Identifying Priority Areas for Planning Urban Green Infrastructure: A Fuzzy Artificial Intelligence-Based Framework DOI Creative Commons
Leonardo Massato Nicácio Nomura, Adriano Bressane,

Vitoria Valente Monteiro

и другие.

Urban Science, Год журнала: 2025, Номер 9(4), С. 126 - 126

Опубликована: Апрель 16, 2025

Urban green infrastructure (UGI) plays a key role in fostering sustainability, resilience, and ecological balance cities. However, the task of identifying priority areas for UGI implementation remains complex due to multifactorial nature urban systems prevailing uncertainties. This study proposes fuzzy inference system (FIS)-based framework composed seven interconnected modules designed assess diverse criteria, including flood vulnerability, water quality, habitat connectivity, vegetation condition, social vulnerability. The model was applied watersheds São José dos Campos, Brazil, municipality recognized its smart city initiatives environmental complexity. Through integration multi-criteria spatial data, effectively prioritized areas, highlighting critical zones extreme event mitigation, quality preservation, conservation, recreational space provision. case demonstrated that with an 11.73% urbanized area 737,310 inhabitants, benefits from targeted typologies, sustainable drainage public spaces, aligning interventions specific demands. Notably, expert validation process involving 18 multidisciplinary specialists confirmed model’s relevance coherence, majority classifying outcomes as “highly coherent”. system’s modular structure, use triangular membership functions, incorporation gamma operator allow adaptable prioritization across different planning horizons. By offering transparent, expert-validated, data-driven approach, proposed method advances evidence-based decision-making equips planners practical tool dynamic contexts.

Язык: Английский

Identifying Priority Areas for Planning Urban Green Infrastructure: A Fuzzy Artificial Intelligence-Based Framework DOI Creative Commons
Leonardo Massato Nicácio Nomura, Adriano Bressane,

Vitoria Valente Monteiro

и другие.

Urban Science, Год журнала: 2025, Номер 9(4), С. 126 - 126

Опубликована: Апрель 16, 2025

Urban green infrastructure (UGI) plays a key role in fostering sustainability, resilience, and ecological balance cities. However, the task of identifying priority areas for UGI implementation remains complex due to multifactorial nature urban systems prevailing uncertainties. This study proposes fuzzy inference system (FIS)-based framework composed seven interconnected modules designed assess diverse criteria, including flood vulnerability, water quality, habitat connectivity, vegetation condition, social vulnerability. The model was applied watersheds São José dos Campos, Brazil, municipality recognized its smart city initiatives environmental complexity. Through integration multi-criteria spatial data, effectively prioritized areas, highlighting critical zones extreme event mitigation, quality preservation, conservation, recreational space provision. case demonstrated that with an 11.73% urbanized area 737,310 inhabitants, benefits from targeted typologies, sustainable drainage public spaces, aligning interventions specific demands. Notably, expert validation process involving 18 multidisciplinary specialists confirmed model’s relevance coherence, majority classifying outcomes as “highly coherent”. system’s modular structure, use triangular membership functions, incorporation gamma operator allow adaptable prioritization across different planning horizons. By offering transparent, expert-validated, data-driven approach, proposed method advances evidence-based decision-making equips planners practical tool dynamic contexts.

Язык: Английский

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