MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging

NASA Astrophysics Data System (ADS)

Gutierrez, R. M.; Cerquera, E. A.; Mañana, G.

2012-07-01

Early detection of small calcifications in mammograms is considered the best preventive tool of breast cancer. However, existing digital mammography with relatively low radiation skin exposure has limited accessibility and insufficient spatial resolution for small calcification detection. Micro Pattern Gaseous Detectors (MPGD) and associated technologies, increasingly provide new information useful to generate images of microscopic structures and make more accessible cutting edge technology for medical imaging and many other applications. In this work we foresee and develop an application for the new information provided by a MPGD camera in the form of highly controlled images with high dynamical resolution. We present a new Super Detail Image (S-DI) that efficiently profits of this new information provided by the MPGD camera to obtain very high spatial resolution images. Therefore, the method presented in this work shows that the MPGD camera with SD-I, can produce mammograms with the necessary spatial resolution to detect microcalcifications. It would substantially increase efficiency and accessibility of screening mammography to highly improve breast cancer prevention.

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.

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.

A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light

PubMed Central

Yao, Huimin; Ge, Chenyang; Xue, Jianru; Zheng, Nanning

2017-01-01

Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth information. In this paper, we propose a depth sensing system that contains a laser projector similar to that used in the Kinect, and two infrared cameras located on both sides of the laser projector, to obtain higher spatial resolution depth information. We apply the block-matching algorithm to estimate the disparity. To improve the spatial resolution, we reduce the size of matching blocks, but smaller matching blocks generate lower matching precision. To address this problem, we combine two matching modes (binocular mode and monocular mode) in the disparity estimation process. Experimental results show that our method can obtain higher spatial resolution depth without loss of the quality of the range image, compared with the Kinect. Furthermore, our algorithm is implemented on a low-cost hardware platform, and the system can support the resolution of 1280 × 960, and up to a speed of 60 frames per second, for depth image sequences. PMID:28397759

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

USDA-ARS?s Scientific Manuscript database

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified ...

Pushing the limits of spatial resolution with the Kuiper Airborne observatory

NASA Technical Reports Server (NTRS)

Lester, Daniel

1994-01-01

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

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.

Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

NASA Astrophysics Data System (ADS)

Engstrom, R.; Ashcroft, E.

2014-12-01

There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to indicators of health and wealth within a developing world city and that the even if the imagery is collected 10 years after the census information, the relationships are still significant.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

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

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

Sharpening advanced land imager multispectral data using a sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2005-01-01

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

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.

The influence of spectral and spatial resolution in classification approaches: Landsat TM data vs. Hyperspectral data

NASA Astrophysics Data System (ADS)

Rodríguez-Galiano, Víctor; Garcia-Soldado, Maria José; Chica-Olmo, Mario

The importance of accurate and timely information describing the nature and extent of land and natural resources is increasing especially in rapidly growing metropolitan areas. While metropolitan area decision makers are in constant need of current geospatial information on patterns and trends in land cover and land use, relatively little researchers has investigated the influence of the satellite data resolution for monitoring geo-enviromental information. In this research a suite of remote sensing and GIS techniques is applied in a land use mapping study. The main task is to asses the influence of the spatial and spectral resolution in the separability between classes and in the classificatiońs accuracy. This study has been focused in a very dynamical area with respect to land use, located in the province of Granada (SE of Spain). The classifications results of the Airborne Hyperspectral Scanner (AHS, Daedalus Enterprise Inc., WA, EEUU) at different spatial resolutions: 2, 4 and 6 m and Landsat 5 TM data have been compared.

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.

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.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Terrain Categorization using LIDAR and Multi-Spectral Data

DTIC Science & Technology

2007-01-01

the same spatial resolution cell will be distinguished. 3. PROCESSING The LIDAR data set used in this study was from a discrete-return...smoothing in the spatial dimension. While it was possible to distinguish different classes of materials using this technique, the spatial resolution was...alone and a combination of the two data-types. Results are compared to significant ground truth information. Keywords: LIDAR, multi- spectral

Fusion of spectral and panchromatic images using false color mapping and wavelet integrated approach

NASA Astrophysics Data System (ADS)

Zhao, Yongqiang; Pan, Quan; Zhang, Hongcai

2006-01-01

With the development of sensory technology, new image sensors have been introduced that provide a greater range of information to users. But as the power limitation of radiation, there will always be some trade-off between spatial and spectral resolution in the image captured by specific sensors. Images with high spatial resolution can locate objects with high accuracy, whereas images with high spectral resolution can be used to identify the materials. Many applications in remote sensing require fusing low-resolution imaging spectral images with panchromatic images to identify materials at high resolution in clutter. A pixel-based false color mapping and wavelet transform integrated fusion algorithm is presented in this paper, the resulting images have a higher information content than each of the original images and retain sensor-specific image information. The simulation results show that this algorithm can enhance the visibility of certain details and preserve the difference of different materials.

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.

Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

NASA Astrophysics Data System (ADS)

Sandborn, A.; Engstrom, R.; Yu, Q.

2014-12-01

Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

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.

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

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

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

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.

High-spatial-resolution nanoparticle x-ray fluorescence tomography

NASA Astrophysics Data System (ADS)

Larsson, Jakob C.; Vâgberg, William; Vogt, Carmen; Lundström, Ulf; Larsson, Daniel H.; Hertz, Hans M.

2016-03-01

X-ray fluorescence tomography (XFCT) has potential for high-resolution 3D molecular x-ray bio-imaging. In this technique the fluorescence signal from targeted nanoparticles (NPs) is measured, providing information about the spatial distribution and concentration of the NPs inside the object. However, present laboratory XFCT systems typically have limited spatial resolution (>1 mm) and suffer from long scan times and high radiation dose even at high NP concentrations, mainly due to low efficiency and poor signal-to-noise ratio. We have developed a laboratory XFCT system with high spatial resolution (sub-100 μm), low NP concentration and vastly decreased scan times and dose, opening up the possibilities for in-vivo small-animal imaging research. The system consists of a high-brightness liquid-metal-jet microfocus x-ray source, x-ray focusing optics and an energy-resolving photon-counting detector. By using the source's characteristic 24 keV line-emission together with carefully matched molybdenum nanoparticles the Compton background is greatly reduced, increasing the SNR. Each measurement provides information about the spatial distribution and concentration of the Mo nanoparticles. A filtered back-projection method is used to produce the final XFCT image.

Photoacoustic tomography guided diffuse optical tomography for small-animal model

NASA Astrophysics Data System (ADS)

Wang, Yihan; Gao, Feng; Wan, Wenbo; Zhang, Yan; Li, Jiao

2015-03-01

Diffuse optical tomography (DOT) is a biomedical imaging technology for noninvasive visualization of spatial variation about the optical properties of tissue, which can be applied to in vivo small-animal disease model. However, traditional DOT suffers low spatial resolution due to tissue scattering. To overcome this intrinsic shortcoming, multi-modal approaches that incorporate DOT with other imaging techniques have been intensively investigated, where a priori information provided by the other modalities is normally used to reasonably regularize the inverse problem of DOT. Nevertheless, these approaches usually consider the anatomical structure, which is different from the optical structure. Photoacoustic tomography (PAT) is an emerging imaging modality that is particularly useful for visualizing lightabsorbing structures embedded in soft tissue with higher spatial resolution compared with pure optical imaging. Thus, we present a PAT-guided DOT approach, to obtain the location a priori information of optical structure provided by PAT first, and then guide DOT to reconstruct the optical parameters quantitatively. The results of reconstruction of phantom experiments demonstrate that both quantification and spatial resolution of DOT could be highly improved by the regularization of feasible-region information provided by PAT.

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.

Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

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.

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.

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

PubMed

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

2018-04-01

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Dissociations within human hippocampal subregions during encoding and retrieval of spatial information.

PubMed

Suthana, Nanthia; Ekstrom, Arne; Moshirvaziri, Saba; Knowlton, Barbara; Bookheimer, Susan

2011-07-01

Although the hippocampus is critical for the formation and retrieval of spatial memories, it is unclear how subregions are differentially involved in these processes. Previous high-resolution functional magnetic resonance imaging (fMRI) studies have shown that CA2, CA3, and dentate gyrus (CA23DG) regions support the encoding of novel associations, whereas the subicular cortices support the retrieval of these learned associations. Whether these subregions are used in humans during encoding and retrieval of spatial information has yet to be explored. Using high-resolution fMRI (1.6 mm × 1.6-mm in-plane), we found that activity within the right CA23DG increased during encoding compared to retrieval. Conversely, right subicular activity increased during retrieval compared to encoding of spatial associations. These results are consistent with the previous studies illustrating dissociations within human hippocampal subregions and further suggest that these regions are similarly involved during the encoding and retrieval of spatial information. Copyright © 2010 Wiley-Liss, Inc.

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.

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.

Multimodal imaging of human cerebellum - merging X-ray phase microtomography, magnetic resonance microscopy and histology

NASA Astrophysics Data System (ADS)

Schulz, Georg; Waschkies, Conny; Pfeiffer, Franz; Zanette, Irene; Weitkamp, Timm; David, Christian; Müller, Bert

2012-11-01

Imaging modalities including magnetic resonance imaging and X-ray computed tomography are established methods in daily clinical diagnosis of human brain. Clinical equipment does not provide sufficient spatial resolution to obtain morphological information on the cellular level, essential for applying minimally or non-invasive surgical interventions. Therefore, generic data with lateral sub-micrometer resolution have been generated from histological slices post mortem. Sub-cellular spatial resolution, lost in the third dimension as a result of sectioning, is obtained using magnetic resonance microscopy and micro computed tomography. We demonstrate that for human cerebellum grating-based X-ray phase tomography shows complementary contrast to magnetic resonance microscopy and histology. In this study, the contrast-to-noise values of magnetic resonance microscopy and phase tomography were comparable whereas the spatial resolution in phase tomography is an order of magnitude better. The registered data with their complementary information permit the distinct segmentation of tissues within the human cerebellum.

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.

Quantifying Information Gain from Dynamic Downscaling Experiments

NASA Astrophysics Data System (ADS)

Tian, Y.; Peters-Lidard, C. D.

2015-12-01

Dynamic climate downscaling experiments are designed to produce information at higher spatial and temporal resolutions. Such additional information is generated from the low-resolution initial and boundary conditions via the predictive power of the physical laws. However, errors and uncertainties in the initial and boundary conditions can be propagated and even amplified to the downscaled simulations. Additionally, the limit of predictability in nonlinear dynamical systems will also damper the information gain, even if the initial and boundary conditions were error-free. Thus it is critical to quantitatively define and measure the amount of information increase from dynamic downscaling experiments, to better understand and appreciate their potentials and limitations. We present a scheme to objectively measure the information gain from such experiments. The scheme is based on information theory, and we argue that if a downscaling experiment is to exhibit value, it has to produce more information than what can be simply inferred from information sources already available. These information sources include the initial and boundary conditions, the coarse resolution model in which the higher-resolution models are embedded, and the same set of physical laws. These existing information sources define an "information threshold" as a function of the spatial and temporal resolution, and this threshold serves as a benchmark to quantify the information gain from the downscaling experiments, or any other approaches. For a downscaling experiment to shown any value, the information has to be above this threshold. A recent NASA-supported downscaling experiment is used as an example to illustrate the application of this scheme.

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.

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.

Solar Confocal Interferometers for Sub-Picometer-Resolution Spectral Filters

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

The 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.

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.

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.

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.

Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

NASA Astrophysics Data System (ADS)

Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

2018-01-01

We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

Spatially-controlled illumination with rescan confocal microscopy enhances image quality, resolution and reduces photodamage

NASA Astrophysics Data System (ADS)

Krishnaswami, Venkataraman; De Luca, Giulia M. R.; Breedijk, Ronald M. P.; Van Noorden, Cornelis J. F.; Manders, Erik M. M.; Hoebe, Ron A.

2017-02-01

Fluorescence microscopy is an important tool in biomedical imaging. An inherent trade-off lies between image quality and photodamage. Recently, we have introduced rescan confocal microscopy (RCM) that improves the lateral resolution of a confocal microscope down to 170 nm. Previously, we have demonstrated that with controlled-light exposure microscopy, spatial control of illumination reduces photodamage without compromising image quality. Here, we show that the combination of these two techniques leads to high resolution imaging with reduced photodamage without compromising image quality. Implementation of spatially-controlled illumination was carried out in RCM using a line scanning-based approach. Illumination is spatially-controlled for every line during imaging with the help of a prediction algorithm that estimates the spatial profile of the fluorescent specimen. The estimation is based on the information available from previously acquired line images. As a proof-of-principle, we show images of N1E-115 neuroblastoma cells, obtained by this new setup with reduced illumination dose, improved resolution and without compromising image quality.

The spatial resolving power of earth resources satellites: A review

NASA Technical Reports Server (NTRS)

Townshend, J. R. G.

1980-01-01

The significance of spatial resolving power on the utility of current and future Earth resources satellites is critically discussed and the relative merits of different approaches in defining and estimating spatial resolution are outlined. It is shown that choice of a particular measure of spatial resolution depends strongly on the particular needs of the user. Several experiments have simulated the capabilities of future satellite systems by degradation of aircraft images. Surprisingly, many of these indicated that improvements in resolution may lead to a reduction in the classification accuracy of land cover types using computer assisted methods. However, where the frequency of boundary pixels is high, the converse relationship is found. Use of imagery dependent upon visual interpretation is likely to benefit more consistently from higher resolutions. Extraction of information from images will depend upon several other factors apart from spatial resolving power: these include characteristics of the terrain being sensed, the image processing methods that are applied as well as certain sensor characteristics.

Combined Landsat-8 and Sentinel-2 Burned Area Mapping

NASA Astrophysics Data System (ADS)

Huang, H.; Roy, D. P.; Zhang, H.; Boschetti, L.; Yan, L.; Li, Z.

2017-12-01

Fire products derived from coarse spatial resolution satellite data have become an important source of information for the multiple user communities involved in fire science and applications. The advent of the MODIS on NASA's Terra and Aqua satellites enabled systematic production of 500m global burned area maps. There is, however, an unequivocal demand for systematically generated higher spatial resolution burned area products, in particular to examine the role of small-fires for various applications. Moderate spatial resolution contemporaneous satellite data from Landsat-8 and the Sentinel-2A and -2B sensors provide the opportunity for detailed spatial mapping of burned areas. Combined, these polar-orbiting systems provide 10m to 30m multi-spectral global coverage more than once every three days. This NASA funded research presents results to prototype a combined Landsat-8 Sentinel-2 burned area product. The Landsat-8 and Sentinel-2 pre-processing, the time-series burned area mapping algorithm, and preliminary results and validation using high spatial resolution commercial satellite data over Africa are presented.

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

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.

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.

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.

Enhanced PET resolution by combining pinhole collimation and coincidence detection

NASA Astrophysics Data System (ADS)

DiFilippo, Frank P.

2015-10-01

Spatial resolution of clinical PET scanners is limited by detector design and photon non-colinearity. Although dedicated small animal PET scanners using specialized high-resolution detectors have been developed, enhancing the spatial resolution of clinical PET scanners is of interest as a more available alternative. Multi-pinhole 511 keV SPECT is capable of high spatial resolution but requires heavily shielded collimators to avoid significant background counts. A practical approach with clinical PET detectors is to combine multi-pinhole collimation with coincidence detection. In this new hybrid modality, there are three locations associated with each event, namely those of the two detected photons and the pinhole aperture. These three locations over-determine the line of response and provide redundant information that is superior to coincidence detection or pinhole collimation alone. Multi-pinhole collimation provides high resolution and avoids non-colinearity error but is subject to collimator penetration and artifacts from overlapping projections. However the coincidence information, though at lower resolution, is valuable for determining whether the photon passed near a pinhole within the cone acceptance angle and for identifying through which pinhole the photon passed. This information allows most photons penetrating through the collimator to be rejected and avoids overlapping projections. With much improved event rejection, a collimator with minimal shielding may be used, and a lightweight add-on collimator for high resolution imaging is feasible for use with a clinical PET scanner. Monte Carlo simulations were performed of a 18F hot rods phantom and a 54-pinhole unfocused whole-body mouse collimator with a clinical PET scanner. Based on coincidence information and pinhole geometry, events were accepted or rejected, and pinhole-specific crystal-map projections were generated. Tomographic images then were reconstructed using a conventional pinhole SPECT algorithm. Hot rods of 1.4 mm diameter were resolved easily in a simulated phantom. System sensitivity was 0.09% for a simulated 70-mm line source corresponding to the NEMA NU-4 mouse phantom. Higher resolution is expected with further optimization of pinhole design, and higher sensitivity is expected with a focused and denser pinhole configuration. The simulations demonstrate high spatial resolution and feasibility of small animal imaging with an add-on multi-pinhole collimator for a clinical PET scanner. Further work is needed to develop geometric calibration and quantitative data corrections and, eventually, to construct a prototype device and produce images with physical phantoms.

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

USGS Publications Warehouse

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

2014-01-01

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

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.

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

PubMed Central

Hu, Mao-Gui; Wang, Jin-Feng; Ge, Yong

2009-01-01

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics. PMID:22291530

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Application of geo-spatial technology in schistosomiasis modelling in Africa: a review.

PubMed

Manyangadze, Tawanda; Chimbari, Moses John; Gebreslasie, Michael; Mukaratirwa, Samson

2015-11-04

Schistosomiasis continues to impact socio-economic development negatively in sub-Saharan Africa. The advent of spatial technologies, including geographic information systems (GIS), Earth observation (EO) and global positioning systems (GPS) assist modelling efforts. However, there is increasing concern regarding the accuracy and precision of the current spatial models. This paper reviews the literature regarding the progress and challenges in the development and utilization of spatial technology with special reference to predictive models for schistosomiasis in Africa. Peer-reviewed papers identified through a PubMed search using the following keywords: geo-spatial analysis OR remote sensing OR modelling OR earth observation OR geographic information systems OR prediction OR mapping AND schistosomiasis AND Africa were used. Statistical uncertainty, low spatial and temporal resolution satellite data and poor validation were identified as some of the factors that compromise the precision and accuracy of the existing predictive models. The need for high spatial resolution of remote sensing data in conjunction with ancillary data viz. ground-measured climatic and environmental information, local presence/absence intermediate host snail surveys as well as prevalence and intensity of human infection for model calibration and validation are discussed. The importance of a multidisciplinary approach in developing robust, spatial data capturing, modelling techniques and products applicable in epidemiology is highlighted.

Spatial resolution in visual memory.

PubMed

Ben-Shalom, Asaf; Ganel, Tzvi

2015-04-01

Representations in visual short-term memory are considered to contain relatively elaborated information on object structure. Conversely, representations in earlier stages of the visual hierarchy are thought to be dominated by a sensory-based, feed-forward buildup of information. In four experiments, we compared the spatial resolution of different object properties between two points in time along the processing hierarchy in visual short-term memory. Subjects were asked either to estimate the distance between objects or to estimate the size of one of the objects' features under two experimental conditions, of either a short or a long delay period between the presentation of the target stimulus and the probe. When different objects were referred to, similar spatial resolution was found for the two delay periods, suggesting that initial processing stages are sensitive to object-based properties. Conversely, superior resolution was found for the short, as compared with the long, delay when features were referred to. These findings suggest that initial representations in visual memory are hybrid in that they allow fine-grained resolution for object features alongside normal visual sensitivity to the segregation between objects. The findings are also discussed in reference to the distinction made in earlier studies between visual short-term memory and iconic memory.

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

Graesser, Jordan B; Cheriyadat, Anil M; Vatsavai, Raju

The high rate of global urbanization has resulted in a rapid increase in informal settlements, which can be de ned as unplanned, unauthorized, and/or unstructured housing. Techniques for ef ciently mapping these settlement boundaries can bene t various decision making bodies. From a remote sensing perspective, informal settlements share unique spatial characteristics that distinguish them from other types of structures (e.g., industrial, commercial, and formal residential). These spatial characteristics are often captured in high spatial resolution satellite imagery. We analyzed the role of spatial, structural, and contextual features (e.g., GLCM, Histogram of Oriented Gradients, Line Support Regions, Lacunarity) for urbanmore » neighborhood mapping, and computed several low-level image features at multiple scales to characterize local neighborhoods. The decision parameters to classify formal-, informal-, and non-settlement classes were learned under Decision Trees and a supervised classi cation framework. Experiments were conducted on high-resolution satellite imagery from the CitySphere collection, and four different cities (i.e., Caracas, Kabul, Kandahar, and La Paz) with varying spatial characteristics were represented. Overall accuracy ranged from 85% in La Paz, Bolivia, to 92% in Kandahar, Afghanistan. While the disparities between formal and informal neighborhoods varied greatly, many of the image statistics tested proved robust.« less

Extracting spatial information from large aperture exposures of diffuse sources

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture

NASA Astrophysics Data System (ADS)

Elarab, Manal; Ticlavilca, Andres M.; Torres-Rua, Alfonso F.; Maslova, Inga; McKee, Mac

2015-12-01

Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS-NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm-2, efficiency of 0.76, and 9 relevance vectors.

Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

NASA Astrophysics Data System (ADS)

Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

2014-12-01

Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

Increasing spatial resolution and comparison of MR imaging sequences for the inner ear

NASA Astrophysics Data System (ADS)

Snyder, Carl J.; Bolinger, Lizann; Rubinstein, Jay T.; Wang, Ge

2002-04-01

The size and location of the cochlea and cochlear nerve are needed to assess the feasibility of cochlea implantation, provide information for surgical planning, and aid in construction of cochlear models. Models of implant stimulation incorporating anatomical and physiological information are likely to provide a better understanding of the biophysics of information transferred with cochlear implants and aid in electrode design and arrangement on cochlear implants. Until recently MR did not provide the necessary image resolution and suffered from long acquisition times. The purpose of this study was to optimize both Fast Spin Echo (FSE) and Steady State Free Precession (FIESTA) imaging scan parameters for the inner ear and comparatively examine both for improved image quality and increased spatial resolution. Image quality was determined by two primary measurements, signal to noise ratio (SNR), and image sharpness. Optimized parameters for FSE were 120ms, 3000ms, 64, and 32.25kHz for the TE, TR, echo train length, and bandwidth, respectively. FIESTA parameters were optimized to 2.7, 5.5ms, 70 degree(s), and 62.5kHz, for TE, TR, flip angle, and bandwidth, respectively. While both had the same in-plane spatial resolution, 0.625mm, FIESTA data shows higher SNR per acquisition time and better edge sharpness.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Conjunctions between motion and disparity are encoded with the same spatial resolution as disparity alone.

PubMed

Allenmark, Fredrik; Read, Jenny C A

2012-10-10

Neurons in cortical area MT respond well to transparent streaming motion in distinct depth planes, such as caused by observer self-motion, but do not contain subregions excited by opposite directions of motion. We therefore predicted that spatial resolution for transparent motion/disparity conjunctions would be limited by the size of MT receptive fields, just as spatial resolution for disparity is limited by the much smaller receptive fields found in primary visual cortex, V1. We measured this using a novel "joint motion/disparity grating," on which human observers detected motion/disparity conjunctions in transparent random-dot patterns containing dots streaming in opposite directions on two depth planes. Surprisingly, observers showed the same spatial resolution for these as for pure disparity gratings. We estimate the limiting receptive field diameter at 11 arcmin, similar to V1 and much smaller than MT. Higher internal noise for detecting joint motion/disparity produces a slightly lower high-frequency cutoff of 2.5 cycles per degree (cpd) versus 3.3 cpd for disparity. This suggests that information on motion/disparity conjunctions is available in the population activity of V1 and that this information can be decoded for perception even when it is invisible to neurons in MT.

Resolution analysis of archive films for the purpose of their optimal digitization and distribution

NASA Astrophysics Data System (ADS)

Fliegel, Karel; Vítek, Stanislav; Páta, Petr; Myslík, Jiří; Pecák, Josef; Jícha, Marek

2017-09-01

With recent high demand for ultra-high-definition (UHD) content to be screened in high-end digital movie theaters but also in the home environment, film archives full of movies in high-definition and above are in the scope of UHD content providers. Movies captured with the traditional film technology represent a virtually unlimited source of UHD content. The goal to maintain complete image information is also related to the choice of scanning resolution and spatial resolution for further distribution. It might seem that scanning the film material in the highest possible resolution using state-of-the-art film scanners and also its distribution in this resolution is the right choice. The information content of the digitized images is however limited, and various degradations moreover lead to its further reduction. Digital distribution of the content in the highest image resolution might be therefore unnecessary or uneconomical. In other cases, the highest possible resolution is inevitable if we want to preserve fine scene details or film grain structure for archiving purposes. This paper deals with the image detail content analysis of archive film records. The resolution limit in captured scene image and factors which lower the final resolution are discussed. Methods are proposed to determine the spatial details of the film picture based on the analysis of its digitized image data. These procedures allow determining recommendations for optimal distribution of digitized video content intended for various display devices with lower resolutions. Obtained results are illustrated on spatial downsampling use case scenario, and performance evaluation of the proposed techniques is presented.

Overlapping MALDI-Mass Spectrometry Imaging for In-Parallel MS and MS/MS Data Acquisition without Sacrificing Spatial Resolution

NASA Astrophysics Data System (ADS)

Hansen, Rebecca L.; Lee, Young Jin

2017-09-01

Metabolomics experiments require chemical identifications, often through MS/MS analysis. In mass spectrometry imaging (MSI), this necessitates running several serial tissue sections or using a multiplex data acquisition method. We have previously developed a multiplex MSI method to obtain MS and MS/MS data in a single experiment to acquire more chemical information in less data acquisition time. In this method, each raster step is composed of several spiral steps and each spiral step is used for a separate scan event (e.g., MS or MS/MS). One main limitation of this method is the loss of spatial resolution as the number of spiral steps increases, limiting its applicability for high-spatial resolution MSI. In this work, we demonstrate multiplex MS imaging is possible without sacrificing spatial resolution by the use of overlapping spiral steps, instead of spatially separated spiral steps as used in the previous work. Significant amounts of matrix and analytes are still left after multiple spectral acquisitions, especially with nanoparticle matrices, so that high quality MS and MS/MS data can be obtained on virtually the same tissue spot. This method was then applied to visualize metabolites and acquire their MS/MS spectra in maize leaf cross-sections at 10 μm spatial resolution. [Figure not available: see fulltext.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Velocity distributions in a micromixer measured by NMR imaging.

PubMed

Ahola, Susanna; Telkki, Ville-Veikko; Stapf, Siegfried

2012-04-24

Velocity distributions (so-called propagators) with two-dimensional spatial resolution inside a chemical micromixer were measured by pulsed-field-gradient spin-echo (PGSE) nuclear magnetic resonance (NMR). A surface coil matching the volume of interest was built to enhance the signal-to-noise ratio. This enabled the acquisition of velocity maps with a very high spatial resolution of 29 μm × 39 μm. The measured propagators are compared with theoretical distributions and a good agreement is found. The results show that the propagator data provide much richer information about flow behaviour than conventional NMR velocity imaging and the information is essential for understanding the performance of a micromixer. It reveals, for example, deviations in the shape and size of the channel structures and multicomponent flow velocity distribution of overlapping channels. Propagator data efficiently compensate lost information caused by insufficient 3D resolution in conventional velocity imaging.

Assessing the performance of multiple spectral-spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network

NASA Astrophysics Data System (ADS)

Pullanagari, Reddy; Kereszturi, Gábor; Yule, Ian J.; Ghamisi, Pedram

2017-04-01

Accurate and spatially detailed mapping of complex urban environments is essential for land managers. Classifying high spectral and spatial resolution hyperspectral images is a challenging task because of its data abundance and computational complexity. Approaches with a combination of spectral and spatial information in a single classification framework have attracted special attention because of their potential to improve the classification accuracy. We extracted multiple features from spectral and spatial domains of hyperspectral images and evaluated them with two supervised classification algorithms; support vector machines (SVM) and an artificial neural network. The spatial features considered are produced by a gray level co-occurrence matrix and extended multiattribute profiles. All of these features were stacked, and the most informative features were selected using a genetic algorithm-based SVM. After selecting the most informative features, the classification model was integrated with a segmentation map derived using a hidden Markov random field. We tested the proposed method on a real application of a hyperspectral image acquired from AisaFENIX and on widely used hyperspectral images. From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation.

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

Treesearch

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

2018-01-01

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

Example-Based Super-Resolution Fluorescence Microscopy.

