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Proceedings Paper

Comparison of IGBP DISCover land cover dataset with a land cover dataset in China
Author(s): Hua Chen; Dafang Zhuang
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Paper Abstract

Land cover information is important for the study of physical, chemical, biological and anthropological process on the surface of earth. Remote sensing data has been used to produce the land cover map by visual interpretation or automatic classification method in the past years. IGBP DISCover land cover dataset is a global land cover dataset based on remote sensing method in recent years. Firstly, we present a method to compare different land cover dataset based on invariant reliable land unit. Secondly, we compare IGBP Discover land cover dataset with Chinese land cover dataset. Finally, we analyze the possible reasons impacting the differences among the land cover classifications. The comparison results show that most of the land surface in China was identified as different types in those two datasets. For example, 63.7% of the deciduous needleleaf forest units in CLCD are mapped to the mixed forest by IDLCD. The different classification scheme and method used in these datasets are most likely the reasons to explain the differences between them.

Paper Details

Date Published: 15 September 2004
PDF: 9 pages
Proc. SPIE 5549, Weather and Environmental Satellites, (15 September 2004); doi: 10.1117/12.559263
Show Author Affiliations
Hua Chen, Institute of Geographic Sciences and Natural Resources Research, CAS (China)
Graduate School, CAS (China)
Dafang Zhuang, Institute of Geographic Sciences and Natural Resources Research, CAS (China)

Published in SPIE Proceedings Vol. 5549:
Weather and Environmental Satellites
Thomas H. Vonder Haar; Hung-Lung Allen Huang, Editor(s)

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