IMPROVING THE METHOD FOR COMPREHENSIVE ASSESSMENT OF DEHKAN FARM LANDS

Abstract

This article proposes an improved method for comprehensive assessment of dehkan farm lands based on the integration of remote sensing, land-cadastral, soil, irrigation and official statistical data within a unified geospatial analysis framework. The methodological basis was developed through a comparative review of the European Union Area Monitoring System (AMS), the USDA Cropland Data Layer (CDL), the FAO WaPOR platform and the Indian FASAL/CAPE approach. Official statistics for Beshariq District show that agriculture, forestry and fisheries generated UZS 2.9 trillion in 2024, while dehkan and household farms accounted for 58.5% of agricultural output in January–September 2024. The proposed methodology treats the cadastral parcel as the principal assessment unit and combines multi-temporal Sentinel-2/Sentinel-1 observations with soil, irrigation, cadastral and production indicators. The indicators are normalized to a 0–1 scale, weighted using the Analytic Hierarchy Process (AHP), and aggregated into a Comprehensive Assessment Index (CAI). The paper also proposes a five-level classification and a validation scheme based on field observations, yield data and parcel-level spatial statistics. The approach is intended to improve the objectivity, repeatability and management relevance of land monitoring for dehkan farms.