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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Radar Monitoring of Wetlands for Malaria Control

Malaria is the most important vector-borne tropical disease (Collins and Paskewitz, 1995) and there is no simple and universally applicable form of vector control. While new methods such as malaria vaccine or genetic manipulation of mosquitoes are being explored in the laboratories, the need for more field research on malaria transmission remains very strong. For the foreseeable future many malaria programs must focus on controlling the vector, the anopheline mosquito, often under the specter of shrinking budgets. Therefore information on which human populations are at the greatest risk is especially valuable when allocating scarce resources. The goal of the Radar Monitoring of Wetlands for Malaria Control Project is to demonstrate the feasibility of using Radarsat or other comparable satellite radar imaging systems to determine where and when human populations are at greatest risk for contracting malaria. The study area is northern Belize, a region with abundant wetlands and a potentially serious malaria problem. A key aspect of this study is the analysis of multi-temporal satellite imagery to track seasonal flooding of anopheline mosquito breeding sites. Radarsat images of the test site in Belize have been acquired one to three times a month over the last year, however,, to date only one processed image has been received from the Alaska SAR Facility for analysis. Therefore analysis at this stage is focussed on determining the radar backscatter characteristics of known anopheline breeding sites, with future work to be dedicated toward seasonal changes.

Pope, Kevin O.↗
NASA NTRS2000

Global Boreal Forest Mapping with JERS-1: North America

Collaborative effort is underway to map boreal forests worldwide using L-band, single polarization Synthetic Aperture Radar (SAR) imagery from the Japanese Earth Resources (JERS-1) satellite. Final products of the North American Boreal Forest Mapping Project will include two continental scale radar mosaics and supplementary multitemporal mosaics for Alaska, central Canada, and eastern Canada. For selected sites, we are also producing local scale (100 km x 100 km) and regional scale maps (1000 km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web. Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR Facility.

Williams, Cynthia L.↗
NASA NTRS2001

Radarsat Antarctic Mapping Project: Antarctic Imaging Campaign 2

The Radarsat Antarctic Mapping Project is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first, high-resolution SAR image map of Antarctica. The limited amount of data suitable for interferometric analysis have also been used to produce remarkably detailed maps of surface velocity for a few selected regions. Most importantly, the results from AMM-1 are now available to the general science community in the form of various resolution, radiometrically calibrated and geometrically accurate image mosaics. The second Antarctic imaging campaign occurred during the fall of 2000. Modified from AMM-1, the satellite remained in north looking mode during AMM-2 restricting coverage to regions north of about -80 degrees latitude. But AMM-2 utilized for the first time RADARSAT-1 fine beams providing an unprecedented opportunity to image many of Antarctica's fast glaciers whose extent was revealed through AMM-1 data. AMM-2 also captured extensive data suitable for interferometric analysis of the surface velocity field. This report summarizes the science goals, mission objectives, and project status through the acquisition phase and the start of the processing phase. The reports describes the efforts of team members including Alaska SAR Facility, Jet Propulsion Laboratory, Vexcel Corporation, Goddard Space Flight Center, Wallops Flight Facility, Ohio State University, Environmental Research Institute of Michigan, White Sands Facility, Canadian Space Agency Mission Planning and Operations Groups, and the Antarctic Mapping Planning Group.

Source record↗
NASA NTRS1994

Ice Lead Orientation Characteristics in the Winter Beaufort Sea

The directional orientations of leads in the winter ice pack of the Beaufort Sea are studied both spatially and temporally. Data from the European Earth Resources Satellite-1 (ERS-1) Synthetic Aperture Radar (SAR) was used. The SAR data was produced in image form at the Alaska SAR Facility (ASF) with 100 x 100 m pixel resolution. The lead ice pixels, which included all non-multiyear ice, were defined using a simple thresholding of the radar backscatter values. The orientations of the leads covering the Beaufort Sea during the period of January through March of 1992 were derived using a lead skeletonization technique. Results show a strong temporal persistence in the distribution and orientation of the leads during this period.

SAR ice lead orientation↗
NASA NTRS1998

Data Quality of the JERS-1 SAR Global Rain Forest Mapping (GRFM) Project

The National Space Development Agency of Japan's (NASDA) JERS-1 SAR began collecting data in 1995 for the Global Rain Forest Mapping Project (GRFM). The GRFM data quality has been examined for products resulting from both the NASDA and Alaska SAR facility's (ASF) processing facilities.

JERS-1 SAR Rain Forest Mapping↗
NASA NTRS1987

The Alaska synthetic aperture radar (SAR) facility project

A receiving station for the acquisition and processing of spaceborne synthetic aperture radar (SAR) data is being established by the National Aeronautics and Space Administration (NASA) at the University of Alaska, Fairbanks. The data that will be received from a number of SAR satellites that are to be launched starting in 1990 will allow U.S. researchers to study sea ice, oceanographic and geological features, hydrological processes, glaciers, and vegetation cover in Alaska and its surrounding seas.

