Drought poses a critical threat to rangeland ecosystems, land use sustainability, and the resilience of infrastructure systems, including energy networks near urban fringes. This study applies a multi-index remote sensing approach to evaluate the spatial and temporal impacts of drought on rangelands by comparing nondrought (2023) and drought (2024) conditions. Satellite-derived indices such as Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Normalized Difference Vegetation Index (NDVI), Soil Moisture Index (SMI), Normalized Difference Water Index (NDWI), Temperature Condition Index (TCI), Land Surface Temperature (LST), Standardized Precipitation Index (SPI), Evaporative Stress Index (ESI), Palmer Drought Severity Index (PDSI), and Drought Severity Index (DSI) were integrated to characterize drought manifestations. Principal Component Analysis identified three core drought dimensions: vegetation response, thermal stress, and soil moisture dynamics, explaining 78% of the total variance. Notably, VCI, NDWI, and TCI emerged as the most sensitive indicators of drought stress. Western regions rangelands experienced the highest severity, while eastern regions showed greater ecological resilience. Land cover analysis revealed a 1.2% increase in rangeland area during drought, largely due to the conversion of shrublands, indicating a potential shift in vegetation regimes. These findings inform not only ecological management but also urban fringe planning, where land-use shifts under drought may affect infrastructure vulnerability and power system reliability. By offering a comprehensive, spatially explicit drought assessment framework, this study supports integrated land-use planning and enhances the adaptive capacity of socio-ecological and energy systems in semi-arid urbanizing regions. The results enhance our understanding of how rangeland ecosystems respond to drought and offer a methodological framework for assessing drought impacts in comparable semi-arid regions worldwide. (c) 2025 The Society for Range Management. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.