Abstract
Abstract The use of a vegetation index in the study of vegetation changes requires that the influences of the signal gain, of atmospheric conditions and of soil be removed. This paper presents a theoretical basis for technique that theoretically removes all these influences from raw data without the use of external inputs. It produces a normalized perpendicular vegetation index that is suitable for vegetation change studies based on non-corrected radiometric data. For several years our remote sensing group has worked on techniques to compare multi-temporal raw data images. It has developed two techniques to normalize vegetation index values (Caloz et al. 1986, Collet and Abednego 1987, Abednego 1989) and soil index values (Caloz et al. 1988, Abednego 1989) derived from uncorrected digital values acquired by satellite remote sensing systems.
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