Modeling Housing Development Potential with Climate-Sensitive Urban Indicators: A Data-Driven Approach

Urban housing development faces unprecedented challenges in the context of climate change, rapid urbanization, and shifting socio-economic demands. This study proposes a data-driven framework for modeling housing development potential using climate-sensitive urban indicators as a guiding construct. The conceptual analysis draws upon environmental resilience, smart urban systems, socio-economic affordability, and governance transparency, integrating these dimensions into a unified framework. The research problem is situated in the tension between the need for sustainable, affordable housing and the vulnerability of urban systems to climate risks and market uncertainties. A quantitative-analytical methodology is proposed, combining geospatial modeling, indicator-based evaluation, and predictive data analytics to assess development potential across varied urban contexts. Preliminary results suggest that incorporating climate-sensitive metrics such as heat exposure, flood risk, renewable energy integration, and green infrastructure accessibility enhances the accuracy of housing potential assessments compared to conventional socio-economic or market-driven approaches. Furthermore, governance and ESG (environmental, social, governance) factors are shown to significantly influence market transparency, investment flows, and long-term housing resilience. The findings advance a replicable and scalable model that integrates environmental sustainability, affordability, and governance accountability. The implications extend to urban planners, policymakers, and real estate stakeholders, enabling evidence-based decision-making that aligns with international sustainability goals. By bridging data-driven analytics with climate-sensitive housing indicators, this research contributes to a paradigm shift in urban development planning, emphasizing resilience, inclusivity, and long-term viability. Keywords Climate-sensitive urban indicators, Housing development potential, Data-driven modeling, Smart housing systems, Sustainability, Governance and ESG, Affordable housing, Urban resilience, Real estate transparency, Geospatial analysis.