Global land cover mapping: a review and uncertainty analysis

Remote Sensing
By: , and 

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Abstract

Given the advances in remotely sensed imagery and associated technologies, several global land cover maps have been produced in recent times including IGBP DISCover, UMD Land Cover, Global Land Cover 2000 and GlobCover 2009. However, the utility of these maps for specific applications has often been hampered due to considerable amounts of uncertainties and inconsistencies. A thorough review of these global land cover projects including evaluating the sources of error and uncertainty is prudent and enlightening. Therefore, this paper describes our work in which we compared, summarized and conducted an uncertainty analysis of the four global land cover mapping projects using an error budget approach. The results showed that the classification scheme and the validation methodology had the highest error contribution and implementation priority. A comparison of the classification schemes showed that there are many inconsistencies between the definitions of the map classes. This is especially true for the mixed type classes for which thresholds vary for the attributes/discriminators used in the classification process. Examination of these four global mapping projects provided quite a few important lessons for the future global mapping projects including the need for clear and uniform definitions of the classification scheme and an efficient, practical, and valid design of the accuracy assessment.

Publication type Article
Publication Subtype Journal Article
Title Global land cover mapping: a review and uncertainty analysis
Series title Remote Sensing
DOI 10.3390/rs61212070
Volume 6
Issue 12
Year Published 2014
Language English
Publisher MDPI
Contributing office(s) Western Geographic Science Center
Description 24 p.
First page 12070
Last page 12093
Online Only (Y/N) N
Additional Online Files (Y/N) N
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