Predicting land use dynamics and ecosystem service valuation in the coal-affected region of Ramgarh, India: an integrated approach using cellular automata and artificial neural networks

This study aims to assess the impact of land use and land cover (LULC) changes on the monetary valuation of ecosystem service valuations (ESVs) in the coal mining-affected region of Ramgarh district, Jharkhand, India. The key objectives include (a) analyzing LULC dynamics from 1990 to 2021 and predicting changes for 2061 and (b) quantifying the gains and losses in ESVs across different land categories. To achieve this, satellite imagery was used to generate LULC maps for the years 1990 and 2021, while projections for 2061 were developed with the cellular automata-Markov model. The benefit transfer method was employed to estimate the ESVs based on per-hectare value coefficients assigned to specific land use types. Results reveal that between 1990 and 2021, the total ESV declined by approximately $18.52 million in U.S. dollars, primarily due to the loss of vegetation and water bodies. A further projected decline of $38.82 million is anticipated between 2021 and 2061, totaling a cumulative loss of $57.34 million over the study period. While cropland and built-up areas recorded marginal increases in ESVs, these gains were insufficient to compensate for the substantial losses in regulating and supporting services. The findings underscore the critical need to integrate ESV into land use planning, particularly in mining-intensive landscapes. The study demonstrates that without policy interventions favoring ecological conservation, continued land transformation will undermine long-term environmental sustainability and socioeconomic resilience in the region.