FUZZY MODELING OF SOIL SALINITY BASED ON SPECTRAL INDICATORS DERIVED FROM DIGITAL IMAGERY

This study addresses the assessment of soil salinity levels in irrigated agricultural lands using digital remote sensing data. The main objective of the research is to develop a mathematical model for the quantitative assessment of soil salinity by processing spectral information contained in digital imagery and remote-sensing indicators associated with salinity on the basis of fuzzy set theory. The proposed approach considers the use of membership functions to account for the natural and transitional nature of salinity boundaries, the fuzzy evaluation of different spectral indicators, and their aggregation into a single integral salinity indicator. Based on the model, an algorithm for spatial identification and digital mapping of salinity levels is envisaged. The research results are aimed at establishing a scientific and methodological basis for rapid and spatially differentiated assessment of the salinity status of irrigated agricultural lands, supplementing existing field studies with remote sensing data, and automating salinity monitoring.

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