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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Multipolarization SAR data for surface feature delineation

This paper presents the techniques and the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation. Three channels of ratioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The technique assumes redundancy of the VH and HV polarization and only VH polarization is used. The ratioed data are linearly stretched to yield a digital number within a range of 0 to 255. Based on the separability measure for two-class delineation, it was found that (1) the ratioed data resulted in a better delineation of surface features with high like (HH or VV) polarization digital number, and (2) the use of ratioed data provided further information not available from the original three-polarization data. The results suggest an advantage in using the ratioed data and the original three-polarization data for surface feature delineation.

Wu, S. T.↗
NASA NTRS2014

An Efficient, Multi-Layered Crown Delineation Algorithm for Mapping Individual Tree Structure Across Multiple Ecosystems

Deriving individual tree information from discrete return, small footprint LiDAR data may improve forest above ground biomass estimates, and provide tree-level information that is important in many ecological studies. Several crown delineation algorithms have been developed to extract individual tree information from LiDAR point clouds or rasterized canopy height models (CHM), but many of these algorithms have difficulty discriminating between overlapping crowns, and also may fail to detect understory trees. Our approach uses a watershed based delineation of a CHM, which is subsequently refined using the LiDAR point cloud. Individual tree detection was validated with stem mapped field data from the Smithsonian Environmental Research Center (SERC), Maryland, and on a plot and stand level through comparisons of stem density and basal area to delineated metrics at both SERC and a study area in the Sierra Nevada, California. For individual tree detection, the algorithm correctly identified 70% of dominant trees, 58% of co-dominant trees, 35% of intermediate trees and 21% of suppressed trees at SERC. The algorithm had difficulty distinguishing between crowns of small, dense understory trees of approximately the same height. Delineated crown volume alone explained 53% and 84% of the variability in basal area at the SERC and Sierra Nevada sites, respectively. The algorithm produced crown area distributions comparable to diameter at breast height (DBH) size class distributions observed in the field in both study sites. The algorithm detected understory crowns better in the conifer-dominated Sierra Nevada site than in the closed-canopy deciduous site in Maryland. The ability for the algorithm to reproduce both accurate tree size distributions and individual crown geometries in two dissimilar and complex forests suggests great promise for applicability to a wide range of forest systems.

LiDAR↗
NASA NTRS1987

Multipolarization SAR data for surface feature delineation and forest vegetation characterization

This paper presents the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation and forest vegetation characterization. Three channels of radioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The radioed data are linearly stretched to yield a digital number within a range of 0 to 255. The techniques for reducing SAR speckle noise and for measuring the degree of separation are discussed. For surface feature delineation, the results indicate that cross polarization as well as cross polarization radioed data better delineate those surface features that are difficult to separate by like polarization data. The results suggest using a median value filtering technique to reduce within-plot data fluctuation to increase the separability measure. For forest vegetation characterization, the results indicate that multipolarization SAR data may be used to estimate forest properties such as total-tree biomass, basal area, and tree height.

Wu, Shih-Tseng↗
NASA NTRS2013

A Comparative Review of North American Tundra Delineations

Recent profound changes have been observed in the Arctic environment, including record low sea ice extents and high latitude greening. Studying the Arctic and how it is changing is an important element of climate change science. The Tundra, an ecoregion of the Arctic, is directly related to climate change due to its effects on the snow ice feedback mechanism and greenhouse gas cycling. Like all ecoregions, the Tundra border is shifting, yet studies and policies require clear delineation of boundaries. There are many options for ecoregion classification systems, as well as resources for creating custom maps. To help decision makers identify the best classification system possible, we present a review of North American Tundra ecoregion delineations and further explore the methodologies, purposes, limitations, and physical properties of five common ecoregion classification systems. We quantitatively compare the corresponding maps by area using a geographic information system.

Delineations↗
NASA NTRS2015

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗
NASA NTRS1974

ERTS-1 MSS imagery: Its use in delineating soil associations and as a base map for publishing soils information

ERTS 1 imagery is a useful tool in the identification and refinement of soil association areas and an excellent base map upon which soil association information can be published. Prints of bands 5 and 7 were found to be most useful to help delineate major soil and vegetation areas. After delineating major soil areas, over 4800 land sale prices covering a period of 1967-72 were located in the soil areas and averaged. The soil association then were described as soil association value areas and published on a 1:1,000,000 scale ERTS mosaic of South Dakota constructed using negative prints of band 7. The map is intended for use by state and county revenue officers, by individual buyers and sellers of land and lending institutions, and as a reference map by those planning road routes and cable lines and pipelines.

Westin, F. C.↗
NASA NTRS1974

Application of remote sensing techniques in land-use planning: Flood-plain delineation

The delineation of areas subject to inundation by means of remotely-sensed data acquisition represents a considerable saving in personnel time. Repeated input from aerial sensor sources provides the planner with a potent tool for the formation of a data base and for the monitoring of land use patterns over a period of time. The primary output of this project was a set of base map overlays at a scale of 1:62,500 delineating areas which require special regulations when proposed for land use involving human habitation or certain classes of storage. A secondary product of the study was county-wide maps of watershed configurations and of soil hydrologic groups. Further research is anticipated to extend the mapping of watershed areas outside the political boundaries of Cochise County, which will provide data for subsequent rainfall-runoff relationship studies in the area. All of the data provided will be incorporated into the Cochise County composite computer mapping project now operational. Results of this project have improved the pool of information available to the planning staff of Cochise County.

