Detailed height mapping of trees and buildings (HiTAB) in Chicago and its implications to urban climate studies

Abstract

The vertical dimensions of urban morphology, specifically the heights of trees and buildings, exert significant influence on wind flow fields in urban street canyons and the thermal environment of the urban fabric, subsequently affecting the microclimate, noise levels, and air quality. Despite their importance, these critical attributes are less commonly available and rarely utilized in urban climate models compared to planar land use and land cover data. In this study, we explicitly mapped the height of trees and buildings (HiTAB) across the city of Chicago at 1 m spatial resolution using a data fusion approach. This approach integrates high-precision light detection and ranging (LiDAR) cloud point data, building footprint inventory, and multi-band satellite images. Specifically, the digital terrain and surface models were first created from the LiDAR dataset to calculate the height of surface objects, while the rest of the datasets were used to delineate trees and buildings. We validated the derived height information against the existing building database in downtown Chicago and the Meter-scale Urban Land Cover map from the Environmental Protection Agency, respectively. The co-investigation on trees and building heights offers a valuable initiative in the effort to inform urban land surface parameterizations using real-world data. Given their high spatial resolution, the height maps can be adopted in physical-based and data-driven urban models to achieve higher resolution and accuracy while lowering uncertainties. Moreover, our method can be extended to other urban regions, benefiting from the growing availability of high-resolution urban informatics globally. Collectively, these datasets can substantially contribute to future studies on hyper-local weather dynamics, urban heterogeneity, morphology, and planning, providing a more comprehensive understanding of urban environments.