TY - JOUR
T1 - Large-Area Characterization of Urban Morphology - Mapping of Built-Up Height and Density Using TanDEM-X and Sentinel-2 Data
AU - Geis, Christian
AU - Leichtle, Tobias
AU - Wurm, Michael
AU - Pelizari, Patrick Aravena
AU - Standfus, Ines
AU - Zhu, Xiao Xiang
AU - So, Emily
AU - Siedentop, Stefan
AU - Esch, Thomas
AU - Taubenbock, Hannes
N1 - Publisher Copyright:
© 2008-2012 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - 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 large-area 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 Sentinel-2 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.
AB - 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 large-area 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 Sentinel-2 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.
KW - Built-up density estimation
KW - Sentinel-2
KW - TanDEM-X
KW - built-up height estimation
KW - urban morphology
UR - http://www.scopus.com/inward/record.url?scp=85072629770&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2019.2917755
DO - 10.1109/JSTARS.2019.2917755
M3 - Article
AN - SCOPUS:85072629770
SN - 1939-1404
VL - 12
SP - 2912
EP - 2927
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 8
M1 - 8745682
ER -