolution of a good pace map for targeting ventricular tachycardia/ectopy is 1.8 cm2 in the right ventricular outflow tract and therefore is inferior to the spatial resolution of activation mapping as assessed by isochronal activation. In approximately 20% of patients, pace mapping is unreliable in identifying the site of origin, possibly due a deeper site of origin and preferential conduction via fibers connecting the focus to the endocardial surface.

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.

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

PubMed

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

2018-02-12

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

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

PubMed Central

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

2018-01-01

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

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. 

A compact large-format streak tube for imaging lidar

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

NASA Astrophysics Data System (ADS)

Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

2018-06-01

The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

Effects of electrode size and spacing on sensory modalities in the phantom thumb perception area for the forearm amputees.

PubMed

Li, P; Chai, G H; Zhu, K H; Lan, N; Sui, X H

2015-01-01

Tactile sensory feedback plays a key role in accomplishing the dexterous manipulation of prosthetic hands for the amputees, and the non-invasive transcutaneous electrical nerve stimulation (TENS) of the phantom finger perception (PFP) area would be an effective way to realize sensory feedback clinically. In order to realize the high-spatial-resolution tactile sensory feedback in the PFP region, we investigated the effects of electrode size and spacing on the tactile sensations for potentially optimizing the surface electrode array configuration. Six forearm-amputated subjects were recruited in the psychophysical studies. With the diameter of the circular electrode increasing from 3 mm to 12 mm, the threshold current intensity was enhanced correspondingly under different sensory modalities. The smaller electrode could potentially lead to high sensation spatial resolution. Whereas, the smaller the electrode, the less the number of sensory modalities. For an Φ-3 mm electrode, it is even hard for the subject to perceive any perception modalities under normal stimulating current. In addition, the two-electrode discrimination distance (TEDD) in the phantom thumb perception area decreased with electrode size decreasing in two directions of parallel or perpendicular to the forearm. No significant difference of TEDD existed along the two directions. Studies in this paper would guide the configuration optimization of the TENS electrode array for potential high spatial-resolution sensory feedback.

Vapor cell geometry effect on Rydberg atom-based microwave electric field measurement

NASA Astrophysics Data System (ADS)

Zhang, Linjie; Liu, Jiasheng; Jia, Yue; Zhang, Hao; Song, Zhenfei; Jia, Suotang

2018-03-01

The geometry effect of a vapor cell on the metrology of a microwave electric field is investigated. Based on the splitting of the electromagnetically induced transparency spectra of cesium Rydberg atoms in a vapor cell, high-resolution spatial distribution of the microwave electric field strength is achieved for both a cubic cell and a cylinder cell. The spatial distribution of the microwave field strength in two dimensions is measured with sub-wavelength resolution. The experimental results show that the shape of a vapor cell has a significant influence on the abnormal spatial distribution because of the Fabry–Pérot effect inside a vapor cell. A theoretical simulation is obtained for different vapor cell wall thicknesses and shows that a restricted wall thickness results in a measurement fluctuation smaller than 3% at the center of the vapor cell. Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA03044200 and 2016YFF0200104), the National Natural Science Foundation of China (Grant Nos. 91536110, 61505099, and 61378013), and the Fund for Shanxi “331 Project” Key Subjects Construction, China.

Effect of Downscaled Forcings and Soil Texture Properties on Hyperresolution Hydrologic Simulations in a Regional Basin in Northwest Mexico

NASA Astrophysics Data System (ADS)

Ko, A.; Mascaro, G.; Vivoni, E. R.

2017-12-01

Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.

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.

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.

High-resolution room-temperature sample scanning superconducting quantum interference device microscope configurable for geological and biomagnetic applications

NASA Astrophysics Data System (ADS)

Fong, L. E.; Holzer, J. R.; McBride, K. K.; Lima, E. A.; Baudenbacher, F.; Radparvar, M.

2005-05-01

We have developed a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with submillimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensors are mounted on the tip of a sapphire and thermally anchored to the helium reservoir. A 25μm sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows us to adjust the sample-to-sensor spacing from the top of the Dewar. We achieved a sensor-to-sample spacing of 100μm, which could be maintained for periods of up to four weeks. Different SQUID sensor designs are necessary to achieve the best combination of spatial resolution and field sensitivity for a given source configuration. For imaging thin sections of geological samples, we used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80μm, and achieved a field sensitivity of 1.5pT/Hz1/2 and a magnetic moment sensitivity of 5.4×10-18Am2/Hz1/2 at a sensor-to-sample spacing of 100μm in the white noise region for frequencies above 100Hz. Imaging action currents in cardiac tissue requires a higher field sensitivity, which can only be achieved by compromising spatial resolution. We developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250μm to 1mm, and achieved sensitivities of 480-180fT /Hz1/2 in the white noise region for frequencies above 100Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

BLIPPED (BLIpped Pure Phase EncoDing) high resolution MRI with low amplitude gradients

NASA Astrophysics Data System (ADS)

Xiao, Dan; Balcom, Bruce J.

2017-12-01

MRI image resolution is proportional to the maximum k-space value, i.e. the temporal integral of the magnetic field gradient. High resolution imaging usually requires high gradient amplitudes and/or long spatial encoding times. Special gradient hardware is often required for high amplitudes and fast switching. We propose a high resolution imaging sequence that employs low amplitude gradients. This method was inspired by the previously proposed PEPI (π Echo Planar Imaging) sequence, which replaced EPI gradient reversals with multiple RF refocusing pulses. It has been shown that when the refocusing RF pulse is of high quality, i.e. sufficiently close to 180°, the magnetization phase introduced by the spatial encoding magnetic field gradient can be preserved and transferred to the following echo signal without phase rewinding. This phase encoding scheme requires blipped gradients that are identical for each echo, with low and constant amplitude, providing opportunities for high resolution imaging. We now extend the sequence to 3D pure phase encoding with low amplitude gradients. The method is compared with the Hybrid-SESPI (Spin Echo Single Point Imaging) technique to demonstrate the advantages in terms of low gradient duty cycle, compensation of concomitant magnetic field effects and minimal echo spacing, which lead to superior image quality and high resolution. The 3D imaging method was then applied with a parallel plate resonator RF probe, achieving a nominal spatial resolution of 17 μm in one dimension in the 3D image, requiring a maximum gradient amplitude of only 5.8 Gauss/cm.

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.

Effects of speckle/pixel size ratio on temporal and spatial speckle-contrast analysis of dynamic scattering systems: Implications for measurements of blood-flow dynamics.

