NDLI: Comparison of object-oriented and Maximum Likelihood Classification of land use in Karst area

Content Provider	IEEE Xplore Digital Library
Author	Guoqing Zhou Shengyun Xiong
Copyright Year	2012
Description	Author affiliation: GuangXi Key Lab. for Spatial Inf. & Geomatics, Guilin Univ. of Technol., Guilin, China (Guoqing Zhou; Shengyun Xiong)
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.
Sponsorship	IEEE Geoscience Remote Sensing Soc.
Starting Page	6099
Ending Page	6102
File Size	952017
Page Count	4
File Format	PDF
ISBN	9781467311601
ISSN	21536996
e-ISBN	9781467311595
e-ISBN	9781467311588
DOI	10.1109/IGARSS.2012.6352215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-22
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Remote sensing Satellites Standards Vegetation mapping Land surface temperature Spatial resolution
Content Type	Text
Resource Type	Article

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