First High-Resolution 3D Map Of Earth’s 2.75 Billion Buildings Enhances Urban Planning And Climate Studies

Researchers in Germany have created a detailed digital model of the world's built environment, marking a significant achievement. This high-resolution, three-dimensional dataset includes 2.75 billion buildings. The GlobalBuildingAtlas was developed by the Technical University of Munich (TUM) team and is intended to aid advanced climate studies and support the UN Sustainable Development Goals.

The map's development was led by Xiaoxiang Zhu, PhD, a professor at TUM. She explained that it will improve urbanisation, disaster management, and infrastructure models. This will assist cities in becoming more inclusive and resilient. Zhu highlighted that 3D building data provides more accurate insights into urbanisation and poverty than traditional 2D maps.

New 3D Map of Earth’s Buildings Unveiled

The three-dimensional data offers a precise foundation for urban development planning and monitoring. It aims to help cities implement targeted measures for creating more inclusive living conditions. This includes adding housing or public facilities in densely populated areas that lack resources.

Zhu introduced a new metric called building volume per capita, which measures total building mass per person. This global indicator highlights social and economic disparities. "This indicator supports sustainable urban development and helps cities become more inclusive and resilient," she stated.

The map is crucial for climate adaptation as it enhances models of energy demand, CO2 emissions, and green infrastructure planning. It also strengthens disaster-prevention efforts by enabling quicker assessments of risks from natural events.

Three-dimensional building data reveals patterns of urbanisation and poverty with greater accuracy than two-dimensional maps. "With 3D models, we see not only the footprint but also the volume of each building, enabling far more precise insights into living conditions," Zhu said.

This comprehensive dataset is expected to provide a precise basis for planning urban development. It will help cities take targeted actions to create equitable living conditions by providing additional housing or public facilities in underserved areas.

With inputs from WAM

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