PubMed

Ramirez-San-Juan, J C; Mendez-Aguilar, E; Salazar-Hermenegildo, N; Fuentes-Garcia, A; Ramos-Garcia, R; Choi, B

2013-01-01

Laser Speckle Contrast Imaging (LSCI) is an optical technique used to generate blood flow maps with high spatial and temporal resolution. It is well known that in LSCI, the speckle size must exceed the Nyquist criterion to maximize the speckle's pattern contrast. In this work, we study experimentally the effect of speckle-pixel size ratio not only in dynamic speckle contrast, but also on the calculation of the relative flow speed for temporal and spatial analysis. Our data suggest that the temporal LSCI algorithm is more accurate at assessing the relative changes in flow speed than the spatial algorithm.

Requirements Engineering for inter-organizational health information systems with functions for spatial analyses: modeling a WHO safe community applying Use Case Maps.

PubMed

Olvingson, C; Hallberg, N; Timpka, T; Lindqvist, K

2002-01-01

To evaluate Use Case Maps (UCMs) as a technique for Requirements Engineering (RE) in the development of information systems with functions for spatial analyses in inter-organizational public health settings. In this study, Participatory Action Research (PAR) is used to explore the UCM notation for requirements elicitation and to gather the opinions of the users. The Delphi technique is used to reach consensus in the construction of UCMs. The results show that UCMs can provide a visualization of the system's functionality and in combination with PAR provide a sound basis for gathering requirements in inter-organizational settings. UCMs were found to represent a suitable level for describing the organization and the dynamic flux of information including spatial resolution to all stakeholders. Moreover, by using PAR, the voices of the users and their tacit knowledge is intercepted. Further, UCMs are found useful in generating intuitive requirements by the creation of use cases. With UCMs and PAR it is possible to study the effects of design changes in the general information display and the spatial resolution in the same context. Both requirements on the information system in general and the functions for spatial analyses are possible to elicit when identifying the different responsibilities and the demands on spatial resolution associated to the actions of each administrative unit. However, the development process of UCM is not well documented and needs further investigation and formulation of guidelines.

Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

NASA Astrophysics Data System (ADS)

Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

2016-10-01

Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

3D noninvasive ultrasound Joule heat tomography based on acousto-electric effect using unipolar pulses: a simulation study

PubMed Central

Yang, Renhuan; Li, Xu; Song, Aiguo; He, Bin; Yan, Ruqiang

2012-01-01

Electrical properties of biological tissues are highly sensitive to their physiological and pathological status. Thus it is of importance to image electrical properties of biological tissues. However, spatial resolution of conventional electrical impedance tomography (EIT) is generally poor. Recently, hybrid imaging modalities combining electric conductivity contrast and ultrasonic resolution based on acouto-electric effect has attracted considerable attention. In this study, we propose a novel three-dimensional (3D) noninvasive ultrasound Joule heat tomography (UJHT) approach based on acouto-electric effect using unipolar ultrasound pulses. As the Joule heat density distribution is highly dependent on the conductivity distribution, an accurate and high resolution mapping of the Joule heat density distribution is expected to give important information that is closely related to the conductivity contrast. The advantages of the proposed ultrasound Joule heat tomography using unipolar pulses include its simple inverse solution, better performance than UJHT using common bipolar pulses and its independence of any priori knowledge of the conductivity distribution of the imaging object. Computer simulation results show that using the proposed method, it is feasible to perform a high spatial resolution Joule heat imaging in an inhomogeneous conductive media. Application of this technique on tumor scanning is also investigated by a series of computer simulations. PMID:23123757

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.

Cross-Sectional Transport Imaging in a Multijunction Solar Cell

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

Haegel, Nancy M.; Ke, Chi-Wen; Taha, Hesham

2015-06-14

Combining highly localized electron-beam excitation at a point with the spatial resolution capability of optical near-field imaging, we have imaged carrier transport in a cross-sectioned multijunction (GaInP/GaInAs/Ge) solar cell. We image energy transport associated with carrier diffusion throughout the full width of the middle (GaInAs) cell and luminescent coupling from point excitation in the top cell GaInP to the middle cell. Supporting cathodoluminescence and near-field photoluminescence measurements demonstrate excitation-dependent Fermi level splitting effects that influence cross-sectioned spectroscopy results as well as transport limitations on the spatial resolution of cross-sectional measurements.

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.

MWIR imaging spectrometer with digital time delay integration for remote sensing and characterization of solar system objects

NASA Astrophysics Data System (ADS)

Kendrick, Stephen E.; Harwit, Alex; Kaplan, Michael; Smythe, William D.

2007-09-01

An MWIR TDI (Time Delay and Integration) Imager and Spectrometer (MTIS) instrument for characterizing from orbit the moons of Jupiter and Saturn is proposed. Novel to this instrument is the planned implementation of a digital TDI detector array and an innovative imaging/spectroscopic architecture. Digital TDI enables a higher SNR for high spatial resolution surface mapping of Titan and Enceladus and for improved spectral discrimination and resolution at Europa. The MTIS imaging/spectroscopic architecture combines a high spatial resolution coarse wavelength resolution imaging spectrometer with a hyperspectral sensor to spectrally decompose a portion of the data adjacent to the data sampled in the imaging spectrometer. The MTIS instrument thus maps with high spatial resolution a planetary object while spectrally decomposing enough of the data that identification of the constituent materials is highly likely. Additionally, digital TDI systems have the ability to enable the rejection of radiation induced spikes in high radiation environments (Europa) and the ability to image in low light levels (Titan and Enceladus). The ability to image moving objects that might be missed utilizing a conventional TDI system is an added advantage and is particularly important for characterizing atmospheric effects and separating atmospheric and surface components. This can be accomplished with on-orbit processing or collecting and returning individual non co-added frames.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2014-12-15

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

Mars-solar wind interaction: LatHyS, an improved parallel 3-D multispecies hybrid model

NASA Astrophysics Data System (ADS)

Modolo, Ronan; Hess, Sebastien; Mancini, Marco; Leblanc, Francois; Chaufray, Jean-Yves; Brain, David; Leclercq, Ludivine; Esteban-Hernández, Rosa; Chanteur, Gerard; Weill, Philippe; González-Galindo, Francisco; Forget, Francois; Yagi, Manabu; Mazelle, Christian

2016-07-01

In order to better represent Mars-solar wind interaction, we present an unprecedented model achieving spatial resolution down to 50 km, a so far unexplored resolution for global kinetic models of the Martian ionized environment. Such resolution approaches the ionospheric plasma scale height. In practice, the model is derived from a first version described in Modolo et al. (2005). An important effort of parallelization has been conducted and is presented here. A better description of the ionosphere was also implemented including ionospheric chemistry, electrical conductivities, and a drag force modeling the ion-neutral collisions in the ionosphere. This new version of the code, named LatHyS (Latmos Hybrid Simulation), is here used to characterize the impact of various spatial resolutions on simulation results. In addition, and following a global model challenge effort, we present the results of simulation run for three cases which allow addressing the effect of the suprathermal corona and of the solar EUV activity on the magnetospheric plasma boundaries and on the global escape. Simulation results showed that global patterns are relatively similar for the different spatial resolution runs, but finest grid runs provide a better representation of the ionosphere and display more details of the planetary plasma dynamic. Simulation results suggest that a significant fraction of escaping O+ ions is originated from below 1200 km altitude.

