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The Urban Morphology on Our Planet - Global perspectives from Space

Zhu, Xiao Xiang and Qiu, Chunping and Hu, Jingliang and Shi, Yilei and Wang, Yuanyuan and Schmitt, Michael and Taubenböck, Hannes (2022) The Urban Morphology on Our Planet - Global perspectives from Space. Remote Sensing of Environment, 269, p. 112794. Elsevier. doi: 10.1016/j.rse.2021.112794. ISSN 0034-4257.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0034425721005149

Abstract

Urbanization is the second largest mega-trend right after climate change. Accurate measurements of urban morphological and demographic figures are at the core of many international endeavors to address issues of urbanization, such as the United Nations’ call for “Sustainable Cities and Communities”. In many countries – particularly developing countries –, however, this database does not yet exist. Here, we demonstrate a novel deep learning and big data analytics approach to fuse freely available global radar and multi-spectral satellite data, acquired by the Sentinel-1 and Sentinel-2 satellites. Via this approach, we created the firstever global and quality controlled urban local climate zones classification covering all cities across the globe with a population greater than 300K and made it available to the community. Statistical analysis of the data quantifies a global inequality problem: approximately 40% of the area defined as compact or light/large low-rise accommodates about 60% of the total population, whereas approximately 30% of the area defined as sparsely built accommodates only about 10% of the total population. Beyond, patterns of urban morphology were discovered from the global classification map, confirming a morphologic relationship to the geographical region and related cultural heritage. We expect the open access of our dataset to encourage research on the global change process of urbanization, as a multidisciplinary crowd of researchers will use this baseline for spatial perspective in their work. In addition, it can serve as a unique dataset for stakeholders such as the United Nations to improve their spatial assessments of urbanization.

Item URL in elib:https://elib.dlr.de/145714/
Document Type:Article
Title:The Urban Morphology on Our Planet - Global perspectives from Space
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Zhu, Xiao Xiangxiaoxiang.zhu (at) dlr.dehttps://orcid.org/0000-0001-5530-3613
Qiu, ChunpingTechnical University MünchenUNSPECIFIED
Hu, Jingliangjingliang.hu (at) dlr.deUNSPECIFIED
Shi, YileiTUM-MünchenUNSPECIFIED
Wang, YuanyuanYuanyuan.Wang (at) dlr.deUNSPECIFIED
Schmitt, MichaelMichael.Schmitt (at) dlr.deUNSPECIFIED
Taubenböck, Hanneshannes.taubenboeck (at) dlr.dehttps://orcid.org/0000-0003-4360-9126
Date:February 2022
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:269
DOI :10.1016/j.rse.2021.112794
Page Range:p. 112794
Publisher:Elsevier
ISSN:0034-4257
Status:Published
Keywords:remote sensing, sentinels, big data, data fusion, deep learning, local climate zones, urban morphology, global urban LCZ dataset, global inequality
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research, R - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Remote Sensing Technology Institute > EO Data Science
Deposited By: Rösel, Anja
Deposited On:19 Nov 2021 09:08
Last Modified:09 Dec 2021 18:35

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