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Proceedings Paper

Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China
Author(s): Tao Cheng; Jialong Zhang; Xinyan Zheng; Rujin Yuan
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Paper Abstract

The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.

Paper Details

Date Published: 8 March 2018
PDF: 9 pages
Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1061103 (8 March 2018); doi: 10.1117/12.2282828
Show Author Affiliations
Tao Cheng, National Geomatics Ctr. of China (China)
Jialong Zhang, Southwest Forestry Univ. (China)
Xinyan Zheng, National Geomatics Ctr. of China (China)
Rujin Yuan, Heilongjiang Institute of Geomatics Engineering (China)


Published in SPIE Proceedings Vol. 10611:
MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Nong Sang; Jie Ma; Zhong Chen, Editor(s)

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