TY - JOUR
T1 - Large disagreements in estimates of urban land across scales and their implications
AU - Chakraborty, T. C.
AU - Venter, Zander S.
AU - Demuzere, Matthias
AU - Zhan, Wenfeng
AU - Gao, Jing
AU - Zhao, Lei
AU - Qian, Yun
N1 - Pacific Northwest National Laboratory is operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under contract DE-AC05-76RL01830. This study is supported by a DOE Early Career award to T.C. as well as the Coastal Observations, Mechanisms, and Predictions Across Systems and Scales-Great Lakes Modeling (COMPASS-GLM) and Integrated Coastal Modeling (ICoM) projects. The latter two are multi-institutional projects supported by DOE\u2019s Office of Science\u2019s Office of Biological and Environmental Research. L.Z. acknowledges the support by the U.S. National Science Foundation (CAREER Award Grant No. 2145362) and the Institute for Sustainability, Energy, and Environment at the University of Illinois Urbana-Champaign. We thank Samapriya Roy and the Earth Engine Community Data Catalog for providing seamless access to many of these data products, Mattia Marconcini for discussions on the world settlement footprint suite of products, Panagiotis Sismanidis for providing details on the methodology used to develop the ESA CCI dataset, and Kanishka Balu Narayan for discussions on urban representation in Integrated Assessment Models.
PY - 2024/12
Y1 - 2024/12
N2 - Improvements in high-resolution satellite remote sensing and computational advancements have sped up the development of global datasets that delineate urban land, crucial for understanding climate risks in our increasingly urbanizing world. Here, we analyze urban land cover patterns across spatiotemporal scales from several such current-generation products. While all the datasets show a rapidly urbanizing world, with global urban land nearly tripling between 1985 and 2015, there are substantial discrepancies in urban land area estimates among the products influenced by scale, differing urban definitions, and methodologies. We discuss the implications of these discrepancies for several use cases, including for monitoring urban climate hazards and for modeling urbanization-induced impacts on weather and climate from regional to global scales. Our results demonstrate the importance of choosing fit-for-purpose datasets for examining specific aspects of historical, present, and future urbanization with implications for sustainable development, resource allocation, and quantification of climate impacts.
AB - Improvements in high-resolution satellite remote sensing and computational advancements have sped up the development of global datasets that delineate urban land, crucial for understanding climate risks in our increasingly urbanizing world. Here, we analyze urban land cover patterns across spatiotemporal scales from several such current-generation products. While all the datasets show a rapidly urbanizing world, with global urban land nearly tripling between 1985 and 2015, there are substantial discrepancies in urban land area estimates among the products influenced by scale, differing urban definitions, and methodologies. We discuss the implications of these discrepancies for several use cases, including for monitoring urban climate hazards and for modeling urbanization-induced impacts on weather and climate from regional to global scales. Our results demonstrate the importance of choosing fit-for-purpose datasets for examining specific aspects of historical, present, and future urbanization with implications for sustainable development, resource allocation, and quantification of climate impacts.
UR - https://www.scopus.com/pages/publications/85207331496
UR - https://www.scopus.com/pages/publications/85207331496#tab=citedBy
U2 - 10.1038/s41467-024-52241-5
DO - 10.1038/s41467-024-52241-5
M3 - Article
C2 - 39448573
AN - SCOPUS:85207331496
SN - 2041-1723
VL - 15
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 9165
ER -