An object-based classification approach for mapping "migrant housing" in the mega-urban area of the Pearl River Delta (China)

Urban areas develop on formal and informal levels. Informal development is often highly dynamic, leading to a lag of spatial information about urban structure types. In this work, an object-based remote sensing approach will be presented to map the migrant housing urban structure type in the Pearl River Delta, China. SPOT5 data were utilized for the classification (auxiliary data, particularly up-to-date cadastral data, were not available). A hierarchically structured classification process was used to create (spectral) independence from single satellite scenes and to arrive at a transferrable classification process. Using the presented classification approach, an overall classification accuracy of migrant housing of 68.0% is attained.

Metadaten
Author:	Sebastian D'Oleire-Oltmanns, Bodo Coenradie, Birgit Kleinschmit
URN:	urn:nbn:de:hebis:30:3-250008
DOI:	https://doi.org/10.3390/rs3081710
ISSN:	2072-4292
Parent Title (English):	Remote sensing
Publisher:	Molecular Diversity Preservation International (MDPI)
Place of publication:	Basel
Document Type:	Article
Language:	English
Date of Publication (online):	2011/08/17
Date of first Publication:	2011/08/16
Publishing Institution:	Universitätsbibliothek Johann Christian Senckenberg
Release Date:	2012/06/22
Tag:	SPOT5; land-use change; object-based classification; urban sprawl; urban structure types
Volume:	3
Issue:	8
Page Number:	14
First Page:	1710
Last Page:	1723
HeBIS-PPN:	357341155
Institutes:	Geowissenschaften / Geographie / Geographie
Dewey Decimal Classification:	7 Künste und Unterhaltung / 71 Landschaftsgestaltung, Raumplanung / 710 Städtebau, Raumplanung, Landschaftsgestaltung
Sammlungen:	Universitätspublikationen
Licence (German):	Creative Commons - Namensnennung 3.0

Open Access