India is using AI and satellites to map urban heat vulnerability down to the building level
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At present, heat action plans (HAP) are India's primary approach for managing heat waves and keeping essential services running. Developed annually by state, district, and city governments-the Delhi government released its citywide HAP for 2025 in April-these plans are designed to help cities prepare for, respond to, and recover from extreme heat. And they're not working.
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To try to better capture that variability, SEEDS, a Delhi-based disaster-preparedness nonprofit, along with Chintan, a nonprofit working on waste management and livelihoods, have used GIS mapping of indoor heat risks across homes in low-income settlements in Delhi, located near landfills and industrial zones, and inhabited by waste pickers.
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They used an artificial intelligence model called Sunny Lives-built by SEEDS and Microsoft-to assess indoor heat risk across different types of buildings. "Our model looks at how heat is experienced inside individual homes," says Anshu Sharma, cofounder of SEEDS. "If the outside temperature is 40 degrees Celsius, a house with a tin roof can reach 45 degrees Celsius indoors. And that's where the most vulnerable people-infants, elderly, and the unwell-are stuck during the hottest times of the day."
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The team tracked conditions in homes topped with tin roofs, tiles, plastic sheeting, and concrete to figure out which are at the highest risk of extreme indoor heat. "That trained the model to recognize patterns, which we then combined with satellite imagery to identify roof types and building materials at scale. We can now assess indoor heat exposure for individual buildings even without installing sensors for similar geographic locations."
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