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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