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NASA NTRS1999

Enhancement of Capabilities in Hyperspectral and Radar Remote Sensing for Environmental Assessment and Monitoring

The University of Utah, Department of Geography has developed a research and instructional program in satellite remote sensing and image processing. The University requested funds for the purchase of software licenses, mass storage for massive hyperspectral imager data sets, upgrades for the central data server to handle the additional storage capacity, a spectroradiometer for field data collection. These purchases have been made. This equipment will support research in one of the newest and most rapidly expanding areas of remote sensing.

Hepner, George F.↗
NASA NTRS1999

SeaWiFS Postlaunch Technical Report Series: The 1997 Prelaunch Radiometric Calibration of SeaWiFS - Volume 4

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) was originally calibrated by the instrument's manufacturer, Santa Barbara Research Center (SBRC), in November 1993. In preparation for an August 1997 launch, the SeaWiFS Project and the National Institute of Standards and Technology (NIST) undertook a second calibration of SeaWiFS in January and April 1997 at the facility of the spacecraft integrator, Orbital Sciences Corporation (OSC). This calibration occurred in two phases, the first after the final thermal vacuum test, and the second after the final vibration test of the spacecraft. For the calibration, SeaWiFS observed an integrating sphere from the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) at four radiance levels. The spectral radiance of the sphere at these radiance levels was also measured by the SeaWiFS Transfer Radiometer (SXR). In addition, during the calibration, SeaWiFS and the SXR observed the sphere at 16 radiance levels to determine the linearity of the SeaWiFS response. As part of the calibration analysis, the GSFC sphere was also characterized using a GSFC spectroradiometer. The 1997 calibration agrees with the initial 1993 calibration to within +/- 4%. The new calibration coefficients, computed before and after the vibration test, agree to within 0.5%. The response of the SeaWiFS channels in each band is linear to better than 1%. In order to compare to previous and current methods, the SeaWiFS radiometric responses are presented in two ways: using the nominal center wave-lengths for the eight bands; and using band-averaged spectral radiances. The band-averaged values are used in the flight calibration table. An uncertainty analysis for the calibration coefficients is also presented.

Hooker, Stanford B.↗
NASA NTRS1999

Intercomparison of Satellite-Derived Snow-Cover Maps

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Hall, Dorothy K.↗
NASA NTRS1998

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Hall, D. K.↗
NASA NTRS1998

Remote Sensing of Tropospheric Aerosols from Space: Past, Present, and Future

Aerosol particles originate from man-made sources such as urban/industrial activities,rurning associated with land use processes, wind-blown dust, and natural sources. Their interaction with sunlight and their effect on cloud microphysics forms a major uncertainty in predicting climate change. Furthermore, the lifetime of only a few days causes high spatial variability in aerosol optical and radiative properties that requires global observations from space. Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sun-photometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

King, Michael D.↗
NASA NTRS1998

Clouds, Radiation, and Climate from the Earth Observing System

In this presentation, I will present and discuss key areas of scientific uncertainty in understanding climate and global change, focusing on specific examples of how EOS will contribute to improving our understanding of global change. In particular, I will describe how scientists intend to use MODIS, an earth-viewing cross-track scanning spectroradiometer to be flown on the Earth Observing System (EOS) AM-1 satellite to be launched in summer 1998, for the remote sensing of cloud properties. MODIS will scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and will provide images in 36 spectral bands between 0.415 and 14-235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmosphere processes. As part of this presentation, I will review the various methods that have been developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. Additional applications of MODIS data to the determination of precipitable water over land will be described, as will the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, shadows on the ground, and fires. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application to aircraft and/or satellite measurements.

King, Michael D.↗
NASA NTRS1999

EOS Science Plan and EOS Science Plan Executive Summary

Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper, we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sunphotometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

King, Michael D.↗
NASA NTRS1999

Earth Observing System: Present Capabilities and Promises for the Future

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year 5 EOS science missions are scheduled for launch, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) atmospheric chemistry (both tropospheric and stratospheric). In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists intend to use MODIS, an earth-viewing cross-track scanning spectroradiometer to be launched on the Terra satellite in summer 1999, for the remote sensing of cloud and aerosol properties. MODIS will scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km. In addition, I will describe key elements of other instruments recently launched or planned for flight in the coming months. Finally, I will lay out a plan for the future space-based observing system being planned by NASA and its partners.

