ABSTRACT Understanding, analyzing, monitoring, and modeling urban expansion are essential for urban planners aiming to achieve sustainable development. Various geospatial techniques, such as quantitative and spatiotemporal models, can be applied to identify areas undergoing environmental transformation and shifts in urban layout. The use of geospatial analysis to examine Land Use/Land Cover (LULC) patterns is crucial for formulating and implementing effective urban development policies. Planners and policymakers increasingly rely on comprehensive metrics that integrate diverse datasets, spatial analysis, and qualitative assessments. This study investigated the spatiotemporal processes of urban expansion through geospatial analysis. A comprehensive approach was adopted to analyze the dynamics and transitions in LULC using satellite data from the years 2000, 2010, and 2021. Key explanatory variables included vegetation, urban land, bare land, water bodies, and infrastructure elements such as roads and urban centers, which were used to assess specific trends and spatial patterns. LULC modeling was performed using the Random Forest algorithm within the Google Earth Engine platform. The accuracy assessment of the model indicated satisfactory performance compared to previous studies. The results revealed that urban growth in Peshawar was 22.41% from 2000 to 2010 and 7.46% from 2010 to 2021, with an overall increase of 31.54% over the two‐decade period. This expansion has significantly contributed to the degradation of green spaces and water resources, placing Peshawar among cities facing considerable environmental stress. These outcomes highlight a need for urgency for strategies that are not only innovative but also adaptive in nature. Initiatives such as smart city development and data‐driven resource management are vital to improving urban resilience, managing infrastructure demands, and enhancing the quality of life amid rapid urbanization and growing population pressures.
Liang et al. (Sun,) studied this question.