Abbos Khamidov
About
My research project
Soil salinity monitoring, mapping, and assessment in Mirzaabad district, Syrdarya province, UzbekistanSoil salinity is a major land degradation problem in Uzbekistan, where more than half of the irrigated land is affected. It prevents crops from growing, developing, and producing higher yields sustainably. With the added pressures of global climate change, including rising temperatures and reduced precipitation, the extent of salinized soils in the country continues to expand. To ensure the sustainable growth, development, and productivity of crops, it is crucial to monitor, map, and assess soil salinity using reliable approaches.
My research focuses on identifying which land use and land cover (LULC) types contribute most to soil salinity and explain its variability, predicting salinity at different soil depths using salinity indices, integrating remote sensing data with Machine Learning algorithms, and evaluating the suitability of water for irrigation in the study area. These efforts are valuable because they provide practical insights for improving land management, guiding irrigation practices, and supporting strategies to reduce soil salinity and ensure sustainable agricultural production.
Supervisors
Soil salinity is a major land degradation problem in Uzbekistan, where more than half of the irrigated land is affected. It prevents crops from growing, developing, and producing higher yields sustainably. With the added pressures of global climate change, including rising temperatures and reduced precipitation, the extent of salinized soils in the country continues to expand. To ensure the sustainable growth, development, and productivity of crops, it is crucial to monitor, map, and assess soil salinity using reliable approaches.
My research focuses on identifying which land use and land cover (LULC) types contribute most to soil salinity and explain its variability, predicting salinity at different soil depths using salinity indices, integrating remote sensing data with Machine Learning algorithms, and evaluating the suitability of water for irrigation in the study area. These efforts are valuable because they provide practical insights for improving land management, guiding irrigation practices, and supporting strategies to reduce soil salinity and ensure sustainable agricultural production.