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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Various urban environmental and social challenges have emerged during the rapid urban development. Urban agriculture has emerged as one of the practical solutions to address these urban issues and climate change. This study aims to establish a decision model for urban agriculture regeneration that can be applied to improve the implementation of related projects. The study first reviews existing research on Urban Agriculture within the Greyfield Regeneration Environments (UAGR) and outlines the processes involved, including project initiation, construction, and operation management. It identifies 25 factors influencing UAGR and employs the Fuzzy Delphi method (FDM) to prioritize them based on expert judgments. Subsequently, the interpretative structural model (ISM) analysis method is applied to analyze the interrelationships among the 11 most important factors. Matrix operations and MATLAB programming are utilized to establish the influence relationship model based on expert questionnaires to determine the influence between each pair of factors. This results in a hierarchically structured decision model for UAGR. Finally, the decision-making model is applied to analyze the case study in Shanghai and Hangzhou. As urban agricultural activities are proliferating in rapid urbanization, the establishment of a decision-making model for UAGR can offer practical guidance to practitioners, facilitating the development of urban agriculture and mitigating climate change.

Details

Title
Integrated Decision-Making of Urban Agriculture within the Greyfield Regeneration Environments (UAGR)
Author
Dong, Wenli  VIAFID ORCID Logo  ; Lin, Gangjian  VIAFID ORCID Logo 
First page
1415
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20755309
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3059506078
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.