PubMed

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

2018-04-23

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

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

NASA Astrophysics Data System (ADS)

Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

2010-08-01

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Ultimate Limit to the Spatial Resolution in Magnetic Imaging

NASA Astrophysics Data System (ADS)

Matthews, John; Wellstood, Frederick C.; Chatraphorn, Sojiphong

2003-03-01

Motivated by the continual improvement in the spatial resolution of source currents detected by magnetic field imaging, in particular scanning SQUID microscopy, we have determined a theoretical limit to the spatial resolution for a given set of parameters. The guiding principle here is that by adding known information (e.g. CAD diagram) about the source currents into the inversion algorithm, we reduce the number of unknown parameters and hence lower the uncertainty in the remaining parameters. We consider the ultimate limit to be the case where all the information about the system is known, except for a single parameter, e.g. the separation w of two long, straight wires each carrying a current I/2. For this particular example we find that for a current I=100;μA, with magnetic field noise Δ B=10 pT, at a standoff z=100;μm, the minimum resolvable separation is 2;μm, about an order of magnitude less than the present limit.

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.

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

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

NASA Technical Reports Server (NTRS)

Lauer, D. T. (Principal Investigator)

1984-01-01

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

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

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

HIRIS (High-Resolution Imaging Spectrometer: Science opportunities for the 1990s. Earth observing system. Volume 2C: Instrument panel report

NASA Technical Reports Server (NTRS)

1987-01-01

The high-resolution imaging spectrometer (HIRIS) is an Earth Observing System (EOS) sensor developed for high spatial and spectral resolution. It can acquire more information in the 0.4 to 2.5 micrometer spectral region than any other sensor yet envisioned. Its capability for critical sampling at high spatial resolution makes it an ideal complement to the MODIS (moderate-resolution imaging spectrometer) and HMMR (high-resolution multifrequency microwave radiometer), lower resolution sensors designed for repetitive coverage. With HIRIS it is possible to observe transient processes in a multistage remote sensing strategy for Earth observations on a global scale. The objectives, science requirements, and current sensor design of the HIRIS are discussed along with the synergism of the sensor with other EOS instruments and data handling and processing requirements.

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.

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.

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.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

NASA Technical Reports Server (NTRS)

Hammerling, Dorit M.; Michalak, Anna M.; Kawa, S. Randolph

2012-01-01

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

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.

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

NASA Astrophysics Data System (ADS)

Ji, C.; Shao, G.

2007-12-01

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

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.

Spatiotemporal Pixelization to Increase the Recognition Score of Characters for Retinal Prostheses

PubMed Central

Kim, Hyun Seok; Park, Kwang Suk

2017-01-01

Most of the retinal prostheses use a head-fixed camera and a video processing unit. Some studies proposed various image processing methods to improve visual perception for patients. However, previous studies only focused on using spatial information. The present study proposes a spatiotemporal pixelization method mimicking fixational eye movements to generate stimulation images for artificial retina arrays by combining spatial and temporal information. Input images were sampled with a resolution that was four times higher than the number of pixel arrays. We subsampled this image and generated four different phosphene images. We then evaluated the recognition scores of characters by sequentially presenting phosphene images with varying pixel array sizes (6 × 6, 8 × 8 and 10 × 10) and stimulus frame rates (10 Hz, 15 Hz, 20 Hz, 30 Hz, and 60 Hz). The proposed method showed the highest recognition score at a stimulus frame rate of approximately 20 Hz. The method also significantly improved the recognition score for complex characters. This method provides a new way to increase practical resolution over restricted spatial resolution by merging the higher resolution image into high-frame time slots. PMID:29073735

[EEG source localization using LORETA (low resolution electromagnetic tomography)].

PubMed

Puskás, Szilvia

2011-03-30

Eledctroencephalography (EEG) has excellent temporal resolution, but the spatial resolution is poor. Different source localization methods exist to solve the so-called inverse problem, thus increasing the accuracy of spatial localization. This paper provides an overview of the history of source localization and the main categories of techniques are discussed. LORETA (low resolution electromagnetic tomography) is introduced in details: technical informations are discussed and localization properties of LORETA method are compared to other inverse solutions. Validation of the method with different imaging techniques is also discussed. This paper reviews several publications using LORETA both in healthy persons and persons with different neurological and psychiatric diseases. Finally future possible applications are discussed.

Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

NASA Technical Reports Server (NTRS)

Dozier, Jeff; Davis, Robert E.

1987-01-01

Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

Signal enhancement and Patterson-search phasing for high-spatial-resolution coherent X-ray diffraction imaging of biological objects.

PubMed

Takayama, Yuki; Maki-Yonekura, Saori; Oroguchi, Tomotaka; Nakasako, Masayoshi; Yonekura, Koji

2015-01-28

In this decade coherent X-ray diffraction imaging has been demonstrated to reveal internal structures of whole biological cells and organelles. However, the spatial resolution is limited to several tens of nanometers due to the poor scattering power of biological samples. The challenge is to recover correct phase information from experimental diffraction patterns that have a low signal-to-noise ratio and unmeasurable lowest-resolution data. Here, we propose a method to extend spatial resolution by enhancing diffraction signals and by robust phasing. The weak diffraction signals from biological objects are enhanced by interference with strong waves from dispersed colloidal gold particles. The positions of the gold particles determined by Patterson analysis serve as the initial phase, and this dramatically improves reliability and convergence of image reconstruction by iterative phase retrieval. A set of calculations based on current experiments demonstrates that resolution is improved by a factor of two or more.

Signal enhancement and Patterson-search phasing for high-spatial-resolution coherent X-ray diffraction imaging of biological objects

PubMed Central

Takayama, Yuki; Maki-Yonekura, Saori; Oroguchi, Tomotaka; Nakasako, Masayoshi; Yonekura, Koji

2015-01-01

In this decade coherent X-ray diffraction imaging has been demonstrated to reveal internal structures of whole biological cells and organelles. However, the spatial resolution is limited to several tens of nanometers due to the poor scattering power of biological samples. The challenge is to recover correct phase information from experimental diffraction patterns that have a low signal-to-noise ratio and unmeasurable lowest-resolution data. Here, we propose a method to extend spatial resolution by enhancing diffraction signals and by robust phasing. The weak diffraction signals from biological objects are enhanced by interference with strong waves from dispersed colloidal gold particles. The positions of the gold particles determined by Patterson analysis serve as the initial phase, and this dramatically improves reliability and convergence of image reconstruction by iterative phase retrieval. A set of calculations based on current experiments demonstrates that resolution is improved by a factor of two or more. PMID:25627480

High-angular-resolution stellar imaging with occultations from the Cassini spacecraft - III. Mira

NASA Astrophysics Data System (ADS)

Stewart, Paul N.; Tuthill, Peter G.; Nicholson, Philip D.; Hedman, Matthew M.

2016-04-01

We present an analysis of spectral and spatial data of Mira obtained by the Cassini spacecraft, which not only observed the star's spectra over a broad range of near-infrared wavelengths, but was also able to obtain high-resolution spatial information by watching the star pass behind Saturn's rings. The observed spectral range of 1-5 microns reveals the stellar atmosphere in the crucial water-bands which are unavailable to terrestrial observers, and the simultaneous spatial sampling allows the origin of spectral features to be located in the stellar environment. Models are fitted to the data, revealing the spectral and spatial structure of molecular layers surrounding the star. High-resolution imagery is recovered revealing the layered and asymmetric nature of the stellar atmosphere. The observational data set is also used to confront the state-of-the-art cool opacity-sampling dynamic extended atmosphere models of Mira variables through a detailed spectral and spatial comparison, revealing in general a good agreement with some specific departures corresponding to particular spectral features.

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

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.

Information transfer in auditoria and room-acoustical quality.

PubMed

Summers, Jason E

2013-04-01

It is hypothesized that room-acoustical quality correlates with the information-transfer rate. Auditoria are considered as multiple-input multiple-output communication channels and a theory of information-transfer is outlined that accounts for time-variant multipath, spatial hearing, and distributed directional sources. Source diversity and spatial hearing are shown to be the mechanisms through which multipath increases the information-transfer rate by overcoming finite spatial resolution. In addition to predictions that are confirmed by recent and historical findings, the theory provides explanations for the influence of factors such as musical repertoire and ensemble size on subjective preference and the influence of multisource, multichannel auralization on perceived realism.

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.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Modeling of digital information optical encryption system with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Bondareva, Alyona P.; Cheremkhin, Pavel A.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Rostislav S.; Starikov, Sergey N.

2015-10-01

State of the art micromirror DMD spatial light modulators (SLM) offer unprecedented framerate up to 30000 frames per second. This, in conjunction with high speed digital camera, should allow to build high speed optical encryption system. Results of modeling of digital information optical encryption system with spatially incoherent illumination are presented. Input information is displayed with first SLM, encryption element - with second SLM. Factors taken into account are: resolution of SLMs and camera, holograms reconstruction noise, camera noise and signal sampling. Results of numerical simulation demonstrate high speed (several gigabytes per second), low bit error rate and high crypto-strength.

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.

Surface water classification and monitoring using polarimetric synthetic aperture radar

NASA Astrophysics Data System (ADS)

Irwin, Katherine Elizabeth

Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data. The RS-2 data allows for the discrimination of open water, marshes/fields and forested areas. However, the RS-2 data is less applicable to small scale surface water monitoring (e.g. beaver dam failure), due to its low spatial resolution. By understanding the strengths and weaknesses of available SAR technology, an appropriate product can be chosen for a specific target application involving surface water change. This research benefits the eventual development of a space-based monitoring strategy over longer periods.

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

Information loss and reconstruction in diffuse fluorescence tomography

PubMed Central

Bonfert-Taylor, Petra; Leblond, Frederic; Holt, Robert W.; Tichauer, Kenneth; Pogue, Brian W.; Taylor, Edward C.

2012-01-01

This paper is a theoretical exploration of spatial resolution in diffuse fluorescence tomography. It is demonstrated that, given a fixed imaging geometry, one cannot—relative to standard techniques such as Tikhonov regularization and truncated singular value decomposition—improve the spatial resolution of the optical reconstructions via increasing the node density of the mesh considered for modeling light transport. Using techniques from linear algebra, it is shown that, as one increases the number of nodes beyond the number of measurements, information is lost by the forward model. It is demonstrated that this information cannot be recovered using various common reconstruction techniques. Evidence is provided showing that this phenomenon is related to the smoothing properties of the elliptic forward model that is used in the diffusion approximation to light transport in tissue. This argues for reconstruction techniques that are sensitive to boundaries, such as L1-reconstruction and the use of priors, as well as the natural approach of building a measurement geometry that reflects the desired image resolution. PMID:22472763

Generating high temporal and spatial resolution thermal band imagery using robust sharpening approach

USDA-ARS?s Scientific Manuscript database

Thermal infrared band imagery provides key information for detecting wild fires, mapping land surface energy fluxes and evapotranspiration, monitoring urban heat fluxes and drought monitoring. Thermal infrared (TIR) imagery at fine resolution is required for field scale applications. However, therma...

A quality assurance phantom for the performance evaluation of volumetric micro-CT systems

NASA Astrophysics Data System (ADS)

Du, Louise Y.; Umoh, Joseph; Nikolov, Hristo N.; Pollmann, Steven I.; Lee, Ting-Yim; Holdsworth, David W.

2007-12-01

Small-animal imaging has recently become an area of increased interest because more human diseases can be modeled in transgenic and knockout rodents. As a result, micro-computed tomography (micro-CT) systems are becoming more common in research laboratories, due to their ability to achieve spatial resolution as high as 10 µm, giving highly detailed anatomical information. Most recently, a volumetric cone-beam micro-CT system using a flat-panel detector (eXplore Ultra, GE Healthcare, London, ON) has been developed that combines the high resolution of micro-CT and the fast scanning speed of clinical CT, so that dynamic perfusion imaging can be performed in mice and rats, providing functional physiological information in addition to anatomical information. This and other commercially available micro-CT systems all promise to deliver precise and accurate high-resolution measurements in small animals. However, no comprehensive quality assurance phantom has been developed to evaluate the performance of these micro-CT systems on a routine basis. We have designed and fabricated a single comprehensive device for the purpose of performance evaluation of micro-CT systems. This quality assurance phantom was applied to assess multiple image-quality parameters of a current flat-panel cone-beam micro-CT system accurately and quantitatively, in terms of spatial resolution, geometric accuracy, CT number accuracy, linearity, noise and image uniformity. Our investigations show that 3D images can be obtained with a limiting spatial resolution of 2.5 mm-1 and noise of ±35 HU, using an acquisition interval of 8 s at an entrance dose of 6.4 cGy.

Photoacoustic microscopy and computed tomography: from bench to bedside

PubMed Central

Wang, Lihong V.; Gao, Liang

2014-01-01

Photoacoustic imaging (PAI) of biological tissue has seen immense growth in the past decade, providing unprecedented spatial resolution and functional information at depths in the optical diffusive regime. PAI uniquely combines the advantages of optical excitation and acoustic detection. The hybrid imaging modality features high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth. Here we first summarize the fundamental principles underpinning the technology, then highlight its practical implementation, and finally discuss recent advances towards clinical translation. PMID:24905877

Carotid Stenosis And Ulcer Detectability As A Function Of Pixel Size

NASA Astrophysics Data System (ADS)

Mintz, Leslie J.; Enzmann, Dieter R.; Keyes, Gary S.; Mainiero, Louis M.; Brody, William R.

1981-11-01

Digital radiography, in conjunction with digital subtraction methods can provide high quality images of the vascular system,1-4 Spatial resolution is one important limiting factor of this imaging technique. Since spatial resolution of a digital image is a function of pixel size, it is important to determine the pixel size threshold necessary to provide information comparable to that of conventional angiograms. This study was designed to establish the pixel size necessary to identify accurately stenotic and ulcerative lesions of the carotid artery.

Elevated-temperature luminescence measurements to improve spatial resolution

NASA Astrophysics Data System (ADS)

Pluska, Mariusz; Czerwinski, Andrzej

2018-01-01

Various branches of applied physics use luminescence based methods to investigate light-emitting specimens with high spatial resolution. A key problem is that luminescence signals lack all the advantages of high locality (i.e. of high spatial resolution) when structures with strong built-in electric field are measured. Such fields exist intentionally in most photonic structures, and occur unintentionally in many other materials. In this case, as a result of beam-induced current generation and its outflow, information that indicates irregularities, nonuniformities and inhomogeneities, such as defects, is lost. We show that to avoid nonlocality and enable truly local luminescence measurements, an elevated measurement temperature as high as 350 K (or even higher) is, perhaps surprisingly, advantageous. This is in contrast to a widely used approach, where cryogenic temperatures, or at least room temperature, are recommended. The elevated temperature of a specimen, together with the current outflow being limited by focused ion beam (FIB) milling, is shown to improve the spatial resolution of luminescence measurements greatly. All conclusions drawn using the example of cathodoluminescence are useful for other luminescence techniques.

Magnetic field sensing with nitrogen-vacancy color centers in diamond

NASA Astrophysics Data System (ADS)

Pham, Linh My

In recent years, the nitrogen-vacancy (NV) center has emerged as a promising magnetic sensor capable of measuring magnetic fields with high sensitivity and spatial resolution under ambient conditions. This combination of characteristics allows NV magnetometers to probe magnetic structures and systems that were previously inaccessible with alternative magnetic sensing technologies This dissertation presents and discusses a number of the initial efforts to demonstrate and improve NV magnetometry. In particular, a wide-field CCD based NV magnetic field imager capable of micron-scale spatial resolution is demonstrated; and magnetic field alignment, preferential NV orientation, and multipulse dynamical decoupling techniques are explored for enhancing magnetic sensitivity. The further application of dynamical decoupling control sequences as a spectral probe to extract information about the dynamics of the NV spin environment is also discussed; such information may be useful for determining optimal diamond sample parameters for different applications. Finally, several proposed and recently demonstrated applications which take advantage of NV magnetometers' sensitivity and spatial resolution at room temperature are presented, with particular focus on bio-magnetic field imaging.

Nanoscale simultaneous chemical and mechanical imaging via peak force infrared microscopy

PubMed Central

Wang, Le; Wang, Haomin; Wagner, Martin; Yan, Yong; Jakob, Devon S.; Xu, Xiaoji G.

2017-01-01

Nondestructive chemical and mechanical measurements of materials with ~10-nm spatial resolution together with topography provide rich information on the compositions and organizations of heterogeneous materials and nanoscale objects. However, multimodal nanoscale correlations are difficult to achieve because of the limitation on spatial resolution of optical microscopy and constraints from instrumental complexities. We report a novel noninvasive spectroscopic scanning probe microscopy method—peak force infrared (PFIR) microscopy—that allows chemical imaging, collection of broadband infrared spectra, and mechanical mapping at a spatial resolution of 10 nm. In our technique, chemical absorption information is directly encoded in the withdraw curve of the peak force tapping cycle after illumination with synchronized infrared laser pulses in a simple apparatus. Nanoscale phase separation in block copolymers and inhomogeneity in CH3NH3PbBr3 perovskite crystals are studied with correlative infrared/mechanical nanoimaging. Furthermore, we show that the PFIR method is sensitive to the presence of surface phonon polaritons in boron nitride nanotubes. PFIR microscopy will provide a powerful analytical tool for explorations at the nanoscale across wide disciplines. PMID:28691096

Documentation and analysis of a geographic information system application for combining data layers, using nonpoint-source pollution as an example

USGS Publications Warehouse

Kiesler, James L.

2002-01-01

An analysis of the application indicates that the selected data layers to be combined should be at the greatest spatial resolution possible; however, all data layers do not have to be at the same spatial resolution. The spatial variation of the data layers should be adequately defined. The size of each grid cell should be small enough to maintain the spatial definition of smaller features within the data layers. The most accurate results are shown to occur when the values for the grid cells representing the individual data layers are summed and the mean of the summed grid-cell values is used to describe the watershed of interest.

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Treesearch

Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

2012-01-01

Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

Urban Spatial Ecological Performance Based on the Data of Remote Sensing of Guyuan

NASA Astrophysics Data System (ADS)

Ren, X.-J.; Chen, X.-J.; Ma, Q.

2018-04-01

The evolution analysis of urban landuse and spatial ecological performance are necessary and useful to recognizing the stage of urban development and revealing the regularity and connotation of urban spatial expansion. Moreover, it lies in the core that should be exmined in the urban sustainable development. In this paper, detailed information has been acquired from the high-resolution satellite imageries of Guyuan, China case study. With the support of GIS, the land-use mapping information and the land cover changes are analyzed, and the process of urban spatial ecological performance evolution by the hierarchical methodology is explored. Results demonstrate that in the past 11 years, the urban spatial ecological performance show an improved process with the dramatic landcover change in Guyuan. Firstly, the landuse structure of Guyuan changes significantly and shows an obvious stage characteristic. Secondly, the urban ecological performance of Guyuan continues to be optimized over the 11 years. Thirdly, the findings suggest that a dynamic monitoring mechanism of urban land use based on high-resolution remote sensing data should be established in urban development, and the rational development of urban land use should be guided by the spatial ecological performance as the basic value orientation.

Very high resolution time-lapse photography for plant and ecosystems research

USDA-ARS?s Scientific Manuscript database

Very high resolution gigapixel photography increasingly is being used to support a broad range of ecosystem and physical process research because it offers an inexpensive means of simultaneously collecting information at a range of spatial scales. Recently, methods have been developed to incorporate...

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Scattered electrons in microscopy and microanalysis

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

Ottensmeyer, F.P.

The use of scattered electrons alone for direct imaging of biological specimens makes it possible to obtain structural information at atomic and near-atomic spatial resolutions of 0.3 to 0.5 nanometer. While this is not as good as the resolution possible with x-ray crystallography, such an approach provides structural information rapidly on individual macromolecules that have not been, and possibly cannot be, crystallized. Analysis of the spectrum of energies of scattered electrons and imaging of the latter with characteristic energy bands within the spectrum produces a powerful new technique of atomic microanalysis. This technique, which has a spatial resolution of aboutmore » 0.5 nanometer and a minimum detection sensitivity of about 50 atoms of phosphorus, is especially useful for light atom analysis and appears to have applications in molecular biology, cell biology, histology, pathology, botany, and many other fields.« less

Scattered electrons in microscopy and microanalysis

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

Ottensmeyer, F.P.

The use of scattered electrons alone for direct imaging of biological specimens makes it possible to obtain structural information at atomic and near-atomic spatial resolutions of 0.3 to 0.5 nanometer. While this is not as good as the resolution possible with x-ray crystallography, such an approach provides structural information rapidly on individual macromolecules that have not been, and possibly cannot be, crystallized. Analysis of the spectrum of energies of scattered electrons and imaging of the latter with characteristic energy bands within the spectrum produce a powerful new technique of atomic microanalysis. This technique, which has a spatial resolution of aboutmore » 0.5 nanometer and a minimum detection sensitivity of about 50 atoms of phosphorus, is especially useful for light atom analysis and appears to have applications in molecular biology, cell biology, histology, pathology, botany, and many other fields.« less

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

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

PubMed

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

2018-02-14

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

High resolution population distribution maps for Southeast Asia in 2010 and 2015.

PubMed

Gaughan, Andrea E; Stevens, Forrest R; Linard, Catherine; Jia, Peng; Tatem, Andrew J

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.

High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015

PubMed Central

Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org. PMID:23418469

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

PubMed Central

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

de Kleer, Katherine R.; de Pater, Imke

2017-10-01

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

Thermal Physical Property-Based Fusion of Geostationary Meteorological Satellite Visible and Infrared Channel Images

PubMed Central

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-01-01

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017

Thermal physical property-based fusion of geostationary meteorological satellite visible and infrared channel images.

PubMed

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-06-10

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.

Increased tree-ring network density reveals more precise estimations of sub-regional hydroclimate variability and climate dynamics in the Midwest, USA

NASA Astrophysics Data System (ADS)

Maxwell, Justin T.; Harley, Grant L.

2017-08-01

Understanding the historic variability in the hydroclimate provides important information on possible extreme dry or wet periods that in turn inform water management plans. Tree rings have long provided historical context of hydroclimate variability of the U.S. However, the tree-ring network used to create these countrywide gridded reconstructions is sparse in certain locations, such as the Midwest. Here, we increase ( n = 20) the spatial resolution of the tree-ring network in southern Indiana and compare a summer (June-August) Palmer Drought Severity Index (PDSI) reconstruction to existing gridded reconstructions of PDSI for this region. We find both droughts and pluvials that were previously unknown that rival the most intense PDSI values during the instrumental period. Additionally, historical drought occurred in Indiana that eclipsed instrumental conditions with regard to severity and duration. During the period 1962-2004 CE, we find that teleconnections of drought conditions through the Atlantic Meridional Overturning Circulation have a strong influence ( r = -0.60, p < 0.01) on secondary tree growth in this region for the late spring-early summer season. These findings highlight the importance of continuing to increase the spatial resolution of the tree-ring network used to infer past climate dynamics to capture the sub-regional spatial variability. Increasing the spatial resolution of the tree-ring network for a given region can better identify sub-regional variability, improve the accuracy of regional tree-ring PDSI reconstructions, and provide better information for climatic teleconnections.

Influence of resolution in irrigated area mapping and area estimation

USGS Publications Warehouse

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

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Beam test results of the BTeV silicon pixel detector

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

Gabriele Chiodini et al.

2000-09-28

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

GOW2.0: A global wave hindcast of high resolution

NASA Astrophysics Data System (ADS)

Menendez, Melisa; Perez, Jorge; Losada, Inigo

2016-04-01

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

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

NASA Technical Reports Server (NTRS)

Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki

2002-01-01

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

Far Infrared Imaging Spectrometer for Large Aperture Infrared Telescope System

DTIC Science & Technology

1985-12-01

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

High-resolution remote sensing of water quality in the San Francisco Bay-Delta Estuary

USGS Publications Warehouse

Fichot, Cédric G.; Downing, Bryan D.; Bergamaschi, Brian; Windham-Myers, Lisamarie; Marvin-DiPasquale, Mark C.; Thompson, David R.; Gierach, Michelle M.

2015-01-01

The San Francisco Bay–Delta Estuary watershed is a major source of freshwater for California and a profoundly human-impacted environment. The water quality monitoring that is critical to the management of this important water resource and ecosystem relies primarily on a system of fixed water-quality monitoring stations, but the limited spatial coverage often hinders understanding. Here, we show how the latest technology in visible/near-infrared imaging spectroscopy can facilitate water quality monitoring in this highly dynamic and heterogeneous system by enabling simultaneous depictions of several water quality indicators at very high spatial resolution. The airborne portable remote imaging spectrometer (PRISM) was used to derive high-spatial-resolution (2.6 × 2.6 m) distributions of turbidity, and dissolved organic carbon (DOC) and chlorophyll-a concentrations in a wetland-influenced region of this estuary. A filter-passing methylmercury vs DOC relationship was also developed using in situ samples and enabled the high-spatial-resolution depiction of surface methylmercury concentrations in this area. The results illustrate how high-resolution imaging spectroscopy can inform management and policy development in important inland and estuarine water bodies by facilitating the detection of point- and nonpoint-source pollution, and by providing data to help assess the complex impacts of wetland restoration and climate change on water quality and ecosystem productivity.

Example-based super-resolution for single-image analysis from the Chang'e-1 Mission

NASA Astrophysics Data System (ADS)

Wu, Fan-Lu; Wang, Xiang-Jun

2016-11-01

Due to the low spatial resolution of images taken from the Chang'e-1 (CE-1) orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution (SR) algorithm is employed to obtain high-resolution (HR) images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.

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.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Ecologic Niche Modeling and Spatial Patterns of Disease Transmission

PubMed Central

2006-01-01

Ecologic niche modeling (ENM) is a growing field with many potential applications to questions regarding the geography and ecology of disease transmission. Specifically, ENM has the potential to inform investigations concerned with the geography, or potential geography, of vectors, hosts, pathogens, or human cases, and it can achieve fine spatial resolution without the loss of information inherent in many other techniques. Potential applications and current frontiers and challenges are reviewed. PMID:17326931

Tactile Feedback Display with Spatial and Temporal Resolutions

PubMed Central

Vishniakou, Siarhei; Lewis, Brian W.; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-01-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications. PMID:23982053

Tactile feedback display with spatial and temporal resolutions.

PubMed

Vishniakou, Siarhei; Lewis, Brian W; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-01-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications.

Tactile Feedback Display with Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Vishniakou, Siarhei; Lewis, Brian W.; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-08-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Atomic-Resolution Spectrum Imaging of Semiconductor Nanowires.

PubMed

Zamani, Reza R; Hage, Fredrik S; Lehmann, Sebastian; Ramasse, Quentin M; Dick, Kimberly A

2018-03-14

Over the past decade, III-V heterostructure nanowires have attracted a surge of attention for their application in novel semiconductor devices such as tunneling field-effect transistors (TFETs). The functionality of such devices critically depends on the specific atomic arrangement at the semiconductor heterointerfaces. However, most of the currently available characterization techniques lack sufficient spatial resolution to provide local information on the atomic structure and composition of these interfaces. Atomic-resolution spectrum imaging by means of electron energy-loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) is a powerful technique with the potential to resolve structure and chemical composition with sub-angstrom spatial resolution and to provide localized information about the physical properties of the material at the atomic scale. Here, we demonstrate the use of atomic-resolution EELS to understand the interface atomic arrangement in three-dimensional heterostructures in semiconductor nanowires. We observed that the radial interfaces of GaSb-InAs heterostructure nanowires are atomically abrupt, while the axial interface in contrast consists of an interfacial region where intermixing of the two compounds occurs over an extended spatial region. The local atomic configuration affects the band alignment at the interface and, hence, the charge transport properties of devices such as GaSb-InAs nanowire TFETs. STEM-EELS thus represents a very promising technique for understanding nanowire physical properties, such as differing electrical behavior across the radial and axial heterointerfaces of GaSb-InAs nanowires for TFET applications.

Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis

PubMed Central

Jain, Saurabh; Sima, Diana M.; Sanaei Nezhad, Faezeh; Hangel, Gilbert; Bogner, Wolfgang; Williams, Stephen; Van Huffel, Sabine; Maes, Frederik; Smeets, Dirk

2017-01-01

Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications. PMID:28197066

Temporal and spatial scaling impacts on extreme precipitation

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Acquisition of a full-resolution image and aliasing reduction for a spatially modulated imaging polarimeter with two snapshots

PubMed Central

Zhang, Jing; Yuan, Changan; Huang, Guohua; Zhao, Yinjun; Ren, Wenyi; Cao, Qizhi; Li, Jianying; Jin, Mingwu

2018-01-01

A snapshot imaging polarimeter using spatial modulation can encode four Stokes parameters allowing instantaneous polarization measurement from a single interferogram. However, the reconstructed polarization images could suffer a severe aliasing signal if the high-frequency component of the intensity image is prominent and occurs in the polarization channels, and the reconstructed intensity image also suffers reduction of spatial resolution due to low-pass filtering. In this work, a method using two anti-phase snapshots is proposed to address the two problems simultaneously. The full-resolution target image and the pure interference fringes can be obtained from the sum and the difference of the two anti-phase interferograms, respectively. The polarization information reconstructed from the pure interference fringes does not contain the aliasing signal from the high-frequency component of the object intensity image. The principles of the method are derived and its feasibility is tested by both computer simulation and a verification experiment. This work provides a novel method for spatially modulated imaging polarization technology with two snapshots to simultaneously reconstruct a full-resolution object intensity image and high-quality polarization components. PMID:29714224

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

D Object Classification Based on Thermal and Visible Imagery in Urban Area

NASA Astrophysics Data System (ADS)

Hasani, H.; Samadzadegan, F.

