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Large-Area Characterization of Urban Morphology: Mapping Built-Up Height and Density with the TanDEM-X Mission and Sentinel-2

Geiß, Christian and Leichtle, Tobias and Wurm, Michael and Aravena Pelizari, Patrick and Standfuß, Ines and Zhu, Xiao Xiang and So, Emily and Siedentop, Stefan and Esch, Thomas and Taubenböck, Hannes (2019) Large-Area Characterization of Urban Morphology: Mapping Built-Up Height and Density with the TanDEM-X Mission and Sentinel-2. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12 (8), pp. 2912-2927. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2019.2917755 ISSN 1939-1404

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Official URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8745682

Abstract

In this paper, we establish a novel multistep procedure for morphologic characterization of built environments in terms of built-up height and density. We rely on elevation measurements from the TanDEM-X mission (TDM) and multispectral Sentinel-2 imagery. These earth observation systems feature a notable tradeoff between a fairly high spatial resolution and largearea coverage and, thus, allow for spatially continuous analysis of built environments around the globe. To this purpose, we follow an automated workflow that foresees the distinction of “built-up” and “non-built-up” areas by relying on the so-called Global Urban Footprint processor. This information is deployed within a tailored filtering procedure for the TDM digital surface model data to extract elevation information for built-up areas. Subsequently, the intra-urban land cover is mapped under consideration of Sentinel2 imagery and serves as basis to compute built-up heights and densities. These two measures are finally combined for a morphologic characterization of the built environment on an ordinal scale of measurement. Empirical validation efforts are provided based on comparative analysis with respect to more than 3.2 million individual building geometries and affiliated height measurements from cadastral data sources. The datasets cover the settlement areas of the capital cities and other major cities in Germany, England, and the Netherlands. The experimental results underline the capability for a morphologic characterization of built environments with viable accuracies.

Item URL in elib:https://elib.dlr.de/130000/
Document Type:Article
Title:Large-Area Characterization of Urban Morphology: Mapping Built-Up Height and Density with the TanDEM-X Mission and Sentinel-2
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Geiß, Christianchristian.geiss (at) dlr.dehttps://orcid.org/0000-0002-7961-8553
Leichtle, Tobiastobias.leichtle (at) dlr.deUNSPECIFIED
Wurm, Michaelmichael.wurm (at) dlr.deUNSPECIFIED
Aravena Pelizari, PatrickPatrick.AravenaPelizari (at) dlr.deUNSPECIFIED
Standfuß, InesInes.Standfuss (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
So, EmilyUniversity of Cambridge, Cambridge, UKUNSPECIFIED
Siedentop, StefanILS DortmundUNSPECIFIED
Esch, ThomasThomas.Esch (at) dlr.deUNSPECIFIED
Taubenböck, HannesHannes.Taubenboeck (at) dlr.deUNSPECIFIED
Date:August 2019
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12
DOI :10.1109/JSTARS.2019.2917755
Page Range:pp. 2912-2927
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Built-up density estimation, built-up height estimation, Sentinel-2, TanDEM-X, urban morphology.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience, R - Vorhaben Sicherheitsrelevante Erdbeobachtung
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Remote Sensing Technology Institute > EO Data Science
Deposited By: Geiß, Christian
Deposited On:05 Nov 2019 12:11
Last Modified:05 Nov 2019 12:11

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