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

Abstract

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

Keywords:

• Urban green space
• AHP-FCE
• artificial neural network-Markov chain
• land-use simulation
• future vulnerable zone
• Kolkata

Acknowledgements

Dinda, S and Ghosh, S acknowledges the University Grants Commission (UGC), India for providing continuous research fellowship (JRF-SRF Research Fellowship) for carrying out the research at Vidyasagar University. The authors have acknowledged the Department of Science and Technology (DST), Government of India, for providing financial assistance to the Department of Geography, Vidyasagar University, Midnapore (India) to enhancing the skills for teaching and research.

Declarations

There has no specific funding particularly for this work but Dinda, S, and Ghosh, S is willing to thank the University Grant Commission (UGC), India for providing the research fellowship.

Disclosure statement

The authors declare that they have no conflict of interest.

Additional information

Funding

Dinda, S and Ghosh, S acknowledges the University Grants Commission (UGC), India for providing continuous research fellowship (JRF-SRF Research Fellowship) for carrying out the research at Vidyasagar University. The authors have acknowledged the Department of Science and Technology (DST), Government of India, for providing financial assistance to the Department of Geography, Vidyasagar University, Midnapore (India) to enhancing the skills for teaching and research.