The Hotspot Stoplight Tool: Building the Evidence Base to Optimize Urban Growth and Minimize Environmental Risk

Against a global backdrop of biodiversity loss and climate change, growing cities around the world are making decisions every day about where and how to develop. Most have very little evidence base. As a result, many face the high costs of sprawl and infrastructural lock-in as they exacerbate landscape fragmentation and greenhouse gas emissions. The alternative is to plan for the future, which will require getting to grips with a constantly evolving landscape.

In response, UN-Habitat and the University of Pennsylvania have co-created the Hotspot Stoplight. This modular tool uses a unique workflow based on artificial intel­ligence and deep learning algorithms to estimate the proba­bilities of (1) land use change; (2) biodiversity loss; and (3) risk of effects of climate change across space, and map these for any metropolitan area at a resolution of 30 square meters. All three overlayed form a gradated ‘stoplight’ map that indi­cates combined risks of develop­ment in a particular area. Instead of only providing a picture of the present, the Stoplight pro­jects into the future. It transforms raw data into visualizations that help municipalities envision pos­sible paths of action and catalyze conversations about which strat­egies might least harm to planet and people.

During this session, UN-Habitat and the University of Pennsylvania explained how the Stoplight works, shared some of the learnings from its groundtruthing in the Greater Metropolitan Area of San José, Costa Rica, and led a discussion on its potential applications. The discussion also highlighted UN-Habitat’s and the University of Pennsylvania’s advocacy for a preventative approach to development and the challenges and benefits in pairing the catalyzation of local action with the achievement of global goals.

Addressing biodiversity loss and climate change through sustainable urbanization is a priority of the GEF and its implementation partners under the Sustainable Cities Integrated Program. Through this session, the GEF facilitated a discussion on the use of AI-based geospatial data tools to assist cities in biodiversity-inclusive planning, thereby contributing to local, national, and global goals.