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

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

1,2,* , 1
 and
1
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)
Download PDF [969 KB, 19 June 2014; original version 19 June 2014]

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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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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