2015-12-01

The spatial distribution of land cover in the urban area especially 3D objects (buildings and trees) is a fundamental dataset for urban planning, ecological research, disaster management, etc. According to recent advances in sensor technologies, several types of remotely sensed data are available from the same area. Data fusion has been widely investigated for integrating different source of data in classification of urban area. Thermal infrared imagery (TIR) contains information on emitted radiation and has unique radiometric properties. However, due to coarse spatial resolution of thermal data, its application has been restricted in urban areas. On the other hand, visible image (VIS) has high spatial resolution and information in visible spectrum. Consequently, there is a complementary relation between thermal and visible imagery in classification of urban area. This paper evaluates the potential of aerial thermal hyperspectral and visible imagery fusion in classification of urban area. In the pre-processing step, thermal imagery is resampled to the spatial resolution of visible image. Then feature level fusion is applied to construct hybrid feature space include visible bands, thermal hyperspectral bands, spatial and texture features and moreover Principle Component Analysis (PCA) transformation is applied to extract PCs. Due to high dimensionality of feature space, dimension reduction method is performed. Finally, Support Vector Machines (SVMs) classify the reduced hybrid feature space. The obtained results show using thermal imagery along with visible imagery, improved the classification accuracy up to 8% respect to visible image classification.

DEM generation from contours and a low-resolution DEM

NASA Astrophysics Data System (ADS)

Li, Xinghua; Shen, Huanfeng; Feng, Ruitao; Li, Jie; Zhang, Liangpei

2017-12-01

A digital elevation model (DEM) is a virtual representation of topography, where the terrain is established by the three-dimensional co-ordinates. In the framework of sparse representation, this paper investigates DEM generation from contours. Since contours are usually sparsely distributed and closely related in space, sparse spatial regularization (SSR) is enforced on them. In order to make up for the lack of spatial information, another lower spatial resolution DEM from the same geographical area is introduced. In this way, the sparse representation implements the spatial constraints in the contours and extracts the complementary information from the auxiliary DEM. Furthermore, the proposed method integrates the advantage of the unbiased estimation of kriging. For brevity, the proposed method is called the kriging and sparse spatial regularization (KSSR) method. The performance of the proposed KSSR method is demonstrated by experiments in Shuttle Radar Topography Mission (SRTM) 30 m DEM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m global digital elevation model (GDEM) generation from the corresponding contours and a 90 m DEM. The experiments confirm that the proposed KSSR method outperforms the traditional kriging and SSR methods, and it can be successfully used for DEM generation from contours.

A Global Map of Thermal Inertia from Mars Global Surveyor Mapping-Mission Data

NASA Technical Reports Server (NTRS)

Mellon, M. T.; Kretke, K. A.; Smith, M. D.; Pelkey, S. M.

2002-01-01

TES (thermal emission spectrometry) has obtained high spatial resolution surface temperature observations from which thermal inertia has been derived. Seasonal coverage of these data now provides a nearly global view of Mars, including the polar regions, at high resolution. Additional information is contained in the original extended abstract.

Analysis of long term trends of precipitation estimates acquired using radar network in Turkey

NASA Astrophysics Data System (ADS)

Tugrul Yilmaz, M.; Yucel, Ismail; Kamil Yilmaz, Koray

2016-04-01

Precipitation estimates, a vital input in many hydrological and agricultural studies, can be obtained using many different platforms (ground station-, radar-, model-, satellite-based). Satellite- and model-based estimates are spatially continuous datasets, however they lack the high resolution information many applications often require. Station-based values are actual precipitation observations, however they suffer from their nature that they are point data. These datasets may be interpolated however such end-products may have large errors over remote locations with different climate/topography/etc than the areas stations are installed. Radars have the particular advantage of having high spatial resolution information over land even though accuracy of radar-based precipitation estimates depends on the Z-R relationship, mountain blockage, target distance from the radar, spurious echoes resulting from anomalous propagation of the radar beam, bright band contamination and ground clutter. A viable method to obtain spatially and temporally high resolution consistent precipitation information is merging radar and station data to take advantage of each retrieval platform. An optimally merged product is particularly important in Turkey where complex topography exerts strong controls on the precipitation regime and in turn hampers observation efforts. There are currently 10 (additional 7 are planned) weather radars over Turkey obtaining precipitation information since 2007. This study aims to optimally merge radar precipitation data with station based observations to introduce a station-radar blended precipitation product. This study was supported by TUBITAK fund # 114Y676.

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

PubMed Central

Calera, Alfonso; Campos, Isidro; Osann, Anna; D’Urso, Guido; Menenti, Massimo

2017-01-01

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. PMID:28492515

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users.

PubMed

Calera, Alfonso; Campos, Isidro; Osann, Anna; D'Urso, Guido; Menenti, Massimo

2017-05-11

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data.

PubMed

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R

2015-09-11

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite's Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

PubMed Central

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R.

2015-01-01

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

Application of future remote sensing systems to irrigation

NASA Technical Reports Server (NTRS)

Miller, L. D.

1982-01-01

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Spatially resolved D-T(2) correlation NMR of porous media.

PubMed

Zhang, Yan; Blümich, Bernhard

2014-05-01

Within the past decade, 2D Laplace nuclear magnetic resonance (NMR) has been developed to analyze pore geometry and diffusion of fluids in porous media on the micrometer scale. Many objects like rocks and concrete are heterogeneous on the macroscopic scale, and an integral analysis of microscopic properties provides volume-averaged information. Magnetic resonance imaging (MRI) resolves this spatial average on the contrast scale set by the particular MRI technique. Desirable contrast parameters for studies of fluid transport in porous media derive from the pore-size distribution and the pore connectivity. These microscopic parameters are accessed by 1D and 2D Laplace NMR techniques. It is therefore desirable to combine MRI and 2D Laplace NMR to image functional information on fluid transport in porous media. Because 2D Laplace resolved MRI demands excessive measuring time, this study investigates the possibility to restrict the 2D Laplace analysis to the sum signals from low-resolution pixels, which correspond to pixels of similar amplitude in high-resolution images. In this exploratory study spatially resolved D-T2 correlation maps from glass beads and mortar are analyzed. Regions of similar contrast are first identified in high-resolution images to locate corresponding pixels in low-resolution images generated with D-T2 resolved MRI for subsequent pixel summation to improve the signal-to-noise ratio of contrast-specific D-T2 maps. This method is expected to contribute valuable information on correlated sample heterogeneity from the macroscopic and the microscopic scales in various types of porous materials including building materials and rock. Copyright © 2014 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

A Submillimeter Resolution PET Prototype Evaluated With an 18F Inkjet Printed Phantom

NASA Astrophysics Data System (ADS)

Schneider, Florian R.; Hohberg, Melanie; Mann, Alexander B.; Paul, Stephan; Ziegler, Sibylle I.

2015-10-01

This work presents a submillimeter resolution PET (Positron Emission Tomography) scanner prototype based on SiPM/MPPC arrays (Silicon Photomultiplier/Multi Pixel Photon Counter). Onto each active area a 1 ×1 ×20 mm3 LYSO (Lutetium-Yttrium-Oxyorthosilicate) scintillator crystal is coupled one-to-one. Two detector modules facing each other in a distance of 10.0 cm have been set up with in total 64 channels that are digitized by SADCs (Sampling Analog to Digital Converters) with 80 MHz, 10 bit resolution and FPGA (Field Programmable Gate Array) based extraction of energy and time information. Since standard phantoms are not sufficient for testing submillimeter resolution at which positron range is an issue, a 18F inkjet printed phantom has been used to explore the limit in spatial resolution. The phantom could be successfully reconstructed with an iterative MLEM (Maximum Likelihood Expectation Maximization) and an analytically calculated system matrix based on the DRF (Detector Response Function) model. The system yields a coincidence time resolution of 4.8 ns FWHM, an energy resolution of 20%-30% FWHM and a spatial resolution of 0.8 mm.

Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

PubMed

Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

2018-01-01

The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Electro-triggering and electrochemical monitoring of dopamine exocytosis from a single cell by using ultrathin electrodes based on Au nanowires

NASA Astrophysics Data System (ADS)

Kang, Mijeong; Yoo, Seung Min; Gwak, Raekeun; Eom, Gayoung; Kim, Jihwan; Lee, Sang Yup; Kim, Bongsoo

2015-12-01

A sophisticated set of an Au nanowire (NW) stimulator-Au NW detector system is developed for electrical cell stimulation and electrochemical analysis of subsequent exocytosis with very high spatial resolution. Dopamine release from a rat pheochromocytoma cell is more stimulated by a more negative voltage pulse. This system could help to improve the therapeutic efficacy of electrotherapies by providing valuable information on their healing mechanism.A sophisticated set of an Au nanowire (NW) stimulator-Au NW detector system is developed for electrical cell stimulation and electrochemical analysis of subsequent exocytosis with very high spatial resolution. Dopamine release from a rat pheochromocytoma cell is more stimulated by a more negative voltage pulse. This system could help to improve the therapeutic efficacy of electrotherapies by providing valuable information on their healing mechanism. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06021d

A Phenomenological Two-Ribbon Model for Spatially Unresolved Observations of Stellar Flares

NASA Astrophysics Data System (ADS)

Kowalski, Adam

2018-06-01

Solar flares and flares that occur in much more magnetically active stars share some striking properties, such as the observed Neupert effect. However, stellar flares with the most impressive multi-wavelength data sets are typically much more energetic than solar flares, thus making robust connections difficult to establish. Whereas solar data have the advantage of high spatial resolution providing critical information about the development of flare ribbons, the major advantage of stellar flare data is the readily available broad-wavelength coverage of the white-light radiation and the Balmer jump spectral region. Due to the lack of direct spatial resolution for stellar flares and rarely coverage of the Balmer jump region for solar flares, it is not clear how to make a direct comparison. I will present a new method for modeling stellar flares based on high spatial resolution information of solar flare two-ribbon development for comparisons of the physics of their observed phenomena, such as the red-wing asymmetries in chromospheric lines and the white-light continuum radiation. The new modeling method combines aspects of "multi-thread" modeling and 1D radiative-hydrodynamic modeling. Our algorithm is important for interpreting the impulsive phase of superflares in young G dwarfs in Kepler and understanding how hour-long decay timescales are attained in the gradual phase of some very energetic stellar flares.

High-resolution forest mapping for behavioural studies in the Nature Reserve ‘Les Nouragues’, French Guiana

PubMed Central

Ringler, Max; Mangione, Rosanna; Pašukonis, Andrius; Rainer, Gerhard; Gyimesi, Kristin; Felling, Julia; Kronaus, Hannes; Réjou-Méchain, Maxime; Chave, Jérôme; Reiter, Karl; Ringler, Eva

2015-01-01

For animals with spatially complex behaviours at relatively small scales, the resolution of a global positioning system (GPS) receiver location is often below the resolution needed to correctly map animals’ spatial behaviour. Natural conditions such as canopy cover, canyons or clouds can further degrade GPS receiver reception. Here we present a detailed, high-resolution map of a 4.6 ha Neotropical river island and a 8.3 ha mainland plot with the location of every tree >5 cm DBH and all structures on the forest floor, which are relevant to our study species, the territorial frog Allobates femoralis (Dendrobatidae). The map was derived using distance- and compass-based survey techniques, rooted on dGPS reference points, and incorporates altitudinal information based on a LiDAR survey of the area. PMID:27053943

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

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

2008-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Optimization of high count rate event counting detector with Microchannel Plates and quad Timepix readout

NASA Astrophysics Data System (ADS)

Tremsin, A. S.; Vallerga, J. V.; McPhate, J. B.; Siegmund, O. H. W.

2015-07-01

Many high resolution event counting devices process one event at a time and cannot register simultaneous events. In this article a frame-based readout event counting detector consisting of a pair of Microchannel Plates and a quad Timepix readout is described. More than 104 simultaneous events can be detected with a spatial resolution of 55 μm, while >103 simultaneous events can be detected with <10 μm spatial resolution when event centroiding is implemented. The fast readout electronics is capable of processing >1200 frames/sec, while the global count rate of the detector can exceed 5×108 particles/s when no timing information on every particle is required. For the first generation Timepix readout, the timing resolution is limited by the Timepix clock to 10-20 ns. Optimization of the MCP gain, rear field voltage and Timepix threshold levels are crucial for the device performance and that is the main subject of this article. These devices can be very attractive for applications where the photon/electron/ion/neutron counting with high spatial and temporal resolution is required, such as energy resolved neutron imaging, Time of Flight experiments in lidar applications, experiments on photoelectron spectroscopy and many others.

Solar Confocal interferometers for Sub-Picometer-Resolution Spectral Filters

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Novel medical imaging technologies for disease diagnosis and treatment

NASA Astrophysics Data System (ADS)

Olego, Diego

2009-03-01

New clinical approaches for disease diagnosis, treatment and monitoring will rely on the ability of simultaneously obtaining anatomical, functional and biological information. Medical imaging technologies in combination with targeted contrast agents play a key role in delivering with ever increasing temporal and spatial resolution structural and functional information about conditions and pathologies in cardiology, oncology and neurology fields among others. This presentation will review the clinical motivations and physics challenges in on-going developments of new medical imaging techniques and the associated contrast agents. Examples to be discussed are: *The enrichment of computer tomography with spectral sensitivity for the diagnosis of vulnerable sclerotic plaque. *Time of flight positron emission tomography for improved resolution in metabolic characterization of pathologies. *Magnetic particle imaging -a novel imaging modality based on in-vivo measurement of the local concentration of iron oxide nano-particles - for blood perfusion measurement with better sensitivity, spatial resolution and 3D real time acquisition. *Focused ultrasound for therapy delivery.

Daniel K. Inouye Solar Telescope: High-resolution observing of the dynamic Sun

NASA Astrophysics Data System (ADS)

Tritschler, A.; Rimmele, T. R.; Berukoff, S.; Casini, R.; Kuhn, J. R.; Lin, H.; Rast, M. P.; McMullin, J. P.; Schmidt, W.; Wöger, F.; DKIST Team

2016-11-01

The 4-m aperture Daniel K. Inouye Solar Telescope (DKIST) formerly known as the Advanced Technology Solar Telescope (ATST) is currently under construction on Haleakalā (Maui, Hawai'i) projected to start operations in 2019. At the time of completion, DKIST will be the largest ground-based solar telescope providing unprecedented resolution and photon collecting power. The DKIST will be equipped with a set of first-light facility-class instruments offering unique imaging, spectroscopic and spectropolarimetric observing opportunities covering the visible to infrared wavelength range. This first-light instrumentation suite will include: a Visible Broadband Imager (VBI) for high-spatial and -temporal resolution imaging of the solar atmosphere; a Visible Spectro-Polarimeter (ViSP) for sensitive and accurate multi-line spectropolarimetry; a Fabry-Pérot based Visible Tunable Filter (VTF) for high-spatial resolution spectropolarimetry; a fiber-fed Diffraction-Limited Near Infra-Red Spectro-Polarimeter (DL-NIRSP) for two-dimensional high-spatial resolution spectropolarimetry (simultaneous spatial and spectral information); and a Cryogenic Near Infra-Red Spectro-Polarimeter (Cryo-NIRSP) for coronal magnetic field measurements and on-disk observations of, e.g., the CO lines at 4.7 μm. We will provide an overview of the DKIST's unique capabilities with strong focus on the first-light instrumentation suite, highlight some of the additional properties supporting observations of transient and dynamic solar phenomena, and touch on some operational strategies and the DKIST critical science plan.

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

PubMed

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

2016-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

NASA Astrophysics Data System (ADS)

Tarolli, Jay G.; Jackson, Lauren M.; Winograd, Nicholas

2014-12-01

The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images but also by detection sensitivity. As the probe size is reduced to below 1 μm, for example, a low signal in each pixel limits lateral resolution because of counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure.

[Non-contrast time-resolved magnetic resonance angiography combining high resolution multiple phase echo planar imaging based signal targeting and alternating radiofrequency contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency in intracranial arteries].

PubMed

Nakamura, Masanobu; Yoneyama, Masami; Tabuchi, Takashi; Takemura, Atsushi; Obara, Makoto; Sawano, Seishi

2012-01-01

Detailed information on anatomy and hemodynamics in cerebrovascular disorders such as AVM and Moyamoya disease is mandatory for defined diagnosis and treatment planning. Arterial spin labeling technique has come to be applied to magnetic resonance angiography (MRA) and perfusion imaging in recent years. However, those non-contrast techniques are mostly limited to single frame images. Recently we have proposed a non-contrast time-resolved MRA technique termed contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency (CINEMA-STAR). CINEMA-STAR can extract the blood flow in the major intracranial arteries at an interval of 70 ms and thus permits us to observe vascular construction in full by preparing MIP images of axial acquisitions with high spatial resolution. This preliminary study demonstrates the usefulness of the CINEMA-STAR technique in evaluating the cerebral vasculature.

X-ray Tomography and Chemical Imaging within Butterfly Wing Scales

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

Chen Jianhua; Lee Yaochang; Tang, M.-T.

2007-01-19

The rainbow like color of butterfly wings is associated with the internal and surface structures of the wing scales. While the photonic structure of the scales is believed to diffract specific lights at different angle, there is no adequate probe directly answering the 3-D structures with sufficient spatial resolution. The NSRRC nano-transmission x-ray microscope (nTXM) with tens nanometers spatial resolution is able to image biological specimens without artifacts usually introduced in sophisticated sample staining processes. With the intrinsic deep penetration of x-rays, the nTXM is capable of nondestructively investigating the internal structures of fragile and soft samples. In this study,more » we imaged the structure of butterfly wing scales in 3-D view with 60 nm spatial resolution. In addition, synchrotron-radiation-based Fourier transform Infrared (FT-IR) microspectroscopy was employed to analyze the chemical components with spatial information of the butterfly wing scales. Based on the infrared spectral images, we suggest that the major components of scale structure were rich in protein and polysaccharide.« less

Determination of scattering structures from spatial coherence measurements.

PubMed

Zarubin, A M

1996-03-01

A new method of structure determination and microscopic imaging with short-wavelength radiations (charged particles, X-rays, neutrons), based on measurements of the modulus and the phase of the degree of spatial coherence of the scattered radiation, is developed. The underlying principle of the method--transfer of structural information about the scattering potential via spatial coherence of the secondary (scattering) source of radiation formed by this potential--is expressed by the generalization of the van Cittert-Zernike theorem to wave and particle scattering [A.M. Zarubin, Opt. Commun. 100 (1993) 491; Opt. Commun. 102 (1993) 543]. Shearing interferometric techniques are proposed for implementing the above measurements; the limits of spatial resolution attainable by reconstruction of the absolute square of a 3D scattering potential and its 2D projections from the measurements are analyzed. It is shown theoretically that 3D imaging with atomic resolution can be realized in a "synthetic aperture" electron or ion microscope and that a 3D resolution of about 6 nm can be obtained with a "synthetic aperture" X-ray microscope. A proof-of-principle optical experiment is presented.

Digital disaster evaluation and its application to 2015 Ms 8.1 Nepal Earthquake

NASA Astrophysics Data System (ADS)

WANG, Xiaoqing; LV, Jinxia; DING, Xiang; DOU, Aixia

2016-11-01

The purpose of the article is to probe the technique resolution of disaster information extraction and evaluation from the digital RS images based on the internet environment and aided by the social and geographic information. The solution is composed with such methods that the fast post-disaster assessment system will assess automatically the disaster area and grade, the multi-phase satellite and airborne high resolution digital RS images will provide the basis to extract the disaster areas or spots, assisted by the fast position of potential serious damage risk targets according to the geographic, administrative, population, buildings and other information in the estimated disaster region, the 2D digital map system or 3D digital earth system will provide platforms to interpret cooperatively the damage information in the internet environment, and further to estimate the spatial distribution of damage index or intensity, casualties or economic losses, which are very useful for the decision-making of emergency rescue and disaster relief, resettlement and reconstruction. The spatial seismic damage distribution of 2015 Ms 8.1 Nepal earthquake, as an example of the above solution, is evaluated by using the high resolution digital RS images, auxiliary geographic information and ground survey. The results are compared with the statistical disaster information issued by the ground truth by field surveying, and show good consistency.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Highly-resolved Modeling of Emissions and Concentrations of Carbon Monoxide, Carbon Dioxide, Nitrogen Oxides, and Fine Particulate Matter in Salt Lake City, Utah

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Ehleringer, J. R.

2014-12-01

Accurate, high-resolution data on air pollutant emissions and concentrations are needed to understand human exposures and for both policy and pollutant management purposes. An important step in this process is also quantification of uncertainties. We present a spatially explicit and highly resolved emissions inventory for Salt Lake County, Utah, and trace gas concentration estimates for carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx) and fine particles (PM2.5) within Salt Lake City. We assess the validity of this approach by comparing measured concentrations against simulated values derived from combining the emissions inventory with an atmospheric model. The emissions inventory for the criteria pollutants was constructed using the 2011 National Emissions Inventory (NEI). The spatial and temporal allocation methods from the Emission Modeling Clearinghouse data set are used to downscale the NEI data from annual to hourly scales and from county-level to 500 m x 500 m resolution. Onroad mobile source emissions were estimated by combining a bottom-up emissions calculation approach for large roadway links with a top-down spatial allocation approach for other roadways. Vehicle activity data for road links were derived from automatic traffic responder data. The emissions inventory for CO2 was obtained from the Hestia emissions data product at an hourly, building, facility, and road link resolution. The AERMOD and CALPUFF dispersion models were used to transport emissions and estimate air pollutant concentrations at an hourly temporal and 500 m x 500 m spatial resolution. Modeled results were compared against measurements from a mobile lab equipped with trace gas measurement equipment traveling on pre-determined routes in the Salt Lake City area. The comparison between both approaches to concentration estimation highlights spatial locations and hours of high variability/uncertainty. Results presented here will inform understanding of variability and uncertainty in emissions and concentrations to better inform future policy. This work will also facilitate the development of a systematic approach to incorporate measurement data and models to better inform estimates of pollutant concentrations that determine the extent to which urban populations are exposed to adverse air quality.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A modeling framework for characterizing near-road air pollutant concentration at community scales

EPA Science Inventory

In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LIN...

A Geospatial Database for Wind and Solar Energy Applications: The Kingdom of Bahrain Study Case

NASA Astrophysics Data System (ADS)

Al-Joburi, Khalil; Dahman, Nidal

2017-11-01

This research is aimed at designing, implementing, and testing a geospatial database for wind and solar energy applications in the Kingdom of Bahrain. All decision making needed to determine economic feasibility and establish site location for wind turbines or solar panels depends primarily on geospatial feature theme information and non-spatial (attribute) data for wind, solar, rainfall, temperature and weather characteristics of a particular region. Spatial data includes, but is not limited to, digital elevation, slopes, land use, zonings, parks, population density, road utility maps, and other related information. Digital elevations for over 450,000 spot at 50 m spatial horizontal resolution plus field surveying and GPS (at selected locations) was obtained from the Surveying and Land Registration Bureau (SLRB). Road, utilities, and population density are obtained from the Central Information Organization (CIO). Land use zoning, recreational parks, and other data are obtained from the Ministry of Municipalities and Agricultural Affairs. Wind, solar, humidity, rainfall, and temperature data are obtained from the Ministry of Transportation, Civil Aviation Section. LandSat Satellite and others images are obtained from NASA and online sources respectively. The collected geospatial data was geo-referenced to Ain el-Abd UTM Zone 39 North. 3D Digital Elevation Model (DEM)-50 m spatial resolutions was created using SLRB spot elevations. Slope and aspect maps were generate based on the DEM. Supervised image classification to identify open spaces was performed utilizing satellite images. Other geospatial data was converted to raster format with the same cell resolution. Non-spatial data are entered as an attribute to spatial features. To eliminate ambiguous solution, multi-criteria GIS model is developed based on, vector (discrete point, line, and polygon representations) as well as raster model (continuous representation). The model was tested at the Al-Areen proposed project, a relatively small area (15 km2). Optimum site spatial location for the location of wind turbines and solar panels was determined and initial results indicates that the combination of wind and solar energy would be sufficient for the project to meet the energy demand at the present per capita consummation rate..

AVIRIS Spectrometer Maps Total Water Vapor Column

NASA Technical Reports Server (NTRS)

Conel, James E.; Green, Robert O.; Carrere, Veronique; Margolis, Jack S.; Alley, Ronald E.; Vane, Gregg A.; Bruegge, Carol J.; Gary, Bruce L.

1992-01-01

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) processes maps of vertical-column abundances of water vapor in atmosphere with good precision and spatial resolution. Maps provide information for meteorology, climatology, and agriculture.

Atomic-Scale Nuclear Spin Imaging Using Quantum-Assisted Sensors in Diamond

NASA Astrophysics Data System (ADS)

Ajoy, A.; Bissbort, U.; Lukin, M. D.; Walsworth, R. L.; Cappellaro, P.

2015-01-01

Nuclear spin imaging at the atomic level is essential for the understanding of fundamental biological phenomena and for applications such as drug discovery. The advent of novel nanoscale sensors promises to achieve the long-standing goal of single-protein, high spatial-resolution structure determination under ambient conditions. In particular, quantum sensors based on the spin-dependent photoluminescence of nitrogen-vacancy (NV) centers in diamond have recently been used to detect nanoscale ensembles of external nuclear spins. While NV sensitivity is approaching single-spin levels, extracting relevant information from a very complex structure is a further challenge since it requires not only the ability to sense the magnetic field of an isolated nuclear spin but also to achieve atomic-scale spatial resolution. Here, we propose a method that, by exploiting the coupling of the NV center to an intrinsic quantum memory associated with the nitrogen nuclear spin, can reach a tenfold improvement in spatial resolution, down to atomic scales. The spatial resolution enhancement is achieved through coherent control of the sensor spin, which creates a dynamic frequency filter selecting only a few nuclear spins at a time. We propose and analyze a protocol that would allow not only sensing individual spins in a complex biomolecule, but also unraveling couplings among them, thus elucidating local characteristics of the molecule structure.

Integration of ultra-high field MRI and histology for connectome based research of brain disorders

PubMed Central

Yang, Shan; Yang, Zhengyi; Fischer, Karin; Zhong, Kai; Stadler, Jörg; Godenschweger, Frank; Steiner, Johann; Heinze, Hans-Jochen; Bernstein, Hans-Gert; Bogerts, Bernhard; Mawrin, Christian; Reutens, David C.; Speck, Oliver; Walter, Martin

2013-01-01

Ultra-high field magnetic resonance imaging (MRI) became increasingly relevant for in vivo neuroscientific research because of improved spatial resolutions. However, this is still the unchallenged domain of histological studies, which long played an important role in the investigation of neuropsychiatric disorders. While the field of biological psychiatry strongly advanced on macroscopic levels, current developments are rediscovering the richness of immunohistological information when attempting a multi-level systematic approach to brain function and dysfunction. For most studies, histology sections lost information on three-dimensional reconstructions. Translating histological sections to 3D-volumes would thus not only allow for multi-stain and multi-subject alignment in post mortem data, but also provide a crucial step in big data initiatives involving the network analyses currently performed with in vivo MRI. We therefore investigated potential pitfalls during integration of MR and histological information where no additional blockface information is available. We demonstrated that strengths and requirements from both methods can be effectively combined at a spatial resolution of 200 μm. However, the success of this approach is heavily dependent on choices of hardware, sequence and reconstruction. We provide a fully automated pipeline that optimizes histological 3D reconstructions, providing a potentially powerful solution not only for primary human post mortem research institutions in neuropsychiatric research, but also to help alleviate the massive workloads in neuroanatomical atlas initiatives. We further demonstrate (for the first time) the feasibility and quality of ultra-high spatial resolution (150 μm isotopic) imaging of the entire human brain MRI at 7T, offering new opportunities for analyses on MR-derived information. PMID:24098272

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

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

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

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

NASA Astrophysics Data System (ADS)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

PubMed

Nallikuzhy, Jiss J; Dandapat, S

2017-06-01

In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.

