Assessment of Drought Vulnerability in Faisalabad Through Remote Sensing and GIS

This research has used a multi-indices geospatial framework to combine the utilization of the Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI), and Standardized Precipitation Evapotranspiration Index (SPEI) to measure drought risk in Faisalabad Division, Pakistan (2015–2023). It integrated remote sensing, GIS analysis, and change detection in Land Use Land Cover (LULC) and used Moderate Resolution Imaging Spectroradiometer (MODIS) datasets along with SPEI grids. It was found that the spatial heterogeneity that occurred with District Jhang is at high risk because it is arid (SPEI −1.5), sparsely vegetated (NDVI 0.2), and has high thermal stress (TCI -30), whereas the central/eastern parts are resilient (NDVI 0.4) due to irrigation. Through MODIS LULC analysis, the occurrence of urban growth (13.42 km2 of vegetative cover loss), agricultural intensification, and afforestation (147.34 km2) were identified. As per the risk map, 74 percent of the area was defined as low risk (74 percent), 20 percent as moderate risk, and 6 percent as high risk. The findings highlight the role of water management in climate resilience. Future research should integrate high-resolution imagery, machine learning, and socioeconomic data for improved prediction.