Russian Federation
Russian Federation
UDC 528.88
UDC 911.3
The article analyzes the impact of natural factors on the condition of agricultural lands in Dong Nai Province using remote sensing (RS) and geographic information system (GIS) technologies. The study covers the period of 2022, utilizing multispectral Landsat 8 images and SRTM radar data to assess key indicators such as the vegetation index (NDVI), soil moisture index (NDMI), land surface temperature (LST), and terrain characteristics, including elevation, slope, and aspect. A scoring model was developed to determine land suitability for agricultural use, based on normalized data and incorporating positive, negative, and neutral indicators. The spatial distribution of scores was visualized using kriging interpolation, enabling the identification of areas with high and low agricultural potential. The main results of the study highlight the most promising areas for agricultural use and provide recommendations for their optimization. The data obtained confirm the high accuracy of the proposed model in identifying areas with the healthiest vegetation cover. The application of the proposed approach contributes to the sustainability and productivity of agricultural resources, which is particularly relevant in the context of climate change and increasing demand for food. Thus, the article makes a significant contribution to the development of land resource management methods, offering practical tools for strategic planning and enhancing the efficiency of agricultural land use. The results are applicable not only to current agricultural activities but also to long-term strategies in agriculture.
agricultural lands, NDVI, NDMI, aspect, land surface temperature (LST), euclidean distances, remote sensing, scoring assessment, interpolation
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