High Resolution PET with 250 micrometer LSO Detectors and Adaptive Zoom

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

Cherry, Simon R.; Qi, Jinyi

2012-01-08

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Microwat : a new Earth Explorer mission proposal to measure the Sea surface Temperature and the Sea Ice Concentration

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Aires, Filipe; Heygster, Georg

2017-04-01

Ocean surface characterization from satellites is required to understand, monitor and predict the general circulation of the ocean and atmosphere. With more than 70% global cloud coverage at any time, visible and infrared satellite observations only provide limited information. The polar regions are particularly vulnerable to the climate changes and are home to complex mesoscale mechanisms that are still poorly understood. They are also under very persis- tent cloudiness. Passive microwave observations can provide surface information such as Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) regardless of the cloud cover, but up to now they were limited in spatial resolution. Here, we propose a passive microwave conically scanning imager, MICROWAT, in a polar orbit, for the retrieval of the SST and SIC, with a spatial resolution of 15km. It observes at 6 and 10GHz, with low-noise dual polarization receivers, and a foldable mesh antenna of 5m-diameter. Furthermore, MICROWAT will fly in tandem with MetOp-SG B to benefit from the synergy with scatterometers (SCA) and microwave imagers (MWI). MICROWAT will provide global SST estimates, twice daily, regardless of cloud cover, with an accuracy of 0.3K and a spatial resolution of 15km. The SIC will be derived with an accuracy of 3%. With its unprecedented "all weather" accurate SST and SIC at 15km, MICROWAT will provide the atmospheric and oceanic forecasting sys- tems with products compatible with their increasing spatial resolution and complexity, with impact for societal applications. It will also answer fundamental science questions related to the ocean, the atmosphere and their interactions. * Prigent, Aires, Bernardo, Orlhac, Goutoule, Roquet, & Donlon, Analysis of the potential and limitations of microwave radiometry for the retrieval of sea surface temperature: Definition

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

Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S.; Domowicz, Miriam

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflectmore » local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. Conclusions: High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.« less

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.

Fast high resolution reconstruction in multi-slice and multi-view cMRI

NASA Astrophysics Data System (ADS)

Velasco Toledo, Nelson; Romero Castro, Eduardo

2015-01-01

Cardiac magnetic resonance imaging (cMRI) is an useful tool in diagnosis, prognosis and research since it functionally tracks the heart structure. Although useful, this imaging technique is limited in spatial resolution because heart is a constant moving organ, also there are other non controled conditions such as patient movements and volumetric changes during apnea periods when data is acquired, those conditions limit the time to capture high quality information. This paper presents a very fast and simple strategy to reconstruct high resolution 3D images from a set of low resolution series of 2D images. The strategy is based on an information reallocation algorithm which uses the DICOM header to relocate voxel intensities in a regular grid. An interpolation method is applied to fill empty places with estimated data, the interpolation resamples the low resolution information to estimate the missing information. As a final step a gaussian filter that denoises the final result. A reconstructed image evaluation is performed using as a reference a super-resolution reconstructed image. The evaluation reveals that the method maintains the general heart structure with a small loss in detailed information (edge sharpening and blurring), some artifacts related with input information quality are detected. The proposed method requires low time and computational resources.

Exploration into technical procedures for vertical integration. [information systems

NASA Technical Reports Server (NTRS)

Michel, R. J.; Maw, K. D.

1979-01-01

Issues in the design and use of a digital geographic information system incorporating landuse, zoning, hazard, LANDSAT, and other data are discussed. An eleven layer database was generated. Issues in spatial resolution, registration, grid versus polygonal structures, and comparison of photointerpreted landuse to LANDSAT land cover are examined.

Long-term monitoring on environmental disasters using multi-source remote sensing technique

NASA Astrophysics Data System (ADS)

Kuo, Y. C.; Chen, C. F.

2017-12-01

Environmental disasters are extreme events within the earth's system that cause deaths and injuries to humans, as well as causing damages and losses of valuable assets, such as buildings, communication systems, farmlands, forest and etc. In disaster management, a large amount of multi-temporal spatial data is required. Multi-source remote sensing data with different spatial, spectral and temporal resolutions is widely applied on environmental disaster monitoring. With multi-source and multi-temporal high resolution images, we conduct rapid, systematic and seriate observations regarding to economic damages and environmental disasters on earth. It is based on three monitoring platforms: remote sensing, UAS (Unmanned Aircraft Systems) and ground investigation. The advantages of using UAS technology include great mobility and availability in real-time rapid and more flexible weather conditions. The system can produce long-term spatial distribution information from environmental disasters, obtaining high-resolution remote sensing data and field verification data in key monitoring areas. It also supports the prevention and control on ocean pollutions, illegally disposed wastes and pine pests in different scales. Meanwhile, digital photogrammetry can be applied on the camera inside and outside the position parameters to produce Digital Surface Model (DSM) data. The latest terrain environment information is simulated by using DSM data, and can be used as references in disaster recovery in the future.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale

PubMed Central

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2018-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage. PMID:29888751

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale.

PubMed

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

The Acuity of Echolocation: Spatial Resolution in Sighted Persons Compared to the Performance of an Expert Who Is Blind

ERIC Educational Resources Information Center

Teng, Santani; Whitney, David

2011-01-01

Echolocation is a specialized application of spatial hearing that uses reflected auditory information to localize objects and represent the external environment. Although it has been documented extensively in nonhuman species, such as bats and dolphins, its use by some persons who are blind as a navigation and object-identification aid has…

Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock.

PubMed

Gerke, Kirill M; Karsanina, Marina V; Mallants, Dirk

2015-11-02

Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution. Merging multiscale images of shale rock is pivotal to quantify more reliably petrophysical properties needed for production optimization and environmental impacts minimization. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Practical applications are not limited to petroleum engineering or more broadly geosciences, but will also find their way in material sciences, climatology, and remote sensing.

Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock

PubMed Central

Gerke, Kirill M.; Karsanina, Marina V.; Mallants, Dirk

2015-01-01

Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution. Merging multiscale images of shale rock is pivotal to quantify more reliably petrophysical properties needed for production optimization and environmental impacts minimization. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Practical applications are not limited to petroleum engineering or more broadly geosciences, but will also find their way in material sciences, climatology, and remote sensing. PMID:26522938

[Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

PubMed

Zhang, Pei-feng; Hu, Yuan-man; He, Hong-shi

2010-05-01

The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

Evaluation of resolution-precision relationships when using Structure-from-Motion to measure low intensity erosion processes, within a laboratory setting.

NASA Astrophysics Data System (ADS)

Benaud, Pia; Anderson, Karen; Quine, Timothy; James, Mike; Quinton, John; Brazier, Richard E.

2017-04-01

The accessibility of Structure-from-Motion Multi-Stereo View (SfM) and the potential for multi-temporal applications, offers an exciting opportunity to quantify soil erosion spatially. Accordingly, published research provides examples of the successful quantification of large erosion features and events, to centimetre accuracy. Through rigorous control of the camera and image network geometry, the centimetre accuracy achievable at the field scale, can translate to sub-millimetre accuracies within a laboratory environment. The broad aim of this study, therefore, was to understand how ultra-high-resolution spatial information on soil surface topography, derived from SfM, can be utilised to develop a spatially explicit, mechanistic understanding of rill and inter-rill erosion, under experimental conditions. A rainfall simulator was used to create three soil surface conditions; compaction and rainsplash erosion, inter-rill erosion, and rill erosion. Total sediment capture was the primary validation for the experiments, allowing the comparison between structurally and volumetrically derived change, and true soil loss. A Terrestrial Laser Scanner (resolution of ca. 0.8mm) was employed to assess spatial discrepancies within the SfM datasets and to provide an alternative measure of volumetric change. The body of work will present the workflow that has been developed for the laboratory-scale studies and provide information on the importance of DTM resolution for volumetric calculations of soil loss, under different soil surface conditions. To-date, using the methodology presented, point clouds with ca. 3.38 x 107 points per m2, and RMSE values of 0.17 to 0.43 mm (relative precision 1:2023-5117), were constructed. Preliminary results suggest a decrease in DTM resolution from 0.5 to 10 mm does not result in a significant change in volumetric calculations (p = 0.088), while affording a 24-fold decrease in processing times, but may impact negatively on mechanistic understanding of patterns of erosion. It is argued that the approach can be an invaluable tool for the spatially-explicit evaluation of soil erosion models.

The future of structural fieldwork - UAV assisted aerial photogrammetry

NASA Astrophysics Data System (ADS)

Vollgger, Stefan; Cruden, Alexander

2015-04-01

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are opening new and low cost possibilities to acquire high-resolution aerial images and digital surface models (DSM) for applications in structural geology. UAVs can be programmed to fly autonomously along a user defined grid to systematically capture high-resolution photographs, even in difficult to access areas. The photographs are subsequently processed using software that employ SIFT (scale invariant feature transform) and SFM (structure from motion) algorithms. These photogrammetric routines allow the extraction of spatial information (3D point clouds, digital elevation models, 3D meshes, orthophotos) from 2D images. Depending on flight altitude and camera setup, sub-centimeter spatial resolutions can be achieved. By "digitally mapping" georeferenced 3D models and images, orientation data can be extracted directly and used to analyse the structural framework of the mapped object or area. We present UAV assisted aerial mapping results from a coastal platform near Cape Liptrap (Victoria, Australia), where deformed metasediments of the Palaeozoic Lachlan Fold Belt are exposed. We also show how orientation and spatial information of brittle and ductile structures extracted from the photogrammetric model can be linked to the progressive development of folds and faults in the region. Even though there are both technical and legislative limitations, which might prohibit the use of UAVs without prior commercial licensing and training, the benefits that arise from the resulting high-resolution, photorealistic models can substantially contribute to the collection of new data and insights for applications in structural geology.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Evaluation of Pan-Sharpening Methods for Automatic Shadow Detection in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

de Azevedo, Samara C.; Singh, Ramesh P.; da Silva, Erivaldo A.

2017-04-01

Finer spatial resolution of areas with tall objects within urban environment causes intense shadows that lead to wrong information in urban mapping. Due to the shadows, automatic detection of objects (such as buildings, trees, structures, towers) and to estimate the surface coverage from high spatial resolution is difficult. Thus, automatic shadow detection is the first necessary preprocessing step to improve the outcome of many remote sensing applications, particularly for high spatial resolution images. Efforts have been made to explore spatial and spectral information to evaluate such shadows. In this paper, we have used morphological attribute filtering to extract contextual relations in an efficient multilevel approach for high resolution images. The attribute selected for the filtering was the area estimated from shadow spectral feature using the Normalized Saturation-Value Difference Index (NSVDI) derived from pan-sharpening images. In order to assess the quality of fusion products and the influence on shadow detection algorithm, we evaluated three pan-sharpening methods - Intensity-Hue-Saturation (IHS), Principal Components (PC) and Gran-Schmidt (GS) through the image quality measures: Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative Dimensionless Global Error in Synthesis (ERGAS) and Universal Image Quality Index (UIQI). Experimental results over Worldview II scene from São Paulo city (Brazil) show that GS method provides good correlation with original multispectral bands with no radiometric and contrast distortion. The automatic method using GS method for NSDVI generation clearly provide a clear distinction of shadows and non-shadows pixels with an overall accuracy more than 90%. The experimental results confirm the effectiveness of the proposed approach which could be used for further shadow removal and reliable for object recognition, land-cover mapping, 3D reconstruction, etc. especially in developing countries where land use and land cover are rapidly changing with tall objects within urban areas.

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.

Implications of high-spatial-resolution thermal infrared (Termoskan) data for Mars landing site selection

NASA Technical Reports Server (NTRS)

Betts, Bruce H.

1994-01-01

Thermal infrared observations of Mars from spacecraft provide physical information about the upper thermal skin depth of the surface, which is on the order of a few centimeters in depth and thus very significant for lander site selection. The Termoskan instrument onboard the Soviet Phobos '88 spacecraft acquired the highest spatial-resolution thermal infrared data obtained for Mars, ranging in resolution from 300 m to 3 km per pixel. It simultaneously obtained broadband reflected solar flux data. Although the 6 deg N - 30 deg S Termoskan coverage only slightly overlaps the nominal Mars Pathfinder target range, the implications of Termoskan data for that overlap region and the extrapolations that can be made to other regions give important clues for optimal landing site selection.

From high spatial resolution imagery to spatial indicators : Application for hydromorphy follow-up on Bourgneuf wetland

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Puech, C.; Lukac, F.; Massé, J.

2003-04-01

On Atlantic coastal wetlands, the understanding of hydrological processes may refer to hydraulic surface structures characterization as small ditches or channels networks, permanent and temporary water bodies. Moreover to improve the understanding, this characerization should be realized regarding different seasons and different spatial scales: elementary parcel, managment unit and whole wetland scales. In complement to usual observations on a few local ground points, high spatial resolution remote sensing may be a good information support for extraction and characterization on elementary objects, especially water bodies, permanents or temporary ones and ditches. To carry out a floow-up on wetlands, a seasonal image acquisition rate, reachable from most of satelite systems, is in that case informative for hydrological needs. In this work, georeferencing methods on openfield wetlands have been handled with care in order to use diachronic images or combined geographical data; lack of relief, short vegetation and well structured landscape make this preprocess easier in comparison to other landscape situations. In this presentation we focus on spatial hydromorphy parameters constructed from images with specific processes. Especially, hydromorphy indicators for parcels or managment units have been developped using an IRC winter-spring-summer metric resolution set of images: these descriptors are based on water areas evolution or hydrophyl vegetations presence traducing hydrodynamic submersion behaviour in temporary water bodies. An other example presents a surface water network circulation indicator elaborated on IRC aerial photography combined with vectorized geographic database. This indicator is based on ditches width and vegetation presence : a specific process uses vectorized geo data set to define transects across ditches on which classified image analysis is carried out (supervised classification). These first results proposing hydromorphy descriptors from very high resolution don't give complete indicators for follow-up and monitoring of coastal wetlands, but their combinaison, aggregation should present good technical bases to carry it out with success.

Remote Sensing, GIS, and Vector-Borne Disease

NASA Technical Reports Server (NTRS)

Beck, Louisa R.

2001-01-01

The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).

Computational multispectral video imaging [Invited].

PubMed

Wang, Peng; Menon, Rajesh

2018-01-01

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

Ultra-high spatial resolution multi-energy CT using photon counting detector technology

NASA Astrophysics Data System (ADS)

Leng, S.; Gutjahr, R.; Ferrero, A.; Kappler, S.; Henning, A.; Halaweish, A.; Zhou, W.; Montoya, J.; McCollough, C.

2017-03-01

Two ultra-high-resolution (UHR) imaging modes, each with two energy thresholds, were implemented on a research, whole-body photon-counting-detector (PCD) CT scanner, referred to as sharp and UHR, respectively. The UHR mode has a pixel size of 0.25 mm at iso-center for both energy thresholds, with a collimation of 32 × 0.25 mm. The sharp mode has a 0.25 mm pixel for the low-energy threshold and 0.5 mm for the high-energy threshold, with a collimation of 48 × 0.25 mm. Kidney stones with mixed mineral composition and lung nodules with different shapes were scanned using both modes, and with the standard imaging mode, referred to as macro mode (0.5 mm pixel and 32 × 0.5 mm collimation). Evaluation and comparison of the three modes focused on the ability to accurately delineate anatomic structures using the high-spatial resolution capability and the ability to quantify stone composition using the multi-energy capability. The low-energy threshold images of the sharp and UHR modes showed better shape and texture information due to the achieved higher spatial resolution, although noise was also higher. No noticeable benefit was shown in multi-energy analysis using UHR compared to standard resolution (macro mode) when standard doses were used. This was due to excessive noise in the higher resolution images. However, UHR scans at higher dose showed improvement in multi-energy analysis over macro mode with regular dose. To fully take advantage of the higher spatial resolution in multi-energy analysis, either increased radiation dose, or application of noise reduction techniques, is needed.

High Resolution Surface Geometry and Albedo by Combining Laser Altimetry and Visible Images

NASA Technical Reports Server (NTRS)

Morris, Robin D.; vonToussaint, Udo; Cheeseman, Peter C.; Clancy, Daniel (Technical Monitor)

2001-01-01

The need for accurate geometric and radiometric information over large areas has become increasingly important. Laser altimetry is one of the key technologies for obtaining this geometric information. However, there are important application areas where the observing platform has its orbit constrained by the other instruments it is carrying, and so the spatial resolution that can be recorded by the laser altimeter is limited. In this paper we show how information recorded by one of the other instruments commonly carried, a high-resolution imaging camera, can be combined with the laser altimeter measurements to give a high resolution estimate both of the surface geometry and its reflectance properties. This estimate has an accuracy unavailable from other interpolation methods. We present the results from combining synthetic laser altimeter measurements on a coarse grid with images generated from a surface model to re-create the surface model.

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.

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.

Influence of Spatial Resolution in Three-dimensional Cine Phase Contrast Magnetic Resonance Imaging on the Accuracy of Hemodynamic Analysis

PubMed Central

Fukuyama, Atsushi; Isoda, Haruo; Morita, Kento; Mori, Marika; Watanabe, Tomoya; Ishiguro, Kenta; Komori, Yoshiaki; Kosugi, Takafumi

2017-01-01

Introduction: We aim to elucidate the effect of spatial resolution of three-dimensional cine phase contrast magnetic resonance (3D cine PC MR) imaging on the accuracy of the blood flow analysis, and examine the optimal setting for spatial resolution using flow phantoms. Materials and Methods: The flow phantom has five types of acrylic pipes that represent human blood vessels (inner diameters: 15, 12, 9, 6, and 3 mm). The pipes were fixed with 1% agarose containing 0.025 mol/L gadolinium contrast agent. A blood-mimicking fluid with human blood property values was circulated through the pipes at a steady flow. Magnetic resonance (MR) images (three-directional phase images with speed information and magnitude images for information of shape) were acquired using the 3-Tesla MR system and receiving coil. Temporal changes in spatially-averaged velocity and maximum velocity were calculated using hemodynamic analysis software. We calculated the error rates of the flow velocities based on the volume flow rates measured with a flowmeter and examined measurement accuracy. Results: When the acrylic pipe was the size of the thoracicoabdominal or cervical artery and the ratio of pixel size for the pipe was set at 30% or lower, spatially-averaged velocity measurements were highly accurate. When the pixel size ratio was set at 10% or lower, maximum velocity could be measured with high accuracy. It was difficult to accurately measure maximum velocity of the 3-mm pipe, which was the size of an intracranial major artery, but the error for spatially-averaged velocity was 20% or less. Conclusions: Flow velocity measurement accuracy of 3D cine PC MR imaging for pipes with inner sizes equivalent to vessels in the cervical and thoracicoabdominal arteries is good. The flow velocity accuracy for the pipe with a 3-mm-diameter that is equivalent to major intracranial arteries is poor for maximum velocity, but it is relatively good for spatially-averaged velocity. PMID:28132996

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

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

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

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

Spatially explicit spectral analysis of point clouds and geospatial data

USGS Publications Warehouse

Buscombe, Daniel D.

2015-01-01

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

A Synopsis of Global Mapping of Freshwater Habitats and Biodiversity: Implications for Conservation

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

McManamay, Ryan A.; Griffiths, Natalie A.; DeRolph, Christopher R.

Accurately mapping freshwater habitats and biodiversity at high-resolutions across the globe is essential for assessing the vulnerability and threats to freshwater organisms and prioritizing conservation efforts. Since the 2000s, extensive efforts have been devoted to mapping global freshwater habitats (rivers, lakes, and wetlands), the spatial representation of which has changed dramatically over time with new geospatial data products and improved remote sensing technologies. Some of these mapping efforts, however, are still coarse representations of actual conditions. Likewise, the resolution and scope of global freshwater biodiversity compilation efforts have also increased, but are yet to mirror the spatial resolution and fidelitymore » of mapped freshwater environments. In our synopsis, we find that efforts to map freshwater habitats have been conducted independently of those for freshwater biodiversity; subsequently, there is little congruence in the spatial representation and resolution of the two efforts. We suggest that global species distribution models are needed to fill this information gap; however, limiting data on habitat characteristics at scales that complement freshwater habitats has prohibited global high-resolution biogeography efforts. Emerging research trends, such as mapping habitat alteration in freshwater ecosystems and trait biogeography, show great promise in mechanistically linking global anthropogenic stressors to freshwater biodiversity decline and extinction risk.« less

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.

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

DOE PAGES

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

2018-02-07

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

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

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

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

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

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Optical performance analysis of plenoptic camera systems

NASA Astrophysics Data System (ADS)

Langguth, Christin; Oberdörster, Alexander; Brückner, Andreas; Wippermann, Frank; Bräuer, Andreas

2014-09-01

Adding an array of microlenses in front of the sensor transforms the capabilities of a conventional camera to capture both spatial and angular information within a single shot. This plenoptic camera is capable of obtaining depth information and providing it for a multitude of applications, e.g. artificial re-focusing of photographs. Without the need of active illumination it represents a compact and fast optical 3D acquisition technique with reduced effort in system alignment. Since the extent of the aperture limits the range of detected angles, the observed parallax is reduced compared to common stereo imaging systems, which results in a decreased depth resolution. Besides, the gain of angular information implies a degraded spatial resolution. This trade-off requires a careful choice of the optical system parameters. We present a comprehensive assessment of possible degrees of freedom in the design of plenoptic systems. Utilizing a custom-built simulation tool, the optical performance is quantified with respect to particular starting conditions. Furthermore, a plenoptic camera prototype is demonstrated in order to verify the predicted optical characteristics.

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

Sadoulet, B.

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Object-based methods for individual tree identification and tree species classification from high-spatial resolution imagery

NASA Astrophysics Data System (ADS)

Wang, Le

2003-10-01

Modern forest management poses an increasing need for detailed knowledge of forest information at different spatial scales. At the forest level, the information for tree species assemblage is desired whereas at or below the stand level, individual tree related information is preferred. Remote Sensing provides an effective tool to extract the above information at multiple spatial scales in the continuous time domain. To date, the increasing volume and readily availability of high-spatial-resolution data have lead to a much wider application of remotely sensed products. Nevertheless, to make effective use of the improving spatial resolution, conventional pixel-based classification methods are far from satisfactory. Correspondingly, developing object-based methods becomes a central challenge for researchers in the field of Remote Sensing. This thesis focuses on the development of methods for accurate individual tree identification and tree species classification. We develop a method in which individual tree crown boundaries and treetop locations are derived under a unified framework. We apply a two-stage approach with edge detection followed by marker-controlled watershed segmentation. Treetops are modeled from radiometry and geometry aspects. Specifically, treetops are assumed to be represented by local radiation maxima and to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate overlapping trees and to produce a segmented image comprised of individual tree crowns. The image segmentation method developed achieves a promising result for a 256 x 256 CASI image. Then further effort is made to extend our methods to the multiscales which are constructed from a wavelet decomposition. A scale consistency and geometric consistency are designed to examine the gradients along the scale-space for the purpose of separating true crown boundary from unwanted textures occurring due to branches and twigs. As a result from the inverse wavelet transform, the tree crown boundary is enhanced while the unwanted textures are suppressed. Based on the enhanced image, an improvement is achieved when applying the two-stage methods to a high resolution aerial photograph. To improve tree species classification, we develop a new method to choose the optimal scale parameter with the aid of Bhattacharya Distance (BD), a well-known index of class separability in traditional pixel-based classification. The optimal scale parameter is then fed in the process of a region-growing-based segmentation as a break-off value. Our object classification achieves a better accuracy in separating tree species when compared to the conventional Maximum Likelihood Classification (MLC). In summary, we develop two object-based methods for identifying individual trees and classifying tree species from high-spatial resolution imagery. Both methods achieve promising results and will promote integration of Remote Sensing and GIS in forest applications.

Fine‐resolution conservation planning with limited climate‐change information

USGS Publications Warehouse

Shah, Payal; Mallory, Mindy L.; Ando , Amy W.; Guntenspergen, Glenn R.

2017-01-01

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.

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

NASA Astrophysics Data System (ADS)

Xu, Bing

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

Object-based land cover classification and change analysis in the Baltimore metropolitan area using multitemporal high resolution remote sensing data

Treesearch

Weiqi Zhou; Austin Troy; Morgan Grove

2008-01-01

Accurate and timely information about land cover pattern and change in urban areas is crucial for urban land management decision-making, ecosystem monitoring and urban planning. This paper presents the methods and results of an object-based classification and post-classification change detection of multitemporal high-spatial resolution Emerge aerial imagery in the...

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

PubMed Central

Tarolli, Jay G.; Jackson, Lauren M.; Winograd, Nicholas

2014-01-01

The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images, but also by detection sensitivity. As the probe size is reduced to below 1 µm, for example, a low signal in each pixel limits lateral resolution due to counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure. PMID:24912432

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.

Contribution of LANDSAT-4 thematic mapper data to geologic exploration

NASA Technical Reports Server (NTRS)

Everett, J. R.; Dykstra, J. D.; Sheffield, C. A.

1983-01-01

The increased number of carefully selected narrow spectral bands and the increased spatial resolution of thematic mapper data over previously available satellite data contribute greatly to geologic exploration, both by providing spectral information that permits lithologic differentiation and recognition of alteration and spatial information that reveals structure. As vegetation and soil cover increase, the value of spectral components of TM data decreases relative to the value of the spatial component of the data. However, even in vegetated areas, the greater spectral breadth and discrimination of TM data permits improved recognition and mapping of spatial elements of the terrain. As our understanding of the spectral manifestations of the responses of soils and vegetation to unusual chemical environments increases, the value of spectral components of TM data to exploration will greatly improve in covered areas.

Multi-scales and multi-satellites estimates of evapotranspiration with a residual energy balance model in the Muzza agricultural district in Northern Italy

NASA Astrophysics Data System (ADS)

Corbari, C.; Bissolati, M.; Mancini, M.

2015-05-01

Evapotranspiration estimates were performed with a residual energy balance model (REB) over an agricultural area using remote sensing data. REB uses land surface temperature (LST) as main input parameter so that energy fluxes were computed instantaneously at the time of data acquisition. Data from MODIS and SEVIRI sensors were used and downscaling techniques were implemented to improve their spatial resolutions. Energy fluxes at the original spatial resolutions (1000 m for MODIS and 5000 m for SEVIRI) as well as at the downscaled resolutions (250 m for MODIS and 1000 m for SEVIRI) were calculated with the REB model. Ground eddy covariance data and remote sensing information from the Muzza agricultural irrigation district in Italy from 2010 to 2012 gave the opportunity to validate and compare spatially distributed energy fluxes. The model outputs matched quite well ground observations when ground LST data were used, while differences increased when MODIS and SEVIRI LST were used. The spatial analysis revealed significant differences between the two sensors both in term of LST (around 2.8 °C) and of latent heat fluxes with values (around 100 W m-2).

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

Improving carbon monitoring and reporting in forests using spatially-explicit information.

PubMed

Boisvenue, Céline; Smiley, Byron P; White, Joanne C; Kurz, Werner A; Wulder, Michael A

2016-12-01

Understanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere-specifically the process of C removal from the atmosphere, and how this process is changing-is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada. Our results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year -1 ) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha -1 . Comparisons between our estimates and estimates from Canada's National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates. Both estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences between these estimates. This study represents an important first step towards the integration of spatially-explicit information into Canada's NFCMARS.

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE PAGES

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.; ...

2016-03-26

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

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

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Mass loss from red giants - Infrared spectroscopy

NASA Technical Reports Server (NTRS)

Wannier, P. G.

1985-01-01

A discussion is presented of IR spectroscopy, particularly high-resolution spectroscopy in the approximately 1-20 micron band, as it impacts the study of circumstellar envelopes. The molecular bands within this region contain an enormous amount of information, especially when observed with sufficient resolution to obtain kinematic information. In a single spectrum, it is possible to resolve lines from up to 50 different rotational/vibrational levels of a given molecule and to detect several different isotopic variants. When high resolution techniques are combined with mapping techniques and/or time sequence observations of variable stars, the resulting information can paint a very detailed picture of the mass-loss phenomenon. To date, near-IR observations have been made of 20 molecular species. CO is the most widely observed molecule and useful information has been gleaned from the observed rotational excitation, kinematics, time variability and spatial structure of its lines. Examples of different observing techniques are discussed in the following sections.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

High Spatial Resolution Commercial Satellite Imaging Product Characterization

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

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.

Estimation of Fine-Scale Histologic Features at Low Magnification.

