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Proceedings Paper

Extraction and analysis of LUCC information based on DTCs
Author(s): Ping Wang; Jixian Zhang; Yongguo Zheng; He Ting; Chunyan Zhou
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Paper Abstract

With the development of technology of remote sensing and computer, the quantity of data and information is increased greatly. After a long-time research, we find that it is impracticable to manage and handle information only using information. Only decision-making system can do it, Decision Tree is an important method in classification of land use and land cover. This paper gives the formation process from building synthetic database to designing decision tree model, knowledge base to provide some forms of data for extracting LUCC information, there are three aspect data include about: 1) grid data such as remote sensing data TM, SPOT, 2) Ground-measured data such as DEM, and 3) thematic Vector data such as land use data and so on. Regularity base consists of all the transformation rules from the source state to the destination of the problem, each dot include at least one rule, the foundation can resolve recognize where change in land area and type. At last, according to the level of complexity of the change of LUCC, it gives two kinds of decision tree models: the classified comparative between single result and the synchronic analysis with multi-temporal images. (1) The classified comparison between single results. We take the information extracting for ice changes as an example, and the result is very ideal. (2) The synchronic analysis with multi-temporal images. We construct decision tree in Hei bei, the condition include the grey value and the other features such as slope gradient and GIS thematic supported data, the result shows that the biggest change type is that other lands are transferred to the forest. The area precision is excess to 85%, and the sort precision 90%.

Paper Details

Date Published: 10 November 2004
PDF: 8 pages
Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); doi: 10.1117/12.565377
Show Author Affiliations
Ping Wang, Shandong Univ. of Science and Technology/Taian (China)
Chinese Academy of Surveying and Mapping (China)
Jixian Zhang, Chinese Academy of Surveying and Mapping (China)
Yongguo Zheng, Shandong Univ. of Science and Technology/Taian (China)
He Ting, China Land Institute of Surveying and Planning (China)
Chunyan Zhou, Shandong Univ. of Science and Technology/Taian (China)


Published in SPIE Proceedings Vol. 5573:
Image and Signal Processing for Remote Sensing X
Lorenzo Bruzzone, Editor(s)

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