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At least 163 records · Page 9

Spectral mapping of soil organic matter

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Kristof, S. J.↗

A solid state multispectral imager.

Photodiode arrays used as image sensors in satellite remote imaging systems offer the advantages of geometric accuracy, precise registration of scene elements, enhanced operational reliability, and wide spectral response. Principles of photodiode-array operation are reviewed, and the latest developments in self-scanned array chip technology are described along with optical system requirements for multispectral coverage. Results of development efforts with a spaceborne solid-state multispectral camera based on linear sensing array technology are outlined to demonstrate the capabilities of this approach to multispectral sensing.

Green, A.↗

A summary of Michigan program for earth resource information systems

A summary and guide to the development of earth resources information systems which employ multispectral remote sensing are reported. Major areas of activities center on improved throughput parallel processing systems, improved processing techniques, practical use of techniques in user applications, and improved sensors. Cost effectiveness considerations point to signature extension, parallel processing all-digital computers, and airborne multispectral imaging radar as some of the improvement technologies.

Erickson, J. D.↗

Determination of lunar ilmenite abundance from remotely sensed data

Of fundamental importance in the utilization of indigenous resources for a future permanently manned lunar base is the identification and mapping of the abundance distribution of the mineral ilmenite, which is currently considered the most readily identifiable and most easily accessible source of oxygen needed for human consumables and spacecraft propellant. Solid state detector array technology now permits the use of ground based multispectral remote sensing techniques to produce maps with better than one kilometer spatial resolution and uncertainties of about two weight-percent TiO2 abundance. An empirical relationship between the weight-percent abundance of titanium dioxide and the 400/560 nm spectral ratio measured in returned lunar samples was used. Because this abundance correlation is valid only for mature lunar mare regolith, the distribution of immature mafic minerals which were found to be correlated primarily with steep slopes exposing bedrock was qualitatively mapped. The first mapping phase focused on the entire lunar nearside at 5.3 km per pixel, and on experiments with more sensitive spectral ratios. Relative spectrophotometry was employed to aid in identifying wavelengths that provide greater spectral contrast. It was found that the 400/730 nm ratio improved the abundance sensitivity by 37 percent, while the 950/730 nm ratio improved mafic mineral contrast about 100 percent. The second mapping phase utilized a large experimental CCD at 280 m per pixel to map the high titanium regions identified in the phase one mapping. The high resolution maps provide data on the small scale (500 m) variations in abundance and their relationship to morphological units.

Larson, S. M.↗

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperatures

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (plus or minus 5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Laymon, Charles A.↗

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperature

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Laymon, Charles A.↗

Analytical inversions in remote sensing of particle size distributions. I - Multispectral extinctions in the anomalous diffraction approximation. II Angular and spectral scattering in diffraction approximations

Consideration is given to analytical inversions in the remote sensing of particle size distributions, noting multispectral extinctions in anomalous diffraction approximation and angular and spectral scattering in diffraction approximation. A closed-form analytical inverse solution is derived in order to reconstruct the size distribution of atmospheric aerosols. The anomalous diffraction approximation to Mie's solution is used to describe the particles. Experimental data yield the geometrical area of aerosol polydispersion. Size distribution is thus found from a set of multispectral extinction measurements. In terms of the angular and spectral scattering of light in a narrow forward cone, it is shown that an analytical inverse solution may also be found for the Fraunhofer approximation to the Kirchhoff diffraction, and for an improved expression of this approximation due to Penndorf (1962) and Shifrin-Punina (1968).

Fymat, A. L.↗

Multispectral color photography for mineral exploration by the remote sensing of biogeochemical anomalies

Selected band multispectral photography was evaluated as a mineral exploration tool by detecting stress on trees caused by underground mineralization. Ground truth consisted of two test sites in the Prescott National Forest within which the mineralization had been established by a drilling program. Species of trees were categorized as background, intermediate, and anomalous based upon where they grew with respect to this underlying mineralization. Soil geochemistry and the metal content of ashed samples of the trees were studied in relation to the inferred locus of mineralization. Computer analysis of the reflectance spectra of mineralized trees confirmed that the relative percent reflectance differences of trees growing in anomalous areas was less than that of the same tree species growing in background areas.

