Аннотация
This study assesses the spatial patterns of modeled environmental sensitivity in Eastern Kazakhstan using the Mediterranean Desertification and Land Use (MEDALUS) framework integrated with satellite remote sensing and cloud-based geospatial analysis.Four composite indices were calculated: the Soil Quality Index (SQI), Vegetation Quality Index (VQI), Climate Quality Index (CQI), and Management Quality Index (MQI).Twenty indicators derived from remote sensing products, climate datasets, soil databases, and socio-economic spatial data were integrated to generate the Environmental Sensitivity Area (ESA) index.The results demonstrate clear spatial differentiation of modeled environmental sensitivity across Eastern Kazakhstan.Mountainous and forested landscapes of the Altai region show relatively lower sensitivity levels, whereas intermontane depressions and steppe lowlands exhibit higher sensitivity classes associated with differences in climate conditions, vegetation characteristics, soil properties, and landscape structure.Correlation analysis indicates strong statistical associations of VQI and CQI with ESA spatial variability, while SQI contributes substantially to sensitivity patterns in mountainous and foothill areas.MQI demonstrates more localized associations in areas affected by mining, urban development, and transport infrastructure.The findings demonstrate the applicability of integrated geospatial approaches for regional-scale environmental sensitivity assessment and provide spatial information to support sustainable land management planning in Eastern Kazakhstan.