New Urban Morphology Dataset with Tree and Building Heights for Sustainable Urban Planning

A new high-resolution dataset was created to better understand impacts of tree and building height on urban climate and morphology.

Image is described in caption.

Tree and building heights are important factors influencing urban microclimate. In this aerial photo of a single-family residential neighborhood, tree canopies are taller than the surrounding buildings, acting as the “roughness element” of the landscape.

[Courtesy Peiyuan Li.]

The Science

Trees and building height change how heat distribution, wind direction, noise levels, and air quality affect cities. However, information about tree and building heights is often not available. Instead, urban climate models often use 2D land cover data. With high-precision light detection and ranging (LiDAR) data, building footprint inventories, and multiband satellite images, researchers mapped tree and building heights in Chicago at a high-detail, 1-meter resolution for a better picture of these vertical dimensions. These measurements make up HiTAB, a high-resolution dataset, which helps show the influence of tree and building heights on urban environments.

The Impact

The HiTAB dataset provides city planners, scientists, and government officials with new tree and building height data. This data is essential for urban climate modeling, tree inventory management, and green infrastructure planning. Since this data is more precise than previous options, it allows for more accurate quantification of variables such as land-surface roughness. Using HiTAB enables more realistic process-based and data-driven urban canopy modeling. More realistic modeling provides more information for key decision-makers. HiTAB can also show where the city lacks canopy cover. This knowledge allows the city to create a more comprehensive urban plan.

Summary

Merging LiDAR, satellite imagery, and building footprint data, researchers mapped the heights of buildings and trees in Chicago at an unprecedented 1-meter resolution. The resulting dataset, HiTAB, is crucial for advancing urban environmental models. Significant progress was made in developing height group categories for specific building types. These categories shed light on Chicago’s urban form and the need for better inclusion of trees in urban canopy modeling. Accounting for the interplay between green and gray elements in modeling can provide a clearer picture of the city’s climate.

The combined analysis of trees and buildings also helped define their height ratio, providing a more detailed look at how surface features vary within the city. This can allow for adjustments in the way dataset users calculate the dimensions of urban street canyons. Findings derived from the HiTAB dataset will aid in addressing urban challenges such as heat mitigation, flood prevention, and pollution control, contributing to a more sustainable and resilient urban future. Furthermore, the method used to create HiTAB can be extended to other urban regions, allowing for broader application of high-resolution urban informatics and a more comprehensive understanding of urban environments worldwide.

Principal Investigator

Ashish Sharma
Discovery Partners Institute at the University of Illinois System and Argonne National Laboratory
[email protected]

Program Manager

Sally McFarlane
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Urban Integrated Field Laboratories
[email protected]

Funding

This work is supported by the Biological and Environmental Research program within the U.S. Department of Energy’s Office of Science under contract DE-AC02-06CH11357. This research is also supported by National Science Foundation awards 2139316, 2230772, and 2330565; and NASA award #80NSSC22K1683. Researchers also acknowledge the City of Chicago and the Chicago Metropolitan Agency for Planning for providing the data used in this study.

Related Links

References

Li, Peiyuan, and A. Sharma. "Detailed Height Mapping of Trees and Buildings (HiTAB) in Chicago and its Implications to Urban Climate Studies." Environmental Research Letters 19 (9), 094013  (2024). https://doi.org/10.1088/1748-9326/ad661a.