PubMed

Zarella, Mark D; Quaschnick, Matthew R; Breen, David E; Garcia, Fernando U

2018-06-18

- Whole-slide imaging has ushered in a new era of technology that has fostered the use of computational image analysis for diagnostic support and has begun to transfer the act of analyzing a slide to computer monitors. Due to the overwhelming amount of detail available in whole-slide images, analytic procedures-whether computational or visual-often operate at magnifications lower than the magnification at which the image was acquired. As a result, a corresponding reduction in image resolution occurs. It is unclear how much information is lost when magnification is reduced, and whether the rich color attributes of histologic slides can aid in reconstructing some of that information. - To examine the correspondence between the color and spatial properties of whole-slide images to elucidate the impact of resolution reduction on the histologic attributes of the slide. - We simulated image resolution reduction and modeled its effect on classification of the underlying histologic structure. By harnessing measured histologic features and the intrinsic spatial relationships between histologic structures, we developed a predictive model to estimate the histologic composition of tissue in a manner that exceeds the resolution of the image. - Reduction in resolution resulted in a significant loss of the ability to accurately characterize histologic components at magnifications less than ×10. By utilizing pixel color, this ability was improved at all magnifications. - Multiscale analysis of histologic images requires an adequate understanding of the limitations imposed by image resolution. Our findings suggest that some of these limitations may be overcome with computational modeling.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Ultrafast all-optical imaging technique using low-temperature grown GaAs/AlxGa1 - xAs multiple-quantum-well semiconductor

NASA Astrophysics Data System (ADS)

Gao, Guilong; Tian, Jinshou; Wang, Tao; He, Kai; Zhang, Chunmin; Zhang, Jun; Chen, Shaorong; Jia, Hui; Yuan, Fenfang; Liang, Lingliang; Yan, Xin; Li, Shaohui; Wang, Chao; Yin, Fei

2017-11-01

We report and experimentally demonstrate an ultrafast all-optical imaging technique capable of single-shot ultrafast recording with a picosecond-scale temporal resolution and a micron-order two-dimensional spatial resolution. A GaAs/AlxGa1 - xAs multiple-quantum-well (MQW) semiconductor with a picosecond response time, grown using molecular beam epitaxy (MBE) at a low temperature (LT), is used for the first time in ultrafast imaging technology. The semiconductor transforms the signal beam information to the probe beam, the birefringent delay crystal time-serializes the input probe beam, and the beam displacer maps different polarization probe beams onto different detector locations, resulting in two frames with an approximately 9 ps temporal separation and approximately 25 lp/mm spatial resolution in the visible range.

General solution for quantitative dark-field contrast imaging with grating interferometers

NASA Astrophysics Data System (ADS)

Strobl, M.

2014-11-01

Grating interferometer based imaging with X-rays and neutrons has proven to hold huge potential for applications in key research fields conveying biology and medicine as well as engineering and magnetism, respectively. The thereby amenable dark-field imaging modality implied the promise to access structural information beyond reach of direct spatial resolution. However, only here a yet missing approach is reported that finally allows exploiting this outstanding potential for non-destructive materials characterizations. It enables to obtain quantitative structural small angle scattering information combined with up to 3-dimensional spatial image resolution even at lab based x-ray or at neutron sources. The implied two orders of magnitude efficiency gain as compared to currently available techniques in this regime paves the way for unprecedented structural investigations of complex sample systems of interest for material science in a vast range of fields.

Perspectives of cross-sectional scanning tunneling microscopy and spectroscopy for complex oxide physics

NASA Astrophysics Data System (ADS)

Wang, Aaron; Chien, TeYu

2018-03-01

Complex oxide heterostructure interfaces have shown novel physical phenomena which do not exist in bulk materials. These heterostructures can be used in the potential applications in the next generation devices and served as the playgrounds for the fundamental physics research. The direct measurements of the interfaces with excellent spatial resolution and physical property information is rather difficult to achieve with the existing tools. Recently developed cross-sectional scanning tunneling microscopy and spectroscopy (XSTM/S) for complex oxide interfaces have proven to be capable of providing local electronic density of states (LDOS) information at the interface with spatial resolution down to nanometer scale. In this perspective, we will briefly introduce the basic idea and some recent achievements in using XSTM/S to study complex oxide interfaces. We will also discuss the future of this technique and the field of the interfacial physics.

Integrative Structure Determination of Protein Assemblies by Satisfaction of Spatial Restraints

NASA Astrophysics Data System (ADS)

Alber, Frank; Chait, Brian T.; Rout, Michael P.; Sali, Andrej

To understand the cell, we need to determine the structures of macromolecular assemblies, many of which consist of tens to hundreds of components. A great variety of experimental data can be used to characterize the assemblies at several levels of resolution, from atomic structures to component configurations. To maximize completeness, resolution, accuracy, precision and efficiency of the structure determination, a computational approach is needed that can use spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. We illustrate the approach by determining the configuration of the 456 proteins in the nuclear pore complex from Baker's yeast.

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.

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

PubMed

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

2016-10-01

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

Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

DTIC Science & Technology

2007-09-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Multi-modal diffuse optical techniques for breast cancer neoadjuvant chemotherapy monitoring (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cochran, Jeffrey M.; Busch, David R.; Ban, Han Y.; Kavuri, Venkaiah C.; Schweiger, Martin J.; Arridge, Simon R.; Yodh, Arjun G.

2017-02-01

We present high spatial density, multi-modal, parallel-plate Diffuse Optical Tomography (DOT) imaging systems for the purpose of breast tumor detection. One hybrid instrument provides time domain (TD) and continuous wave (CW) DOT at 64 source fiber positions. The TD diffuse optical spectroscopy with PMT- detection produces low-resolution images of absolute tissue scattering and absorption while the spatially dense array of CCD-coupled detector fibers (108 detectors) provides higher-resolution CW images of relative tissue optical properties. Reconstruction of the tissue optical properties, along with total hemoglobin concentration and tissue oxygen saturation, is performed using the TOAST software suite. Comparison of the spatially-dense DOT images and MR images allows for a robust validation of DOT against an accepted clinical modality. Additionally, the structural information from co-registered MR images is used as a spatial prior to improve the quality of the functional optical images and provide more accurate quantification of the optical and hemodynamic properties of tumors. We also present an optical-only imaging system that provides frequency domain (FD) DOT at 209 source positions with full CCD detection and incorporates optical fringe projection profilometry to determine the breast boundary. This profilometry serves as a spatial constraint, improving the quality of the DOT reconstructions while retaining the benefits of an optical-only device. We present initial images from both human subjects and phantoms to display the utility of high spatial density data and multi-modal information in DOT reconstruction with the two systems.

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.

Optical Probes for Neurobiological Sensing and Imaging.

PubMed

Kim, Eric H; Chin, Gregory; Rong, Guoxin; Poskanzer, Kira E; Clark, Heather A

2018-05-15

Fluorescent nanosensors and molecular probes are next-generation tools for imaging chemical signaling inside and between cells. Electrophysiology has long been considered the gold standard in elucidating neural dynamics with high temporal resolution and precision, particularly on the single-cell level. However, electrode-based techniques face challenges in illuminating the specific chemicals involved in neural cell activation with adequate spatial information. Measuring chemical dynamics is of fundamental importance to better understand synergistic interactions between neurons as well as interactions between neurons and non-neuronal cells. Over the past decade, significant technological advances in optical probes and imaging methods have enabled entirely new possibilities for studying neural cells and circuits at the chemical level. These optical imaging modalities have shown promise for combining chemical, temporal, and spatial information. This potential makes them ideal candidates to unravel the complex neural interactions at multiple scales in the brain, which could be complemented by traditional electrophysiological methods to obtain a full spatiotemporal picture of neurochemical dynamics. Despite the potential, only a handful of probe candidates have been utilized to provide detailed chemical information in the brain. To date, most live imaging and chemical mapping studies rely on fluorescent molecular indicators to report intracellular calcium (Ca 2+ ) dynamics, which correlates with neuronal activity. Methodological advances for monitoring a full array of chemicals in the brain with improved spatial, temporal, and chemical resolution will thus enable mapping of neurochemical circuits with finer precision. On the basis of numerous studies in this exciting field, we review the current efforts to develop and apply a palette of optical probes and nanosensors for chemical sensing in the brain. There is a strong impetus to further develop technologies capable of probing entire neurobiological units with high spatiotemporal resolution. Thus, we introduce selected applications for ion and neurotransmitter detection to investigate both neurons and non-neuronal brain cells. We focus on families of optical probes because of their ability to sense a wide array of molecules and convey spatial information with minimal damage to tissue. We start with a discussion of currently available molecular probes, highlight recent advances in genetically modified fluorescent probes for ions and small molecules, and end with the latest research in nanosensors for biological imaging. Customizable, nanoscale optical sensors that accurately and dynamically monitor the local environment with high spatiotemporal resolution could lead to not only new insights into the function of all cell types but also a broader understanding of how diverse neural signaling systems act in conjunction with neighboring cells in a spatially relevant manner.

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.

Characterizing the Diurnal Cycle of Land Surface Temperature and Evapotranspiration at High Spatial Resolution Using Thermal Observations from sUAS.

NASA Astrophysics Data System (ADS)

Dutta, D.; Drewry, D.; Johnson, W. R.

2017-12-01

The surface temperature of plant canopies is an important indicator of the stomatal regulation of plant water use and the associated water flux from plants to atmosphere (evapotranspiration (ET)). Remotely sensed thermal observations using compact, low-cost, lightweight sensors from small unmanned aerial systems (sUAS) have the potential to provide surface temperature (ST) and ET estimates at unprecedented spatial and temporal resolutions, allowing us to characterize the intra-field diurnal variations in canopy ST and ET for a variety of vegetation systems. However, major challenges exist for obtaining accurate surface temperature estimates from low-cost uncooled microbolometer-type sensors. Here we describe the development of calibration methods using thermal chamber experiments, taking into account the ambient optics and sensor temperatures, and applying simple models of spatial non-uniformity correction to the sensor focal-plane-array. We present a framework that can be used to derive accurate surface temperatures using radiometric observations from low-cost sensors, and demonstrate this framework using a sUAS-mounted sensor across a diverse set of calibration and vegetation targets. Further, we demonstrate the use of the Surface Temperature Initiated Closure (STIC) model for computing spatially explicit, high spatial resolution ET estimates across several well-monitored agricultural systems, as driven by sUAS acquired surface temperatures. STIC provides a physically-based surface energy balance framework for the simultaneous retrieval of the surface and atmospheric vapor conductances and surface energy fluxes, by physically integrating radiometric surface temperature information into the Penman-Monteith equation. Results of our analysis over agricultural systems in Ames, IA and Davis, CA demonstrate the power of this approach for quantifying the intra-field spatial variability in the diurnal cycle of plant water use at sub-meter resolutions.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

Concept of dual-resolution light field imaging using an organic photoelectric conversion film for high-resolution light field photography.

PubMed

Sugimura, Daisuke; Kobayashi, Suguru; Hamamoto, Takayuki

2017-11-01

Light field imaging is an emerging technique that is employed to realize various applications such as multi-viewpoint imaging, focal-point changing, and depth estimation. In this paper, we propose a concept of a dual-resolution light field imaging system to synthesize super-resolved multi-viewpoint images. The key novelty of this study is the use of an organic photoelectric conversion film (OPCF), which is a device that converts spectra information of incoming light within a certain wavelength range into an electrical signal (pixel value), for light field imaging. In our imaging system, we place the OPCF having the green spectral sensitivity onto the micro-lens array of the conventional light field camera. The OPCF allows us to acquire the green spectra information only at the center viewpoint with the full resolution of the image sensor. In contrast, the optical system of the light field camera in our imaging system captures the other spectra information (red and blue) at multiple viewpoints (sub-aperture images) but with low resolution. Thus, our dual-resolution light field imaging system enables us to simultaneously capture information about the target scene at a high spatial resolution as well as the direction information of the incoming light. By exploiting these advantages of our imaging system, our proposed method enables the synthesis of full-resolution multi-viewpoint images. We perform experiments using synthetic images, and the results demonstrate that our method outperforms other previous methods.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

NASA Technical Reports Server (NTRS)

Gardner, Margaret E.; Roberts, Dar A.; Funk, Chris; Noronha, Val

2001-01-01

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

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.

Hyperspectral classification of grassland species: towards a UAS application for semi-automatic field surveys

NASA Astrophysics Data System (ADS)

Lopatin, Javier; Fassnacht, Fabian E.; Kattenborn, Teja; Schmidtlein, Sebastian

2017-04-01

Grasslands are one of the ecosystems that have been strongly intervened during the past decades due to anthropogenic impacts, affecting their structural and functional composition. To monitor the spatial and/or temporal changes of these environments, a reliable field survey is first needed. As quality relevés are usually expensive and time consuming, the amount of information available is usually poor or not well spatially distributed at the regional scale. In the present study, we investigate the possibility of a semi-automated method used for repeated surveys of monitoring sites. We analyze the applicability of very high spatial resolution hyperspectral data to classify grassland species at the level of individuals. The AISA+ imaging spectrometer mounted on a scaffold was applied to scan 1 m2 grassland plots and assess the impact of four sources of variation on the predicted species cover: (1) the spatial resolution of the scans, (2) the species number and structural diversity, (3) the species cover, and (4) the species functional types (bryophytes, forbs and graminoids). We found that the spatial resolution and the diversity level (mainly structural diversity) were the most important source of variation for the proposed approach. A spatial resolution below 1 cm produced relatively high model performances, while predictions with pixel sizes over that threshold produced non adequate results. Areas with low interspecies overlap reached classification median values of 0.8 (kappa). On the contrary, results were not satisfactory in plots with frequent interspecies overlap in multiple layers. By means of a bootstrapping procedure, we found that areas with shadows and mixed pixels introduce uncertainties into the classification. We conclude that the application of very high resolution hyperspectral remote sensing as a robust alternative or supplement to field surveys is possible for environments with low structural heterogeneity. This study presents the first try of a full classification of grassland species at the individuum level using spectral data.

Science Objectives of EOS-Aura's Ozone Monitoring Instrument (OMI)

NASA Technical Reports Server (NTRS)

Levelt, P. F.; Veefkind, J. P.; Stammes, P.; Hilsenrath, E.; Bhartia, P. K.; Chance, K. V.; Leppelmeier, G. W.; Maelkki, A.; Bhartia, Pawan (Technical Monitor)

2002-01-01

OMI is a UV/VIS nadir solar backscatter spectrograph, which provides near global coverage in one day with a spatial resolution of 13 x 24 sq km. OMI is a new instrument, with a heritage from the European satellite instruments GOME, GOMOS and SCIAMACHY. OMI's unique capabilities for measuring important trace gases with a small footprint and daily global coverage, in conjunction with the other Aura instruments, will make a major contribution to our understanding of stratospheric and tropospheric chemistry and climate change. OMI will measure solar irradiance and Earth radiances in the wavelength range of 270 to 500 nm with spectral resolution of about 0.5 nm and a spectral sampling of about 2-3 per FWHM. From these observations, total columns of O3, NO2, BrO and SO2 will be derived from the back-scattered solar radiance using differential absorption spectroscopy (DOAS). The TOMS total ozone record will also be continued by employing the well established TOMS algorithm. Because of the high accuracy and spatial resolution of the measurements, a good estimate of tropospheric amounts of ozone and NO2 are expected. Ozone profiles will be derived using the optimal estimation method. The spectral aerosol optical depth will be determined from measurements between 340 and 500 nm. This will provide information on aerosol concentration, aerosol size distribution and aerosol type. This wavelength range makes it possible to retrieve aerosol information over both land and sea. OMI observations will also allow retrievals of cloud coverage and cloud heights. From these products, the UV-B flux at the surface can then be derived with high spatial resolution.

Spatial Resolution Requirements for Traffic-Related Air Pollutant Exposure Evaluations

PubMed Central

Batterman, Stuart; Chambliss, Sarah; Isakov, Vlad

2014-01-01

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

A scintillator geometry suitable for very small PET gantries

NASA Astrophysics Data System (ADS)

Gonzalez, A. J.; Gonzalez-Montoro, A.; Aguilar, A.; Cañizares, G.; Martí, R.; Iranzo, S.; Lamprou, E.; Sanchez, S.; Sanchez, F.; Benlloch, J. M.

2017-12-01

In this work we are describing a novel approach to the scintillator crystal configuration as used in nuclear medicine imaging. Our design is related to the coupling in one PET module of the two separate crystal configurations used so far there: monolithic and crystal arrays. The particular design we have studied is based on a two-layer scintillator approach (hybrid) composed of a monolithic LYSO crystal (5-6 mm thickness) and a LYSO crystal array with 4-5 mm height (0.8 and 1 mm pixels). We show here the detector block performance, in terms of spatial, energy and DOI information, to be used as a module in the design of PET scanners. The design we propose allows one to achieve accurate three-dimensional spatial resolution (including DOI information) while assuring high detection efficiency at reasonable cost. Moreover, the proposed design improves the spatial response uniformity across the whole detector module, and especially at the edge region. The crystal arrays are mounted in the front and were well resolved. The monolithic crystal inserted between crystal array and the photosensor, provided measured FWHM resolution as good as 1.5-1.7 mm including the 1 mm source size. The monolithic block achieved a DOI resolution (FWHM) nearing 3 mm. We compared these results with an approach in which we use a single monolithic block with total volume equals to the hybrid approach. In general, comparable performances were obtained.

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010

PubMed Central

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Roy, Partha Sarathi; Joshi, Pawan Kumar; Gilani, Hammad; Murthy, Manchiraju Sri Ramachandra; Jin, Cui; Wang, Jie; Zhang, Yao; Chen, Bangqian; Menarguez, Michael Angelo; Biradar, Chandrashekhar M.; Bajgain, Rajen; Li, Xiangping; Dai, Shengqi; Hou, Ying; Xin, Fengfei; Moore III, Berrien

2016-01-01

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 106 km2. The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests. PMID:26864143

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Roy, Partha Sarathi; Joshi, Pawan Kumar; Gilani, Hammad; Murthy, Manchiraju Sri Ramachandra; Jin, Cui; Wang, Jie; Zhang, Yao; Chen, Bangqian; Menarguez, Michael Angelo; Biradar, Chandrashekhar M; Bajgain, Rajen; Li, Xiangping; Dai, Shengqi; Hou, Ying; Xin, Fengfei; Moore, Berrien

2016-02-11

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 10(6 )km(2). The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Spatial Frequency Requirements and Gaze Strategy in Visual-Only and Audiovisual Speech Perception

PubMed Central

Wilson, Amanda H.; Paré, Martin; Munhall, Kevin G.

2016-01-01

Purpose The aim of this article is to examine the effects of visual image degradation on performance and gaze behavior in audiovisual and visual-only speech perception tasks. Method We presented vowel–consonant–vowel utterances visually filtered at a range of frequencies in visual-only, audiovisual congruent, and audiovisual incongruent conditions (Experiment 1; N = 66). In Experiment 2 (N = 20), participants performed a visual-only speech perception task and in Experiment 3 (N = 20) an audiovisual task while having their gaze behavior monitored using eye-tracking equipment. Results In the visual-only condition, increasing image resolution led to monotonic increases in performance, and proficient speechreaders were more affected by the removal of high spatial information than were poor speechreaders. The McGurk effect also increased with increasing visual resolution, although it was less affected by the removal of high-frequency information. Observers tended to fixate on the mouth more in visual-only perception, but gaze toward the mouth did not correlate with accuracy of silent speechreading or the magnitude of the McGurk effect. Conclusions The results suggest that individual differences in silent speechreading and the McGurk effect are not related. This conclusion is supported by differential influences of high-resolution visual information on the 2 tasks and differences in the pattern of gaze. PMID:27537379

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2018-07-16

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

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

NASA Astrophysics Data System (ADS)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Fusion of Modis and Palsar Principal Component Images Through Curvelet Transform for Land Cover Classification

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Kumar, Harish

Earth observation satellites provide data that covers different portions of the electromagnetic spectrum at different spatial and spectral resolutions. The increasing availability of information products generated from satellite images are extending the ability to understand the patterns and dynamics of the earth resource systems at all scales of inquiry. In which one of the most important application is the generation of land cover classification from satellite images for understanding the actual status of various land cover classes. The prospect for the use of satel-lite images in land cover classification is an extremely promising one. The quality of satellite images available for land-use mapping is improving rapidly by development of advanced sensor technology. Particularly noteworthy in this regard is the improved spatial and spectral reso-lution of the images captured by new satellite sensors like MODIS, ASTER, Landsat 7, and SPOT 5. For the full exploitation of increasingly sophisticated multisource data, fusion tech-niques are being developed. Fused images may enhance the interpretation capabilities. The images used for fusion have different temporal, and spatial resolution. Therefore, the fused image provides a more complete view of the observed objects. It is one of the main aim of image fusion to integrate different data in order to obtain more information that can be de-rived from each of the single sensor data alone. A good example of this is the fusion of images acquired by different sensors having a different spatial resolution and of different spectral res-olution. Researchers are applying the fusion technique since from three decades and propose various useful methods and techniques. The importance of high-quality synthesis of spectral information is well suited and implemented for land cover classification. More recently, an underlying multiresolution analysis employing the discrete wavelet transform has been used in image fusion. It was found that multisensor image fusion is a tradeoff between the spectral information from a low resolution multi-spectral images and the spatial information from a high resolution multi-spectral images. With the wavelet transform based fusion method, it is easy to control this tradeoff. A new transform, the curvelet transform was used in recent years by Starck. A ridgelet transform is applied to square blocks of detail frames of undecimated wavelet decomposition, consequently the curvelet transform is obtained. Since the ridgelet transform possesses basis functions matching directional straight lines therefore, the curvelet transform is capable of representing piecewise linear contours on multiple scales through few significant coefficients. This property leads to a better separation between geometric details and background noise, which may be easily reduced by thresholding curvelet coefficients before they are used for fusion. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 m to 14.4 m and also it is freely available. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. In this paper, the band 1 of spatial resolution 250 m and bandwidth 620-670 nm, and band 2, of spatial resolution of 250m and bandwidth 842-876 nm is considered as these bands has special features to identify the agriculture and other land covers. In January 2006, the Advanced Land Observing Satellite (ALOS) was successfully launched by the Japan Aerospace Exploration Agency (JAXA). The Phased Arraytype L-band SAR (PALSAR) sensor onboard the satellite acquires SAR imagery at a wavelength of 23.5 cm (frequency 1.27 GHz) with capabilities of multimode and multipolarization observation. PALSAR can operate in several modes: the fine-beam single (FBS) polarization mode (HH), fine-beam dual (FBD) polariza-tion mode (HH/HV or VV/VH), polarimetric (PLR) mode (HH/HV/VH/VV), and ScanSAR (WB) mode (HH/VV) [15]. These makes PALSAR imagery very attractive for spatially and temporally consistent monitoring system. The Overview of Principal Component Analysis is that the most of the information within all the bands can be compressed into a much smaller number of bands with little loss of information. It allows us to extract the low-dimensional subspaces that capture the main linear correlation among the high-dimensional image data. This facilitates viewing the explained variance or signal in the available imagery, allowing both gross and more subtle features in the imagery to be seen. In this paper we have explored the fusion technique for enhancing the land cover classification of low resolution satellite data espe-cially freely available satellite data. For this purpose, we have considered to fuse the PALSAR principal component data with MODIS principal component data. Initially, the MODIS band 1 and band 2 is considered, its principal component is computed. Similarly the PALSAR HH, HV and VV polarized data are considered, and there principal component is also computed. con-sequently, the PALSAR principal component image is fused with MODIS principal component image. The aim of this paper is to analyze the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of PALSAR data to MODIS data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied for the resultant fused image. It is qualitatively and visually observed that the overall classification accuracy of MODIS image after fusion is enhanced. This type of fusion technique may be quite helpful in near future to use freely available satellite data to develop monitoring system for different land cover classes on the earth.

Can Satellite Remote Sensing be Applied in Geological Mapping in Tropics?

NASA Astrophysics Data System (ADS)

Magiera, Janusz

2018-03-01

Remote sensing (RS) techniques are based on spectral data registered by RS scanners as energy reflected from the Earth's surface or emitted by it. In "geological" RS the reflectance (or emittence) should come from rock or sediment. The problem in tropical and subtropical areas is a dense vegetation. Spectral response from the rocks and sediments is gathered only from the gaps among the trees and shrubs. Images of high resolution are appreciated here, therefore. New generation of satellites and scanners (Digital Globe WV2, WV3 and WV4) yield imagery of spatial resolution of 2 m and up to 16 spectral bands (WV3). Images acquired by Landsat (TM, ETM+, OLI) and Sentinel 2 have good spectral resolution too (6-12 bands in visible and infrared) and, despite lower spatial resolution (10-60 m of pixel size) are useful in extracting lithological information too. Lithological RS map may reveal good precision (down to a single rock or outcrop of a meter size). Supplemented with the analysis of Digital Elevation Model and high resolution ortophotomaps (Google Maps, Bing etc.) allows for quick and cheap mapping of unsurveyed areas.

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.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Imaging White Matter in Human Brainstem

PubMed Central

Ford, Anastasia A.; Colon-Perez, Luis; Triplett, William T.; Gullett, Joseph M.; Mareci, Thomas H.; FitzGerald, David B.

2013-01-01

The human brainstem is critical for the control of many life-sustaining functions, such as consciousness, respiration, sleep, and transfer of sensory and motor information between the brain and the spinal cord. Most of our knowledge about structure and organization of white and gray matter within the brainstem is derived from ex vivo dissection and histology studies. However, these methods cannot be applied to study structural architecture in live human participants. Tractography from diffusion-weighted magnetic resonance imaging (MRI) may provide valuable insights about white matter organization within the brainstem in vivo. However, this method presents technical challenges in vivo due to susceptibility artifacts, functionally dense anatomy, as well as pulsatile and respiratory motion. To investigate the limits of MR tractography, we present results from high angular resolution diffusion imaging of an intact excised human brainstem performed at 11.1 T using isotropic resolution of 0.333, 1, and 2 mm, with the latter reflecting resolution currently used clinically. At the highest resolution, the dense fiber architecture of the brainstem is evident, but the definition of structures degrades as resolution decreases. In particular, the inferred corticopontine/corticospinal tracts (CPT/CST), superior (SCP) and middle cerebellar peduncle (MCP), and medial lemniscus (ML) pathways are clearly discernable and follow known anatomical trajectories at the highest spatial resolution. At lower resolutions, the CST/CPT, SCP, and MCP pathways are artificially enlarged due to inclusion of collinear and crossing fibers not inherent to these three pathways. The inferred ML pathways appear smaller at lower resolutions, indicating insufficient spatial information to successfully resolve smaller fiber pathways. Our results suggest that white matter tractography maps derived from the excised brainstem can be used to guide the study of the brainstem architecture using diffusion MRI in vivo. PMID:23898254

Deriving temporally continuous soil moisture estimations at fine resolution by downscaling remotely sensed product

NASA Astrophysics Data System (ADS)

Jin, Yan; Ge, Yong; Wang, Jianghao; Heuvelink, Gerard B. M.

2018-06-01

Land surface soil moisture (SSM) has important roles in the energy balance of the land surface and in the water cycle. Downscaling of coarse-resolution SSM remote sensing products is an efficient way for producing fine-resolution data. However, the downscaling methods used most widely require full-coverage visible/infrared satellite data as ancillary information. These methods are restricted to cloud-free days, making them unsuitable for continuous monitoring. The purpose of this study is to overcome this limitation to obtain temporally continuous fine-resolution SSM estimations. The local spatial heterogeneities of SSM and multiscale ancillary variables were considered in the downscaling process both to solve the problem of the strong variability of SSM and to benefit from the fusion of ancillary information. The generation of continuous downscaled remote sensing data was achieved via two principal steps. For cloud-free days, a stepwise hybrid geostatistical downscaling approach, based on geographically weighted area-to-area regression kriging (GWATARK), was employed by combining multiscale ancillary variables with passive microwave remote sensing data. Then, the GWATARK-estimated SSM and China Soil Moisture Dataset from Microwave Data Assimilation SSM data were combined to estimate fine-resolution data for cloudy days. The developed methodology was validated by application to the 25-km resolution daily AMSR-E SSM product to produce continuous SSM estimations at 1-km resolution over the Tibetan Plateau. In comparison with ground-based observations, the downscaled estimations showed correlation (R ≥ 0.7) for both ascending and descending overpasses. The analysis indicated the high potential of the proposed approach for producing a temporally continuous SSM product at fine spatial resolution.

Imaging white matter in human brainstem.

PubMed

Ford, Anastasia A; Colon-Perez, Luis; Triplett, William T; Gullett, Joseph M; Mareci, Thomas H; Fitzgerald, David B

2013-01-01

The human brainstem is critical for the control of many life-sustaining functions, such as consciousness, respiration, sleep, and transfer of sensory and motor information between the brain and the spinal cord. Most of our knowledge about structure and organization of white and gray matter within the brainstem is derived from ex vivo dissection and histology studies. However, these methods cannot be applied to study structural architecture in live human participants. Tractography from diffusion-weighted magnetic resonance imaging (MRI) may provide valuable insights about white matter organization within the brainstem in vivo. However, this method presents technical challenges in vivo due to susceptibility artifacts, functionally dense anatomy, as well as pulsatile and respiratory motion. To investigate the limits of MR tractography, we present results from high angular resolution diffusion imaging of an intact excised human brainstem performed at 11.1 T using isotropic resolution of 0.333, 1, and 2 mm, with the latter reflecting resolution currently used clinically. At the highest resolution, the dense fiber architecture of the brainstem is evident, but the definition of structures degrades as resolution decreases. In particular, the inferred corticopontine/corticospinal tracts (CPT/CST), superior (SCP) and middle cerebellar peduncle (MCP), and medial lemniscus (ML) pathways are clearly discernable and follow known anatomical trajectories at the highest spatial resolution. At lower resolutions, the CST/CPT, SCP, and MCP pathways are artificially enlarged due to inclusion of collinear and crossing fibers not inherent to these three pathways. The inferred ML pathways appear smaller at lower resolutions, indicating insufficient spatial information to successfully resolve smaller fiber pathways. Our results suggest that white matter tractography maps derived from the excised brainstem can be used to guide the study of the brainstem architecture using diffusion MRI in vivo.

