Geo-Analytics and Eco-Gentrification: A Framework for Equitable Resilience in the Gowanus Canal

This conceptual paper examines the intersection of Geospatial Artificial Intelligence, Internet of Things technologies, and urban climate resilience through a justice-centered lens. Using the Gowanus Canal Superfund redevelopment in Brooklyn, New York, as a focal case, the paper explores how AI-driven zoning models shape environmental outcomes and socioeconomic equity in post-industrial cities. Drawing on interdisciplinary literature in sustainability, planning, and digital governance, this analysis examines tools such as predictive modeling, equity mapping, and algorithmic audits to evaluate displacement risk, eco-gentrification, and the reproduction of spatial inequality. The paper proposes a conceptual mixed-methods framework that integrates geospatial analytics, participatory zoning, and policy audits, supported by comparative case studies of the New York City High Line and the Atlanta BeltLine. The study presents a novel governance model that emphasizes transparency protocols, affordable housing mandates, and community-led planning that is inclusive. It argues that without inclusive governance mechanisms, GeoAI and IoT innovations may deepen socio-spatial disparities despite their potential to enhance environmental resilience. The framework provides policymakers with measurable equity indicators, including distributional and procedural justice metrics, to assess and mitigate the unintended consequences of smart redevelopment. By synthesizing environmental technology with anti-displacement strategies, this research offers a roadmap for ethical and inclusive climate adaptation in urban planning.