In this paper, we propose a Possibilistic C Repulsive Medoids (PCRMDD) clustering algorithm, based on possibility theory and principle of c-medoids clustering method.The PCRMDD algorithm is applied to mixed-pixel classification on Landsat ETM+ images of Shanghai central city, and endmember fraction images and spectral reflectance of endmembers on images are automatically acquired.Accuracy analysis of pixels unmixing demonstrates that PCRMDD represents a robust and efficient tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in noisy environment.Furthermore, according to the obtained multi-temporal land cover classification of the study area, the pattern of spatio-temporal land use evolvement and urban land spatial sprawl with urbanization in Shanghai central city are explored with the application of spatial analytical function of GIS.Results show that the urban land use structure is optimizing during vigorous urban renewal and large-scale development of the whole Pudong District, which will have an active influence to improve urban space landscape and enhance quality of ecological environment.
DAI Xiao-yan, GUO Zhong-yang, ZHANG Li-quan, WU Jian-ping
. Spatio-temporal Pattern of Urban Land Cover Evolvement Based on Mixed-pixel Classification for Remote Sensing Imagery[J]. SCIENTIA GEOGRAPHICA SINICA, 2009
, 29(1)
: 111
-116
.
DOI: 10.13249/j.cnki.sgs.2009.01.111
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