BEYOND THE EDGE: REPROGRAMMING GREENFIELDS FOR EQUITABLE URBAN FUTURES AN AI-ASSISTED FRAMEWORK FOR SUSTAINABLE PERI-URBAN PLANNING IN THE AGE OF CLIMATE VOLATILITY

Peri-urban regions—transitional zones between urban cores and rural hinterlands—are increasingly at the forefront of climate vulnerability, socio-spatial inequality, and unsustainable development. This paper proposes an AI-assisted planning framework that integrates climate resilience, equity, and sustainability into peri-urban land use strategies. Drawing from recent advancements in urban informatics, digital twins, and participatory AI, the framework addresses the challenges of fragmented governance, rapid land-use change, and environmental degradation. Through a synthesis of literature and case studies, we demonstrate how AI can support equitable decision-making and adaptive planning in peri-urban contexts.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-07
DOI
https://doi.org/10.5281/zenodo.15612794
Primary Topic
Reliability and Agreement in Measurement
Type
article
Field-Weighted Citation Impact
0.00
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article

BEYOND THE EDGE: REPROGRAMMING GREENFIELDS FOR EQUITABLE URBAN FUTURES AN AI-ASSISTED FRAMEWORK FOR SUSTAINABLE PERI-URBAN PLANNING IN THE AGE OF CLIMATE VOLATILITY

Zenodo (CERN European Organization for Nuclear Research)
Reliability and Agreement in Measurement
article

BEYOND THE EDGE: REPROGRAMMING GREENFIELDS FOR EQUITABLE URBAN FUTURES AN AI-ASSISTED FRAMEWORK FOR SUSTAINABLE PERI-URBAN PLANNING IN THE AGE OF CLIMATE VOLATILITY

article en

Abstract

Peri-urban regions—transitional zones between urban cores and rural hinterlands—are increasingly at the forefront of climate vulnerability, socio-spatial inequality, and unsustainable development. This paper proposes an AI-assisted planning framework that integrates climate resilience, equity, and sustainability into peri-urban land use strategies. Drawing from recent advancements in urban informatics, digital twins, and participatory AI, the framework addresses the challenges of fragmented governance, rapid land-use change, and environmental degradation. Through a synthesis of literature and case studies, we demonstrate how AI can support equitable decision-making and adaptive planning in peri-urban contexts.

Zenodo (CERN European Organization for Nuclear Research)
Climate action
Openalex Percentile: Top 53%
Reliability and Agreement in Measurement
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