Minimization of atmospheric effects on the ISVI spectral vegetation index

Abstract

It is essential to minimize atmospheric effects on spectral information of remote sensors from space platforms to avoid under estimation of biophysical variables associated with satellite image data. In this paper, a generic algorithm was developed, based on sound theoretical arguments, to analyze time series ISVI spectral vegetation index (vegetation index based on iso-soil curves), thus avoiding the problems associated with the classic design of vegetation indices, where the spectral signal saturates quickly. The results, when applying the algorithm in pixel time series of AVHRR satellite images, showed that reduction and standardization of atmospheric effects in the ISVI was achieved. Using ISVI maximum values in time series (temporal window), a reasonable approximation to atmospheric conditions with minimum or standardized effects was obtained. In conclusion, although the scheme developed failed to eliminate the atmospheric effect on ISVI entirely, it was reduced to a minimum. The algorithm developed was simple enough for operational use, with regard to atmospheric correction methods using radiative model inversions.