Area-based tests for association between spatial patterns

NASA Astrophysics Data System (ADS)

Maruca, Susan L.; Jacquez, Geoffrey M.

Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new ``spatially explicit'' techniques provide information and insights that cannot be obtained from the spectral information alone.

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.

Magneto-optical imaging of thin magnetic films using spins in diamond

NASA Astrophysics Data System (ADS)

Simpson, David A.; Tetienne, Jean-Philippe; McCoey, Julia M.; Ganesan, Kumaravelu; Hall, Liam T.; Petrou, Steven; Scholten, Robert E.; Hollenberg, Lloyd C. L.

2016-03-01

Imaging the fields of magnetic materials provides crucial insight into the physical and chemical processes surrounding magnetism, and has been a key ingredient in the spectacular development of magnetic data storage. Existing approaches using the magneto-optic Kerr effect, x-ray and electron microscopy have limitations that constrain further development, and there is increasing demand for imaging and characterisation of magnetic phenomena in real time with high spatial resolution. Here we show how the magneto-optical response of an array of negatively-charged nitrogen-vacancy spins in diamond can be used to image and map the sub-micron stray magnetic field patterns from thin ferromagnetic films. Using optically detected magnetic resonance, we demonstrate wide-field magnetic imaging over 100 × 100 μm2 with sub-micron spatial resolution at video frame rates, under ambient conditions. We demonstrate an all-optical spin relaxation contrast imaging approach which can image magnetic structures in the absence of an applied microwave field. Straightforward extensions promise imaging with sub-μT sensitivity and sub-optical spatial and millisecond temporal resolution. This work establishes practical diamond-based wide-field microscopy for rapid high-sensitivity characterisation and imaging of magnetic samples, with the capability for investigating magnetic phenomena such as domain wall and skyrmion dynamics and the spin Hall effect in metals.

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

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.

Interrogating Surface Functional Group Heterogeneity of Activated Thermoplastics Using Super-Resolution Fluorescence Microscopy.

PubMed

ONeil, Colleen E; Jackson, Joshua M; Shim, Sang-Hee; Soper, Steven A

2016-04-05

We present a novel approach for characterizing surfaces utilizing super-resolution fluorescence microscopy with subdiffraction limit spatial resolution. Thermoplastic surfaces were activated by UV/O3 or O2 plasma treatment under various conditions to generate pendant surface-confined carboxylic acids (-COOH). These surface functional groups were then labeled with a photoswitchable dye and interrogated using single-molecule, localization-based, super-resolution fluorescence microscopy to elucidate the surface heterogeneity of these functional groups across the activated surface. Data indicated nonuniform distributions of these functional groups for both COC and PMMA thermoplastics with the degree of heterogeneity being dose dependent. In addition, COC demonstrated relative higher surface density of functional groups compared to PMMA for both UV/O3 and O2 plasma treatment. The spatial distribution of -COOH groups secured from super-resolution imaging were used to simulate nonuniform patterns of electroosmotic flow in thermoplastic nanochannels. Simulations were compared to single-particle tracking of fluorescent nanoparticles within thermoplastic nanoslits to demonstrate the effects of surface functional group heterogeneity on the electrokinetic transport process.

Sharpening method of satellite thermal image based on the geographical statistical model

NASA Astrophysics Data System (ADS)

Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

2016-04-01

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

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.

Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager

DOE PAGES

Nagayama, T.; Mancini, R. C.; Mayes, D.; ...

2015-11-18

Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. In this paper, we synthetically quantify the accuracymore » of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ~6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ~10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. Finally, it is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.« less

Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager

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

Nagayama, T.; Mancini, R. C.; Mayes, D.

2015-11-15

Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of imagesmore » and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.« less

Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager.

PubMed

Nagayama, T; Mancini, R C; Mayes, D; Tommasini, R; Florido, R

2015-11-01

Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.

A device to measure the effects of strong magnetic fields on the image resolution of PET scanners

NASA Astrophysics Data System (ADS)

Burdette, D.; Albani, D.; Chesi, E.; Clinthorne, N. H.; Cochran, E.; Honscheid, K.; Huh, S. S.; Kagan, H.; Knopp, M.; Lacasta, C.; Mikuz, M.; Schmalbrock, P.; Studen, A.; Weilhammer, P.

2009-10-01

Very high resolution images can be achieved in small animal PET systems utilizing solid state silicon pad detectors. As these systems approach sub-millimeter resolutions, the range of the positron is becoming the dominant contribution to image blur. The size of the positron range effect depends on the initial positron energy and hence the radioactive tracer used. For higher energy positron emitters, such as Ga68 and Tc94m, which are gaining importance in small animal studies, the width of the annihilation point distribution dominates the spatial resolution. This positron range effect can be reduced by embedding the field of view of the PET scanner in a strong magnetic field. In order to confirm this effect experimentally, we developed a high resolution PET instrument based on silicon pad detectors that can operate in a 7 T magnetic field. In this paper, we describe the instrument and present initial results of a study of the effects of magnetic fields up to 7 T on PET image resolution for Na22 and Ga68 point sources.

Spatial resolution and measurement uncertainty of strains in bone and bone-cement interface using digital volume correlation.

