Evaluation of several classification schemes for mapping forest cover types in Michigan †
作者:
W. D. HUDSON,
期刊:
International Journal of Remote Sensing
(Taylor Available online 1987)
卷期:
Volume 8,
issue 12
页码: 1785-1796
ISSN:0143-1161
年代: 1987
DOI:10.1080/01431168708954816
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
Landsat MSS data were evaluated for mapping forest cover types in the northern Lower Peninsula of Michigan. The study examined seasonal variations, interpretation procedures and vegetation composition/distribution and their effect on overall classification accuracy and ability to identify individual pine species. Photographic images were used for visual interpretations while digital analysis was performed using a common (ERDAS) microcomputer image processing system. The classification schemes were evaluated using contingency tables and were ranked using the KAPPA statistic. The various classification schemes were ranked differentially according to study site location. Visual interpretation procedures ranked best, or least accurate, depending on the spatial distribution and complexity of the forest cover. Supervised classification techniques were more accurate than unsupervised clustering over all sites and seasons. Maximum likelihood classification of June data was superior to any digital classification technique of February data. The study indicates that classification accuracy is more dependent on the composition and distribution of forests in the northern Lower Peninsula of Michigan than on the selection of a particular classification scheme.
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