GROUND-BASED MULTICRITERIA METHOD FOR VALIDATING THE RESULTS OF REMOTE SENSING OF SOIL SALINITY

Currently, the indices used to estimate the degree of salinity of the soil, calculated as the ratio of samples in the visible and infrared regions, are more informative than the indices based on measurements in the one spectral zone. The normalized difference index of salinity calculated on the Landsat OLI database has a fairly strong correlation with the electrical conductivity of the soil. Extreme combined indices are of some interest for the validation of the results of on-board measurements of soil salinity, where the possibility of automating the search for the extremum of such combined indices allows for the validation of the results of on-board estimates of soil salinity. The purpose of this work is (a) to study the possibility of developing a new, essentially extreme spectral composite index for assessing the salinity of land plots, where the first component of this index is calculated from the well-known model of on-board measurements, and the second from the results of ground measurements: (b) to study the possibility of using the proposed extreme index to validate the results of remote sensing of soil salinity. The article presents the theoretical foundations of the proposed new multicriteria method for validating the results of on-board measurements. The extreme property of scalar convolution of the multi-criteria optimization method, which is a weighted linear combination of partial criteria, is used as a basis. To validate on-board data, the sign of the appearance of an extremum in the target functional is used when using the results of ground and on- board measurements separately as a general argument. In this case, the measurements are carried out on the test site, where there is a gradient of soil salinity in geometric coordinates. The coincidence of the geometric locations of the occurrence of extremes in two cases indicates a positive result of the validation.

optimization, validation, soil, salinity, ground measurements, scalar convolution, remote sensing, combined indices, airborne measurements, test site

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