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Urbanization in India – Spatiotemporal analysis using remote sensing data

Taubenböck, Hannes and Wegmann, Martin and Roth, Achim and Mehl, Harald and Dech, Stefan (2009) Urbanization in India – Spatiotemporal analysis using remote sensing data. Computers, Environment and Urban Systems, 33 (3), pp. 179-188. Elsevier. DOI: doi:10.1016/j.compenvurbsys.2008.09.003 ISSN 0198-9715

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Official URL: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V9K-4TT1FYG-1&_user=100058&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000007338&_version=1&_urlVersion=0&_userid=100058&md5=ce759cc4f1ef30b394314a39c0ffb892&errMsg=1

Abstract

Urbanization is arguably the most dramatic form of irreversible land transformation. Though urbanization is a worldwide phenomenon, it is especially prevalent in India, where urban areas have experienced an unprecedented rate of growth over the last 30 years. In this uncontrolled situation, city planners lack tools to measure, monitor, and understand urban sprawl processes. Multitemporal remote sensing has become an important data-gathering tool for analysing these changes. By using time-series of Landsat data, we classify urban footprints since the 1970s. This lets us detect temporal and spatial urban sprawl, redensification and urban development in the tremendously growing 12 largest Indian urban agglomerations. A multi-scale analysis aims to identify spatiotemporal urban types. At city level, the combination of absolute parameters (e.g. areal growth or built-up density) and landscape metrics (e.g. SHAPE index) quantitatively characterise the spatial pattern of the cities. Spider charts can display the spatial urban types at three time stages, showing temporal development and helping the reader compare all cities based on normalized scales. In addition, gradient analysis provides insight into location-based spatiotemporal patterns of urbanization. Therefore, we analyse zones defining the urban core versus the urban edges. The study aims to detect similarities and differences in spatial growth in the large Indian urban agglomerations. These cities in the same cultural area range from 2.5 million inhabitants to 20 million (in the metropolitan region of Mumbai). The results paint a characteristic picture of spatial pattern, gradients and landscape metrics, and thus illustrate spatial growth and future modelling of urban development in India.

Item URL in elib:https://elib.dlr.de/58674/
Document Type:Article
Title:Urbanization in India – Spatiotemporal analysis using remote sensing data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Taubenböck, Hanneshannes.taubenboeck (at) dlr.deUNSPECIFIED
Wegmann, Martinmartin.wegmann (at) uni-wuerzburg.deUNSPECIFIED
Roth, AchimAchim.Roth (at) dlr.deUNSPECIFIED
Mehl, Haraldharald.mehl (at) dlr.deUNSPECIFIED
Dech, Stefanstefan.dech (at) dlr.deUNSPECIFIED
Date:May 2009
Journal or Publication Title:Computers, Environment and Urban Systems
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:33
DOI :doi:10.1016/j.compenvurbsys.2008.09.003
Page Range:pp. 179-188
Publisher:Elsevier
ISSN:0198-9715
Status:Published
Keywords:Urban growth; Multitemporal remote sensing; Landscape metrics; Gradient analysis; Classification of cities; Mega cities; India
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Environment and Security
Deposited By: Taubenböck, Dr. Hannes
Deposited On:20 Apr 2009
Last Modified:06 Sep 2019 15:24

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