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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

marine boundary layer↗
NASA NTRS2013

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

vegetation canopy↗
NASA NTRS1994

Simulated ASTER data for Geologic Studies

The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a high spatial resolution imaging instrument, due to be launched on NASA's Earth Observing System AM-1 satellite platform in 1998. ASTER acquires data in 14 bands, spanning the wavelength region from the visible, near infrared, short wavelength infrared, and thermal infrared, with spatial resolution varying from 15 m to 90 m, depending on wavelength region. In order to evaluate our ability to use ASTER data for geological mapping, we used aircraft data over Cuprite, Nevada to create a simulated 14-band ASTER data set. The study site has sparse vegetation, and exposes a wide range of unaltered and hydrothermally altered volcanic rocks. The wide range of wavelengths covered by ASTER allowed us to recognize or separate iron oxide minerals, clay-bearing minerals, sulfate minerals, ammonia minerals, siliceous rocks, and carbonates. Combined with laboratory spectral measurements, we were able to identify these constituents. Based on both sets of information, we produced an alteration map showing the distribution of argillized rocks, opalized rocks with alunite, silicified rocks, and areas dominated by kaolinite and buddingtonite. The map was as accurate as published maps made by traditional field methods. ASTER promises to be a major improvement over existing satellite systems for geologic mapping.

Advanced↗
NASA NTRS1992

Concept of ASTER calibration requirement

The document of ASTER Calibration Requirement specifies the following items related to spectral and radiometric characteristics of the ASTER instrument: (1) characteristics whose knowledge is specified, (2) requirement for knowledge of the characteristics, (3) methodology for characteristics evaluation, and (4) supplementary information and data related with characteristics evaluation. This document is applicable to the document of the ASTER Instrument Specification on Observational Performances, and will be a part of the ASTER Calibration Plan. ASTER Calibration Requirement is scheduled to establish the concept and framework by March 1992 when the 5th Calibration and Data Validation Panel Meeting is held, and to determine details including requirement values and evaluation methodologies by October 1992 around which the Calibration Peer Review may be held. The ASTER Calibration Plan is planned to finish by the same time.

Ono, A.↗
NASA NTRS2011

On-Orbit Spatial Characterization of MODIS with ASTER Aboard the Terra Spacecraft

This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (MODIS) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of MODIS, making it feasible to characterize MODIS on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit MODIS BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each MODIS band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each MODIS band. The best measurement match between ASTER and each MODIS band is obtained when the measurement difference reaches its weighted minimum. The position of each MODIS band in the AMPC is then used to calculate the BBR. The results are compared with those derived from MODIS onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 MODIS pixel. This approach is useful for other sensors without onboard spatial characterization capability. Index Terms Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), band-to-band registration (BBR), MODerate resolution Imaging Spectroradiometer (MODIS), spatial characterization.

Xie, Yong↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Alamosa and Saguache Counties, Colorado

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Archuleta County

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Dolores County

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Fremont County, Colorado

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Routt County, Colorado

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled"warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, San Miguel County, Colorado

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Northern Saguache County, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data around Pinkerton Hot Springs, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Northwest Delta, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Ouray, Colorado

This map shows areas of anomalous surface temperature in Ouray identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data around South Canyon Hot Springs, Garfield County, Colorado

This map shows areas of anomalous surface temperature around South Canyon Hot Springs as identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Southwest Steamboat Springs, Garfield County, Colorado

This map shows areas of anomalous surface temperature around south Steamboat Springs as identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
NASA NTRS1993

ASTER, a multinational Earth observing concept

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a facility instrument selected for launch in 1998 on the first in a series of spacecraft for NASA's Earth Observing System (EOS). The ASTER instrument is being sponsored and built in Japan. It is a three telescope, high spatial resolution imaging instrument with 15 spectral bands covering the visible through to the thermal infrared. It will play a significant role within EOS providing geological, biological, land hydrological information necessary for intense study of the Earth. The operational capabilities for ASTER, including the necessary interfaces and operational collaborations between the US and Japanese participants, are under development. EOS operations are the responsibility of the EOS Project at NASA's Goddard Space Flight Center (GSFC). Although the primary EOS control center is at GSFC, the ASTER control facility will be in Japan. Other aspects of ASTER are discussed.

Bothwell, Graham W.↗