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

High Resolution Stratigraphic Mapping in Complex Terrain: A Comparison of Traditional Remote Sensing Techniques with Unmanned Aerial Vehicle - Structure from Motion Photogrammetry

NASA Astrophysics Data System (ADS)

Nesbit, P. R.; Hugenholtz, C.; Durkin, P.; Hubbard, S. M.; Kucharczyk, M.; Barchyn, T.

2016-12-01

Remote sensing and digital mapping have started to revolutionize geologic mapping in recent years as a result of their realized potential to provide high resolution 3D models of outcrops to assist with interpretation, visualization, and obtaining accurate measurements of inaccessible areas. However, in stratigraphic mapping applications in complex terrain, it is difficult to acquire information with sufficient detail at a wide spatial coverage with conventional techniques. We demonstrate the potential of a UAV and Structure from Motion (SfM) photogrammetric approach for improving 3D stratigraphic mapping applications within a complex badland topography. Our case study is performed in Dinosaur Provincial Park (Alberta, Canada), mapping late Cretaceous fluvial meander belt deposits of the Dinosaur Park formation amidst a succession of steeply sloping hills and abundant drainages - creating a challenge for stratigraphic mapping. The UAV-SfM dataset (2 cm spatial resolution) is compared directly with a combined satellite and aerial LiDAR dataset (30 cm spatial resolution) to reveal advantages and limitations of each dataset before presenting a unique workflow that utilizes the dense point cloud from the UAV-SfM dataset for analysis. The UAV-SfM dense point cloud minimizes distortion, preserves 3D structure, and records an RGB attribute - adding potential value in future studies. The proposed UAV-SfM workflow allows for high spatial resolution remote sensing of stratigraphy in complex topographic environments. This extended capability can add value to field observations and has the potential to be integrated with subsurface petroleum models.

Application of travel time information for traffic management : technical summary.

DOT National Transportation Integrated Search

2012-01-01

Using conventional methods, it is extremely costly to measure detailed traffic characteristics in high quality spatial or temporal resolution. For analyzing travel characteristics on roadways, the floating car method, developed in the 1920s, has hist...

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.

Business innovation symposium ‘At what price? IP-related thoughts on new business models for space information’

NASA Astrophysics Data System (ADS)

Smith, Lesley Jane

2011-09-01

Spatial data and imagery generators are set to become tomorrow's key players in the information society. This is why satellite owners and operators are examining new revenue-producing models for developing space-related products and services. The use and availability of broadband internet width and satellite data-based services will continue to increase in the future. With the capacity to deliver real time precision downstream data, space agencies and the satellite industry can respond to the demand for high resolution digital space information which, with the appropriate technology, can be integrated into a variety of web-based applications. At a time when the traditional roles of space agencies are becoming more hybrid, largely as a result of the greater drive towards commercial markets, new value-added markets for space-related information products are continuing to attract attention. This paper discusses whether traditional data policies on space data access and IP licensing schemes stand to remain the feasible prototype for distributing and marketing space data, and how this growth market might benefit from looking at an 'up and running' global IP management system already operating to manage end user digital demand. PrefaceThe terminology describing the various types of spatial data and space-based information is not uniformly used within the various principles, laws and policies that govern space data. For convenience only this paper refers to primary or raw data gathered by the space-based industry as spatial or raw data, and the data as processed and sold on or distributed by ground-based companies as space information products and services. In practise, spatial data range from generic to specific data sets, digital topography, through to pictures and imagery services at various resolutions, with 3-D perspectives underway. The paper addresses general IP considerations relating to spatial data, with some reference to remote sensing itself. Exact IP details will depend at all times on the final product and service in question.

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.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

NASA Astrophysics Data System (ADS)

Lazaridou, M. A.; Karagianni, A. Ch.

2016-06-01

Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

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

DTIC Science & Technology

1990-12-01

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

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.

The Balloon Experimental Twin Telescope for Infrared Interferometry

NASA Technical Reports Server (NTRS)

Silverburg, Robert

2009-01-01

Astronomical studies at infrared wavelengths have dramatically improved our understanding of the universe, and observations with Spitzer, the upcoming Herschel mission, and SOFIA will continue to provide exciting new discoveries. The comparatively low spatial resolution of these missions, however, is insufficient to resolve the physical scales on which mid- to far-infrared emission arises, resulting in source and structure ambiguities that limit our ability to answer key science questions. Interferometry enables high angular resolution at these wavelengths. We have proposed a new high altitude balloon experiment, the Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII). High altitude operation makes far-infrared (30- 300micron) observations possible, and BETTII's 8-meter baseline provides unprecedented angular resolution (approx. 0.5 arcsec) in this band. BETTII will use a double-Fourier instrument to simultaneously obtain both spatial and spectral information. The spatially resolved spectroscopy provided by BETTII will address key questions about the nature of disks in young cluster stars and active galactic nuclei and the envelopes of evolved stars. BETTII will also lay the groundwork for future space interferometers.

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

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

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

Spatially encoded phase-contrast MRI-3D MRI movies of 1D and 2D structures at millisecond resolution.

PubMed

Merboldt, Klaus-Dietmar; Uecker, Martin; Voit, Dirk; Frahm, Jens

2011-10-01

This work demonstrates that the principles underlying phase-contrast MRI may be used to encode spatial rather than flow information along a perpendicular dimension, if this dimension contains an MRI-visible object at only one spatial location. In particular, the situation applies to 3D mapping of curved 2D structures which requires only two projection images with different spatial phase-encoding gradients. These phase-contrast gradients define the field of view and mean spin-density positions of the object in the perpendicular dimension by respective phase differences. When combined with highly undersampled radial fast low angle shot (FLASH) and image reconstruction by regularized nonlinear inversion, spatial phase-contrast MRI allows for dynamic 3D mapping of 2D structures in real time. First examples include 3D MRI movies of the acting human hand at a temporal resolution of 50 ms. With an even simpler technique, 3D maps of curved 1D structures may be obtained from only three acquisitions of a frequency-encoded MRI signal with two perpendicular phase encodings. Here, 3D MRI movies of a rapidly rotating banana were obtained at 5 ms resolution or 200 frames per second. In conclusion, spatial phase-contrast 3D MRI of 2D or 1D structures is respective two or four orders of magnitude faster than conventional 3D MRI. Copyright © 2011 Wiley-Liss, Inc.

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

The absolute calibration of KOMPSAT-3 and 3A high spatial resolution satellites using radiometric tarps and MFRSR measurments

NASA Astrophysics Data System (ADS)

Yeom, J. M.

2017-12-01

Recently developed Korea Multi-Purpose Satellite-3A (KOMPSAT-3A), which is a continuation of the KOMPSAT-1, 2 and 3 earth observation satellite (EOS) programs from the Korea Aerospace Research Institute (KARI) was launched on March, 25 2015 on a Dnepr-1 launch vehicle from the Jasny Dombarovsky site in Russia. After launched, KARI performed in-orbit-test (IOT) including radiometric calibration for 6 months from 14 Apr. to 4 Sep. 2015. KOMPSAT-3A is equipped with two distinctive sensors; one is a high resolution multispectral optical sensor, namely the Advances Earth Image Sensor System-A (AEISS-A) and the other is the Scanner Infrared Imaging System (SIIS). In this study, we focused on the radiometric calibration of AEISS-A. The multispectral wavelengths of AEISS-A are covering three visible regions: blue (450 - 520 nm), green (520 - 600 nm), red (630 - 690 nm), one near infrared (760 - 900 nm) with a 2.0 m spatial resolution at nadir, whereas the panchromatic imagery (450 - 900 nm) has a 0.5 m resolution. Those are the same spectral response functions were same with KOMPSAT-3 multispectral and panchromatic bands but the spatial resolutions are improved. The main mission of KOMPSAT-3A is to develop for Geographical Information System (GIS) applications in environmental, agriculture, and oceanographic sciences, as well as natural hazard monitoring.

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.

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_TRMM-PFM-VIRS_Beta4)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Evolution in High Spatial Resolution Imaging of Faint, Complex Objects

NASA Astrophysics Data System (ADS)

van Belle, G.

The astrophysical community has been working at the task of obtaining image information of the smallest structures in the sky via the use of optical interferometry for well over a century. A richly diverse family of technology architectures has been explored over the years, and yet the current family of facilities are all striking similar. Although there may be other, heretofore undeployed, architectures that support the goal of collecting image information at the highest resolutions, we expect dramatic advances at the component level of long-baseline interferometry to be the best avenue for advancing the technique, rather than entirely new architectures.

An atlas of high-resolution IRAS maps on nearby galaxies

NASA Technical Reports Server (NTRS)

Rice, Walter

1993-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

Analytical 3D views and virtual globes — scientific results in a familiar spatial context

NASA Astrophysics Data System (ADS)

Tiede, Dirk; Lang, Stefan

In this paper we introduce analytical three-dimensional (3D) views as a means for effective and comprehensible information delivery, using virtual globes and the third dimension as an additional information carrier. Four case studies are presented, in which information extraction results from very high spatial resolution (VHSR) satellite images were conditioned and aggregated or disaggregated to regular spatial units. The case studies were embedded in the context of: (1) urban life quality assessment (Salzburg/Austria); (2) post-disaster assessment (Harare/Zimbabwe); (3) emergency response (Lukole/Tanzania); and (4) contingency planning (faked crisis scenario/Germany). The results are made available in different virtual globe environments, using the implemented contextual data (such as satellite imagery, aerial photographs, and auxiliary geodata) as valuable additional context information. Both day-to-day users and high-level decision makers are addressees of this tailored information product. The degree of abstraction required for understanding a complex analytical content is balanced with the ease and appeal by which the context is conveyed.

Fine-resolution conservation planning with limited climate-change information.

PubMed

Shah, Payal; Mallory, Mindy L; Ando, Amy W; Guntenspergen, Glenn R

2017-04-01

Climate-change induced uncertainties in future spatial patterns of conservation-related outcomes make it difficult to implement standard conservation-planning paradigms. A recent study translates Markowitz's risk-diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate-change scenarios for carrying out fine-resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk-return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate-change information and full climate-change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate-change forecasts such that the best possible risk-return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate-change information could be reduced by 17% relative to other iterative approaches. © 2016 Society for Conservation Biology.

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

DTIC Science & Technology

2007-03-01

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

Guided filter and principal component analysis hybrid method for hyperspectral pansharpening

NASA Astrophysics Data System (ADS)

Qu, Jiahui; Li, Yunsong; Dong, Wenqian

2018-01-01

Hyperspectral (HS) pansharpening aims to generate a fused HS image with high spectral and spatial resolution through integrating an HS image with a panchromatic (PAN) image. A guided filter (GF) and principal component analysis (PCA) hybrid HS pansharpening method is proposed. First, the HS image is interpolated and the PCA transformation is performed on the interpolated HS image. The first principal component (PC1) channel concentrates on the spatial information of the HS image. Different from the traditional PCA method, the proposed method sharpens the PAN image and utilizes the GF to obtain the spatial information difference between the HS image and the enhanced PAN image. Then, in order to reduce spectral and spatial distortion, an appropriate tradeoff parameter is defined and the spatial information difference is injected into the PC1 channel through multiplying by this tradeoff parameter. Once the new PC1 channel is obtained, the fused image is finally generated by the inverse PCA transformation. Experiments performed on both synthetic and real datasets show that the proposed method outperforms other several state-of-the-art HS pansharpening methods in both subjective and objective evaluations.

Global-scale surface spectral variations on Titan seen from Cassini/VIMS

USGS Publications Warehouse

Barnes, J.W.; Brown, R.H.; Soderblom, L.; Buratti, B.J.; Sotin, Christophe; Rodriguez, S.; Le, Mouelic S.; Baines, K.H.; Clark, R.; Nicholson, P.

2007-01-01

We present global-scale maps of Titan from the Visual and Infrared Mapping Spectrometer (VIMS) instrument on Cassini. We map at 64 near-infrared wavelengths simultaneously, covering the atmospheric windows at 0.94, 1.08, 1.28, 1.6, 2.0, 2.8, and 5 ??m with a typical resolution of 50 km/pixel or a typical total integration time of 1 s. Our maps have five to ten times the resolution of ground-based maps, better spectral resolution across most windows, coverage in multiple atmospheric windows, and represent the first spatially resolved maps of Titan at 5 ??m. The VIMS maps provide context and surface spectral information in support of other Cassini instruments. We note a strong latitudinal dependence in the spectral character of Titan's surface, and partition the surface into 9 spectral units that we describe in terms of spectral and spatial characteristics. ?? 2006 Elsevier Inc. All rights reserved.

Rapid mapping of polarization switching through complete information acquisition

NASA Astrophysics Data System (ADS)

Somnath, Suhas; Belianinov, Alex; Kalinin, Sergei V.; Jesse, Stephen

2016-12-01

Polarization switching in ferroelectric and multiferroic materials underpins a broad range of current and emergent applications, ranging from random access memories to field-effect transistors, and tunnelling devices. Switching in these materials is exquisitely sensitive to local defects and microstructure on the nanometre scale, necessitating spatially resolved high-resolution studies of these phenomena. Classical piezoresponse force microscopy and spectroscopy, although providing necessary spatial resolution, are fundamentally limited in data acquisition rates and energy resolution. This limitation stems from their two-tiered measurement protocol that combines slow (~1 s) switching and fast (~10 kHz-1 MHz) detection waveforms. Here we develop an approach for rapid probing of ferroelectric switching using direct strain detection of material response to probe bias. This approach, facilitated by high-sensitivity electronics and adaptive filtering, enables spectroscopic imaging at a rate 3,504 times faster the current state of the art, achieving high-veracity imaging of polarization dynamics in complex microstructures.

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

Development of an Unmanned Aerial System (UAS) for Scaling Terrestrial Ecosystem Traits

NASA Astrophysics Data System (ADS)

Meng, R.; McMahon, A. M.; Serbin, S.; Rogers, A.

2015-12-01

The next generation of Ecosystem and Earth System Models (EESMs) will require detailed information on ecosystem structure and function, including properties of vegetation related to carbon (C), water, and energy cycling, in order to project the future state of ecosystems. High spatial-temporal resolution measurements of terrestrial ecosystem are also important for EESMs, because they can provide critical inputs and benchmark datasets for evaluation of EESMs simulations across scales. The recent development of high-quality, low-altitude remote sensing platforms or small UAS (< 25 kg) enables measurements of terrestrial ecosystems at unprecedented temporal and spatial scales. Specifically, these new platforms can provide detailed information on patterns and processes of terrestrial ecosystems at a critical intermediate scale between point measurements and suborbital and satellite platforms. Given their potential for sub-decimeter spatial resolution, improved mission safety, high revisit frequency, and reduced operation cost, these platforms are of particular interest in the development of ecological scaling algorithms to parameterize and benchmark EESMs, particularly over complex and remote terrain. Our group is developing a small UAS platform and integrated sensor package focused on measurement needs for scaling and informing ecosystem modeling activities, as well as scaling and mapping plant functional traits. To do this we are developing an integrated software workflow and hardware package using off-the-shelf instrumentation including a high-resolution digital camera for Structure from Motion, spectroradiometer, and a thermal infrared camera. Our workflow includes platform design, measurement, image processing, data management, and information extraction. The fusion of 3D structure information, thermal-infrared imagery, and spectroscopic measurements, will provide a foundation for the development of ecological scaling and mapping algorithms. Our initial focus is in temperate forests but near-term research will expand into the high-arctic and eventually tropical systems. The results of this prototype study show that off-the-shelf technology can be used to develop a low-cost alternative for mapping plant traits and three-dimensional structure for ecological research.

Submicrometre geometrically encoded fluorescent barcodes self-assembled from DNA

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

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

PubMed Central

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

2012-01-01

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

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.

Assessment of ground-based monitoring techniques applied to landslide investigations

NASA Astrophysics Data System (ADS)

Uhlemann, S.; Smith, A.; Chambers, J.; Dixon, N.; Dijkstra, T.; Haslam, E.; Meldrum, P.; Merritt, A.; Gunn, D.; Mackay, J.

2016-01-01

A landslide complex in the Whitby Mudstone Formation at Hollin Hill, North Yorkshire, UK is periodically re-activated in response to rainfall-induced pore-water pressure fluctuations. This paper compares long-term measurements (i.e., 2009-2014) obtained from a combination of monitoring techniques that have been employed together for the first time on an active landslide. The results highlight the relative performance of the different techniques, and can provide guidance for researchers and practitioners for selecting and installing appropriate monitoring techniques to assess unstable slopes. Particular attention is given to the spatial and temporal resolutions offered by the different approaches that include: Real Time Kinematic-GPS (RTK-GPS) monitoring of a ground surface marker array, conventional inclinometers, Shape Acceleration Arrays (SAA), tilt meters, active waveguides with Acoustic Emission (AE) monitoring, and piezometers. High spatial resolution information has allowed locating areas of stability and instability across a large slope. This has enabled identification of areas where further monitoring efforts should be focused. High temporal resolution information allowed the capture of 'S'-shaped slope displacement-time behaviour (i.e. phases of slope acceleration, deceleration and stability) in response to elevations in pore-water pressures. This study shows that a well-balanced suite of monitoring techniques that provides high temporal and spatial resolutions on both measurement and slope scale is necessary to fully understand failure and movement mechanisms of slopes. In the case of the Hollin Hill landslide it enabled detailed interpretation of the geomorphological processes governing landslide activity. It highlights the benefit of regularly surveying a network of GPS markers to determine areas for installation of movement monitoring techniques that offer higher resolution both temporally and spatially. The small sensitivity of tilt meter measurements to translational movements limited the ability to record characteristic 'S'-shaped landslide movements at Hollin Hill, which were identified using SAA and AE measurements. This high sensitivity to landslide movements indicates the applicability of SAA and AE monitoring to be used in early warning systems, through detecting and quantifying accelerations of slope movement.

High resolution Cerenkov light imaging of induced positron distribution in proton therapy

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

Yamamoto, Seiichi, E-mail: s-yama@met.nagoya-u.ac.jp; Fujii, Kento; Morishita, Yuki

2014-11-01

Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, theymore » conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a {sup 22}Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm{sup 3}) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The authors conclude that Cerenkov light imaging of proton-induced positron is promising for proton therapy.« less

Efficient Probabilistic Forecasting for High-Resolution Models through Clustered-State Data Assimilation

NASA Astrophysics Data System (ADS)

Hamidi, A.; Grossberg, M.; Khanbilvardi, R.

2016-12-01

Flood response in an urban area is the product of interactions of spatially and temporally varying rainfall and infrastructures. In urban areas, however, the complex sub-surface networks of tunnels, waste and storm water drainage systems are often inaccessible, pose challenges for modeling and prediction of the drainage infrastructure performance. The increased availability of open data in cities is an emerging information asset for a better understanding of the dynamics of urban water drainage infrastructure. This includes crowd sourced data and community reporting. A well-known source of this type of data is the non-emergency hotline "311" which is available in many US cities, and may contain information pertaining to the performance of physical facilities, condition of the environment, or residents' experience, comfort and well-being. In this study, seven years of New York City 311 (NYC311) call during 2010-2016 is employed, as an alternative approach for identifying the areas of the city most prone to sewer back up flooding. These zones are compared with the hydrologic analysis of runoff flooding zones to provide a predictive model for the City. The proposed methodology is an example of urban system phenomenology using crowd sourced, open data. A novel algorithm for calculating the spatial distribution of flooding complaints across NYC's five boroughs is presented in this study. In this approach, the features that represent reporting bias are separated from those that relate to actual infrastructure system performance. The sewer backup results are assessed with the spatial distribution of runoff in NYC during 2010-2016. With advances in radar technologies, a high spatial-temporal resolution data set for precipitation is available for most of the United States that can be implemented in hydrologic analysis of dense urban environments. High resolution gridded Stage IV radar rainfall data along with the high resolution spatially distributed land cover data are employed to investigate the urban pluvial flooding. The monthly results of excess runoff are compared with the sewer backup in NYC to build a predictive model of flood zones according to the 311 phone calls.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Harmful algal bloom characterization at ultra-high spatial and temporal resolution using small unmanned aircraft systems.

PubMed

Van der Merwe, Deon; Price, Kevin P

2015-03-27

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r(2)-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level.

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.

Harmful Algal Bloom Characterization at Ultra-High Spatial and Temporal Resolution Using Small Unmanned Aircraft Systems

PubMed Central

Van der Merwe, Deon; Price, Kevin P.

2015-01-01

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r2-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level. PMID:25826055

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

NASA Technical Reports Server (NTRS)

Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

2013-01-01

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

NASA Technical Reports Server (NTRS)

Joiner, J.; Guanter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

2013-01-01

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 0.5. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Estimation of daily Snow Cover Area combining MODIS and LANDSAT information by using cellular automata

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Juan Collados Lara, Antonio; Pulido-Velazquez, David

2016-04-01

The snow availability in Alpine catchments is essential for the economy of these areas. It plays an important role in tourist development but also in the management of the Water Resources Snow is an important water resource in many river basins with mountains in the catchment area. The determination of the snow water equivalent requires the estimation of the evolution of the snow pack (cover area, thickness and snow density) along the time. Although there are complex physical models of the dynamics of the snow pack, sometimes the data available are scarce and a stochastic model like the cellular automata (CA) can be of great practical interest. CA can be used to model the dynamics of growth and wane of the snow pack. The CA is calibrated with historical data. This requires the determination of transition rules that are capable of modeling the evolution of the spatial pattern of snow cover area. Furthermore, CA requires the definition of states and neighborhoods. We have included topographical variables and climatological variables in order to define the state of each pixel. The evolution of snow cover in a pixel depends on its state, the state of the neighboring pixels and the transition rules. The calibration of the CA is done using daily MODIS data, available for the period 24/02/2002 to present with a spatial resolution of 500 m, and the LANDSAT information available with a sixteen-day periodicity from 1984 to the present and with spatial resolution of 30 m. The methodology has been applied to estimation of the snow cover area of Sierra Nevada mountain range in the Southern of Spain to obtain snow cover area daily information with 500 m spatial resolution for the period 1980-2014. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank NASA DAAC and LANDSAT project for the data provided for this study.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

AVAL - The ASTER Volcanic Ash Library

NASA Astrophysics Data System (ADS)

Williams, D.; Ramsey, M. S.

2016-12-01

Volcanic ash is a rich data source for understanding the causal mechanisms behind volcanic eruptions. Petrologic and morphometric information can provide direct information on the characteristics of the parent magma. Understanding how erupted ash interacts with the atmosphere can help quantify the effect that explosive volcanism has on the local to regional climate, whereas a measure of the particle size distribution enables more accurate modeling of plume propagation. Remote sensing is regularly employed to monitor volcanic plumes using a suite of high temporal/low spatial resolution sensors. These methods employ radiative transfer modeling with assumptions of the transmissive properties of infrared energy through the plume to determine ash density, particle size and sulfur dioxide content. However, such approaches are limited to the optically-transparent regions, and the low spatial resolution data are only useful for large-scale trends. In a new approach, we are treating the infrared-opaque regions of the plume in a similar way to a solid emitting surface. This allows high spatial resolution orbital thermal infrared data from the dense proximal plume to be modeled using a linear deconvolution approach coupled with a spectral library to extract the particle size and petrology. The newly created ASTER Volcanic Ash Library (AVAL) provides the end member spectral suite, and is comprised of laboratory emission measurements of volcanic ash taken from a variety of different volcanic settings, to obtain a wide range of petrologies. These samples have been further subdivided into particle size fractions to account for spectral changes due to diffraction effects. Once mapped to the ASTER sensor's spectral resolution, this library is applied to image data and the plume deconvolved to estimate composition and particle size. We have analyzed eruptions at the Soufrière Hills Volcano, Montserrat, Chaitén and Puyehue-Cordón Caulle, both Chile, and Eyjafjallajökull, Iceland. These results provide particle size distributions within actively-erupting volcanic plumes for the first time in high resolution, and the petrologic information is being studied to understand the underlying eruptive processes observed.

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

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

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

An evaluation of the spatial resolution of soil moisture information

NASA Technical Reports Server (NTRS)

Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.

1981-01-01

Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

Flight Test Results of a Synthetic Vision Elevation Database Integrity Monitor

NASA Technical Reports Server (NTRS)

deHaag, Maarten Uijt; Sayre, Jonathon; Campbell, Jacob; Young, Steve; Gray, Robert

2001-01-01

This paper discusses the flight test results of a real-time Digital Elevation Model (DEM) integrity monitor for Civil Aviation applications. Providing pilots with Synthetic Vision (SV) displays containing terrain information has the potential to improve flight safety by improving situational awareness and thereby reducing the likelihood of Controlled Flight Into Terrain (CFIT). Utilization of DEMs, such as the digital terrain elevation data (DTED), requires a DEM integrity check and timely integrity alerts to the pilots when used for flight-critical terrain-displays, otherwise the DEM may provide hazardous misleading terrain information. The discussed integrity monitor checks the consistency between a terrain elevation profile synthesized from sensor information, and the profile given in the DEM. The synthesized profile is derived from DGPS and radar altimeter measurements. DEMs of various spatial resolutions are used to illustrate the dependency of the integrity monitor s performance on the DEMs spatial resolution. The paper will give a description of proposed integrity algorithms, the flight test setup, and the results of a flight test performed at the Ohio University airport and in the vicinity of Asheville, NC.

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

Water use data to enhance scientific and policy insight

NASA Astrophysics Data System (ADS)

Konar, M.

2017-12-01

We live in an era of big data. However, water use data remains sparse. There is an urgent need to enhance both the quality and resolution of water data. Metered water use information - as opposed to estimated water use, typically based on climate - would enhance the quality of existing water databases. Metered water use data would enable the research community to evaluate the "who, where, and when" of water use. Importantly, this information would enable the scientific community to better understand decision making related to water use (i.e. the "why"), providing the insight necessary to guide policies that promote water conservation. Metered water use data is needed at a sufficient resolution (i.e. spatial, temporal, and water user) to fully resolve how water is used throughout the economy and society. Improving the quality and resolution of water use data will enable scientific understanding that can inform policy.

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

Quantifying forest fragmentation using Geographic Information Systems and Forest Inventory and Analysis plot data

Treesearch

Dacia M. Meneguzzo; Mark H. Hansen

2009-01-01

Fragmentation metrics provide a means of quantifying and describing forest fragmentation. The most common method of calculating these metrics is through the use of Geographic Information System software to analyze raster data, such as a satellite or aerial image of the study area; however, the spatial resolution of the imagery has a significant impact on the results....

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

Effects of Detector Thickness on Geometric Sensitivity and Event Positioning Errors in the Rectangular PET/X Scanner

NASA Astrophysics Data System (ADS)

MacDonald, Lawrence R.; Hunter, William C. J.; Kinahan, Paul E.; Miyaoka, Robert S.

2013-10-01

We used simulations to investigate the relationship between sensitivity and spatial resolution as a function of crystal thickness in a rectangular PET scanner intended for quantitative assessment of breast cancers. The system had two 20 × 15-cm2 and two 10 × 15-cm2 flat detectors forming a box, with the larger detectors separated by 4 or 8 cm. Depth-of-interaction (DOI) resolution was modeled as a function of crystal thickness based on prior measurements. Spatial resolution was evaluated independent of image reconstruction by deriving and validating a surrogate metric from list-mode data ( dFWHM). When increasing crystal thickness from 5 to 40 mm, and without using DOI information, the dFWHM for a centered point source increased from 0.72 to 1.6 mm. Including DOI information improved dFWHM by 12% and 27% for 5- and 40-mm-thick crystals, respectively. For a point source in the corner of the FOV, use of DOI information improved dFWHM by 20% (5-mm crystal) and 44% (40-mm crystal). Sensitivity was 7.7% for 10-mm-thick crystals (8-cm object). Increasing crystal thickness on the smaller side detectors from 10 to 20 mm (keeping 10-mm crystals on the larger detectors) boosted sensitivity by 24% (relative) and degraded dFWHM by only 3%/8% with/without DOI information. The benefits of measuring DOI must be evaluated in terms of the intended clinical task of assessing tracer uptake in small lesions. Increasing crystal thickness on the smaller side detectors provides substantial sensitivity increase with minimal accompanying loss in resolution.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

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

PubMed

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

2015-01-01

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

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

NASA Technical Reports Server (NTRS)

Tsang, Leung; Hwang, Jenq-Neng

1996-01-01

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Interpreting Low Spatial Resolution Thermal Data from Active Volcanoes on Io and the Earth

NASA Technical Reports Server (NTRS)

Keszthelyi, L.; Harris, A. J. L.; Flynn, L.; Davies, A. G.; McEwen, A.