Altenstadter, J.↗
NASA NTRS1974

The use of remote sensing and natural indicators to delineate floodplains - Preliminary findings

Feasibility studies to delineate floodplains using aerial photography have been conducted by the Army Corps of Engineers. The objective of this project is to establish floodplain boundaries using natural indicators such as vegetation types, soil types, moisture differences, and geologic variations. Using aircraft multispectral data, an automated mapping routine should enable the Corps of Engineers to reduce costly field surveys and improve the accuracy of floodplain delineation in pristine areas. The purpose of this paper is to document the methodology utilized in this investigation while using one of a series of available data sets and test sites and to report preliminary findings.

Sollers, S. C.↗
NASA NTRS1977

Urban area delineation and detection of change along the urban-rural boundary as derived from LANDSAT digital data

LANDSAT digital multispectral scanner data, in conjunction with supporting ground truth, were investigated to determine their utility in delineation of urban-rural boundaries. The digital data for the metropolitan areas of Washington, D. C.; Austin, Texas; and Seattle, Washingtion; were processed using an interactive image processing system. Processing focused on identification of major land cover types typical of the zone of transition from urban to rural landscape, and definition of their spectral signatures. Census tract boundaries were input into the interactive image processing system along with the LANDSAT single and overlayed multiple date MSS data. Results of this investigation indicate that satellite collected information has a practical application to the problem of urban area delineation and to change detection.

Christenson, J. W.↗
NASA NTRS1978

Identification and delineation of urbanized areas using Landsat data

The use of Landsat data to delineate urban boundaries in Standard Metropolitan Statistical Areas is considered. The project, which is being conducted by the Census-Urbanized Area Application System Verification program, seeks to develop processing techniques and output products that meet urban fringe delineation requirements. A processing approach which will use an interactive processing system to produce digital enhancement and classification results is described.

Dietrich, D. L.↗
NASA NTRS1983

Automated basin delineation from digital terrain data

While digital terrain grids are now in wide use, accurate delineation of drainage basins from these data is difficult to efficiently automate. A recursive order N solution to this problem is presented. The algorithm is fast because no point in the basin is checked more than once, and no points outside the basin are considered. Two applications for terrain analysis and one for remote sensing are given to illustrate the method, on a basin with high relief in the Sierra Nevada. This technique for automated basin delineation will enhance the utility of digital terrain analysis for hydrologic modeling and remote sensing.

Marks, D.↗
NASA NTRS1986

Delineation of fault zones using imaging radar

The assessment of earthquake hazards and mineral and oil potential of a given region requires a detailed knowledge of geological structure, including the configuration of faults. Delineation of faults is traditionally based on three types of data: (1) seismicity data, which shows the location and magnitude of earthquake activity; (2) field mapping, which in remote areas is typically incomplete and of insufficient accuracy; and (3) remote sensing, including LANDSAT images and high altitude photography. Recently, high resolution radar images of tectonically active regions have been obtained by SEASAT and Shuttle Imaging Radar (SIR-A and SIR-B) systems. These radar images are sensitive to terrain slope variations and emphasize the topographic signatures of fault zones. Techniques were developed for using the radar data in conjunction with the traditional types of data to delineate major faults in well-known test sites, and to extend interpretation techniques to remote areas.

Toksoz, M. N.↗
NASA NTRS1973

Delineation of major soil associations using ERTS-1 imagery

The delineation of a major soil association in the loess region of Obion County has been accomplished using ERTS-1 imagery. Channel 7 provides the clearest differentiation. The separation of other smaller soil associations in an intensive row crop agricultural area is somewhat more difficult. Soil differentiation has been accomplished visually as well as electronically using a scanning microdensitometer. Lower altitude aircraft imagery permits a more refined soil association identification and where imagery is of sufficient scale, even individual soils may be identified.

Parks, W. L.↗
NASA NTRS1973

The use of aerial photography to quantitatively delineate mixing zones - A progress report

Aerial photography has been used to characterize and model the mixing zones which result from waste effluent discharges at seven river sites throughout the state of Wisconsin. The mixing zone is defined as the portion of the river where the waste effluent is totally mixed with the ambient receiving water. An integrated program of field sampling, mathematical modeling, laboratory modeling, and remote sensing was conducted to develop a quantitative relationship for the volumetric configuration of the mixing zone as a function of the measurable characteristics of various effluents, outfalls, and receiving water bodies. Analysis of scanning microdensitometer data extracted from 9-in. color IR transparencies has confirmed the utility of employing image density measurements to quantitatively delineate surficial concentration patterns within the mixing zone.

Lillesand, T. M.↗