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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop‐insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two‐day severe weather event across western Nebraska and central Kansas during 9‐10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

Dryden, Rachel L.↗
NASA NTRS1972

Use of satellite imagery for wildland resource evaluation

The author has identified the following significant results. Accurate identification and delineation of crested wheatgrass seedlings has enabled a broad inventory of this resource. The entire state of Nevada is being inventoried for crested wheatgrass seedlings. Irrigated fields and pastures are easily visible from ERTS-1 imagery and were quantified in total acres on 12,500 square miles of the state. Recent fire scars may be monitored and inventoried from satellite-borne imagery. Inventory and quantification of large native meadows of Nevada have been accomplished on one frame of ERTS-1 data. This inventory would not have been economically feasible with any known ground inventory method. The U-2 sequential data taken in the spring revealed several resource management oriented phenological changes in the vegetation. The green-up of grasses and shrubs was detected on the imagery and supplied a good indicator for livestock turn-out dates. Water level manipulations in the Ruby Marsh were readily detected by noting changes in vegetation growth and reflectance.

Tueller, P. T.↗
NASA NTRS1983

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Logan, T. L.↗
NASA NTRS2016

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

satellite imagery↗
NASA NTRS1975

Measuring snow cover using satellite imagery during 1973 and 1974 melt season: North Santiam, Boise, and Upper Snake Basins, phase 1

Measurements are examined of snow coverage during the snow-melt season in 1973 and 1974 from LANDSAT imagery for the three Columbia River Subbasins. Satellite derived snow cover inventories for the three test basins were obtained as an alternative to inventories performed with the current operational practice of using small aircraft flights over selected snow fields. The accuracy and precision versus cost for several different interactive image analysis procedures was investigated using a display device, the Electronic Satellite Image Analysis Console. Single-band radiance thresholding was the principal technique employed in the snow detection, although this technique was supplemented by an editing procedure involving reference to hand-generated elevation contours. For each data and view measured, a binary thematic map or "mask" depicting the snow cover was generated by a combination of objective and subjective procedures. Photographs of data analysis equipment (displays) are shown.

Wiegman, E. J.↗
NASA NTRS1975

Exploiting the temporal coherence of repetitive satellite imagery

Imagery from ERTS or the Synchronous Meteorological Satellites, because of its precisely repetitive nature, is ideally suited both for subjective enhancement by time-lapse display and for objective measurements of changes with time. A hybrid system providing both viewing and image-processing functions is described. A representative application involves the measurement of changes in the aerial extent of snow cover within specified mountain watersheds. Subjective viewing of time-lapse sequences of the snow scenes provides valuable insight into the nature of numerous extraneous signals, permitting the interim implementation of operationally useful snow-measuring systems and hopefully leading toward the design of fully objective classifiers.

Evans, W. E.↗
NASA NTRS1981

Utilization of Meteorological Satellite Imagery for World-Wide Environmental Monitoring the Lower Mississippi River Flood of 1979 - Case 1

The 1979 Lower Mississippi River flood was selected as a test case of environmental disaster monitoring utilizing NOAA-n imagery. A small scale study of the St. Louis Missouri area comparing ERTS-1 (LANDSAT) and NOAA-2 imagery and flood studies using only LANDSAT imagery for mapping the Rad River of the North, and Nimbus-5 imagery for East Australia show the nonmeteorological applications of NOAA satellites. While the level of NOAA-n imagery detail is not that of a LANDSAT image, for operational environmental monitoring users the NOAA-n imagery may provide acceptable linear resolution and spectral isolation.

Helfert, M. R.↗
NASA NTRS1976

Utilization of satellite imagery by in-flight aircraft

Present and future utilization of satellite weather data by commercial aircraft while in flight was assessed. Weather information of interest to aviation that is available or will become available with future geostationary satellites includes the following: severe weather areas, jet stream location, weather observation at destination airport, fog areas, and vertical temperature profiles. Utilization of this information by in-flight aircraft is especially beneficial for flights over the oceans or over remote land areas where surface-based observations and communications are sparse and inadequate.

Luers, J. K.↗
NASA NTRS1982

Recommended satellite imagery capabilities for disaster management

This study explores the role that satellite imaging systems might play in obtaining information needed in the management of natural and manmade disasters. Information requirements which might conceivably be met by satellite were identified for over twenty disasters. These requirements covered pre-disaster mitigation and preparedness activities, disaster response activities, and post-disaster recovery activities. The essential imaging satellite characteristics needed to meet most of the information requirements are 30 meter (or finer) spatial resolution, frequency of observations of one week or less, data delivery times of one day or less, and stereo, synoptic all-weather coverage of large areas in the visible, near infrared, thermal infrared and microwave bands. Of the current and planned satellite systems investigated for possible application to disaster management, Landsat-D and SPOT appear to have the greatest potential during disaster mitigation and preparedness activities, but all satellites studied have serious deficiencies during response and recovery activities. Several strawman concepts are presented for a satellite system optimized to support all disaster management activities.

