Modeling and predicting spatio-temporal land use land cover changes and urban sprawling in Kalaburagi City Corporation, Karnataka, India: a geospatial analysis

The spatio-temporal dynamics and regional land use driving factors are fundamental considerations in achieving suitable and sustainable urban development. These aspects play a significant role in shaping cities’ physical, social, and environmental dimensions. This article aims to document and analyze the detection of LULC changes and their concentration, along with urban sprawl and prediction for the future. The study utilized multi-temporal satellite imageries of 2001, 2011, and 2021 to analyze the historical land cover, urban expansion, land transformation, growth direction, and urban sprawl in the study area. Subsequently, to predict and simulate future land use/land cover scenarios, the study employed an integrated cellular automata (CA)–Markov model using the theTerrSet software. The change detection results revealed that the built-up area had drastically increased from 17.90 to 40.64% from 2001 to 2021, and the barren land and agricultural land had significantly decreased. The transition matrix shows that the maximum barren land was converted into a built-up area and fallow land; at the same time, agriculture lost its maximum area, and built-up gained maximum area. The predicted LULC map of 2031 indicates specific patterns of change, including converting barren land into built-up areas and expanding vegetation cover due to reforestation and agricultural activities. The built-up area is projected to experience a significant increase and is estimated to expand by 62.29 km2, representing 50.46% of the total land-use area. Further, the study predicts a decrease in barren land over the ten years; the estimated change in barren land is 14.33%. The findings demonstrate that the model performed well in projecting the LULC of 2021, achieving an AUC (Area Under the Curve) of 78%. Additionally, the kappa coefficient of 0.8 further supports the model’s capability as a feasible representation of the study area. The study’s findings contribute to understanding LULC dynamics, urban sprawl, and future projections, and it provides crucial data for planning and decision-making processes, supporting sustainable land use management and informing strategies for suitable urban development in the study area.