Yost, E.↗

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗

Atmospheric effects in multispectral remote sensor data

The problem of radiometric variations in multispectral remote sensing data which occur as a result of a change in geometric and environmental factors is studied. The case of spatially varying atmospheres is considered and the effect of atmospheric scattering is analyzed for realistic conditions. Emphasis is placed upon a simulation of LANDSAT spectral data for agricultural investigations over the United States. The effect of the target-background interaction is thoroughly analyzed in terms of various atmospheric states, geometric parameters, and target-background materials. Results clearly demonstrate that variable atmospheres can alter the classification accuracy and that the presence of various backgrounds can change the effective target radiance by a significant amount. A failure to include these effects in multispectral data analysis will result in a decrease in the classification accuracy.

Turner, R. E.↗

Mapping soil types from multispectral scanner data.

Multispectral remote sensing and computer-implemented pattern recognition techniques were used for automatic ?mapping' of soil types. This approach involves subjective selection of a set of reference samples from a gray-level display of spectral variations which was generated by a computer. Each resolution element is then classified using a maximum likelihood ratio. Output is a computer printout on which the researcher assigns a different symbol to each class. Four soil test areas in Indiana were experimentally examined using this approach, and partially successful results were obtained.

Kristof, S. J.↗

Identification and Mapping of Soils, Vegetation, and Water Resources of Lynn County, Texas, by Computer Analysis of ERTS MSS Data

Results of the analysis and interpretation of ERTS multispectral data obtained over Lynn County, Texas, are presented. The test site was chosen because it embodies a variety of problems associated with the development and management of agricultural resources in the Southern Great Plains. Lynn County is one of ten counties in a larger test site centering around Lubbock, Texas. The purpose of this study is to examine the utility of ERTS data in identifying, characterizing, and mapping soils, vegetation, and water resources in this semiarid region. Successful application of multispectral remote sensing and machine-processing techniques to arid and seminarid land-management problems will provide valuable new tools for the more than one-third of the world's lands lying in arid-semiarid regions.

Baumgardner, M. F.↗

Radiative transfer in real atmospheres

The problem of multiple radiation scattering in an atmosphere characterized by various amounts of aerosol absorption and different particle size distributions was investigated. The visible part of the spectrum was emphasized, including the effect of ozone absorption. An atmosphere bounded by a nonhomogenous, Lambertian surface was also studied, along with the effect of background radiation on target in terms of various atmopheric and geometric conditions. Results of the investigation indicate that comtaminated atmospheres can change the radiation field by a considerable amount, and that the effect of non-uniform surface significantly alters the intrinsic radiation from a target element. The implications of these results for the recognition processing of multispectral remote sensing data is discussed.

Turner, R. E.↗

The decision tree approach to classification

A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers.

Wu, C.↗

Breadboard linear array scan imager program

The performance was evaluated of large scale integration photodiode arrays in a linear array scan imaging system breadboard for application to multispectral remote sensing of the earth's resources. Objectives, approach, implementation, and test results of the program are presented.

Source record↗

Processing corrections for Skylab photographic imagery

Camera filters were inadvertently omitted from the six-channel multispectral photographic camera (S190A) during the exposure of the first roll of film from each channel on the final manned Skylab mission. Each of the films was overexposed and degraded as a result of the filter omissions. Explained are the techniques used by the NASA/JSC Photographic Technology Division to evaluate and process those films. These or similar techniques can be used in other photographic multispectral remote sensing applications in which black-and-white infrared and panchromatic or color infrared film are degraded due to loss of filtration or to overexposure. Results prove that data may be salvaged after camera exposure errors are made thus saving the expense of reacquiring data.

Lockwood, H. E.↗