Remote Sensing and GIS in Urban Land Use Change Studies: A Review of Methods and Indian Applications

Abstract

Indian cities have expanded rapidly over the last four decades, often faster than planning records can follow. Satellite remote sensing, combined with geographic information systems (GIS), offers a consistent way to map how land is used and how it changes over time. This review examines the methods used in urban land use and land cover (LULC) change studies and the way they have been applied in India. It covers the main sources of free satellite imagery, image pre-processing, classification methods from maximum likelihood to random forests, spectral indices for built-up areas, vegetation and water, accuracy assessment, change detection, and measures of urban sprawl such as Shannon’s entropy. Indian studies have shown the value of these methods for cities such as Kolkata and Mangaluru, but many published studies share avoidable weaknesses: small or unreported validation samples, overall accuracy reported without area-adjusted estimates, and classification schemes that are not comparable between studies. The review recommends that urban LULC studies adopt current good-practice guidance on accuracy assessment, use cloud platforms such as Google Earth Engine to analyse long image series, and give more attention to the medium-sized cities, including Solapur, where most of India’s future urban growth is expected.