From Smog to Solar: The Surprising Ways AI-Enhanced Satellite Imagery Is Reshaping Cities

Satellite imagery analysis is increasingly combined with artificial intelligence to deliver geospatial insights used in transitioning to a lower carbon economy.

European company Latitudo 40 has been at the forefront of innovation, with its technology used in several key projects, particularly in Italy.

Latitudo 40 chief executive Francesco Amato said satellite data is being used for many key indicators that would be otherwise difficult to estimate with enough accuracy.

“For example, satellite data can be used to inform the Heatwave Risk Map, identifying areas that are at risk for high temperatures, or the Microclimatic Performance Index, highlighting the ability of green infrastructure to combat the urban heat island (UHI) effect,” Amato wrote in a recent blog post.

“Satellites are especially useful tools in the battle against the rising concentration of air pollutants, but also in addressing issues related to the green infrastructure.”

Amato cited the creation of other indices, such as a Tree Cover Density index, which enables green infrastructure monitoring and assesses land value.

This also plays a role in the carbon market by allowing the determination of carbon credit values with verifiable CO2 sequestration data, boosting market transparency.

Among Latitudo 40’s case studies is GeoGreen, a project run for Autostrade per l’Italia, a concession for constructing and managing toll motorways in Italy.

The company needed a tool to classify the physical areas surrounding highways to identify the best places to install photovoltaic systems.

“Working with us, it was also able to map and monitor the greenery over time so that the physical areas around the road surface could be evaluated for capturing pollutants such as CO2," Amato said.

In another example, the City of Milan could predict the effect of de-paving Neera Street, one of the city’s most prominent thoroughfares, allowing the development of multiple possible scenarios regarding shading, blue-green factors, temperature and CO2 sequestration.

“Cities can face a range of challenges when integrating satellite data into their climate monitoring and action frameworks, and satellite data is often complex and voluminous, requiring advanced processing and interpretation skills,” Amato said.

“Cities can invest in cloud-based platforms that offer scalable storage and computing power and use machine learning algorithms to process and analyze large datasets efficiently.”

Image credit: iStockphoto/Dragon Claws