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Remote Sens. 2011, 3(8), 1710-1723; doi:10.3390/rs3081710

An Object-Based Classification Approach for Mapping Migrant Housing in the Mega-Urban Area of the Pearl River Delta (China)

1
Geoinformation in Environmental Planning, Technische Universität Berlin, D-10623 Berlin, Germany
2
Remote Sensing & GIS Research Group, Department of Physical Geography, Goethe University Frankfurt/Main, D-60438 Frankfurt am Main, Germany
*
Author to whom correspondence should be addressed.
Received: 20 June 2011 / Revised: 19 July 2011 / Accepted: 8 August 2011 / Published: 16 August 2011
(This article belongs to the Special Issue Urban Remote Sensing)
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Abstract

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.
Keywords: urban structure types; object-based classification; land-use change; SPOT5; urban sprawl urban structure types; object-based classification; land-use change; SPOT5; urban sprawl
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

d'Oleire-Oltmanns, S.; Coenradie, B.; Kleinschmit, B. An Object-Based Classification Approach for Mapping Migrant Housing in the Mega-Urban Area of the Pearl River Delta (China). Remote Sens. 2011, 3, 1710-1723.

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