Citizen Centered Climate Intelligence: Operationalizing Open Tree Data for Urban Cooling and Eco-Routing in Indian Cities

TL;DR

This paper introduces a citizen-centric framework in Pune, India, that combines participatory sensing, open analytics, and urban planning tools to enhance urban cooling and eco-routing, fostering shared governance and climate resilience.

Contribution

It presents a scalable, integrated model that operationalizes open tree data for urban cooling and mobility guidance, emphasizing citizen participation and local environmental equity.

Findings

AI-enhanced smartphone toolkit accurately measures tree attributes

New metrics quantify localized cooling and heat relief

Eco-routing improves urban mobility based on environmental quality

Abstract

Urban climate resilience requires more than high-resolution data; it demands systems that embed data collection, interpretation, and action within the daily lives of citizens. This chapter presents a scalable, citizen-centric framework that reimagines environmental infrastructure through participatory sensing, open analytics, and prescriptive urban planning tools. Applied in Pune, India, the framework comprises three interlinked modules: (1) a smartphone-based measurement toolkit enhanced by AI segmentation to extract tree height, canopy diameter, and trunk girth; (2) a percentile-based model using satellite-derived Land Surface Temperature to calculate localized cooling through two new metrics, Cooling Efficacy and Ambient Heat Relief; and (3) an eco-routing engine that guides mobility using a Static Environmental Quality score, based on tree density, species diversity, and cumulative carbon sequestration. Together, these modules form a closed feedback loop where citizens generate actionable data and benefit from personalized, sustainable interventions. This framework transforms open data from a passive repository into an active platform for shared governance and environmental equity. In the face of growing ecological inequality and data centralization, this chapter presents a replicable model for citizen-driven urban intelligence, reframing planning as a co-produced, climate-resilient, and radically local practice.