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Urbanization in India – Spatiotemporal analysis using remote sensing data

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

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Offizielle 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

Kurzfassung

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.

Dokumentart:Zeitschriftenbeitrag
Titel:Urbanization in India – Spatiotemporal analysis using remote sensing data
Autoren:
AutorenInstitution oder E-Mail-Adresse der Autoren
Taubenböck, Hanneshannes.taubenboeck@dlr.de
Wegmann, Martinmartin.wegmann@uni-wuerzburg.de
Roth, AchimAchim.Roth@dlr.de
Mehl, Haraldharald.mehl@dlr.de
Dech, Stefanstefan.dech@dlr.de
Datum:Mai 2009
Erschienen in:Computers, Environment and Urban Systems
Referierte Publikation:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:33
DOI :doi:10.1016/j.compenvurbsys.2008.09.003
Seitenbereich:Seiten 179-188
ISSN:0198-9715
Status:veröffentlicht
Stichwörter:Urban growth; Multitemporal remote sensing; Landscape metrics; Gradient analysis; Classification of cities; Mega cities; India
HGF - Forschungsbereich:Verkehr und Weltraum (alt)
HGF - Programm:Weltraum (alt)
HGF - Programmthema:W EO - Erdbeobachtung
DLR - Schwerpunkt:Weltraum
DLR - Forschungsgebiet:W EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Umwelt und Sicherheit
Hinterlegt von: Dr. Hannes Taubenböck
Hinterlegt am:20 Apr 2009
Letzte Änderung:23 Aug 2013 03:02

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