Modelling the future vulnerability of urban green space for priority-based management and green prosperity strategy planning in Kolkata, India: a PSR-based analysis using AHP-FCE and ANN-Markov model

Changes in land-use and land-cover (LULC) urban areas affect the natural environment, especially green spaces (UGS). The present study examines loss of UGS due to LULC transformation at different periods predict future vulnerable zone UGS, based on 'Pressure-State-Response’ framework. To calculate weight each factor, a combined Analytical Hierarchical Process Fuzzy Comprehensive Evaluation method have been used. An integrated multilayer perceptron artificial neural network Markov chain (MLP-ANN-MC) model has employed area Kolkata. Results indicated that growth rates built-up area, dynamic degree, change intensity index, proximity factors are major responsible for vulnerability. Applying MLP-ANN-MC model, zones were identified management conservation UGS. methodology developed demonstrated this expands analysis provide new dimension vulnerability assessment.