MAPPING IRRIGATED AGRICULTURAL LANDS USING REMOTE SENSING DATA: A CASE STUDY OF ORTACHIRCHIK DISTRICT, UZBEKISTAN
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Abstract
This paper presents a remote sensing-based approach for identifying and mapping irrigated agricultural lands in O‘rtachirchiq District, Tashkent region, Uzbekistan. A time series of the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 imagery was used to calculate the maximum seasonal value (NDVImax) for each pixel. Irrigated areas were identified by integrating NDVImax with a cropland mask derived from the ESA WorldCover dataset. The resulting maps reveal the spatial distribution of irrigated lands and demonstrate the practical potential of satellite data for agricultural land monitoring and spatial planning.
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