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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 / Santanu Dinda in Geocarto international, vol 37 n° 22 ([10/10/2022])  

Public [article]  inGeocarto international > vol 37 n° 22 [10/10/2022] . - pp 6551 - 6578 Titre : 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 Type de document : Article/Communication Auteurs : Santanu Dinda, Auteur ; Nilanjana Das Chatterjee, Auteur ; Subrata Ghosh, Auteur Année de publication : 2022 Article en page(s) : pp 6551 - 6578 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] chaîne de Markov [Termes IGN] changement d'occupation du sol [Termes IGN] croissance urbaine [Termes IGN] densité du bâti [Termes IGN] espace vert [Termes IGN] Inde [Termes IGN] logique floue [Termes IGN] modèle de simulation [Termes IGN] processus de hiérarchisation analytique [Termes IGN] réseau neuronal artificiel [Termes IGN] vulnérabilité [Termes IGN] zone urbaine dense Résumé : (auteur) 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. Numéro de notice : A2022-726 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1952315 Date de publication en ligne : 16/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1952315 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101672 [article]