Quantifying and Predicting Urban Sprawl in Sargodha, Punjab: A Remote Sensing and MLP‑Markov Chain Approach

Abstract

Urbanization, the conversion of rural landscapes into built environments, has accelerated rapidly in developing nations. In Pakistan—where the 2017 census recorded a 36.38% urbanization rate—medium‑sized cities in Punjab play a pivotal role in this transition. This study examines urban growth in Sargodha City through three integrated components: (1) historical land‑use/land‑cover (LULC) analysis using remote sensing from 1998 to 2022; (2) future LULC prediction employing a Multilayer Perceptron–Markov Chain Analysis (MLP–MCA) model; and (3) a structured questionnaire assessing residents’ perceptions of urbanization impacts. Landsat imageries were classified as quantifying LULC changes, revealing a ~5%—18% (between 1998—2022) rise in built‑up area. The MLP–MCA model—calibrated with 10,000 iterations, 50% training/testing samples, static (aspect, slope, elevation) and dynamic (road proximity) variables—achieved 89.19% accuracy and a Kappa of 0.89. A stratified Likert‑scale survey of 385 participants captured attitudes toward urban growth, land‑use change, and associated socio‑environmental effects. Built‑up area expanded from ~77 km²(5%) to ~278 km²(18%) (1998–2022) and is projected to reach 29% (~454 km²) of the study area by 2035 and 32% (~506 km²) by 2050, with hotspots in northwestern and southeastern sectors. Residents reported mixed sentiments: many acknowledge economic and infrastructural benefits, while concerns center on environmental degradation, resource strain, and uneven planning. Awareness of urbanization metrics varied across demographic groups. Sargodha’s transformation from an agrarian landscape toward a predominantly urban environment underscores an accelerating trend that—although currently below national average demands proactive planning. Integrating empirical LULC projections with local perceptions offers a comprehensive framework for sustainable urban management in medium‑sized cities of Punjab.