PubMed

Zhu, Ming-Liang; Zhang, Qing-Hang; Lupton, Colin; Tong, Jie

2016-04-01

The measurement uncertainty of strains has been assessed in a bone analogue (sawbone), bovine trabecular bone and bone-cement interface specimens under zero load using the Digital Volume Correlation (DVC) method. The effects of sub-volume size, sample constraint and preload on the measured strain uncertainty have been examined. There is generally a trade-off between the measurement uncertainty and the spatial resolution. Suitable sub-volume sizes have been be selected based on a compromise between the measurement uncertainty and the spatial resolution of the cases considered. A ratio of sub-volume size to a microstructure characteristic (Tb.Sp) was introduced to reflect a suitable spatial resolution, and the measurement uncertainty associated was assessed. Specifically, ratios between 1.6 and 4 appear to give rise to standard deviations in the measured strains between 166 and 620 με in all the cases considered, which would seem to suffice for strain analysis in pre as well as post yield loading regimes. A microscale finite element (μFE) model was built from the CT images of the sawbone, and the results from the μFE model and a continuum FE model were compared with those from the DVC. The strain results were found to differ significantly between the two methods at tissue level, consistent in trend with the results found in human bones, indicating mainly a limitation of the current DVC method in mapping strains at this level. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-08-01

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

Development and Applications of a New, High-Resolution, Operational MISR Aerosol Product

NASA Astrophysics Data System (ADS)

Garay, M. J.; Diner, D. J.; Kalashnikova, O.

2014-12-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the operational MISR algorithm performs well, with about 75% of MISR AOD retrievals falling within 0.05 or 20% × AOD of the paired validation data from the ground-based Aerosol Robotic Network (AERONET), and is able to distinguish aerosol particles by size and sphericity, over both land and water. These attributes enable a variety of applications, including aerosol transport model validation and global air quality assessment. Motivated by the adverse impacts of aerosols on human health at the local level, and taking advantage of computational speed advances that have occurred since the launch of Terra, we have implemented an operational MISR aerosol product with 4.4 km spatial resolution that maintains, and sometimes improves upon, the quality of the 17.6 km resolution product. We will describe the performance of this product relative to the heritage 17.6 km product, the global AERONET validation network, and high spatial density AERONET-DRAGON sites. Other changes that simplify product content, and make working with the data much easier for users, will also be discussed. Examples of how the new product demonstrates finer spatial variability of aerosol fields than previously retrieved, and ways this new dataset can be used for studies of local aerosol effects, will be shown.

Single-photon semiconductor photodiodes for distributed optical fiber sensors: state of the art and perspectives

NASA Astrophysics Data System (ADS)

Ripamonti, Giancarlo; Lacaita, Andrea L.

1993-03-01

The extreme sensitivity and time resolution of Geiger-mode avalanche photodiodes (GM- APDs) have already been exploited for optical time domain reflectometry (OTDR). Better than 1 cm spatial resolution in Rayleigh scattering detection was demonstrated. Distributed and quasi-distributed optical fiber sensors can take advantage of the capabilities of GM-APDs. Extensive studies have recently disclosed the main characteristics and limitations of silicon devices, both commercially available and developmental. In this paper we report an analysis of the performance of these detectors. The main characteristics of GM-APDs of interest for distributed optical fiber sensors are briefly reviewed. Command electronics (active quenching) is then introduced. The detector timing performance sets the maximum spatial resolution in experiments employing OTDR techniques. We highlight that the achievable time resolution depends on the physics of the avalanche spreading over the device area. On the basis of these results, trade-off between the important parameters (quantum efficiency, time resolution, background noise, and afterpulsing effects) is considered. Finally, we show first results on Germanium devices, capable of single photon sensitivity at 1.3 and 1.5 micrometers with sub- nanosecond time resolution.

Impact of spatial resolution on cirrus infrared satellite retrievals in the presence of cloud heterogeneity

NASA Astrophysics Data System (ADS)

Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.

2015-12-01

Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography

PubMed Central

Leblond, Frederic; Tichauer, Kenneth M.; Pogue, Brian W.

2010-01-01

The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial resolution and singular data mode frequency as a function of singular mode. In the present study, these metrics are used to analyze the effects of different sources of noise and model errors as related to image quality in the form of spatial resolution and contrast recovery. The image quality is demonstrated to be inherently noise-limited even when detection geometries were increased in complexity to allow maximal tissue sampling, suggesting that detection noise characteristics outweigh detection geometry for achieving optimal reconstructions. PMID:21258566

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

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

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

Enhanced Sensitivity for High Spatial Resolution Lipid Analysis by Negative Ion Mode MALDI Imaging Mass Spectrometry

PubMed Central

Angel, Peggi M.; Spraggins, Jeffrey M.; Baldwin, H. Scott; Caprioli, Richard

2012-01-01

We have achieved enhanced lipid imaging to a ~10 μm spatial resolution using negative ion mode matrix assisted laser desorption ionization (MALDI) imaging mass spectrometry, sublimation of 2,5-dihydroxybenzoic acid as the MALDI matrix and a sample preparation protocol that uses aqueous washes. We report on the effect of treating tissue sections by washing with volatile buffers at different pHs prior to negative ion mode lipid imaging. The results show that washing with ammonium formate, pH 6.4, or ammonium acetate, pH 6.7, significantly increases signal intensity and number of analytes recorded from adult mouse brain tissue sections. Major lipid species measured were glycerophosphoinositols, glycerophosphates, glycerolphosphoglycerols, glycerophosphoethanolamines, glycerophospho-serines, sulfatides, and gangliosides. Ion images from adult mouse brain sections that compare washed and unwashed sections are presented and show up to fivefold increases in ion intensity for washed tissue. The sample preparation protocol has been found to be applicable across numerous organ types and significantly expands the number of lipid species detectable by imaging mass spectrometry at high spatial resolution. PMID:22243218

Towards sub-nanometer real-space observation of spin and orbital magnetism at the Fe/MgO interface

PubMed Central

Thersleff, Thomas; Muto, Shunsuke; Werwiński, Mirosław; Spiegelberg, Jakob; Kvashnin, Yaroslav; Hjӧrvarsson, Björgvin; Eriksson, Olle; Rusz, Ján; Leifer, Klaus

2017-01-01

While the performance of magnetic tunnel junctions based on metal/oxide interfaces is determined by hybridization, charge transfer, and magnetic properties at the interface, there are currently only limited experimental techniques with sufficient spatial resolution to directly observe these effects simultaneously in real-space. In this letter, we demonstrate an experimental method based on Electron Magnetic Circular Dichroism (EMCD) that will allow researchers to simultaneously map magnetic transitions and valency in real-space over interfacial cross-sections with sub-nanometer spatial resolution. We apply this method to an Fe/MgO bilayer system, observing a significant enhancement in the orbital to spin moment ratio that is strongly localized to the interfacial region. Through the use of first-principles calculations, multivariate statistical analysis, and Electron Energy-Loss Spectroscopy (EELS), we explore the extent to which this enhancement can be attributed to emergent magnetism due to structural confinement at the interface. We conclude that this method has the potential to directly visualize spin and orbital moments at buried interfaces in magnetic systems with unprecedented spatial resolution. PMID:28338011

