Proceedings of the Symposium on Global and Environmental Monitoring: Proceedings of the Symposium on Global and Environmental Monitoring

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Persistent identifier:: 856665355

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts ; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856665355

Language:: English

Document type:: Multivolume work

Volume

Persistent identifier:: 856669164

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Scope:: XIV, 912 Seiten

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856669164

Illustration:: Illustrationen, Diagramme, Karten

Signature of the source:: ZS 312(28,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [THP-1 HIGH SPECTRAL RESOLUTION MEASUREMENT]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ARTIFICIAL INTELLIGENCE FOR ANALYSIS OF IMAGING SPECTROMETER DATA. F. A. Kruse

Document type:: Multivolume work

Structure type:: Chapter

565 ARTIFICIAL INTELLIGENCE FOR ANALYSIS OF IMAGING SPECTROMETER DATA F. A. Kruse Center for the Study of Earth from Space (CSES) Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado, Boulder, CO 80309 ABSTRACT The Earth Observing System (EOS) scheduled to be launched in the late 1990s will carry high spectral resolution sensors called "imaging spectrometers" into orbit to begin observing in detail the geology and ecosystems of our planet. Imaging spectrometers measure near-laboratory-quality spectra in narrow spectral bands with a corresponding spatial image for each band. While they provide us with the means to improve the geologic mapping procedure by collecting detailed information about the Earth's surface, the major difficulty confronting scientists is that the immense volume of data collected by these systems prohibit detailed manual analysis. An expert system has been developed that allows automated identification of Earth surface materials based on their spectral characteristics in imaging spectrometer data. Field and laboratory spectral reflectance measurements were used to develop a generalized knowledge base for analysis of the visible and infrared reflectance spectra. The knowledge base allows the computer to make decisions similar to those made by an experienced analyst. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were used as an analog to the EOS High Spectral Resolution Imaging Spectrometer (HIRIS). A complete reflectance spectrum for each picture element (pixel) was derived directly from the imaging spectrometer data and automated techniques were used to extract and characterize absorption feature positions and shapes. Each spectrum was classified using a tree hierarchy emphasizing groups of materials with similar spectral characteristics. The final product of the automated analysis was an "image cube" showing the location and probability of occurrence of specific materials. This provides the starting point for detailed scientific analysis. KEY WORDS: Imaging spectrometers, Expert system, spectral analysis, Artificial intelligence, AVIRIS, HIRIS INTRODUCTION Many naturally occurring materials can be identified and characterized based on their reflected- light spectral characteristics. In geology, the exact positions and shapes of visible and infrared absorption bands are different for different minerals, and reflectance spectra allow direct identification (Hunt and Salisbury, 1970; Hunt et al., 1971; Hunt, 1977). Vegetation also has distinct absorption features caused by pigments, cell morphology, internal refractive index discontinuities, and water content (Gates et al., 1965; Knipling, 1970). Studies of plant constituents such as chlorophyll, lignin, sugar, starch, and protein have demonstrated that reflectance measurements can be used to obtain quantitative information about plant biochemistry, health, and productivity (Thomas and Oerther, 1972; Gausman, 1978; Peterson et al., 1988). Imaging spectrometers acquire continuous, near-laboratory-quality reflectance spectra in narrow bands. This makes possible direct identification of surface materials based on spectral characteristics (Figure 1) and presentation of the results as images. A complete spectrum for each picture element (pixel) can be derived from the data to allow quantification of physical parameters. Figure 1. The imaging spectrometer concept (from Vane, 1985). carried on the polar platform "Earth Observing System" (EOS) will provide high spatial and spectral resolution measurements of the Earth's surface for geologic and ecosystems investigations (NASA, 1987). The Moderate Resolution Imaging Spectrometer (MODIS) will make multispectral measurements on the continental scale (NASA, 1986). Simultaneous use of the the HIRIS and MODIS sensors will provide opportunities for nested measurements of high spatial and spectral resolution HIRIS data for selected sites on the regional scale within the lower resolution, synoptic scale MODIS images. These measurements will provide new information about

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