Carsey, F.↗
NASA NTRS1994

Sea ice lead dynamics from ERS-1 SAR

The use of ERS-1 SAR (Synthetic Aperture Radar) images to measure ice lead changes and ice deformation, and thus to determine their relationships and compare them to theory, is reported. ERS-1 SAR data collected at the Alaska (U.S.) SAR facility are processed into low resolution geocoded images which are used as input to the Geophysical Processor System (GPS). The GPS uses cross correlation and edge detection on sequential pairs of images to track a regular 5 km array of grid points. The result for each sequential image pair is a field of ice displacement that contains, on average, more than 200 vectors. The GPS also classifies all the pixels of the images into one of four ice types based on the normalized backscatter coefficients and a seasonal look-up table. This allows all pixels to be labeled as either multiyear ice or as the first year ice and open water that comprise leads.

Stern, Harry L.↗
NASA NTRS1996

RADARSAT Processing System at ASF

This paper outlines the ASF (Alaska SAR[synthetic aperture radar] Facility) Radarsat data processing requirements as driven by the science users and describes the Radarsat processing system design and implementaiton approach to meet the challenge of providing ASF with and integrated operational SAR image production facility. Design and implementation attributes that facilitate syswtem growth in handling future SAR missions such as Envisat and HIROS are also addressed.

ASF↗
NASA NTRS1989

The Alaska SAR processor - Operations and control

The Alaska SAR (synthetic-aperture radar) Facility (ASF) will be capable of receiving, processing, archiving, and producing a variety of SAR image products from three satellite-borne SARs: E-ERS-1 (ESA), J-ERS-1 (NASDA) and Radarsat (Canada). Crucial to the success of the ASF is the Alaska SAR processor (ASP), which will be capable of processing over 200 100-km x 100-km (Seasat-like) frames per day from the raw SAR data, at a ground resolution of about 30 m x 30 m. The processed imagery is of high geometric and radiometric accuracy, and is geolocated to within 500 m. Special-purpose hardware has been designed to execute a SAR processing algorithm to achieve this performance. This hardware is currently undergoing acceptance testing for delivery to the University of Alaska. Particular attention has been devoted to making the operations semi-automated and to providing a friendly operator interface via a computer workstation. The operations and control of the Alaska SAR processor are described.

Carande, Richard E.↗
NASA NTRS1994

The geophysical processor system: Automated analysis of ERS-1 SAR imagery

The Geophysical Processor System (GPS) at the Alaska (U.S.) SAR (Synthetic Aperture Radar) Facility (ASF) uses ERS-1 SAR images as input to generate three types of products: sea ice motion, sea ice type, and ocean wave spectra. The GPS, operating automatically with minimal human intervention, delivers its output to the Archive and Catalog System (ACS) where scientists can search and order the products on line. The GPS has generated more than 10,000 products since it became operational in Feb. 1992, and continues to deliver 500 new products per month to the ACS. These products cover the Beaufort and Chukchi Seas and the western portion of the central Arctic Ocean. More geophysical processing systems are needed to handle the large volumes of data from current and future satellites. Images must be routinely and consistently analyzed to yield useful information for scientists. The current GPS is a good, working prototype on the way to more sophisticated systems.

Stern, Harry L.↗
NASA NTRS1994

Sea ice type maps from Alaska synthetic aperture radar facility imagery: An assessment

Synthetic aperture radar (SAR) imagery received at the Alaskan SAR Facility is routinely and automatically classified on the Geophysical Processor System (GPS) to create ice type maps. We evaluated the wintertime performance of the GPS classification algorithm by comparing ice type percentages from supervised classification with percentages from the algorithm. The root mean square (RMS) difference for multiyear ice is about 6%, while the inconsistency in supervised classification is about 3%. The algorithm separates first-year from multiyear ice well, although it sometimes fails to correctly classify new ice and open water owing to the wide distribution of backscatter for these classes. Our results imply a high degree of accuracy and consistency in the growing archive of multiyear and first-year ice distribution maps. These results have implications for heat and mass balance studies which are furthered by the ability to accurately characterize ice type distributions over a large part of the Arctic.

Fetterer, Florence M.↗
NASA NTRS2017

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.

SERVIR↗
NASA NTRSDate not supplied

A Cloud-Based Operational Surface Water Extent Mapping Service from Sentinel-1 SAR

With its weather independence and day-and-night capabilities, SAR has long been known as a useful data set for flood monitoring. The recently launched Sentinel-1 (S1) C-band sensors, with their regularly acquired, free-and-open data, have finally elevated SAR to a relevant data source in operational hazard response. Leveraging these capabilities of S1, this poster introduces the HYDRO30 product, a 30-m resolution surface water extent product derived from dual-pol S1 SAR data. To enable automatic and near real-time product generation, HYDRO30 is embedded in the HydroSAR service, a cloud-based production pipeline developed by the University of Alaska Fairbanks in collaboration with the NASA Alaska Satellite Facility DAAC and the NASA Marshall and Goddard Space Flight Centers.

Franz J Meyer↗