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World Settlement Footprint 3D - A first three-dimensional survey of the global building stock

Esch, Thomas and Brzoska, Elisabeth and Dech, Stefan and Leutner, Benjamin and Palacios-Lopez, Daniela and Metz-Marconcini, Annekatrin and Marconcini, Mattia and Roth, Achim and Zeidler, Julian (2022) World Settlement Footprint 3D - A first three-dimensional survey of the global building stock. Remote Sensing of Environment, 270 (112877), pp. 1-15. Elsevier. doi: 10.1016/j.rse.2021.112877. ISSN 0034-4257.

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Settlements, and in particular cities, are at the center of key future challenges related to global change and sustainable development. Widely used indicators to assess the efficiency and sustainability of settlement development are the compactness and density of the built-up area. However, at global scale, a temporally consistent and spatially detailed survey of the distribution and concentration of the building stock – meaning the total area and volume of buildings within a defined spatial unit or settlement, commonly referred to as building density – does not yet exist. To fill this data and knowledge gap, an approach was developed to map key characteristics of the world’s building stock in a so far unprecedented level of spatial detail for every single settlement on our planet. The resulting World Settlement Footprint 3D dataset quantifies the fraction, total area, average height, and total volume of buildings for a measuring grid with 90 m cell size. The World Settlement Footprint 3D is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery at 10 m spatial resolution, in combination with 12 m digital elevation data and radar imagery collected by the TanDEM-X mission. The underlying, automated processing framework includes three basic workflows: one estimating the mean building height based on an analysis of height differences along potential building edges, a second module determining the building fraction and total building area within each 90 m cell, and a third part combining the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. Optionally, a simple 3D building model (level of detail 1) can be generated for regions where data on the building footprints is available. A comprehensive validation campaign based on 3D building models obtained for 19 regions (~86,000 km2) and street-view samples indicating the number of floors for >130,000 individual buildings in 15 additional cities documents that the novel World Settlement Footprint 3D data provides valuable and, for the first time, globally consistent information on key characteristics of the building stock in both, large urban agglomerations as well as small-scale rural settlements. Thus, the new dataset represents a promising baseline dataset for a wide range of previously impossible environmental, socioeconomic, and climatological studies worldwide.

Item URL in elib:https://elib.dlr.de/148203/
Document Type:Article
Title:World Settlement Footprint 3D - A first three-dimensional survey of the global building stock
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Esch, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-5868-9045UNSPECIFIED
Leutner, BenjaminUNSPECIFIEDhttps://orcid.org/0000-0002-6893-2002UNSPECIFIED
Metz-Marconcini, AnnekatrinUNSPECIFIEDhttps://orcid.org/0009-0002-3896-4705UNSPECIFIED
Marconcini, MattiaUNSPECIFIEDhttps://orcid.org/0000-0002-5042-5176UNSPECIFIED
Zeidler, JulianUNSPECIFIEDhttps://orcid.org/0000-0001-9444-2296UNSPECIFIED
Date:8 January 2022
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 1-15
Keywords:Global, Building density, 3D, Data fusion, TanDEM-X
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
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
German Remote Sensing Data Center > Leitungsbereich DFD
Deposited By: Esch, Dr.rer.nat. Thomas
Deposited On:12 Jan 2022 10:38
Last Modified:24 May 2022 23:48

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