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Proceedings Paper

The application of high spatial resolution remote sensing image for vegetation type recognition in Dagou Valley
Author(s): Aqiang Yang; Chuang Liu; Jianrong Fan; Jinling Zhao; Jing Tan
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Paper Abstract

This paper present a detail processing procedure about SPOT5 image applied for vegetation type recognition, and determines the capacity of high spatial resolution satellite image data to discriminate vegetation type in a complex ecosystem. A high spatial resolution SPOT5 image, captured in April 2005, and coincident field data covering the Dagou valley, was used in this analysis. Image geometric rectification and image fusion are then introduced to take prepare for classification. Subsequently, a maximum likelihood classification algorithm was applied to the SPOT5 image data to map the vegetation classes. Field validation and accuracy assessment are crucial to ensure the reliability of classification results. The strategy of field work and the resulting accuracy evaluations were presented, and yielded the high classification accuracy (overall accuracy=83.86%, Kappa=80.23%). The result showed that the information on vegetation types can be mapped effectively from high spatial resolution satellite image data.

Paper Details

Date Published: 7 November 2008
PDF: 9 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470F (7 November 2008); doi: 10.1117/12.813215
Show Author Affiliations
Aqiang Yang, Institute of Geographical Sciences and Natural Resources Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Chuang Liu, Institute of Geographical Sciences and Natural Resources Research (China)
Jianrong Fan, Institute of Mountain Hazards and Environment (China)
Jinling Zhao, Institute of Geographical Sciences and Natural Resources Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Jing Tan, Institute of Geographical Sciences and Natural Resources Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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