2001-01-01

The style of volcanism was successfully determined at a number of active volcanoes on Io and the Earth using the same techniques to interpret thermal remote sensing data. Additional information is contained in the original extended abstract.

Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

Climate-physiographically differentiated Pan-European landslide susceptibility assessment using spatial multi-criteria evaluation and transnational landslide information

NASA Astrophysics Data System (ADS)

Günther, Andreas; Van Den Eeckhaut, Miet; Malet, Jean-Philippe; Reichenbach, Paola; Hervás, Javier

2014-11-01

With the adoption of the EU Thematic Strategy for Soil Protection in 2006, small-scale (1:1 M) assessments of threats affecting soils over Europe received increasing attention. As landslides have been recognized as one of eight threats requiring a Pan-European evaluation, we present an approach for landslide susceptibility evaluation at the continental scale over Europe. Unlike previous continental and global scale landslide susceptibility studies not utilizing spatial information on the events, we collected more than 102,000 landslide locations in 22 European countries. These landslides are heterogeneously distributed over Europe, but are indispensable for the evaluation and classification of Pan-European datasets used as spatial predictors, and the validation of the resulting assessments. For the analysis we subdivided the European territory into seven different climate-physiographical zones by combining morphometric and climatic data for terrain differentiation, and adding a coastal zone defined as a 1 km strip inland from the coastline. Landslide susceptibility modeling was performed for each zone using heuristic spatial multicriteria evaluations supported by analytical hierarchy processes, and validated with the inventory data using the receiver operating characteristics. In contrast to purely data-driven statistical modeling techniques, our semi-quantitative approach is capable to introduce expert knowledge into the analysis, which is indispensable considering quality and resolution of the input data, and incompleteness and bias in the inventory information. The reliability of the resulting susceptibility map ELSUS 1000 Version 1 (1 km resolution) was examined on an administrative terrain unit level in areas with landslide information and through the comparison with available national susceptibility zonations. These evaluations suggest that although the ELSUS 1000 is capable for a correct synoptic prediction of landslide susceptibility in the majority of the area, it needs further improvement in terms of data used.

Mapping and modeling the urban landscape in Bangkok, Thailand: Physical-spectral-spatial relations of population-environmental interactions

NASA Astrophysics Data System (ADS)

Shao, Yang

This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants' settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants' spatial clustering in urban space is associated with the source village and a number of socio-demographic variables. In addition, the migrants' neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent.

Mapping Fuel Loads and Dynamics in Rangelands Using Multi-Sensor Data in the Great Basin, USA

NASA Astrophysics Data System (ADS)

Li, Z.; Shi, H.; Vogelmann, J. E.; Hawbaker, T. J.; Reeves, M. C.

2016-12-01

Fuel conditions in rangelands are influenced by disturbances such as wildfires, and is also strongly controlled by weather and climate. These factors impact the availability of fuel loads, which is the key component to stimulate burned area and severity. In this paper, we developed an approach for mapping live fuel loads (biomass density) and their dynamics using field collection, Landsat 8, and MODIS data sets at a spatial resolution of 30 m from the growing season. Using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) modelling process, we generated monthly shrub and grassland greenness levels for 2015. The spatial resolution of Landsat and the temporal resolution of MODIS complimented each other to allow us to produce monthly products. Understanding the dynamics of these greenness patterns helps the fire management community to recognize areas that have high likelihood of burning in the future, thus enabling them to anticipate and plan accordingly. We obtained field biomass information from selected shrub and grass sites located throughout the Great Basin. This information was used to calibrate fire models and generate remotely-sensed data sets. We then used Landsat 8 NDVI dates representing the phenological profile, regression tree models, and product validation. The calculated fuel loads were further examined and validated using high resolution images (World View 2/3), field measurements, and Google Earth. Once we have the requisite image data converted to biomass, we anticipate fire conditions and behavior using various models developed by the fire community. One key element is to use information from this study to improve and inform the Rangeland Vegetation Simulator. Finally, we analyzed the correlations of fire occurrence (frequency) and burn severity with live fuel loads and climate conditions. Our results show modeled fuel loads and their dynamics in rangelands capture the spatiotemporal heterogeneity of non-forest live fuel types and the variations in both wildfire disturbances and climate/weather conditions. This suggests the developed approach to map fuel loads is robust and can improve the existing LANDFIRE fuel data in rangelands. It can also be used to monitor the changes in fuel conditions in response to management activities and climate change.

Challenges of Remote Sensing and Spatial Information Education and Technology Transfer in a Fast Developing Industry

NASA Astrophysics Data System (ADS)

Tsai, F.; Chen, L.-C.

2014-04-01

During the past decade, Taiwan has experienced an unusual and fast growing in the industry of mapping, remote sensing, spatial information and related markets. A successful space program and dozens of advanced airborne and ground-based remote sensing instruments as well as mobile mapping systems have been implemented and put into operation to support the vast demands of geospatial data acquisition. Moreover, in addition to the government agencies and research institutes, there are also tens of companies in the private sector providing geo-spatial data and services. However, the fast developing industry is also posing a great challenge to the education sector in Taiwan, especially the higher education for geo-spatial information. Facing this fast developing industry, the demands of skilled professionals and new technologies in order to address diversified needs are indubitably high. Consequently, while delighting in the expanding and prospering benefitted from the fast growing industry, how to fulfill these demands has become a challenge for the remote sensing and spatial information disciplines in the higher education institutes in Taiwan. This paper provides a brief insight into the status of the remote sensing and spatial information industry in Taiwan as well as the challenges of the education and technology transfer to support the increasing demands and to ensure the continuous development of the industry. In addition to the report of the current status of the remote sensing and spatial information related courses and programs in the colleges and universities, current and potential threatening issues and possible resolutions are also discussed in different points of view.

Development of a portable wireless system for bipolar concentric ECG recording

NASA Astrophysics Data System (ADS)

Prats-Boluda, G.; Ye-Lin, Y.; Bueno Barrachina, J. M.; Senent, E.; Rodriguez de Sanabria, R.; Garcia-Casado, J.

2015-07-01

Cardiovascular diseases (CVDs) remain the biggest cause of deaths worldwide. ECG monitoring is a key tool for early diagnosis of CVDs. Conventional monitors use monopolar electrodes resulting in poor spatial resolution surface recordings and requiring extensive wiring. High-spatial resolution surface electrocardiographic recordings provide valuable information for the diagnosis of a wide range of cardiac abnormalities, including infarction and arrhythmia. The aim of this work was to develop and test a wireless recording system for acquiring high spatial resolution ECG signals, based on a flexible tripolar concentric electrode (TCE) without cable wiring or external reference electrode which would make more comnfortable its use in clinical practice. For this, a portable, wireless sensor node for analogue conditioning, digitalization and transmission of a bipolar concentric ECG signal (BC-ECG) using a TCE and a Mason-likar Lead-I ECG (ML-Lead-I ECG) signal was developed. Experimental results from a total of 32 healthy volunteers showed that the ECG fiducial points in the BC-ECG signals, recorded with external and internal reference electrode, are consistent with those of simultaneous ML-Lead-I ECG. No statistically significant difference was found in either signal amplitude or morphology, regardless of the reference electrode used, being the signal-to-noise similar to that of ML-Lead-I ECG. Furthermore, it has been observed that BC-ECG signals contain information that could not available in conventional records, specially related to atria activity. The proposed wireless sensor node provides non-invasive high-local resolution ECG signals using only a TCE without additional wiring, which would have great potential in medical diagnosis of diseases such as atrial or ventricular fibrillations or arrhythmias that currently require invasive diagnostic procedures (catheterization).

Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2016-04-01

The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

imVisIR - a new tool for high resolution soil characterisation

NASA Astrophysics Data System (ADS)

Steffens, Markus; Buddenbaum, Henning

2014-05-01

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

Concentration Measurements in Self-Excited Momentum Dominated Low-Density Gas Jets

NASA Technical Reports Server (NTRS)

Yildirim, B. S.; Pasumarthi, K. S.; Agrawal, A. K.

2004-01-01

Flow structure of self-excited, laminar, axisymmetric, momentum-dominated helium jets discharged vertically into ambient air was investigated using high-speed rainbow schlieren deflectometry technique. Measurements were obtained at temporal resolution of 1 ms and spatial resolution of 0.19 mm for two test cases with Richardson number of 0.034 and 0.018. Power spectra revealed that the oscillation frequency was independent of spatial coordinates, suggesting global oscillations in the flow. Abel inversion algorithm was used to reconstruct the concentration field of helium. Instantaneous concentration contours revealed changes in the flow field and evolution of vortical structures during an oscillation cycle. Temporal evolution plots of helium concentration at different axial locations provided detailed information about the instability in the flow field.

AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Mladenova, I. E.; Narayan, U.

2009-12-01

Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

SU-F-J-189: A Method to Improve the Spatial Resolution of Prompt Gamma Based Compton Imaging for Proton Range Verification

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

Draeger, E; Chen, H; Polf, J

Purpose: To test two new techniques, the distance-of-closest approach (DCA) and Compton line (CL) filters, developed as a means of improving the spatial resolution of Compton camera (CC) imaging. Methods: Gammas emitted from {sup 22}Na, {sup 137}Cs, and {sup 60}Co point sources were measured with a prototype 3-stage CC. The energy deposited and position of each interaction in each stage were recorded and used to calculate a “cone-of-origin” for each gamma that scattered twice in the CC. A DCA filter was developed which finds the shortest distance from the gamma’s cone-of-origin surface to the location of the gamma source. Themore » DCA filter was applied to the data to determine the initial energy of the gamma and to remove “bad” interactions that only contribute noise to the image. Additionally, a CL filter, which removes gamma events that do not follow the theoretical predictions of the Compton scatter equation, was used to further remove “bad” interactions from the measured data. Then images were reconstructed with raw, unfiltered data, DCA filtered data, and DCA+CL filtered data and the achievable image resolution of each dataset was compared. Results: Spatial resolutions of ∼2 mm, and better than 2 mm, were achievable with the DCA and DCA+CL filtered data, respectively, compared to > 5 mm for the raw, unfiltered data. Conclusion: In many special cases in medical imaging where information about the source position may be known, such as proton radiotherapy range verification, the application of the DCA and CL filters can result in considerable improvements in the achievable spatial resolutions of Compton imaging.« less

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

Remote sensing of potential lunar resources. 2: High spatial resolution mapping of spectral reflectance ratios and implications for nearside mare TiO2 content`

NASA Technical Reports Server (NTRS)

Melendrez, David E.; Johnson, Jeffrey R.; Larson, Stephen M.; Singer, Robert B.

1994-01-01

High spatial resolution maps illustrating variations in spectral reflectance 400/560 nm ratio values have been generated for the following mare regions: (1) the border between southern Mare Serenitatis and northern Mare Tranquillitatis (including the MS-2 standard area and Apollo 17 landing site), (2) central Mare Tranquillitatis, (3) Oceanus Procellarum near Seleucus, and (4) southern Oceanus Procellarum and Flamsteed. We have also obtained 320-1000 nm reflectance spectra of several sites relative to MS-2 to facilitate scaling of the images and provide additional information on surface composition. Inferred TiO2 abundances for these mare regions have been determined using an empirical calibration which relates the weight percent TiO2 in mature mare regolith to the observed 400/560 nm ratio. Mare areas with high TiO2 abundances are probably rich in ilmenite (FeTiO3) a potential lunar resource. The highest potential TiO2 concentrations we have identified in the nearside maria occur in central Mare Tranquillitatis. Inferred TiO2 contents for these areas are greater than 9 wt% and are spatially consistent with the highest-TiO2 regions mapped previously at lower spatial resolution. We note that the morphology of surface units with high 400/560 nm ratio values increases in complexity at higher spatial resolutions. Comparisons have been made with previously published geologic maps, Lunar Orbiter IV, and ground-based images, and some possible morphologic correlatins have been found between our mapped 400/560 nm ratio values and volcanic landforms such as lava flows, mare domes, and collapse pits.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Towards improved hydrologic predictions using data assimilation techniques for water resource management at the continental scale

NASA Astrophysics Data System (ADS)

Naz, Bibi; Kurtz, Wolfgang; Kollet, Stefan; Hendricks Franssen, Harrie-Jan; Sharples, Wendy; Görgen, Klaus; Keune, Jessica; Kulkarni, Ketan

2017-04-01

More accurate and reliable hydrologic simulations are important for many applications such as water resource management, future water availability projections and predictions of extreme events. However, simulation of spatial and temporal variations in the critical water budget components such as precipitation, snow, evaporation and runoff is highly uncertain, due to errors in e.g. model structure and inputs (hydrologic parameters and forcings). In this study, we use data assimilation techniques to improve the predictability of continental-scale water fluxes using in-situ measurements along with remotely sensed information to improve hydrologic predications for water resource systems. The Community Land Model, version 3.5 (CLM) integrated with the Parallel Data Assimilation Framework (PDAF) was implemented at spatial resolution of 1/36 degree (3 km) over the European CORDEX domain. The modeling system was forced with a high-resolution reanalysis system COSMO-REA6 from Hans-Ertel Centre for Weather Research (HErZ) and ERA-Interim datasets for time period of 1994-2014. A series of data assimilation experiments were conducted to assess the efficiency of assimilation of various observations, such as river discharge data, remotely sensed soil moisture, terrestrial water storage and snow measurements into the CLM-PDAF at regional to continental scales. This setup not only allows to quantify uncertainties, but also improves streamflow predictions by updating simultaneously model states and parameters utilizing observational information. The results from different regions, watershed sizes, spatial resolutions and timescales are compared and discussed in this study.

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

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

PubMed

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Dinh Duong, Nguyen; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity. PMID:24465714

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

PubMed

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

2014-07-01

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

Combining Remote Sensing imagery of both fine and coarse spatial resolution to Estimate Crop Evapotranspiration and quantifying its Influence on Crop Growth Monitoring.

NASA Astrophysics Data System (ADS)

Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio; Duveiller, Gregory; Piccard, Isabelle; de Wit, Allard; Tychon, Bernard; Bakary, Djaby; Defourny, Pierre

2010-05-01

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. Evapotranspiration (ET) is a valuable parameter in the crop monitoring context since it provides information on the plant water stress status, which strongly influences crop development and, by extension, crop yield. To assess crop evapotranspiration over the GLOBAM study areas (300x300 km sites in Northern Europe and Central Ethiopia), a Soil-Vegetation-Atmosphere Transfer (SVAT) model forced with remote sensing and numerical weather prediction data has been used. This model runs at pre-operational level in the framework of the EUMETSAT LSA-SAF (Land Surface Analysis Satellite Application Facility) using SEVIRI and ECMWF data, as well as the ECOCLIMAP database to characterize the vegetation. The model generates ET images at the Meteosat Second Generation (MSG) spatial resolution (3 km at subsatellite point),with a temporal resolution of 30 min and monitors the entire MSG disk which covers Europe, Africa and part of Sud America . The SVAT model was run for 2007 using two approaches. The first approach is at the standard pre-operational mode. The second incorporates remote sensing information at various spatial resolutions going from LANDSAT (30m) to SEVIRI (3-5 km) passing by AWIFS (56m) and MODIS (250m). Fine spatial resolution data consists of crop type classification which enable to identify areas where pure crop specific MODIS time series can be compiled and used to derive Leaf Area Index estimations for the most important crops (wheat and maize). The use of this information allowed to characterize the type of vegetation and its state of development in a more accurate way than using the ECOCLIMAP database. Finally, the CASA method was applied using the evapotranspiration images with FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) images from LSA-SAF to obtain Dry Matter Productivity (DMP) and crop yield. The potential of using evapotranspiration obtained from remote sensing in crop growth modeling is studied and discussed. Results of comparing the evapotranspiration obtained with ground truth data are shown as well as the influence of using high resolution information to characterize the vegetation in the evapotranspiration estimation. The values of DMP and yield obtained with the CASA method are compared with those obtained using crop growth modeling and field data, showing the potential of using this simplified remote sensing method for crop monitoring and yield forecasting. This methodology could be applied in an operative way to the entire MSG disk, allowing the continuous crop growth monitoring.

Landsat multispectral sharpening using a sensor system model and panchromatic image

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2003-01-01

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

Multisensor multiresolution data fusion for improvement in classification

NASA Astrophysics Data System (ADS)

Rubeena, V.; Tiwari, K. C.

2016-04-01

The rapid advancements in technology have facilitated easy availability of multisensor and multiresolution remote sensing data. Multisensor, multiresolution data contain complementary information and fusion of such data may result in application dependent significant information which may otherwise remain trapped within. The present work aims at improving classification by fusing features of coarse resolution hyperspectral (1 m) LWIR and fine resolution (20 cm) RGB data. The classification map comprises of eight classes. The class names are Road, Trees, Red Roof, Grey Roof, Concrete Roof, Vegetation, bare Soil and Unclassified. The processing methodology for hyperspectral LWIR data comprises of dimensionality reduction, resampling of data by interpolation technique for registering the two images at same spatial resolution, extraction of the spatial features to improve classification accuracy. In the case of fine resolution RGB data, the vegetation index is computed for classifying the vegetation class and the morphological building index is calculated for buildings. In order to extract the textural features, occurrence and co-occurence statistics is considered and the features will be extracted from all the three bands of RGB data. After extracting the features, Support Vector Machine (SVMs) has been used for training and classification. To increase the classification accuracy, post processing steps like removal of any spurious noise such as salt and pepper noise is done which is followed by filtering process by majority voting within the objects for better object classification.

It's time for a crisper image of the Face of the Earth: Landsat and climate time series for massive land cover & climate change mapping at detailed resolution.

NASA Astrophysics Data System (ADS)

Pons, Xavier; Miquel, Ninyerola; Oscar, González-Guerrero; Cristina, Cea; Pere, Serra; Alaitz, Zabala; Lluís, Pesquer; Ivette, Serral; Joan, Masó; Cristina, Domingo; Maria, Serra Josep; Jordi, Cristóbal; Chris, Hain; Martha, Anderson; Juanjo, Vidal

2014-05-01

Combining climate dynamics and land cover at a relative coarse resolution allows a very interesting approach to global studies, because in many cases these studies are based on a quite high temporal resolution, but they may be limited in large areas like the Mediterranean. However, the current availability of long time series of Landsat imagery and spatially detailed surface climate models allow thinking on global databases improving the results of mapping in areas with a complex history of landscape dynamics, characterized by fragmentation, or areas where relief creates intricate climate patterns that can be hardly monitored or modeled at coarse spatial resolutions. DinaCliVe (supported by the Spanish Government and ERDF, and by the Catalan Government, under grants CGL2012-33927 and SGR2009-1511) is the name of the project that aims analyzing land cover and land use dynamics as well as vegetation stress, with a particular emphasis on droughts, and the role that climate variation may have had in such phenomena. To meet this objective is proposed to design a massive database from long time series of Landsat land cover products (grouped in quinquennia) and monthly climate records (in situ climate data) for the Iberian Peninsula (582,000 km2). The whole area encompasses 47 Landsat WRS2 scenes (Landsat 4 to 8 missions, from path 197 to 202 and from rows 30 to 34), and 52 Landsat WRS1 scenes (for the previous Landsat missions, 212 to 221 and 30 to 34). Therefore, a mean of 49.5 Landsat scenes, 8 quinquennia per scene and a about 6 dates per quinquennium , from 1975 to present, produces around 2376 sets resulting in 30 m x 30 m spatial resolution maps. Each set is composed by highly coherent geometric and radiometric multispectral and multitemporal (to account for phenology) imagery as well as vegetation and wetness indexes, and several derived topographic information (about 10 Tbyte of data). Furthermore, on the basis on a previous work: the Digital Climatic Atlas of the Iberian Peninsula, spatio-temporal surface climate data has been generated with a monthly resolution (from January 1950 to December 2010) through a multiple regression model and residuals spatial interpolation using geographic variables (altitude, latitude and continentality) and solar radiation (only in the case of temperatures). This database includes precipitation, mean minimum and mean maximum air temperature and mean air temperature, improving the previous one by using the ASTER GDEM at 30 m spatial resolution, by deepening to a monthly resolution and by increasing the number of meteorological stations used, representing a total amount of 0.7 Tbyte of data. An initial validation shows accuracies higher than 85 % for land cover maps and an RMS of 1.2 ºC, 1.6 ºC and 22 mm for mean and extreme temperatures, and for precipitation, respectively. This amount of new detailed data for the Iberian Peninsula framework will be used to study the spatial direction, velocity and acceleration of the tendencies related to climate change, land cover and tree line dynamics. A global analysis using all these datasets will try to discriminate the climatic signal when interpreted together with anthropogenic driving forces. Ultimately, getting ready for massive database computation and analysis will improve predictions for global models that will require of the growing high-resolution information available.

Acoustic Observation of Living Organisms Reveals the Upper Limit of the Oxygen Minimum Zone

PubMed Central

Bertrand, Arnaud; Ballón, Michael; Chaigneau, Alexis

2010-01-01

Background Oxygen minimum zones (OMZs) are expanding in the World Ocean as a result of climate change and direct anthropogenic influence. OMZ expansion greatly affects biogeochemical processes and marine life, especially by constraining the vertical habitat of most marine organisms. Currently, monitoring the variability of the upper limit of the OMZs relies on time intensive sampling protocols, causing poor spatial resolution. Methodology/Principal Findings Using routine underwater acoustic observations of the vertical distribution of marine organisms, we propose a new method that allows determination of the upper limit of the OMZ with a high precision. Applied in the eastern South-Pacific, this original sampling technique provides high-resolution information on the depth of the upper OMZ allowing documentation of mesoscale and submesoscale features (e.g., eddies and filaments) that structure the upper ocean and the marine ecosystems. We also use this information to estimate the habitable volume for the world's most exploited fish, the Peruvian anchovy (Engraulis ringens). Conclusions/Significance This opportunistic method could be implemented on any vessel geared with multi-frequency echosounders to perform comprehensive high-resolution monitoring of the upper limit of the OMZ. Our approach is a novel way of studying the impact of physical processes on marine life and extracting valid information about the pelagic habitat and its spatial structure, a crucial aspect of Ecosystem-based Fisheries Management in the current context of climate change. PMID:20442791

Imaging MS Methodology for More Chemical Information in Less Data Acquisition Time Utilizing a Hybrid Linear Ion Trap-Orbitrap Mass Spectrometer

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

Perdian, D. C.; Lee, Young Jin

2010-11-15

A novel mass spectrometric imaging method is developed to reduce the data acquisition time and provide rich chemical information using a hybrid linear ion trap-orbitrap mass spectrometer. In this method, the linear ion trap and orbitrap are used in tandem to reduce the acquisition time by incorporating multiple linear ion trap scans during an orbitrap scan utilizing a spiral raster step plate movement. The data acquisition time was decreased by 43-49% in the current experiment compared to that of orbitrap-only scans; however, 75% or more time could be saved for higher mass resolution and with a higher repetition rate laser.more » Using this approach, a high spatial resolution of 10 {micro}m was maintained at ion trap imaging, while orbitrap spectra were acquired at a lower spatial resolution, 20-40 {micro}m, all with far less data acquisition time. Furthermore, various MS imaging methods were developed by interspersing MS/MS and MSn ion trap scans during orbitrap scans to provide more analytical information on the sample. This method was applied to differentiate and localize structural isomers of several flavonol glycosides from an Arabidopsis flower petal in which MS/MS, MSn, ion trap, and orbitrap images were all acquired in a single data acquisition.« less

The Early Detection of the Emerald Ash Borer (eab) Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Hu, B.; Naveed, F.; Tasneem, F.; Xing, C.

2018-04-01

The objectives of this study were to exploit the synergy of hyperspectral imagery, Light Detection And Ranging (LiDAR) and high spatial resolution data and their synergy in the early detection of the EAB (Emerald Ash Borer) presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, an advanced individual tree delineation method was developed to delineate individual trees using the combined high-spatial resolution worldview-3 imagery was used together with LiDAR data. Individual trees were then classified to ash and non-ash trees using spectral and spatial information. In order to characterize the health state of individual ash trees, leaves from ash trees with various health states were sampled and measured using a field spectrometer. Based on the field measurements, the best indices that sensitive to leaf chlorophyll content were selected. The developed framework and methods were tested using worldview-3, airborne LiDAR data over the Keele campus of York University Toronto Canada. Satisfactory results in terms of individual tree crown delineation, ash tree identification and characterization of the health state of individual ash trees. Quantitative evaluations is being carried out.

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

PubMed Central

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

2017-01-01

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

Assessing population exposure for landslide risk analysis using dasymetric cartography

NASA Astrophysics Data System (ADS)

Garcia, Ricardo A. C.; Oliveira, Sérgio C.; Zêzere, José L.

2016-12-01

Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost-benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

NASA Technical Reports Server (NTRS)

Baumgardner, Marion F.

1995-01-01

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

Spatial resolution enhancement of satellite image data using fusion approach

NASA Astrophysics Data System (ADS)

Lestiana, H.; Sukristiyanti

2018-02-01

Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

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.

Comparing long-term geomorphic model outcomes with sediment archives highlights the need for high-resolution Holocene land cover reconstructions

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert

2013-04-01

During the last decade, several global land cover reconstructions have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models potentially allows to estimate the anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, current land cover reconstructions face some drawbacks. First of all, their low spatial resolution (i.e. 5 arc-minutes at best) questions their use in geomorphic models, as sub-catchment vegetation patterns play an important role in sediment dynamics. Existing global land cover reconstructions also do not differentiate the typology of human impact (cropland, grazing land, disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. Finally, the various land cover reconstructions differ significantly regarding the estimated intensity of human impact for the preindustrial period. In this study, we assessed the performance of a spatially distributed erosion and sediment redistribution model that operates at high resolution (100 m) to the quality and spatial resolution of input land cover maps. This was done through a comparison of two sets of model runs. Firstly, low-resolution land cover (expressed as percentage of non-natural vegetation) maps were resampled to a spatial resolution of 100 m without differentiation of non-natural vegetation types. For the second set of model runs, estimated non-natural vegetation was differentiated in areas of cropland and grassland, and spatially allocated to a high-resolution grid (100 m) using a logistic model that relates contemporary land cover classes to slope, soil characteristics, landforms and distance to rivers. For both land cover maps, different scenarios for the ratio between cropland and grassland were simulated. Analyses were performed for several time periods throughout the Holocene, for the Scheldt River Basin (19,000 km2) in Belgium and northern France. Results indicate that low-resolution land cover information, regardless of the considered cropland/grassland ratio, leads to largely overestimated sediment fluxes when compared to field-based sediment budgets. Allocation of land cover to a higher spatial resolution yields far better results. Variations in model outcomes are related to differences in landscape connectivity between allocated and non-allocated land cover. These results point towards the need for higher-resolution land cover maps that incorporate the patchiness of vegetation at relevant scales regarding geomorphic processes. Also, model results with allocated and non-allocated land cover maps differ greatly for different cropland/grassland ratios. This indicates that there is not only a need for land cover reconstructions at high spatial resolution, but also that differentiation between cropland and grassland is essential for accurate geomorphic modeling. Further improvements in land cover reconstructions are thus needed before reliable quantitative estimates of anthropogenic impact on soil profiles and sediment redistribution can be simulated at continental scales. Detailed historic sediment budgets can provide an important tool not only for validating but also for reconstructing land cover histories.

Ultrahigh resolution photographic films for X-ray/EUV/FUV astronomy

NASA Technical Reports Server (NTRS)

Hoover, Richard B.; Walker, Arthur B. C., Jr.; Deforest, Craig E.; Watts, Richard; Tarrio, Charles

1993-01-01

The quest for ultrahigh resolution full-disk images of the sun at soft X-ray/EUV/FUV wavelengths has increased the demand for photographic films with broad spectral sensitivity, high spatial resolution, and wide dynamic range. These requirements were made more stringent by the recent development of multilayer telescopes and coronagraphs capable of operating at normal incidence at soft X-ray/EUV wavelengths. Photographic films are the only detectors now available with the information storage capacity and dynamic range such as is required for recording images of the solar disk and corona simultaneously with sub arc second spatial resolution. During the Stanford/MSFC/LLNL Rocket X-Ray Spectroheliograph and Multi-Spectral Solar Telescope Array (MSSTA) programs, we utilized photographic films to obtain high resolution full-disk images of the sun at selected soft X-ray/EUV/FUV wavelengths. In order to calibrate our instrumentation for quantitative analysis of our solar data and to select the best emulsions and processing conditions for the MSSTA reflight, we recently tested several photographic films. These studies were carried out at the NIST SURF II synchrotron and the Stanford Synchrotron Radiation Laboratory. In this paper, we provide the results of those investigations.

Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015

PubMed Central

Ambika, Anukesh Krishnankutty; Wardlow, Brian; Mishra, Vimal

2016-01-01

India is among the countries that uses a significant fraction of available water for irrigation. Irrigated area in India has increased substantially after the Green revolution and both surface and groundwater have been extensively used. Under warming climate projections, irrigation frequency may increase leading to increased irrigation water demands. Water resources planning and management in agriculture need spatially-explicit irrigated area information for different crops and different crop growing seasons. However, annual, high-resolution irrigated area maps for India for an extended historical record that can be used for water resources planning and management are unavailable. Using 250 m normalized difference vegetation index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and 56 m land use/land cover data, high-resolution irrigated area maps are developed for all the agroecological zones in India for the period of 2000–2015. The irrigated area maps were evaluated using the agricultural statistics data from ground surveys and were compared with the previously developed irrigation maps. High resolution (250 m) irrigated area maps showed satisfactory accuracy (R2=0.95) and can be used to understand interannual variability in irrigated area at various spatial scales. PMID:27996974

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.

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

USGS Publications Warehouse

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

2012-01-01

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

Resolution of VTI anisotropy with elastic full-waveform inversion: theory and basic numerical examples

NASA Astrophysics Data System (ADS)

Podgornova, O.; Leaney, S.; Liang, L.

2018-07-01

Extracting medium properties from seismic data faces some limitations due to the finite frequency content of the data and restricted spatial positions of the sources and receivers. Some distributions of the medium properties make low impact on the data (including none). If these properties are used as the inversion parameters, then the inverse problem becomes overparametrized, leading to ambiguous results. We present an analysis of multiparameter resolution for the linearized inverse problem in the framework of elastic full-waveform inversion. We show that the spatial and multiparameter sensitivities are intertwined and non-sensitive properties are spatial distributions of some non-trivial combinations of the conventional elastic parameters. The analysis accounts for the Hessian information and frequency content of the data; it is semi-analytical (in some scenarios analytical), easy to interpret and enhances results of the widely used radiation pattern analysis. Single-type scattering is shown to have limited sensitivity, even for full-aperture data. Finite-frequency data lose multiparameter sensitivity at smooth and fine spatial scales. Also, we establish ways to quantify a spatial-multiparameter coupling and demonstrate that the theoretical predictions agree well with the numerical results.

Probing the Complexities of Structural Changes in Layered Oxide Cathode Materials for Li-Ion Batteries during Fast Charge-Discharge Cycling and Heating.

PubMed

Hu, Enyuan; Wang, Xuelong; Yu, Xiqian; Yang, Xiao-Qing

2018-02-20

The rechargeable lithium-ion battery (LIB) is the most promising energy storage system to power electric vehicles with high energy density and long cycling life. However, in order to meet customers' demands for fast charging, the power performances of current LIBs need to be improved. From the cathode aspect, layer-structured cathode materials are widely used in today's market and will continue to play important roles in the near future. The high rate capability of layered cathode materials during charging and discharging is critical to the power performance of the whole cell and the thermal stability is closely related to the safety issues. Therefore, the in-depth understanding of structural changes of layered cathode materials during high rate charging/discharging and the thermal stability during heating are essential in developing new materials and improving current materials. Since structural changes take place from the atomic level to the whole electrode level, combination of characterization techniques covering multilength scales is quite important. In many cases, this means using comprehensive tools involving diffraction, spectroscopy, and imaging to differentiate the surface from the bulk and to obtain structural/chemical information with different levels of spatial resolution. For example, hard X-ray spectroscopy can yield the bulk information and soft X-ray spectroscopy can give the surface information; X-ray based imaging techniques can obtain spatial resolution of tens of nanometers, and electron-based microcopy can go to angstroms. In addition to challenges associated with different spatial resolution, the dynamic nature of structural changes during high rate cycling and heating requires characterization tools to have the capability of collecting high quality data in a time-resolved fashion. Thanks to the advancement in synchrotron based techniques and high-resolution electron microscopy, high temporal and spatial resolutions can now be achieved. In this Account, we focus on the recent works studying kinetic and thermal properties of layer-structured cathode materials, especially the structural changes during high rate cycling and the thermal stability during heating. Advanced characterization techniques relating to the rate capability and thermal stability will be introduced. The different structure evolution behavior of cathode materials cycled at high rate will be compared with that cycled at low rate. Different response of individual transition metals and the inhomogeneity in chemical distribution will be discussed. For the thermal stability, the relationship between structural changes and oxygen release will be emphatically pointed out. In all these studies being reviewed, advanced characterization techniques are critically applied to reveal complexities at multiscale in layer-structured cathode materials.

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

Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

NASA Astrophysics Data System (ADS)

Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

2016-06-01

There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

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

Future Perspective and Long-Term Strategy of the Indian EO Programme

NASA Astrophysics Data System (ADS)

Rao, Mukund; Jayaraman, V.; Sridhara Murthi, K. R.; Kasturirangan, K.

EO technology development will continue to have profound effects on spatial information activities, as we are seeing it today - the changing demand of GIS technology to understanding processes around us and its representation as maps. In the longer term, information needs will drive further RS and GIS technological developments - creating stringent demands for technology solutions for spatial data capture, integration and representation. The emergence of Spatial Business from the highly volatile and dynamic synergy of information, technology and access will see a truly Spatial Society. EO will have a major impact on day-to-day life of nations, communities and even an individual. It will become the One-stop source for information - spatial information at that - thus enabling not only development oriented activities but also Business GIS, quality research and Info-savvy communities. Internationally, there will be a mix of Government and Commercial satellites vying to provide information services to a wide variety of users. EO satellites are also becoming smaller, efficient and less costlier. Almost 5-6 commercial systems will orbit around the Earth in the foreseeable future to generate massive, seamless archives of high-resolution panchromatic and multispectral images - almost reducing the need for aerial surveys for photography and mapping. Reaching resolution of cm level and covering narrower and more spectral bands, the trend is to IMAGE the Earth in its entirety and organize Image Infrastructures. The race will be to imaginatively capture the market with the fullest archive of the globe and cater to any imaging demand of users. One will also see efficient satellite operations that will enable imaging any part of the globe with minimum turn-around time - reaching concepts of IMAGING ON DEMAND. The need of the hour is looking forward now towards how the EO technology can adapt itself to the changing scenario and the steps to be taken to sustain use of EO data it in the future. The continuity of the EO services in India is the fundamental requirement for sustenance and further development of the technology and its utilisation, the stage is now set for transitioning the EO technology by initiating policy adjustments for the commercial use of space-based EO. Orientation needs to change from a "facility concept", which was the adage for the "promotional" era, to "Services concept" for the RS technology. The orientation also needs to change from RS data to Spatial Information and GIS databases. Demand for information would increase with a larger involvement of players in the developmental activities and catering to the information needs is what would be the driver for the commercial development. To that extent, the commercial development of Spatial Information needs to be thrusted forward and RS technology will be the back-bone for this information services initiative, because EO has the capability to provide accurate and timely information at large-scales in a repeated manner which is directly amenable to GIS manipulation. The thrust has to be towards developing an independent sector for Spatial Information with the active involvement of users, private entrepreneurs and other agencies to develop space-based RS market segments. This paper discusses the policy adjustments that will be required to be done for developing a viable and effective commercial EO programme in the country with a major thrust of initial government and industry partnership ultimately leading to a true industry sector for Spatial Information services.

Integral imaging with Fourier-plane recording

NASA Astrophysics Data System (ADS)

Martínez-Corral, M.; Barreiro, J. C.; Llavador, A.; Sánchez-Ortiga, E.; Sola-Pikabea, J.; Scrofani, G.; Saavedra, G.

2017-05-01

Integral Imaging is well known for its capability of recording both the spatial and the angular information of threedimensional (3D) scenes. Based on such an idea, the plenoptic concept has been developed in the past two decades, and therefore a new camera has been designed with the capacity of capturing the spatial-angular information with a single sensor and after a single shot. However, the classical plenoptic design presents two drawbacks, one is the oblique recording made by external microlenses. Other is loss of information due to diffraction effects. In this contribution report a change in the paradigm and propose the combination of telecentric architecture and Fourier-plane recording. This new capture geometry permits substantial improvements in resolution, depth of field and computation time

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.

Soil process-oriented modelling of within-field variability based on high-resolution 3D soil type distribution maps.

NASA Astrophysics Data System (ADS)

Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe

2016-04-01

Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon (SOC), as essential input variable, was predicted by measured soil samples and associated to STD of the upper 30 cm. The comprehensive and high-resolution (4x4 m) soil profile information (up to 2 m soil depth) were then used to initialise a soil process model (Carbon and Nitrogen Dynamics - CANDY) for soil functional modelling (daily steps of matter fluxes, soil temperature and water balances). Our study was conducted on a practical field (~32,000 m²) of an agricultural farm in Central Germany with Chernozem soils under arid conditions (average rainfall < 550 mm). This soil region is known to have differences in soil structure mainly occurring within the subsoil, since topsoil conditions are described as homogenous. The modelled soil functions considered local climate information and practical farming activities. Results show, as expected, distinguished functional variability, both on spatial and temporal resolution for subsoil evident structures, e.g. visible differences for available water capacity within 0-100 cm but homogenous conditions for the topsoil.

An integrated approach for updating cadastral maps in Pakistan using satellite remote sensing data

NASA Astrophysics Data System (ADS)

Ali, Zahir; Tuladhar, Arbind; Zevenbergen, Jaap

2012-08-01

Updating cadastral information is crucial for recording land ownership and property division changes in a timely fashioned manner. In most cases, the existing cadastral maps do not provide up-to-date information on land parcel boundaries. Such a situation demands that all the cadastral data and parcel boundaries information in these maps to be updated in a timely fashion. The existing techniques for acquiring cadastral information are discipline-oriented based on different disciplines such as geodesy, surveying, and photogrammetry. All these techniques require a large number of manpower, time, and cost when they are carried out separately. There is a need to integrate these techniques for acquiring cadastral information to update the existing cadastral data and (re)produce cadastral maps in an efficient manner. To reduce the time and cost involved in cadastral data acquisition, this study develops an integrated approach by integrating global position system (GPS) data, remote sensing (RS) imagery, and existing cadastral maps. For this purpose, the panchromatic image with 0.6 m spatial resolution and the corresponding multi-spectral image with 2.4 m spatial resolution and 3 spectral bands from QuickBird satellite were used. A digital elevation model (DEM) was extracted from SPOT-5 stereopairs and some ground control points (GCPs) were also used for ortho-rectifying the QuickBird images. After ortho-rectifying these images and registering the multi-spectral image to the panchromatic image, fusion between them was attained to get good quality multi-spectral images of these two study areas with 0.6 m spatial resolution. Cadastral parcel boundaries were then identified on QuickBird images of the two study areas via visual interpretation using participatory-GIS (PGIS) technique. The regions of study are the urban and rural areas of Peshawar and Swabi districts in the Khyber Pakhtunkhwa province of Pakistan. The results are the creation of updated cadastral maps with a lot of cadastral information which can be used in updating the existing cadastral data with less time and cost.

SYMPOSIUM ON MULTIMODALITY CARDIOVASCULAR MOLECULAR IMAGING IMAGING TECHNOLOGY - PART 2

PubMed Central

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

2013-01-01

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

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM2-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2003-02-28] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_TRMM-PFM-VIRS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2003-02-28] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM1-MODIS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2D)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2004-05-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

2014-10-01

Giant reed is an aggressive invasive plant of riparian ecosystems in many sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometric similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phenological variability of the invader. We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77%) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2 m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric traits, at leaf, canopy and stand level, which makes the OBIA approach a very suitable technique for management purposes.

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

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

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

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

An Integrated Retrieval Framework for AMSR2: Implications for Light Precipitation and Sea Ice Edge Detectability

NASA Astrophysics Data System (ADS)

Duncan, D.; Kummerow, C. D.; Meier, W.

2016-12-01

Over the lifetime of AMSR-E, operational retrieval algorithms were developed and run for precipitation, ocean suite (SST, wind speed, cloud liquid water path, and column water vapor over ocean), sea ice, snow water equivalent, and soil moisture. With a separate algorithm for each group, the retrievals were never interactive or integrated in any way despite many co-sensitivities. AMSR2, the follow-on mission to AMSR-E, retrieves the same parameters at a slightly higher spatial resolution. We have combined the operational algorithms for AMSR2 in a way that facilitates sharing information between the retrievals. Difficulties that arose were mainly related to calibration, spatial resolution, coastlines, and order of processing. The integration of all algorithms for AMSR2 has numerous benefits, including better detection of light precipitation and sea ice, fewer screened out pixels, and better quality flags. Integrating the algorithms opens up avenues for investigating the limits of detectability for precipitation from a passive microwave radiometer and the impact of spatial resolution on sea ice edge detection; these are investigated using CloudSat and MODIS coincident observations from the A-Train constellation.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

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

NASA Technical Reports Server (NTRS)

Westphal, Russell V.

1988-01-01

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

High resolution MR microscopy

NASA Astrophysics Data System (ADS)

Ciobanu, Luisa

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

Spatial Differentiation of Arable Land and Permanent Grasslands to Improve a Regional Land Management Model for Nutrient Balancing

NASA Astrophysics Data System (ADS)

Gómez Giménez, M.; Della Peruta, R.; de Jong, R.; Keller, A.; Schaepman, M. E.

2015-12-01

Agroecosystems play an important role providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional Land Management Model (LMM) to improve the assessment of spatial explicit nutrient balances for agroecosystems. Remotely sensed data as well as an optimized parameter set contributed to feed the LMM providing a better spatial allocation of agricultural data aggregated at farm level. The integration of land use information in the land allocation process relied predominantly on three factors: i) spatial resolution, ii) classification accuracy and iii) parcels definition. The best-input parameter combination resulted in two different land cover classifications with overall accuracies of 98%, improving the LMM performance by 16% as compared to using non-spatially explicit input. Firstly, the use of spatial explicit information improved the spatial allocation output resulting in a pattern that better followed parcel boundaries (Figure 1). Second, the high classification accuracies ensured consistency between the datasets used. Third, the use of a suitable spatial unit to define the parcels boundaries influenced the model in terms of computational time and the amount of farmland allocated. We conclude that the combined use of remote sensing (RS) data with the LMM has the potential to provide highly accurate information of spatial explicit nutrient balances that are crucial for policy options concerning sustainable management of agricultural soils. Figure 1. Details of the spatial pattern obtained: a) Using only the farm census data, b) using also land use information. Framed in black in the left image (a), examples of artifacts that disappeared when using land use information (right image, b). Colors represent different ownership.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Refining surface net radiation estimates in arid and semi-arid climates of Iran

NASA Astrophysics Data System (ADS)

Golkar, Foroogh; Rossow, William B.; Sabziparvar, Ali Akbar

2018-06-01

Although the downwelling fluxes exhibit space-time scales of dependency on characteristic of atmospheric variations, especially clouds, the upward fluxes and, hence the net radiation, depends on the variation of surface properties, particularly surface skin temperature and albedo. Evapotranspiration at the land surface depends on the properties of that surface and is determined primarily by the net surface radiation, mostly absorbed solar radiation. Thus, relatively high spatial resolution net radiation data are needed for evapotranspiration studies. Moreover, in more arid environments, the diurnal variations of surface (air and skin) temperature can be large so relatively high (sub-daily) time resolution net radiation is also needed. There are a variety of radiation and surface property products available but they differ in accuracy, space-time resolution and information content. This situation motivated the current study to evaluate multiple sources of information to obtain the best net radiation estimate with the highest space-time resolution from ISCCP FD dataset. This study investigates the accuracy of the ISCCP FD and AIRS surface air and skin temperatures, as well as the ISCCP FD and MODIS surface albedos and aerosol optical depths as the leading source of uncertainty in ISCCP FD dataset. The surface air temperatures, 10-cm soil temperatures and surface solar insolation from a number of surface sites are used to judge the best combinations of data products, especially on clear days. The corresponding surface skin temperatures in ISCCP FD, although they are known to be biased somewhat high, disagreed more with AIRS measurements because of the mismatch of spatial resolutions. The effect of spatial resolution on the comparisons was confirmed using the even higher resolution MODIS surface skin temperature values. The agreement of ISCCP FD surface solar insolation with surface measurements is good (within 2.4-9.1%), but the use of MODIS aerosol optical depths as an alternative was checked and found to not improve the agreement. The MODIS surface albedos differed from the ISCCP FD values by no more than 0.02-0.07, but because these differences are mostly at longer wavelengths, they did not change the net solar radiation very much. Therefore to obtain the best estimate of surface net radiation with the best combination of spatial and temporal resolution, we developed a method to adjust the ISCCP FD surface longwave fluxes using the AIRS surface air and skin temperatures to obtain the higher spatial resolution of the latter (45 km), while retaining the 3-h time intervals of the former. Overall, the refinements reduced the ISCCP FD longwave flux magnitudes by about 25.5-42.1 W/m2 RMS (maximum difference -27.5 W/m2 for incoming longwave radiation and -59 W/m2 for outgoing longwave radiation) with the largest differences occurring at 9:00 and 12:00 UTC near local noon. Combining the ISCCP FD net shortwave radiation data and the AIRS-modified net longwave radiation data changed the total net radiation for summertime by 4.64 to 61.5 W/m2 and for wintertime by 1.06 to 41.88 W/m2 (about 11.1-39.2% of the daily mean).

UAS applications in high alpine, snow-covered terrain

NASA Astrophysics Data System (ADS)

Bühler, Y.; Stoffel, A.; Ginzler, C.

2017-12-01

Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology research.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

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

Krishnan, Venkat; Cole, Wesley

2016-11-14

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

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

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

Sanders, Jeremiah, E-mail: jeremiah.sanders@duke.e

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF),more » and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this finding. Conclusions: Clinically informed, patient-specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.« less

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.

Reflecting Schmidt/Littrow Prism Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.; Page, N. A.; Shack, R. V.; Shannon, R. R.

1985-01-01

High resolution achieved with wide field of view. Imaging Spectrometer features off-axis reflecting optics, including reflecting "slit" that also serves as field flattener. Only refracting element is prism. By scanning slit across object or scene and timing out signal, both spectral and spatial information in scene are obtained.

Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

EPA Science Inventory

Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

NASA Astrophysics Data System (ADS)

Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

2015-10-01

The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

Snow Pattern Delineation, Scaling, Fidelity, and Landscape Factors

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.; Wagner, A. M.; Deeb, E. J.; Morriss, B. F.; Sturm, M.

2014-12-01

In many snow-covered landscapes, snow tends to be shallow or deep in the same locations year after year. As snowmelt progresses in spring, areas of shallow snow become snow-free earlier than areas with deep snow. This pattern (Sturm and Wagner 2010) could likely be used to inform or improve modeled snow depth estimates where ground measurements are not collected; however, we must be certain of their utility before ingesting them into model calculations. Do patterns, as we detect them, have a relationship with earlier measured snow distributions? Second, are certain areas on the landscape likely to yield patterns that are influenced too highly by melting to be useful? Our Imnavait Creek Study Area (11 by 19 km) is on Alaska's North Slope, where we have examined a vast library of spring satellite imagery (ranging from mostly snow-covered to mostly snow-free). Landsat TM Imagery has been collected from the early 1980s-present, and the temporal and spatial resolution is roughly two weeks and 30 m, respectively. High resolution satellite imagery (WorldView 1, WorldView 2, IKONOS) has been obtained from 2010-2013 for the same area with almost daily- to monthly-temporal and at 2.5 m spatial resolutions, respectively. We found that there is a striking similarity among patterns from year to year across the span of decades and resolutions. However, the relationship of pattern with observed snow depths was strong in some areas and less clear in others. Overall, we suspect spatial scaling, spatial mismatch, sampling errors, and melt patterns explain most of the areas of pattern and depth disparity.

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

Spatial resolution and chest nodule detection: an interesting incidental finding

NASA Astrophysics Data System (ADS)

Toomey, R. J.; McEntee, M. F.; Ryan, J. T.; Evanoff, M. G.; Hayes, A.; Brennan, P. C.

2010-02-01

This study reports an incidental finding from a larger work. It examines the relationship between spatial resolution and nodule detection for chest radiographs. Twelve examining radiologists with the American Board of Radiology read thirty chest radiographs in two conditions - full (1500 × 1500 pixel) resolution, and 300 × 300 pixel resolution linearly interpolated to 1500 × 1500 pixels. All images were surrounded by a 10-pixel sharp grey border to aid in focussing the observer's eye when viewing the comparatively unsharp interpolated images. Fifteen of the images contained a single simulated pulmonary nodule. Observers were asked to rate their confidence that a nodule was present on each radiograph on a scale of 1 (least confidence, certain no lesion is present) to 6 (most confidence, certain a lesion was present). All other abnormalities were to be ignored. No windowing, levelling or magnification of the images was permitted and viewing distance was constrained to approximately 70cm. Images were displayed on a 3 megapixel greyscale monitor. Receiver operating characteristic (ROC) analysis was applied to the results of the readings using the Dorfman-Berbaum-Metz multiplereader, multiple-case method. No statistically significant differences were found with either readers and cases treated as random or with cases treated as fixed. Low spatial frequency information appears to be sufficient for the detection of chest lesion of the type used in this study.

Virtual mission stage I: Implications of a spaceborne surface water mission

NASA Astrophysics Data System (ADS)

Clark, E. A.; Alsdorf, D. E.; Bates, P.; Wilson, M. D.; Lettenmaier, D. P.

2004-12-01

The interannual and interseasonal variability of the land surface water cycle depend on the distribution of surface water in lakes, wetlands, reservoirs, and river systems; however, measurements of hydrologic variables are sparsely distributed, even in industrialized nations. Moreover, the spatial extent and storage variations of lakes, reservoirs, and wetlands are poorly known. We are developing a virtual mission to demonstrate the feasibility of observing surface water extent and variations from a spaceborne platform. In the first stage of the virtual mission, on which we report here, surface water area and fluxes are emulated using simulation modeling over three continental scale river basins, including the Ohio River, the Amazon River and an Arctic river. The Variable Infiltration Capacity (VIC) macroscale hydrologic model is used to simulate evapotranspiration, soil moisture, snow accumulation and ablation, and runoff and streamflow over each basin at one-eighth degree resolution. The runoff from this model is routed using a linear transfer model to provide input to a much more detailed flow hydraulics model. The flow hydraulics model then routes runoff through various channel and floodplain morphologies at a 250 m spatial and 20 second temporal resolution over a 100 km by 500 km domain. This information is used to evaluate trade-offs between spatial and temporal resolutions of a hypothetical high resolution spaceborne altimeter by synthetically sampling the resultant model-predicted water surface elevations.

Adaptive optics improves multiphoton super-resolution imaging

NASA Astrophysics Data System (ADS)

Zheng, Wei; Wu, Yicong; Winter, Peter; Shroff, Hari

2018-02-01

Three dimensional (3D) fluorescence microscopy has been essential for biological studies. It allows interrogation of structure and function at spatial scales spanning the macromolecular, cellular, and tissue levels. Critical factors to consider in 3D microscopy include spatial resolution, signal-to-noise (SNR), signal-to-background (SBR), and temporal resolution. Maintaining high quality imaging becomes progressively more difficult at increasing depth (where optical aberrations, induced by inhomogeneities of refractive index in the sample, degrade resolution and SNR), and in thick or densely labeled samples (where out-of-focus background can swamp the valuable, in-focus-signal from each plane). In this report, we introduce our new instrumentation to address these problems. A multiphoton structured illumination microscope was simply modified to integrate an adpative optics system for optical aberrations correction. Firstly, the optical aberrations are determined using direct wavefront sensing with a nonlinear guide star and subsequently corrected using a deformable mirror, restoring super-resolution information. We demonstrate the flexibility of our adaptive optics approach on a variety of semi-transparent samples, including bead phantoms, cultured cells in collagen gels and biological tissues. The performance of our super-resolution microscope is improved in all of these samples, as peak intensity is increased (up to 40-fold) and resolution recovered (up to 176+/-10 nm laterally and 729+/-39 nm axially) at depths up to 250 μm from the coverslip surface.

Automated, per pixel Cloud Detection from High-Resolution VNIR Data

NASA Technical Reports Server (NTRS)

Varlyguin, Dmitry L.

2007-01-01

CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.

STARPROBE: A design study for an X-ray imaging instrument

NASA Technical Reports Server (NTRS)

1981-01-01

The primary objective of the X-ray imaging telescope on STARPROBE is the acquisition of very high spacial resolution observations during the spacecraft's perihelion passage. Design parameters, telescope prefilters, and structural and thermal analyses of the equipment are described and discussed. It is believed that the spatial resolution of the information recorded by the baseline design would be at least a factor of 10 better than can be reasonably expected from Earth orbit. Thermal models used in the study are also discussed.

Global Land Survey Impervious Mapping Project Web Site

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Phillips, Jacqueline

2014-01-01

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

The Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method

NASA Astrophysics Data System (ADS)

Lin, Yong-Qing; Lin, Yuan-Chien

2017-04-01

Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality

High-resolution modeling of a marine ecosystem using the FRESCO hydroecological model

NASA Astrophysics Data System (ADS)

Zalesny, V. B.; Tamsalu, R.

2009-02-01

The FRESCO (Finnish Russian Estonian Cooperation) mathematical model describing a marine hydroecosystem is presented. The methodology of the numerical solution is based on the method of multicomponent splitting into physical and biological processes, spatial coordinates, etc. The model is used for the reproduction of physical and biological processes proceeding in the Baltic Sea. Numerical experiments are performed with different spatial resolutions for four marine basins that are enclosed into one another: the Baltic Sea, the Gulf of Finland, the Tallinn-Helsinki water area, and Tallinn Bay. Physical processes are described by the equations of nonhydrostatic dynamics, including the k-ω parametrization of turbulence. Biological processes are described by the three-dimensional equations of an aquatic ecosystem with the use of a size-dependent parametrization of biochemical reactions. The main goal of this study is to illustrate the efficiency of the developed numerical technique and to demonstrate the importance of a high spatial resolution for water basins that have complex bottom topography, such as the Baltic Sea. Detailed information about the atmospheric forcing, bottom topography, and coastline is very important for the description of coastal dynamics and specific features of a marine ecosystem. Experiments show that the spatial inhomogeneity of hydroecosystem fields is caused by the combined effect of upwelling, turbulent mixing, surface-wave breaking, and temperature variations, which affect biochemical reactions.

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

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.

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

USGS Publications Warehouse

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

2018-01-01

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

Effect of Electric Field Gradient on Sub-nanometer Spatial Resolution of Tip-enhanced Raman Spectroscopy

PubMed Central

Meng, Lingyan; Yang, Zhilin; Chen, Jianing; Sun, Mengtao

2015-01-01

Tip-enhanced Raman spectroscopy (TERS) with sub-nanometer spatial resolution has been recently demonstrated experimentally. However, the physical mechanism underlying is still under discussion. Here we theoretically investigate the electric field gradient of a coupled tip-substrate system. Our calculations suggest that the ultra-high spatial resolution of TERS can be partially attributed to the electric field gradient effect owning to its tighter spatial confinement and sensitivity to the infrared (IR)-active of molecules. Particularly, in the case of TERS of flat-lying H2TBPP molecules,we find the electric field gradient enhancement is the dominating factor for the high spatial resolution, which qualitatively coincides with previous experimental report. Our theoretical study offers a new paradigm for understanding the mechanisms of the ultra-high spatial resolution demonstrated in tip-enhanced spectroscopy which is of importance but neglected. PMID:25784161

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

Multiframe super resolution reconstruction method based on light field angular images

NASA Astrophysics Data System (ADS)

Zhou, Shubo; Yuan, Yan; Su, Lijuan; Ding, Xiaomin; Wang, Jichao

2017-12-01

The plenoptic camera can directly obtain 4-dimensional light field information from a 2-dimensional sensor. However, based on the sampling theorem, the spatial resolution is greatly limited by the microlenses. In this paper, we present a method of reconstructing high-resolution images from the angular images. First, the ray tracing method is used to model the telecentric-based light field imaging process. Then, we analyze the subpixel shifts between the angular images extracted from the defocused light field data and the blur in the angular images. According to the analysis above, we construct the observation model from the ideal high-resolution image to the angular images. Applying the regularized super resolution method, we can obtain the super resolution result with a magnification ratio of 8. The results demonstrate the effectiveness of the proposed observation model.