Richards, P. B.↗
NASA NTRS1994

New Perspectives on Active Tectonics: Observing Fault Motion, Mapping Earthquake Strain Fields, and Visualizing Seismic Events in Multiple Dimensions Using Satellite Imagery and Geophysical Data Base

By rapidly alternating displays of SPOT satellite images acquired on 27 July 1991 and 25 July 1992 we are able to see spatial details of terrain movements along fault breaks associated with the 28 June 1992 Landers, California earthquake that are virtually undetectable by any other means.

fields↗
DOE OSTI2025

Satellite Imagery of PV Site Storm Damage

"This repository contains multiple data sets focused on visible damage to photovoltaic (PV) installations following extreme weather events such as hailstorms and hurricanes. Data sets are split into two categories: the first category, the ‘manually labeled’ data, was compiled by researchers manually, and contains manually identified PV sites exposed to storms. The second data set, the ‘aggregated’ data, is a compilation of the manually labeled PV sites and deep learning-identified PV sites. The hail damage data set focuses on post-storm PV damage following a September 24, 2023 hailstorm in Austin, TX, which caused over $600 million in damages in the Austin metro area. The hurricane damage data set focuses on post-storm PV damage following Hurricanes Irma and Maria in Puerto Rico and the US Virgin Islands. Hurricanes Irma and Maria were back-to-back category 5 hurricanes, which pummeled the Caribbean and southeastern United States in September 2017, causing an estimated $115.2 billion in damages."

14 SOLAR ENERGY↗
NASA NTRS2012

Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

chlorophyll fluorescence↗
NASA NTRS1973

Satellite imagery for assessing range fire damage in the Sandhills of Nebraska

The author has identified the following significant results. Initial imagery from the first ERTS indicates that satellite-acquired data is of value in determining the location and extent of range fire in the Sand Hills region of Nebraska. Preliminary results suggest that it can also provide a tool for monitoring soil erosion by wind and evaluating the recovery of vegetation in burned areas.

Drew, J. V.↗
NASA NTRS1985

Estimation of cloud top heights from satellite imagery

Light coming from a cloud to the detector of a multispectral satellite (Landsat) consists of light reflected from the cloud and light scattered by the layer of atmosphere between the cloud and satellite. Because of the strong wavelength dependence of Rayleigh scattering, the comparison of the signals in two spectral channels allows one to find the thickness of the scattering layer and hence the height of the cloud top.

Mekler, Y.↗
NASA NTRS1986

Effects of instrument characteristics on cloud properties retrieved from satellite imagery data

The relationships between sensor resolution and derived cloud properties in satellite remote sensing were studied by comparisons of cloud characteristics determined by spatial coherence analysis of AVHRR and GOES data. The latter data were simulated from 11 microns AVHRR data and were assigned a resolution (8 sq km) half that of the AVHRR. Day and nighttime passes were considered for single-layer maritime cloud systems. Sample radiance vs local standard deviation plots of 1024 points are provided for the same area from AVHRR and GOES-East sensors, demonstrating a qualitative agreement.

Baldwin, D. G.↗
NASA NTRS2012

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

Molthan, Andrew↗
NASA NTRS1976

Variability of wetland reflectance and its effect on automatic catergorization of satellite imagery

The author has identified the following significant results. A technique for training automated analysis of satellite multispectral data based on in situ measurements of target reflectance was tested and applied in delineating cover communities in Delaware's tidal wetlands. Land cover categorization of data from the same overpass in four test wetland areas was carried out using a four category classification system. The tests indicate that training data based on in situ reflectance measurements and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training. Analysis of the four wetlands cover categories (salt marsh cordgrass, salt hay, water, and unvegetated tidal flat) produced average categorization accuracies of 82.1% by conventional relative radiance training and 81.4% by use of in situ reflectance measurements.

Klemas, V.↗
NASA NTRS1986

Calculating Atmospheric Effects in Satellite Imagery

Report presents detailed analysis of atmospheric blurring inherent in photographs or other observations of Earth from satellites or aircraft. Blurring result of scattering of radiation, which diffuses sharp image features by causing light from one part of scene to fall on image of adjacent part. In contrast with earlier approaches to atmospheric optics, one presented in report more accurate and versatile and designed for use on minicomputers.

Diner, D. J.↗