International Journal of Environment and Climate Change

Aims: To assess the spatial and temporal changes in the land cover of Bengaluru Urban district, Karnataka, India, over a thirty-year period (1992-2022) using remote sensing and GIS techniques.

Study Design: Multi-temporal satellite image classification and post-classification change detection analysis.

Place and Duration of Study: Bengaluru Urban district, Karnataka, India (77°19′44″–77°50′13″ E and 12°39′32″–13°14′13″ N); Department of Forest Resource Management, College of Forestry, Ponnampet, Keladi Shivappa Nayaka University of Agricultural and Horticultural Sciences, Shivamogga, using satellite data spanning 1992 to 2022.

Methodology: Post-monsoon-season Landsat 4-5 TM C2L1 and Landsat-8 OLI/TIRS C2L1 images for seven epochs (1992, 1997, 2002, 2007, 2012, 2017 and 2022) were downloaded from the USGS EarthExplorer and classified in QGIS into four land-cover classes: Built-up, Water Bodies, Vegetation and Others, using supervised Gaussian Maximum Likelihood Classification. Classification reliability was evaluated using the Kappa coefficient, and interval-wise post-classification change detection was performed between each pair of consecutive epochs.

Results: Built-up area increased by 288% (nearly quadrupling), from 281.87 km² (13% of the district) in 1992 to 1,094.15 km² (50%) in 2022, while vegetation cover declined by 61.33%, from 1,162.30 km² (53%) to 449.46 km² (20%), over the same period. Built-up growth was fastest between 1997 and 2012 (+15, +4 and +8 percentage points per interval) and slowed to +3 percentage points between 2017 and 2022, the only interval in which vegetation share also rose marginally (+2 percentage points). A full-period conversion matrix showed that direct vegetation-to-built-up conversion (467.00 km²) was the single largest contributor to built-up growth, followed by conversion from the others class (306.11 km²). Overall classification accuracy across the seven epochs ranged from 88.5% to 92.8%, with a Kappa coefficient of 0.84 for 2022.

Conclusion: Bengaluru Urban district has undergone rapid and largely unplanned urban expansion at the cost of vegetation cover over the past three decades, with the pace of built-up growth concentrated in the 1997–2012 period and decelerating thereafter. Remote sensing and GIS-based multi-temporal classification provides an efficient, reproducible approach to long-term monitoring of urban land-cover change and can support evidence-based land-use planning in rapidly urbanising Indian cities.