Finding our cities’ hotspots: using satellites to identify areas that are too hot and have no green space
Urban heat islands are a major health risk. We developed an automatic method using satellite imagery to find the ‘most unfavourable’ areas (high heat, low vegetation) across 16 major Spanish cities.
Why is one street in a city comfortable, while another just a few blocks away feels like an oven? This is the “urban heat island” effect, and in a warming world, it’s a critical issue for public health, environmental justice, and quality of life.
But to fix the problem, you first need to know where it is. In our 2022 paper, published in Urban Forestry & Urban Greening, we developed an automatic method to find the most unfavourable areas in a city: the places that are both dangerously hot and desperately lacking green space.
🧐 The problem: not all concrete is created equal
We know that trees and parks cool cities down. We also know that large areas of concrete and asphalt absorb and radiate heat. This often creates an issue of environmental injustice: affluent areas may be green and cool, while other neighbourhoods are left with concrete and high temperatures.
City planners want to fix this, but to intervene effectively, they need a map. They need to know, “where is the absolute worst combination of high heat and low vegetation?” Manually surveying an entire city (let alone 16 of them) is impossible.
💡 Our solution: using satellites to see heat and green
Our solution was to develop an automatic methodology using remote sensing. We used publicly available data from the Landsat-8 satellite to look at 16 major Spanish cities.
For each city, we measured two key variables for every single pixel:
- LST (Land Surface Temperature): This is a direct measurement of how hot the ground is. It’s the “heat” part of the equation.
- NDVI (Normalized Difference Vegetation Index): This is a classic satellite measurement of how much healthy, green vegetation is present. It’s the “green space” part.
Our method automatically processes these two maps and identifies the “unfavourable areas”—the zones that simultaneously have the highest temperatures (LST) and the lowest amount of vegetation (NDVI).
🚀 The results: a clear map for action
The method was a success. We were able to generate detailed, high-resolution maps for all 16 Spanish cities, clearly pinpointing the neighbourhoods and even city blocks that are suffering the most.
These maps aren’t just academic curiosities; they are actionable tools. A city planner can now look at their city and see, with objective data, “this neighbourhood is a priority for a new park,” or “this street is a critical corridor for planting trees.”
🔬 Why does this matter?
This work provides a scalable and automatic tool for data-driven urban planning. It helps cities move beyond guesswork and make informed decisions about where to invest in green infrastructure.
By finding the hottest, least-green areas, we can help build cities that are cooler, more sustainable, and more equitable for everyone.
📖 The full paper
For the complete methodology, the full list of 16 cities, and all the detailed maps and statistical analyses, you can read the original journal article.
Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities. Authors: Francisco Rodríguez-Gómez, Rafael Fernández-Cañero, Gabriel Pérez, José del Campo-Ávila, Domingo López-Rodríguez, Luis Pérez-Urrestarazu. Journal: Urban Forestry & Urban Greening (vol. 78, 127783)