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Classification using the watershed method

 

作者: A. I. WATSON,   R. A. VAUGHAN,   M. POWELL,  

 

期刊: International Journal of Remote Sensing  (Taylor Available online 1992)
卷期: Volume 13, issue 10  

页码: 1881-1890

 

ISSN:0143-1161

 

年代: 1992

 

DOI:10.1080/01431169208904237

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

Several methods of producing a thematic map, suitable for forestry inventories, are evaluated as to their relative accuracy and efficiency of production. It is argued that all probability-based methods are founded on assumptions that are always false, and therefore necessarily lead to higher error rates. An alternative non-probabilistic method, the watershed, is put forward as a better solution to the classification problem. In order to fully establish the superiority of the watershed method, a complex mountainous area was deliberately chosen to provide difficult and testing conditions. It is demonstrated that the watershed method is far superior to the traditional probability-based methods, both in respect of the efficiency with which a thematic map can be produced, and its accuracy of classification. With the same data, the accuracy of classification were: hybrid method—77 percent supervised maximum likelihood method—82 percent watershed method—96 percent.

 

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