Climate change increasingly affects urban areas, striving to maintain livable environments through green spaces that reduce extreme heat, improve air quality, and enhance mental health. However, traditional satellite analyses have proven inadequate, missing up to 37% of urban vegetation, which leads to flawed urban planning decisions.
A research team led by Rumi Chunara, an associate professor at NYU, has developed a new AI-powered system that more accurately tracks urban areas’ greenery using satellite imagery.
“Previous methods relied on simple light wavelength measurements,” says Chunara. “Our system learns to recognize more subtle patterns that distinguish trees from grass, even in complex urban environments.”
Challenges in Measuring Urban Greenery
Accurately tracking urban vegetation has long been hindered by several factors, including variations in lighting, seasonal changes, and intricate city landscapes. These challenges result in inaccurate data, disproportionately affecting developing cities where green space disparities often go unaddressed.
For instance, in Karachi—Pakistan’s largest city—the study found an average of just 4.17 square meters of green space per person, significantly below the World Health Organization’s recommended minimum of 9 square meters per capita.
How AI Enhances Green Space Detection
The researchers’ system utilizes DeepLabV3+ and a “green augmentation” technique, training AI with diverse vegetation images to improve detection accuracy. This AI model achieved 89.4% accuracy with 90.6% reliability, a significant improvement over traditional methods.
“This type of data is crucial for urban planners to identify neighborhoods lacking greenery so they can develop new green spaces that deliver the most benefits,” Chunara explains.
The Karachi case study highlighted significant inequalities—poorer areas had minimal greenery, while wealthier neighborhoods featured tree-lined streets. Interestingly, areas with more paved roads, often associated with economic development, correlated with higher tree density. This trend is also observed in parts of Africa.
Kobie Brand, Regional Director of ICLEI Africa, emphasizes the importance of urban greenery:
“Urban parks and green spaces allow communities to connect with nature, improving health and well-being.”
Cooling Cities and Reducing Pollution
Vegetation plays a crucial role in mitigating urban heat islands, pockets of extreme heat created by dense infrastructure.
“Anywhere in the U.S., small cities generate less heat than mega-cities,” notes research scientist Lahouari Bounoua. “The reason is the effect vegetation has in keeping temperatures under control.”
Despite similar population densities, Singapore has 9.9 square meters of green space per person, surpassing WHO recommendations through deliberate urban planning.
Climate scientist Professor Vivek Shandas highlights, “Tree canopies and green spaces significantly reduce heat in urban areas, providing natural cooling even under extreme heat conditions.“
Implications for African Cities Facing Rapid Urbanization
Many African cities are experiencing rapid urbanization with limited resources, often leading to insufficient green spaces. AI-driven tracking can help these cities prioritize tree planting and park development, strengthening their climate resilience.
To achieve this, African cities must integrate AI-powered green mapping into their urban planning processes and foster partnerships between AI researchers and city authorities.
Chunara’s team has made their methodology publicly available, enabling global adaptation. AI is poised to become an essential tool in data-driven climate solutions, from air pollution tracking to water management.
“By making this methodology openly accessible, we hope cities worldwide will use AI to build a greener, healthier future,” says Chunara.