Towards sub-nanometer real-space observation of spin and orbital magnetism at the Fe/MgO interface

NASA Astrophysics Data System (ADS)

Thersleff, Thomas; Muto, Shunsuke; Werwiński, Mirosław; Spiegelberg, Jakob; Kvashnin, Yaroslav; Hjӧrvarsson, Björgvin; Eriksson, Olle; Rusz, Ján; Leifer, Klaus

2017-03-01

While the performance of magnetic tunnel junctions based on metal/oxide interfaces is determined by hybridization, charge transfer, and magnetic properties at the interface, there are currently only limited experimental techniques with sufficient spatial resolution to directly observe these effects simultaneously in real-space. In this letter, we demonstrate an experimental method based on Electron Magnetic Circular Dichroism (EMCD) that will allow researchers to simultaneously map magnetic transitions and valency in real-space over interfacial cross-sections with sub-nanometer spatial resolution. We apply this method to an Fe/MgO bilayer system, observing a significant enhancement in the orbital to spin moment ratio that is strongly localized to the interfacial region. Through the use of first-principles calculations, multivariate statistical analysis, and Electron Energy-Loss Spectroscopy (EELS), we explore the extent to which this enhancement can be attributed to emergent magnetism due to structural confinement at the interface. We conclude that this method has the potential to directly visualize spin and orbital moments at buried interfaces in magnetic systems with unprecedented spatial resolution.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Very high resolution Earth Observation features for testing the direct and indirect effects of landscape structure on local habitat quality

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco P.; Tarantino, Cristina; Nagendra, Harini; Didham, Raphael K.

2015-02-01

Modelling the empirical relationships between habitat quality and species distribution patterns is the first step to understanding human impacts on biodiversity. It is important to build on this understanding to develop a broader conceptual appreciation of the influence of surrounding landscape structure on local habitat quality, across multiple spatial scales. Traditional models which report that 'habitat amount' in the landscape is sufficient to explain patterns of biodiversity, irrespective of habitat configuration or spatial variation in habitat quality at edges, implicitly treat each unit of habitat as interchangeable and ignore the high degree of interdependence between spatial components of land-use change. Here, we test the contrasting hypothesis, that local habitat units are not interchangeable in their habitat attributes, but are instead dependent on variation in surrounding habitat structure at both patch- and landscape levels. As the statistical approaches needed to implement such hierarchical causal models are observation-intensive, we utilise very high resolution (VHR) Earth Observation (EO) images to rapidly generate fine-grained measures of habitat patch internal heterogeneities over large spatial extents. We use linear mixed-effects models to test whether these remotely-sensed proxies for habitat quality were influenced by surrounding patch or landscape structure. The results demonstrate the significant influence of surrounding patch and landscape context on local habitat quality. They further indicate that such an influence can be direct, when a landscape variable alone influences the habitat structure variable, and/or indirect when the landscape and patch attributes have a conjoined effect on the response variable. We conclude that a substantial degree of interaction among spatial configuration effects is likely to be the norm in determining the ecological consequences of habitat fragmentation, thus corroborating the notion of the spatial context dependence of habitat quality.

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

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

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.

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

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

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

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.

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.

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

Plautz, Tia E.; Johnson, R. P.; Sadrozinski, H. F.-W.

Purpose: To characterize the modulation transfer function (MTF) of the pre-clinical (phase II) head scanner developed for proton computed tomography (pCT) by the pCT collaboration. To evaluate the spatial resolution achievable by this system. Methods: Our phase II proton CT scanner prototype consists of two silicon telescopes that track individual protons upstream and downstream from a phantom, and a 5-stage scintillation detector that measures a combination of the residual energy and range of the proton. Residual energy is converted to water equivalent path length (WEPL) of the protons in the scanned object. The set of WEPL values and associated pathsmore » of protons passing through the object over a 360° angular scan is processed by an iterative parallelizable reconstruction algorithm that runs on GP-GPU hardware. A custom edge phantom composed of water-equivalent polymer and tissue-equivalent material inserts was constructed. The phantom was first simulated in Geant4 and then built to perform experimental beam tests with 200 MeV protons at the Northwestern Medicine Chicago Proton Center. The oversampling method was used to construct radial and azimuthal edge spread functions and modulation transfer functions. The spatial resolution was defined by the 10% point of the modulation transfer function in units of lp/cm. Results: The spatial resolution of the image was found to be strongly correlated with the radial position of the insert but independent of the relative stopping power of the insert. The spatial resolution varies between roughly 4 and 6 lp/cm in both the the radial and azimuthal directions depending on the radial displacement of the edge. Conclusion: The amount of image degradation due to our detector system is small compared with the effects of multiple Coulomb scattering, pixelation of the image and the reconstruction algorithm. Improvements in reconstruction will be made in order to achieve the theoretical limits of spatial resolution.« less

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution

PubMed Central

Mangiacotti, Marco; Scali, Stefano; Sacchi, Roberto; Bassu, Lara; Nulchis, Valeria; Corti, Claudia

2013-01-01

Patch context is a way to describe the effect that the surroundings exert on a landscape patch. Despite anthropogenic context alteration may affect species distributions by reducing the accessibility to suitable patches, species distribution modelling have rarely accounted for its effects explicitly. We propose a general framework to statistically detect the occurrence and the extent of such a factor, by combining presence-only data, spatial distribution models and information-theoretic model selection procedures. After having established the spatial resolution of the analysis on the basis of the species characteristics, a measure of anthropogenic alteration that can be quantified at increasing distance from each patch has to be defined. Then the distribution of the species is modelled under competing hypotheses: H0, assumes that the distribution is uninfluenced by the anthropogenic variables; H1, assumes the effect of alteration at the species scale (resolution); and H2, H3 … Hn add the effect of context alteration at increasing radii. Models are compared using the Akaike Information Criterion to establish the best hypothesis, and consequently the occurrence (if any) and the spatial scale of the anthropogenic effect. As a study case we analysed the distribution data of two insular lizards (one endemic and one naturalised) using four alternative hypotheses: no alteration (H0), alteration at the species scale (H1), alteration at two context scales (H2 and H3). H2 and H3 performed better than H0 and H1, highlighting the importance of context alteration. H2 performed better than H3, setting the spatial scale of the context at 1 km. The two species respond differently to context alteration, the introduced lizard being more tolerant than the endemic one. The proposed approach supplies reliably and interpretable results, uses easily available data on species distribution, and allows the assessing of the spatial scale at which human disturbance produces the heaviest effects. PMID:23825669