King, Michael D.↗
NASA NTRS1999

Assessed Using Satellite Data and Ground Based Sun/Sky Radiometers

The short aerosol lifetime and the variety of sources and atmospheric processes that affect the aerosol concentration and properties, generate a very heterogeneous aerosol field. Satellite data are needed to assess the daily global distribution of aerosol loading, properties and radiative forcing of climate. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument launched in July 1999 measures the aerosol properties and backscattered radiation in 7 spectral channels across the solar channel with spatial resolution of 500 m. Novel inversion techniques are used to derive the aerosol forcing at the top of the atmosphere in these 7 spectral bands with even higher accuracy than the derivation of the aerosol loading or microphysical properties. But satellites cannot sense the aerosol attenuation of radiation reaching the Earth surface. A network of 100 sun/sky radiometers, members of the AErosol RObotic NEtwork (AERONET) is used to assess, simultaneously, the radiative forcing of aerosol at the surface level. The relevance of MODIS and AERONET to assess the global aerosol forcing, and the inversion techniques will be presented and discussed.

Kaufman, Yoram J.↗
NASA NTRS1999

Earth Science Data Archive and Access at the NASA/Goddard Space Flight Center Distributed Active Archive Center (DAAC)

The Goddard Distributed Active Archive Center (DAAC), as an integral part of the Earth Observing System Data and Information System (EOSDIS), is the official source of data for several important earth remote sensing missions. These include the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) launched in August 1997, the Tropical Rainfall Measuring Mission (TRMM) launched in November 1997, and the Moderate Resolution Imaging Spectroradiometer (MODIS) scheduled for launch in mid 1999 as part of the EOS AM-1 instrumentation package. The data generated from these missions supports a host of users in the hydrological, land biosphere and oceanographic research and applications communities. The volume and nature of the data present unique challenges to an Earth science data archive and distribution system such as the DAAC. The DAAC system receives, archives and distributes a large number of standard data products on a daily basis, including data files that have been reprocessed with updated calibration data or improved analytical algorithms. A World Wide Web interface is provided allowing interactive data selection and automatic data subscriptions as distribution options. The DAAC also creates customized and value-added data products, which allow additional user flexibility and reduced data volume. Another significant part of our overall mission is to provide ancillary data support services and archive support for worldwide field campaigns designed to validate the results from the various satellite-derived measurements. In addition to direct data services, accompanying documentation, WWW links to related resources, support for EOSDIS data formats, and informed response to inquiries are routinely provided to users. The current GDAAC WWW search and order system is being restructured to provide users with a simplified, hierarchical access to data. Data Browsers have been developed for several data sets to aid users in ordering data. These Browsers allow users to specify spatial, temporal, and other parameter criteria in searching for and previewing data.

Leptoukh, Gregory↗
NASA NTRS1999

A Prototype MODI- SSM/I Snow Mapping Algorithm

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Tait, Andrew B.↗
NASA NTRS1999

Utilizing Multiple Datasets for Snow Cover Mapping

Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

Tait, Andrew B.↗
NASA NTRS1999

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Salomonson, Vincent V.↗
NASA NTRS1997

The Algorithm for MODIS Wavelength On-Orbit Calibration using the SRCA

The Spectro-Radiometric Calibration Assembly (SRCA) provides on-orbit spectral calibration of the MODerate resolution Imaging Spectroradiometer (MODIS) reflected solar bands and this paper describes how it is accomplished. The SRCA has two adjacent exit slits: 1) Main slit and 2) Calibration slit. The output from the main slit is measured by a reference silicon photo-diode (SIPD) and then passes through the MODIS. The output from the calibration slit passes through a piece of didymium transmission glass and then it is measured by a calibration SIPD. The centroids of the sharp spectral peaks of a didyrnium glass are utilized as wavelength standards. After normalization using the reference SIPD signal to eliminate the effects of the illuminating source spectra, the calibration SIPD establishes the relationship between the peaks of the didymium spectra and the grating angle; this is accomplished through the grating equation. In the grating equation the monochromator parameters, beta (half angle between the incident and diffractive beams) and theta(sub ff) (offset angle of the grating motor) are determined by matching, in a least square sense, the known centroid wavelengths of the didymium peaks and the calculated centroid grating angles from the calibration SIPD signals for the peaks. A displacement between the calibration SIPD and the reference SIPD complicates the signal processing. The response of the MODIS bands to the SRCA output is also normalized by the reference SIPD signal to eliminate the effect of the source spectrum. That response differs from what is measured by MODIS using the Spectral Measurements Assembly (SpMA), a laboratory double-monochromator, due to the wider slit width of the SRCA. The SRCA slit function, calculated using measurements by the SPMA and the SRCA at the same MODIS temperature, will be used to recover the MODIS spectral response using the SRCA data measured on-orbit.

