A Brazilian teenager created an artificial intelligence to map heat islands and help cool down cities that are becoming open-air ovens under increasingly extreme temperatures.

However, according to Isaque, the urban design did not eliminate thermal inequalities between different areas of the city.

Some regions concentrate more heat than others, which can create micro heat islands within the urban space itself.

In the original text, the student stated that the city was designed to attract residents, but that certain aspects were left out of the planning.

“One of these points has to do with heat,” he said, explaining that certain areas become hotter than nearby regions and start to function as urban micro heat islands.

Urban heat islands occur when built spaces record temperatures higher than those of neighboring areas.

The phenomenon is related to the replacement of vegetation with asphalt, concrete, and other materials that absorb and retain heat.

Low tree cover, soil impermeabilization, street design, building density, and heat generated by human activities also influence this process.

In the case of EcoAção Brasil, the analysis seeks to observe these differences on an intra-urban scale.

Instead of just evaluating a city’s average temperature, the project seeks to identify internal variations and show how heat is distributed among neighborhoods, streets, and areas with different occupation patterns.

How EcoAção Brasil crosses satellite data

The model developed by Isaque gathers environmental data obtained from open sources, especially satellite images and information.

Among the variables analyzed are surface temperature, indicators of vegetation density and health, indices of built areas, and changes in land use over time.

With this data, artificial intelligence identifies spatial and temporal patterns related to urban heat.

The tool seeks to indicate where heat concentrates, how these areas evolve, and which locations can be considered priorities for climate adaptation actions.

“There isn’t a solution out there that tells you what the most important points are where you should focus,” Isaque stated in the original text.

According to him, this gap motivated the creation of a system aimed at supporting more precise decisions about urban interventions.

The tool is not limited to tree planting.

The model also considers solutions such as increasing permeable areas, using materials that reflect more solar radiation, implementing ventilation corridors, redesigning urban sections, and creating vegetated public spaces.

The indication of each measure depends on the characteristics observed in each area.

Extreme heat broadens debate on urban adaptation

The development of EcoAção Brasil occurs in a context of increasing concern with extreme heat in cities.

According to the World Meteorological Organization, the period from 2015 to 2025 brought together the 11 warmest years ever recorded, and 2025 was among the second and third warmest years in the historical series.

These data reinforce the relevance of adaptation policies, especially in dense urban areas.

In cities, the impact of heat is not uniformly distributed.

Elderly people, children, pregnant women, workers exposed to the sun, and low-income individuals tend to face greater risk when living or moving in regions with little shade, low tree cover, inadequate housing, and less access to health services or cooling.

Urban climate experts point out that tackling heat islands requires a combination of technology, urban planning, public health, and social participation.

The data helps locate the problem, but intervention decisions need to consider environmental, economic, social, and cultural factors.

Environmental engineer Zhihua Wang, from Arizona State University, quoted in the original text, assessed that the use of artificial intelligence and machine learning to identify heat spots and mitigation strategies is an idea of technical interest.

He stated, however, that consistent results depend on adequate algorithms, quality databases, and rigorous control of the information used in the model.

Wang also noted that open satellite imagery may be insufficient for very detailed analyses at a hyperlocal scale.

Furthermore, according to him, there is no single solution for all urban contexts.

The choice between tree planting, material changes, street reconfiguration, or other measures must consider residents’ needs, water availability, air quality, socioeconomic conditions, and even cultural preferences.

Tocantins Framework organizes thermal analysis of cities

The methodological basis of EcoAção Brasil is now presented as Tocantins Framework, a structure aimed at analyzing intra-urban thermal anomalies.

The objective is to measure not only where heat islands exist, but also the intensity, spatial reach, and impact of these thermal differences on the surroundings.

On the project’s website, the team describes the use of machine learning, geospatial analysis, and satellite imagery to study heat islands and cool islands within cities.

The initiative mentions metrics such as Severity Score and Impact Score, created to organize the reading of these thermal anomalies and allow comparisons between different urban areas.

The group linked to EcoAção Brasil gathers volunteers and presents the initiative as a tool to support environmental decisions.

The proposal is to bring together technology, scientific education, and urban planning, with attention to cities facing high temperatures and needing to define intervention priorities.

In Palmas, where the observation of the problem gave rise to the project, Isaque stated in the original text that he intends to offer the solution free of charge to local institutions.

The decision maintains the initiative’s initial focus, directed at the city where the student lives and where he identified the micro-heat islands that motivated the research.

The project’s trajectory inserts artificial intelligence into a specific application of public interest.

Instead of operating as a generic tool, EcoAção Brasil seeks to respond to a concrete urban demand: transforming climatic and territorial data into useful information to reduce heat exposure on the streets.

“EcoAção Brasil is something I did to combine my love not only for the environment and technology, but also for people,” Isaque said in the original text.

The statement summarizes the motivation presented by the student to develop a solution that unites programming, environmental analysis, and concern for the effects of heat on the population.

There are still technical steps to be completed before the tool can be used on a broader scale by governments, schools, researchers, or organizations.

Among the points to be monitored are the validation of the models, the resolution of the data used, adaptation to different cities, and the ability to transform diagnoses into executable actions in urban spaces.

Brazilian student creates artificial intelligence tool to map urban heat islands, crossing environmental data and satellite images in a solution aimed at planning cities more prepared for extreme temperatures.

Brazilian student Isaque Carvalho Borges developed a project that uses artificial intelligence, satellite images, and environmental data analysis to identify urban areas where interventions can help reduce heat.

The tool, called EcoAção Brasil, emerged from his experience in Palmas, Tocantins, a planned city where different regions can record temperature variations associated with land use, the presence of vegetation, and the concentration of built surfaces.

