用手机测树+智能算法，让市民参与城市降温与绿色出行规划。
Citizen Centered Climate Intelligence: Operationalizing Open Tree Data for Urban Cooling and Eco-Routing in Indian Cities
- 市民用手机拍树，AI自动测算树高、冠幅和树干粗细。
- 提出两项新指标：冷却效能与环境热缓解，量化树木降温效果。
- 生成个性化绿色路线，适合关注环保的市民和城市规划者。
城市气候韧性不仅需要高分辨率数据，更需将数据采集、解读与行动融入市民日常生活。本文提出一个可扩展的市民中心框架，通过参与式感知、开放分析与预测性城市规划工具重塑环境基础设施。该框架在印度浦那市应用，包含三个相互关联模块：(1) 基于智能手机的测量工具，结合AI分割技术提取树高、冠幅和树干周长；(2) 基于卫星地表温度的百分位模型，引入两项新指标——冷却效能（Cooling Efficacy）与环境热缓解（Ambient Heat Relief），量化局部降温效果；(3) 生态导航引擎，基于树密度、物种多样性和累计碳汇量生成静态环境质量评分，指导低碳出行。三模块构成闭环反馈系统，市民生成可操作数据并获得个性化可持续干预。该框架将开放数据从被动存储变为主动治理平台，推动共享治理与环境公平。面对日益加剧的生态不平等与数据集中化问题，本文提供了一种可复用的市民驱动城市智能模式，将规划重构为共治、气候韧性且高度本地化的实践。
原文摘要 · Abstract (English)
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.
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