DocumentCode :
2228757
Title :
Comparison of object-oriented and Maximum Likelihood Classification of land use in Karst area
Author :
Guoqing Zhou ; Shengyun Xiong
Author_Institution :
GuangXi Key Lab. for Spatial Inf. & Geomatics, Guilin Univ. of Technol., Guilin, China
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6099
Lastpage :
6102
Abstract :
This paper presents a comparison analysis for methods of land use classification, between object-oriented and Maximum likelihood methods in Karst area. Nine types of objects are selected in terms of “Standard of Land Classification” (version 2001)” and “Classification of Land Use (version 2008)”, China for classification. They are Shrub land, dry land, construction land, bare land, woodland, irrigation land, water, forest land, and garden land. Comparison analysis of land uses using object-oriented and Maximum Likelihood Classification method is conducted. Downtown of Daxu county, Guilin, China in a typical karst area is chosen as the study area, and ISR-P6 satellite imagery are chosen for experiments. The experimental results discover that classification results have a significant impacts to land use classification in karst area. The object-oriented classifier achieved the classification accuracy of 93.96%, whereas the maximum likelihood classifier produced a classification accuracy of 78.94%.This study demonstrates that the object-oriented classifier is significantly better for classification of land use in karst area.
Keywords :
geophysical image processing; maximum likelihood estimation; object-oriented methods; terrain mapping; vegetation; vegetation mapping; China; Classification of Land Use; Daxu county; Guilin; ISR-P6 satellite imagery; Standard of Land Classification; bare land; classification accuracy; construction land; dry land; forest land; garden land; irrigation land; karst area; land use classification; maximum likelihood classification method; maximum likelihood classifier; object-oriented classifier; object-oriented method; shrub land; woodland; Accuracy; Land surface temperature; Remote sensing; Satellites; Spatial resolution; Standards; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352215
Filename :
6352215
Link To Document :
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