Montgomery, Harry↗
NASA NTRS1998

Enabling High Performance Reconfigurable Ground Data Processing Systems

The deployment of high data rate instruments onboard satellites with direct broadcast capability demands the implementation of powerful ground data processing systems. Conversely, to enable the widespread usage of direct broadcast data and the generation of subsequent data products, low cost data processing systems must be available. Reconfigurable computers based on Field Programmable Gate Arrays (FPGA) enable the implementation of ground data processing systems that lead to higher performance and lower cost while keeping a high degree of programmability and maintainability. This paper presents the conceptualization of the MODIS Adaptive Level One Accelerator (ALOA), a prototype under construction at NASA's Goddard Space Flight Center. The ALOA is a computer workstation augmented by a reconfigurable computer. The system will calibrate and geographically locate data from the EOS-AM1 MODerate resolution Imaging Spectroradiometer (MODIS) instrument at near real-time data rates.

Hines, Tonjua M.↗
NASA NTRS1999

Hyperspectral Imaging and Related Field Methods: Building the Science

The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

Goetz, Alexander F. H.↗
NASA NTRS1998

MODIS Science Team Member Semi-annual Report

This paper presents a semi-annual report of the MODerate resolution imaging Spectroradiometer (MODIS) Science Team Members. The most important activities undertaken during this reporting period are the following: 1) Versions 2.1 and 2.2 surface reflectance L2/L3 DAAC/SDST delivery; 2) Version 2.0 1km and 250m VI product delivery (assist Arizona); 3) Version 2.1 surface reflectance L2 testing; 4) Land Synthetic data set generator improvements; 5) QA; 6) Surface reflectance error budget generation (SWAMP request); 7) SCF Hardware; 8) Aerosol transport modeling; 9) Aerosol optical depth retrieval from AVHRR data; 10) Aerosol characteristics retrieval from SeaWIFS/AVHRR fusioned data; 11) Validation activities; 12) Aerosol climatology; and 13) 6S code. The report includes summaries of the topics above.

Vermote, Eric↗
NASA NTRS1998

Laboratory Studies of Carbon Emission from Biomass Burning for use in Remote Sensing

Biomass burning is a significant source of many trace gases in the atmosphere. Up to 25% of the total anthropogenic carbon dioxide added to the atmosphere annually is from biomass burning. However, this gaseous emission from fires is not directly detectable from satellite. Infrared radiance from the fires is. In order to see if infrared radiance can be used as a tracer for these emitted gases, we made laboratory measurements to determine the correlation of emitted carbon dioxide, carbon monoxide and total burned biomass with emitted infrared radiance. If the measured correlations among these quantities hold in the field, then satellite-observed infrared radiance can be used to estimate gaseous emission and total burned biomass on a global, daily basis. To this end, several types of biomass fuels were burned under controlled conditions in a large-scale combustion laboratory. Simultaneous measurements of emitted spectral infrared radiance, emitted carbon dioxide, carbon monoxide, and total mass loss were made. In addition measurements of fuel moisture content and fuel elemental abundance were made. We found that for a given fire, the quantity of carbon burned can be estimated from 11 (micro)m radiance measurements only within a factor of five. This variation arises from three sources, 1) errors in our measurements, 2) the subpixel nature of the fires, and 3) inherent differences in combustion of different fuel types. Despite this large range, these measurements can still be used for large-scale satellite estimates of biomass burned. This is because of the very large possible spread of fire sizes that will be subpixel as seen by Moderate Resolution Imaging Spectroradiometer (MODIS). Due to this large spread, even relatively low-precision correlations can still be useful for large-scale estimates of emitted carbon. Furthermore, such estimates using the MODIS 3.9 (micro)m channel should be even more accurate than our estimates based on 11 (micro)m radiance.

Wald, Andrew E.↗