NDLI: A /spl nu/-insensitive SVM approach for compliance monitoring of the conservation reserve program

Content Provider	IEEE Xplore Digital Library
Author	Xiaomu Song Cherian, G. Guoliang Fan
Copyright Year	2004
Abstract	We study an automatic compliance monitoring approach for U.S. Department of Agriculture's (USDA) Conservation Reserve Program (CRP). CRP compliance monitoring checks each CRP tract regarding its contract stipulations, and is formulated as an unsupervised classification of Landsat imageries given the CRP reference data. Assuming the majority of a CRP tract is compliant, we want to locate the non-CRP outliers. A one-class support vector machine (OCSVM) is used to separate minor outliers (non-CRP) from the majority (CRP). /spl nu/ is an important OCSVM parameter that controls the percentage of outliers and is unknown here. Usually, /spl nu/ estimation may be complicated or computationally expensive. We propose a /spl nu/-insensitive approach by incorporating both the OCSVM and two-class support vector machine (TCSVM) sequentially. Specifically, support vector machine scores obtained from the OCSVM, which indicate the distances between data samples and the classification hyperplane in a feature space, are used to select sufficient and reliable training samples for the TCSVM. Simulation results show the effectiveness and robustness of the proposed method.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	99
Ending Page	103
Page Count	5
File Size	438523
File Format	PDF
ISSN	1545598X
Volume Number	2
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification US Department of Agriculture Computerized monitoring Contracts Satellites Remote sensing Water conservation Plants (biology) Large-scale systems unsupervised classification Compliance monitoring Conservation Reserve Program (CRP) support vector machine (SVM)
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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