Impacts of environment on human diseases: a web service for the human exposome

NASA Astrophysics Data System (ADS)

Karssenberg, Derek; Vaartjes, Ilonca; Kamphuis, Carlijn; Strak, Maciek; Schmitz, Oliver; Soenario, Ivan; de Jong, Kor

2017-04-01

The exposome is the totality of human environmental exposures from conception onwards. Identifying the contribution of the exposome to human diseases and health is a key issue in health research. Examples include the effect of air pollution exposure on cardiovascular diseases, the impact of disease vectors (mosquitos) and surface hydrology exposure on malaria, and the effect of fast food restaurant exposure on obesity. Essential to health research is to disentangle the effects of the exposome and genome on health. Ultimately this requires quantifying the totality of all human exposures, for each individual in the studied human population. This poses a massive challenge to geoscientists, as environmental data are required at a high spatial and temporal resolution, with a large spatial and temporal coverage representing the area inhabited by the population studied and the time span representing several decades. Then, these data need to be combined with space-time paths of individuals to calculate personal exposures for each individual in the population. The Global and Geo Health Data Centre is taking this challenge by providing a web service capable of enriching population data with exposome information. Our web service can generate environmental information either from archived national (up to 5 m spatial and 1 h temporal resolution) and global environmental information or generated on the fly using environmental models running as microservices. On top of these environmental data services runs an individual exposure service enabling health researchers to select different spatial and temporal aggregation methods and to upload space-time paths of individuals. These are then enriched with personal exposures and eventually returned to the user. We illustrate the service in an example of individual exposures to air pollutants calculated from hyper resolution air pollution data and various approaches to estimate space-time paths of individuals.

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.

A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

NASA Astrophysics Data System (ADS)

Ghosh, Aniruddha; Fassnacht, Fabian Ewald; Joshi, P. K.; Koch, Barbara

2014-02-01

Knowledge of tree species distribution is important worldwide for sustainable forest management and resource evaluation. The accuracy and information content of species maps produced using remote sensing images vary with scale, sensor (optical, microwave, LiDAR), classification algorithm, verification design and natural conditions like tree age, forest structure and density. Imaging spectroscopy reduces the inaccuracies making use of the detailed spectral response. However, the scale effect still has a strong influence and cannot be neglected. This study aims to bridge the knowledge gap in understanding the scale effect in imaging spectroscopy when moving from 4 to 30 m pixel size for tree species mapping, keeping in mind that most current and future hyperspectral satellite based sensors work with spatial resolution around 30 m or more. Two airborne (HyMAP) and one spaceborne (Hyperion) imaging spectroscopy dataset with pixel sizes of 4, 8 and 30 m, respectively were available to examine the effect of scale over a central European forest. The forest under examination is a typical managed forest with relatively homogenous stands featuring mostly two canopy layers. Normalized digital surface model (nDSM) derived from LiDAR data was used additionally to examine the effect of height information in tree species mapping. Six different sets of predictor variables (reflectance value of all bands, selected components of a Minimum Noise Fraction (MNF), Vegetation Indices (VI) and each of these sets combined with LiDAR derived height) were explored at each scale. Supervised kernel based (Support Vector Machines) and ensemble based (Random Forest) machine learning algorithms were applied on the dataset to investigate the effect of the classifier. Iterative bootstrap-validation with 100 iterations was performed for classification model building and testing for all the trials. For scale, analysis of overall classification accuracy and kappa values indicated that 8 m spatial resolution (reaching kappa values of over 0.83) slightly outperformed the results obtained from 4 m for the study area and five tree species under examination. The 30 m resolution Hyperion image produced sound results (kappa values of over 0.70), which in some areas of the test site were comparable with the higher spatial resolution imagery when qualitatively assessing the map outputs. Considering input predictor sets, MNF bands performed best at 4 and 8 m resolution. Optical bands were found to be best for 30 m spatial resolution. Classification with MNF as input predictors produced better visual appearance of tree species patches when compared with reference maps. Based on the analysis, it was concluded that there is no significant effect of height information on tree species classification accuracies for the present framework and study area. Furthermore, in the examined cases there was no single best choice among the two classifiers across scales and predictors. It can be concluded that tree species mapping from imaging spectroscopy for forest sites comparable to the one under investigation is possible with reliable accuracies not only from airborne but also from spaceborne imaging spectroscopy datasets.

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.

Spectro-spatial relationship between UAV derived high resolution DEM and SWIR hyperspectral data: application to an ombrotrophic peatland

NASA Astrophysics Data System (ADS)

Arroyo-Mora, J. Pablo; Kalacska, Margaret; Lucanus, Oliver; Soffer, Raymond; Leblanc, George

2017-10-01

Peatlands cover 3% of the globe and are key ecosystems for climate regulation. To better understand the potential effects of climate change in peatlands, a major challenge is to determine the complex relationship between hydrology, microtopography, vegetation patterns, and gas exchange. Here we study the spectral and spatial relationship of microtopographic features (e.g. hollows and hummocks) and near-surface water through narrow-band spectral indices derived from hyperspectral imagery. We used a very high resolution digital elevation model (2.5 cm horizontal, 2.2 cm vertical resolution) derived from an UAV based Structure from Motion photogrammetry to map hollows and hummocks in the peatland area. We also created a 2 cm spatial resolution orthophoto mosaic to enhance the visual identification of these hollows and hummocks. Furthermore, we collected SWIR airborne hyperspectral (880-2450 nm) imagery at 1 m pixel resolution over four time periods, from April to June 2016 (phenological gradient: vegetation greening). Our results revealed an increase in the water indices values (NDWI1640 and NDWI2130) and a decrease in the moisture stress index (MSI) between April and June. In addition, for the same period the NDWI2130 shows a bimodal distribution indicating potential to quantitatively assess moisture differences between mosses and vascular plants. Our results, using the digital surface model to extract NDWI2130 values, showed significant differences between hollows and hummocks for each time period, with higher moisture values for hollows (i.e. moss dominated). However, for June, the water index for hummocks approximated the values found in hollows. Our study shows the advantages of using fine spatial and spectral scales to detect temporal trends in near surface water in a peatland.

On the Challenge of Observing Pelagic Sargassum in Coastal Oceans: A Multi-sensor Assessment

NASA Astrophysics Data System (ADS)

Hu, C.; Feng, L.; Hardy, R.; Hochberg, E. J.

