Abstract
Urbanization has altered land surface properties driving changes in micro-climates. Urban form influences people’s activities, environmental exposures, and health. Developing detailed and unified longitudinal measures of urban form is essential to quantify these relationships. Local Climate Zones [LCZ] are a culturally-neutral urban form classification scheme. To date, longitudinal LCZ maps at large scales (i.e., national, continental, or global) are not available. We developed an approach to map LCZs for the continental US from 1986 to 2020 at 100 m spatial resolution. We developed lightweight contextual random forest models using a hybrid model development pipeline that leveraged crowdsourced and expert labeling and cloud-enabled modeling – an approach that could be generalized to other countries and continents. Our model achieved good performance: 0.76 overall accuracy (0.55– 0.96 class-wise F1 scores). To our knowledge, this is the first high-resolution, longitudinal LCZ map for the continental US. Our work may be useful for a variety of fields including earth system science, urban planning, and public health.
Document Type
Article
Publication Date
2-2024
Digital Object Identifier (DOI)
https://doi.org/10.1038/s41597-024-03042-4
Funding Information
This material is based upon work supported by the National Institutes of Health under grant No. R01 HL150119. Matthias Demuzere and Benjamin Bechtel were supported by the ENLIGHT project, funded by the German Research Foundation (DFG) under grant No. 437467569. The authors thank Dr. Andrew Larkin for his valuable suggestion on large-scale mapping and thank Griffin Kearns for his contribution in TAs collection.
Repository Citation
Qi, Meng; Xu, Chunxue; Zhang, Wenwen; Demuzere, Matthias; Hystad, Perry; Lu, Tianjun; James, Peter; Bechtel, Benjamin; and Hankey, Steve, "Mapping urban form into local climate zones for the continental US from 1986–2020" (2024). Earth and Environmental Sciences Faculty Publications. 57.
https://uknowledge.uky.edu/ees_facpub/57
Included in
Databases and Information Systems Commons, Earth Sciences Commons, Environmental Sciences Commons, Other Statistics and Probability Commons
Notes/Citation Information
© The Author(s) 2024
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre- ative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not per- mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.