The system’s proposal is to map heat spots within cities and support decisions on measures such as tree planting, creation of green areas, use of green roofs, permeable pavements, materials with higher reflectance, and improvements in air circulation between streets and buildings.

The focus is on identifying locations where these actions can be prioritized based on data.

The project won the regional stage of The Earth Prize 2025 for Central and South America, an international competition aimed at students aged 13 to 19.

With this recognition, Isaque received US$ 12.5 thousand to advance the development of the initiative.

According to the Instituto Federal do Tocantins, where he studies at Campus Palmas, EcoAção Brasil combines remote sensing, artificial intelligence, and predictive analysis to guide urban heat mitigation strategies.

Artificial intelligence against urban heat islands

Palmas is a planned city, founded in 1989, and was designed to organize the urban occupation of the then new capital of Tocantins.

However, according to Isaque, the urban design did not eliminate thermal inequalities between different areas of the city.

Some regions concentrate more heat than others, which can create micro heat islands within the urban space itself.

In the original text, the student stated that the city was designed to attract residents, but that certain aspects were left out of the planning.

“One of these points has to do with heat,” he said, explaining that certain areas become hotter than nearby regions and start to function as urban micro heat islands.

Urban heat islands occur when built spaces record temperatures higher than those of neighboring areas.

The phenomenon is related to the replacement of vegetation with asphalt, concrete, and other materials that absorb and retain heat.

Low tree cover, soil impermeabilization, street design, building density, and heat generated by human activities also influence this process.

In the case of EcoAção Brasil, the analysis seeks to observe these differences on an intra-urban scale.

Instead of just evaluating a city’s average temperature, the project seeks to identify internal variations and show how heat is distributed among neighborhoods, streets, and areas with different occupation patterns.

How EcoAção Brasil crosses satellite data

The model developed by Isaque gathers environmental data obtained from open sources, especially satellite images and information.

Among the variables analyzed are surface temperature, indicators of vegetation density and health, indices of built areas, and changes in land use over time.

With this data, artificial intelligence identifies spatial and temporal patterns related to urban heat.

The tool seeks to indicate where heat concentrates, how these areas evolve, and which locations can be considered priorities for climate adaptation actions.

“There isn’t a solution out there that tells you what the most important points are where you should focus,” Isaque stated in the original text.

According to him, this gap motivated the creation of a system aimed at supporting more precise decisions about urban interventions.

The tool is not limited to tree planting.

The model also considers solutions such as increasing permeable areas, using materials that reflect more solar radiation, implementing ventilation corridors, redesigning urban sections, and creating vegetated public spaces.

The indication of each measure depends on the characteristics observed in each area.

Extreme heat broadens debate on urban adaptation

The development of EcoAção Brasil occurs in a context of increasing concern with extreme heat in cities.

According to the World Meteorological Organization, the period from 2015 to 2025 brought together the 11 warmest years ever recorded, and 2025 was among the second and third warmest years in the historical series.

These data reinforce the relevance of adaptation policies, especially in dense urban areas.

In cities, the impact of heat is not uniformly distributed.

Elderly people, children, pregnant women, workers exposed to the sun, and low-income individuals tend to face greater risk when living or moving in regions with little shade, low tree cover, inadequate housing, and less access to health services or cooling.

Urban climate experts point out that tackling heat islands requires a combination of technology, urban planning, public health, and social participation.

The data helps locate the problem, but intervention decisions need to consider environmental, economic, social, and cultural factors.

Environmental engineer Zhihua Wang, from Arizona State University, quoted in the original text, assessed that the use of artificial intelligence and machine learning to identify heat spots and mitigation strategies is an idea of technical interest.

He stated, however, that consistent results depend on adequate algorithms, quality databases, and rigorous control of the information used in the model.

Wang also noted that open satellite imagery may be insufficient for very detailed analyses at a hyperlocal scale.

Furthermore, according to him, there is no single solution for all urban contexts.

The choice between tree planting, material changes, street reconfiguration, or other measures must consider residents’ needs, water availability, air quality, socioeconomic conditions, and even cultural preferences.

Tocantins Framework organizes thermal analysis of cities

The methodological basis of EcoAção Brasil is now presented as Tocantins Framework, a structure aimed at analyzing intra-urban thermal anomalies.

The objective is to measure not only where heat islands exist, but also the intensity, spatial reach, and impact of these thermal differences on the surroundings.

On the project’s website, the team describes the use of machine learning, geospatial analysis, and satellite imagery to study heat islands and cool islands within cities.

The initiative mentions metrics such as Severity Score and Impact Score, created to organize the reading of these thermal anomalies and allow comparisons between different urban areas.

The group linked to EcoAção Brasil gathers volunteers and presents the initiative as a tool to support environmental decisions.

The proposal is to bring together technology, scientific education, and urban planning, with attention to cities facing high temperatures and needing to define intervention priorities.

In Palmas, where the observation of the problem gave rise to the project, Isaque stated in the original text that he intends to offer the solution free of charge to local institutions.

The decision maintains the initiative’s initial focus, directed at the city where the student lives and where he identified the micro-heat islands that motivated the research.

The project’s trajectory inserts artificial intelligence into a specific application of public interest.

Instead of operating as a generic tool, EcoAção Brasil seeks to respond to a concrete urban demand: transforming climatic and territorial data into useful information to reduce heat exposure on the streets.

“EcoAção Brasil is something I did to combine my love not only for the environment and technology, but also for people,” Isaque said in the original text.

The statement summarizes the motivation presented by the student to develop a solution that unites programming, environmental analysis, and concern for the effects of heat on the population.

There are still technical steps to be completed before the tool can be used on a broader scale by governments, schools, researchers, or organizations.

Among the points to be monitored are the validation of the models, the resolution of the data used, adaptation to different cities, and the ability to transform diagnoses into executable actions in urban spaces.