2016-02-01

Remote detection of pelagic Sargassum is often hindered by its spectral similarity to other floating materials and by the inadequate spatial resolution. Using measurements from multi-spectral satellite sensors (Moderate Resolution Imaging Spectroradiometer or MODIS), Landsat, WorldView-2 (or WV-2) as well as hyperspectral sensors (Hyperspectral Imager for the Coastal Ocean or HICO, Airborne Visible-InfraRed Imaging Spectrometer or AVIRIS) and airborne digital photos, we analyze and compare their ability (in terms of spectral and spatial resolutions) to detect Sargassum and to differentiate from other floating materials such as Trichodesmium, Syringodium, Ulva, garbage, and emulsified oil. Field measurements suggest that Sargassum has a distinctive reflectance curvature around 630 nm due to its chlorophyll c pigments, which provides a unique spectral signature when combined with the reflectance ratio between brown ( 650 nm) and green ( 555 nm) wavelengths. For a 10-nm resolution sensor on the hyperspectral HyspIRI mission currently being planned by NASA, a stepwise rule to examine several indexes established from 6 bands (centered at 555, 605, 625, 645, 685, 755 nm) is shown to be effective to unambiguously differentiate Sargassum from all other floating materials Numerical simulations using spectral endmembers and noise in the satellite-derived reflectance suggest that spectral discrimination is degraded when a pixel is mixed between Sargassum and water. A minimum of 20-30% Sargassum coverage within a pixel is required to retain such ability, while the partial coverage can be as low as 1-2% when detecting floating materials without spectral discrimination. With its expected signal-to-noise ratios (SNRs 200:1), the hyperspectral HyspIRI mission may provide a compromise between spatial resolution and spatial coverage to improve our capacity to detect, discriminate, and quantify Sargassum.

A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

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

2013-09-06

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

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

High-Resolution Adaptive Optics Test-Bed for Vision Science

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

Wilks, S C; Thomspon, C A; Olivier, S S

2001-09-27

We discuss the design and implementation of a low-cost, high-resolution adaptive optics test-bed for vision research. It is well known that high-order aberrations in the human eye reduce optical resolution and limit visual acuity. However, the effects of aberration-free eyesight on vision are only now beginning to be studied using adaptive optics to sense and correct the aberrations in the eye. We are developing a high-resolution adaptive optics system for this purpose using a Hamamatsu Parallel Aligned Nematic Liquid Crystal Spatial Light Modulator. Phase-wrapping is used to extend the effective stroke of the device, and the wavefront sensing and wavefrontmore » correction are done at different wavelengths. Issues associated with these techniques will be discussed.« less

Temporal Variability in Vertical Groundwater Fluxes and the Effect of Solar Radiation on Streambed Temperatures Based on Vertical High Resolution Distributed Temperature Sensing

NASA Astrophysics Data System (ADS)

Sebok, E.; Karan, S.; Engesgaard, P. K.; Duque, C.

2013-12-01

Due to its large spatial and temporal variability, groundwater discharge to streams is difficult to quantify. Methods using vertical streambed temperature profiles to estimate vertical fluxes are often of coarse vertical spatial resolution and neglect to account for the natural heterogeneity in thermal conductivity of streambed sediments. Here we report on a field investigation in a stream, where air, stream water and streambed sediment temperatures were measured by Distributed Temperature Sensing (DTS) with high spatial resolution to; (i) detect spatial and temporal variability in groundwater discharge based on vertical streambed temperature profiles, (ii) study the thermal regime of streambed sediments exposed to different solar radiation influence, (iii) describe the effect of solar radiation on the measured streambed temperatures. The study was carried out at a field site located along Holtum stream, in Western Denmark. The 3 m wide stream has a sandy streambed with a cobbled armour layer, a mean discharge of 200 l/s and a mean depth of 0.3 m. Streambed temperatures were measured with a high-resolution DTS system (HR-DTS). By helically wrapping the fiber optic cable around two PVC pipes of 0.05 m and 0.075 m outer diameter over 1.5 m length, temperature measurements were recorded with 5.7 mm and 3.8 mm vertical spacing, respectively. The HR-DTS systems were installed 0.7 m deep in the streambed sediments, crossing both the sediment-water and the water-air interface, thus yielding high resolution water and air temperature data as well. One of the HR-DTS systems was installed in the open stream channel with only topographical shading, while the other HR-DTS system was placed 7 m upstream, under the canopy of a tree, thus representing the shaded conditions with reduced influence of solar radiation. Temperature measurements were taken with 30 min intervals between 16 April and 25 June 2013. The thermal conductivity of streambed sediments was calibrated in a 1D flow and heat transport model (HydroGeoSphere). Subsequently, time series of vertical groundwater fluxes were computed based on the high-resolution vertical streambed sediment temperature profiles by coupling the model with PEST. The calculated vertical flux time series show spatial differences in discharge between the two HR-DTS sites. A similar temporal variability in vertical fluxes at the two test sites can also be observed, most likely linked to rainfall-runoff processes. The effect of solar radiation as streambed conduction is visible both at the exposed and shaded test site in form of increased diel temperature oscillations up to 14 cm depth from the streambed surface, with the test site exposed to solar radiation showing larger diel temperature oscillations.

High resolution modelling and observation of wind-driven surface currents in a semi-enclosed estuary

NASA Astrophysics Data System (ADS)

Nash, S.; Hartnett, M.; McKinstry, A.; Ragnoli, E.; Nagle, D.

2012-04-01

Hydrodynamic circulation in estuaries is primarily driven by tides, river inflows and surface winds. While tidal and river data can be quite easily obtained for input to hydrodynamic models, sourcing accurate surface wind data is problematic. Firstly, the wind data used in hydrodynamic models is usually measured on land and can be quite different in magnitude and direction from offshore winds. Secondly, surface winds are spatially-varying but due to a lack of data it is common practice to specify a non-varying wind speed and direction across the full extents of a model domain. These problems can lead to inaccuracies in the surface currents computed by three-dimensional hydrodynamic models. In the present research, a wind forecast model is coupled with a three-dimensional numerical model of Galway Bay, a semi-enclosed estuary on the west coast of Ireland, to investigate the effect of surface wind data resolution on model accuracy. High resolution and low resolution wind fields are specified to the model and the computed surface currents are compared with high resolution surface current measurements obtained from two high frequency SeaSonde-type Coastal Ocean Dynamics Applications Radars (CODAR). The wind forecast models used for the research are Harmonie cy361.3, running on 2.5 and 0.5km spatial grids for the low resolution and high resolution models respectively. The low-resolution model runs over an Irish domain on 540x500 grid points with 60 vertical levels and a 60s timestep and is driven by ECMWF boundary conditions. The nested high-resolution model uses 300x300 grid points on 60 vertical levels and a 12s timestep. EFDC (Environmental Fluid Dynamics Code) is used for the hydrodynamic model. The Galway Bay model has ten vertical layers and is resolved spatially and temporally at 150m and 4 sec respectively. The hydrodynamic model is run for selected hindcast dates when wind fields were highly energetic. Spatially- and temporally-varying wind data is provided by offline coupling with the wind forecast models. Modelled surface currents show good correlation with CODAR observed currents and the resolution of the surface wind data is shown to be important for model accuracy.

