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Routine interpretation of optical sensor data requires the design and development of efficient and reliable data analysis methods, including pre-processing tools to remove contamination of the sensor signal through combined sensor-atmosphere effects as well as suitable inversion models and/or direct mapping algorithms. Imaging spectrometers provide reflectance spectra in the complete solar spectrum through a sequence of contiguous spectral bands. In this experiment, linear spectral mixture analysis is used to decompose AVIRIS spectra into their spectrally distinct components, the fractional abundance of which then provides a largely unbiased measure for direct mapping of vegetation abundance and the identification of soil degradation levels and erosion hazards. Ground verification in a well-controlled test site in the south of France showed very high accuracy in the identification of soil degradation levels.

Additional information

Authors: HILL J, JRC Ispra (IT);MEHL W, JRC Ispra (IT);ALTHERR M, JRC Ispra (IT);SMITH M O, University of Washington, Department of Geological Sciences, Seattle (US)
Bibliographic Reference: Paper presented: 25th International Symposium, Remote Sensing and Global Environmental Change, Graz (AT), April 4-8, 1993
Availability: Available from (1) as Paper EN 37499 ORA
Record Number: 199310932 / Last updated on: 1994-11-29
Original language: en
Available languages: en
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