The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 28-872
Full Name: Wei Su
Position: Senior Lecturer
Age: ON
Sex: Female
Address: College of Information and Electrical Engineering, China Agricultural University, P.O. Box 121, Beijing, 100083, P.R. CHINA
Country: CHINA
Tel: 62737994
Tel prefix: 8610
Fax: 62737741
E-mail address: suwei@cau.edu.cn
Other E-mails: chenyingyi@cau.edu.cn
Title of the Paper: A Hierarchical Object Oriented Method for Land Cover Classification of SPOT 5 Imagery
Authors as they appear in the Paper: Wei Su, Chao Zhang, Xiang Zhu, Daoliang Li
Email addresses of all the authors: suwei@cau.edu.cn,zhangchao_bj@163.com,zhuxiang1018@126.com,li_daoliang@yahoo.com
Number of paper pages: 10
Abstract: Land cover classification with a high accuracy is necessary, especially in waste dump area, accurate land cover information is very important to eco-environment research, vegetation condition study and soil recovery destination. Funded by the international cooperation project Novel Indicator Technologies for Minesite Rehabilitation and sustainable development, a hierarchical object oriented land cover classification is produced in this study. The ample spectral information, textural information, structure and shape information of high resolution SPOT 5 imagery are used synthetically in this method. There are two steps in object oriented information extraction: image segmentation and classification. First, the image is segmented using chessboard segmentation and multi-resolution segmentation method. Second, NDVI is used to distinguish vegetation and non-vegetation; vegetation is classified as high density vegetation, middling density vegetation and low density veget!
ation using spectral information, object oriented image texture analysis; non-vegetation is classified as vacant land and main road using length/width. Accuracy assessment indicate that this hierarchical method can be used to do land cover classification in waste dump area, the total accuracy increases to 86.53%, and Kappa coefficient increases to 0.7907.
Keywords: hierarchical land cover classification, NDVI, object oriented texture analysis, waste dump opencast coalmine area, SPOT 5
EXTENSION of the file: .pdf
Special (Invited) Session: Hierarchical Object Oriented Land Cover Classification Method Using SPOT 5 Imagery in Waste Dump Opencast Coalmine Area
Organizer of the Session: 604-297
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