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.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

PubMed Central

Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael

2015-01-01

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful. PMID:26509448

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).

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

PubMed

Yamamoto, Kyosuke; Togami, Takashi; Yamaguchi, Norio

2017-11-06

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

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

PubMed Central

Togami, Takashi; Yamaguchi, Norio

2017-01-01

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

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.

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

PubMed

Kloog, Itai; Chudnovsky, Alexandra A; Just, Allan C; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

PubMed Central

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Spatiotemporal comparison of highly-resolved emissions and concentrations of carbon dioxide and criteria pollutants in Salt Lake City, Utah for health and policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Fasoli, B.; Bares, R.; o'Keefe, D.; Song, T.; Huang, J.; Horel, J.; Crosman, E.; Ehleringer, J. R.

2015-12-01

This study addresses the need for robust highly-resolved emissions and concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are dependent on proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present emissions inventories and modeled concentrations for CO2 and CAPs: carbon monoxide (CO), lead (Pb), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10), and sulfur oxides (SOx) for Salt Lake County, Utah. We compare the resulting concentrations against stationary and mobile measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at an hourly, building and road link resolution as well as hourly gridded emissions with a 0.002o x 0.002o spatial resolution. Two methods for deriving criteria pollutant emission inventories were compared. One was constructed using methods similar to Hestia but downscales total emissions based on the 2011 National Emissions Inventory (NEI). The other used Emission Modeling Clearinghouse spatial and temporal surrogates to downscale the NEI data from annual and county-level resolution to hourly and 0.002o x 0.002o grid cells. The gridded emissions from both criteria pollutant methods were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The CALPUFF dispersion model was used to transport emissions and estimate air pollutant concentrations at an hourly 0.002o x 0.002o resolution. The resulting concentrations were spatially compared in the same manner as the emissions. Modeled results were compared against stationary measurements and from equipment mounted atop a light rail car in the Salt Lake City area. The comparison between both approaches to emissions estimation and resulting concentrations highlights spatial locations and hours of high variability and uncertainty.

Experimental characterization of a direct conversion amorphous selenium detector with thicker conversion layer for dual-energy contrast-enhanced breast imaging.

PubMed

Scaduto, David A; Tousignant, Olivier; Zhao, Wei

2017-08-01

Dual-energy contrast-enhanced imaging is being investigated as a tool to identify and localize angiogenesis in the breast, a possible indicator of malignant tumors. This imaging technique requires that x-ray images are acquired at energies above the k-shell binding energy of an appropriate radiocontrast agent. Iodinated contrast agents are commonly used for vascular imaging, and require x-ray energies greater than 33 keV. Conventional direct conversion amorphous selenium (a-Se) flat-panel imagers for digital mammography show suboptimal absorption efficiencies at these higher energies. We use spatial-frequency domain image quality metrics to evaluate the performance of a prototype direct conversion flat-panel imager with a thicker a-Se layer, specifically fabricated for dual-energy contrast-enhanced breast imaging. Imaging performance was evaluated in a prototype digital breast tomosynthesis (DBT) system. The spatial resolution, noise characteristics, detective quantum efficiency, and temporal performance of the detector were evaluated for dual-energy imaging for both conventional full-field digital mammography (FFDM) and DBT. The zero-frequency detective quantum efficiency of the prototype detector is improved by approximately 20% over the conventional detector for higher energy beams required for imaging with iodinated contrast agents. The effect of oblique entry of x-rays on spatial resolution does increase with increasing photoconductor thickness, specifically for the most oblique views of a DBT scan. Degradation of spatial resolution due to focal spot motion was also observed. Temporal performance was found to be comparable to conventional mammographic detectors. Increasing the a-Se thickness in direct conversion flat-panel imagers results in better performance for dual-energy contrast-enhanced breast imaging. The reduction in spatial resolution due to oblique entry of x-rays is appreciable in the most extreme clinically relevant cases, but may not profoundly affect reconstructed images due to the algorithms and filters employed. Degradation to projection domain spatial resolution is thus outweighed by the improvement in detective quantum efficiency for high-energy x-rays. © 2017 American Association of Physicists in Medicine.

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

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)

Preparatory neural activity predicts performance on a conflict task.

PubMed

Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

2007-10-24

Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

Intrinsic spatial resolution evaluation of the X'tal cube PET detector based on a 3D crystal block segmented by laser processing.

PubMed

Yoshida, Eiji; Tashima, Hideaki; Inadama, Naoko; Nishikido, Fumihiko; Moriya, Takahiro; Omura, Tomohide; Watanabe, Mitsuo; Murayama, Hideo; Yamaya, Taiga

2013-01-01

The X'tal cube is a depth-of-interaction (DOI)-PET detector which is aimed at obtaining isotropic resolution by effective readout of scintillation photons from the six sides of a crystal block. The X'tal cube is composed of the 3D crystal block with isotropic resolution and arrays of multi-pixel photon counters (MPPCs). In this study, to fabricate the 3D crystal block efficiently and precisely, we applied a sub-surface laser engraving (SSLE) technique to a monolithic crystal block instead of gluing segmented small crystals. The SSLE technique provided micro-crack walls which carve a groove into a monolithic scintillator block. Using the fabricated X'tal cube, we evaluated its intrinsic spatial resolution to show a proof of concept of isotropic resolution. The 3D grids of 2 mm pitch were fabricated into an 18 × 18 × 18 mm(3) monolithic lutetium yttrium orthosilicate (LYSO) crystal by the SSLE technique. 4 × 4 MPPCs were optically coupled to each surface of the crystal block. The X'tal cube was uniformly irradiated by (22)Na gamma rays, and all of the 3D grids on the 3D position histogram were separated clearly by an Anger-type calculation from the 96-channel MPPC signals. Response functions of the X'tal cube were measured by scanning with a (22)Na point source. The gamma-ray beam with a 1.0 mm slit was scanned in 0.25 mm steps by positioning of the X'tal cube at vertical and 45° incident angles. The average FWHM resolution at both incident angles was 2.1 mm. Therefore, we confirmed the isotropic spatial resolution performance of the X'tal cube.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.