TY  - JOUR
A1  - Taubenböck, H
A1  - Wurm, M
A1  - Netzband, M
A1  - Zwenzner, H
A1  - Roth, A
A1  - Rahman, A
A1  - Dech, S
T1  - Flood risks in urbanized areas - multi-sensoral approaches using remotely sensed data for risk assessment
JF  - NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
N2  - Estimating flood risks and managing disasters combines knowledge in climatology, meteorology, hydrology, hydraulic engineering, statistics, planning and geography - thus a complex multi-faceted problem. This study focuses on the capabilities of multi-source remote sensing data to support decision-making before, during and after a flood event. With our focus on urbanized areas, sample methods and applications show multi-scale products from the hazard and vulnerability perspective of the risk framework. From the hazard side, we present capabilities with which to assess flood-prone areas before an expected disaster. Then we map the spatial impact during or after a flood and finally, we analyze damage grades after a flood disaster. From the vulnerability side, we monitor urbanization over time on an urban footprint level, classify urban structures on an individual building level, assess building stability and quantify probably affected people. The results show a large database for sustainable development and for developing mitigation strategies, ad-hoc coordination of relief measures and organizing rehabilitation.
KW  - damage assessment disaster
KW  - satellite data
KW  - management
KW  - radar
KW  - inundation
KW  - disaster
KW  - sar
KW  - gis
KW  - integration
KW  - earthquake
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-139605
VL  - 11
IS  - 2
ER  - 
TY  - JOUR
A1  - Taubenböck, H.
A1  - Weigand, M.
A1  - Esch, T.
A1  - Staab, J.
A1  - Wurm, M.
A1  - Mast, J.
A1  - Dech, S.
T1  - A new ranking of the world's largest cities—Do administrative units obscure morphological realities?
JF  - Remote Sensing of Environment
N2  - With 37 million inhabitants, Tokyo is the world's largest city in UN statistics. With this work we call this ranking into question. Usually, global city rankings are based on nationally collected population figures, which rely on administrative units. Sprawling urban growth, however, leads to morphological city extents that may surpass conventional administrative units. In order to detect spatial discrepancies between the physical and the administrative city, we present a methodology for delimiting Morphological Urban Areas (MUAs). We understand MUAs as a territorially contiguous settlement area that can be distinguished from low-density peripheral and rural hinterlands. We design a settlement index composed of three indicators (settlement area, settlement area proportion and density within the settlements) describing a gradient of built-up density from the urban center to the periphery applying a sectoral monocentric city model. We assume that the urban-rural transition can be defined along this gradient. With it, we re-territorialize the conventional administrative units. Our data basis are recent mapping products derived from multi-sensoral Earth observation (EO) data – namely the Global Urban Footprint (GUF) and the GUF Density (GUF-DenS) – providing globally consistent knowledge about settlement locations and densities. For the re-territorialized MUAs we calculate population numbers using WorldPop data. Overall, we cover the 1692 cities with >300,000 inhabitants on our planet. In our results we compare the consistently re-territorialized MUAs and the administrative units as well as their related population figures. We find the MUA in the Pearl River Delta the largest morphologically contiguous urban agglomeration in the world with a calculated population of 42.6 million. Tokyo, in this new list ranked number 2, loses its top position. In rank-size distributions we present the resulting deviations from previous city rankings. Although many MUAs outperform administrative units by area, we find that, contrary to what we assumed, in most cases MUAs are considerably smaller than administrative units. Only in Europe we find MUAs largely outweighing administrative units in extent.
KW  - city size
KW  - urban agglomeration
KW  - rank-size distribution
KW  - remote sensing
KW  - global urban footprint
KW  - urban morphology
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-240634
VL  - 232
ER  -