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Remote Sens. 2014, 6(9), 8739-8759; doi:10.3390/rs6098739

Assessing Consistency of Five Global Land Cover Data Sets in China

1
State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
General Staff Information Center of Surveying and Mapping, Beijing 100088, China
*
Author to whom correspondence should be addressed.
Received: 10 June 2014 / Revised: 7 August 2014 / Accepted: 9 September 2014 / Published: 18 September 2014
View Full-Text   |   Download PDF [5638 KB, uploaded 18 September 2014]   |  

Abstract

Global land cover mapping with high accuracy is essential to downstream researches. Five global land cover data sets derived from moderate-resolution satellites, i.e., Global Land Cover Characterization (GLCC), University of Maryland land cover product (UMd), Global Land Cover 2000 project data (GLC2000), MODIS Land Cover product (MODIS LC), and GLOBCOVER land cover product (GlobCover), have been widely used in many researches. However, these data sets were produced using different data sources and class definitions, which led to high uncertainty and inconsistency when using them. This study looked into the consistencies and discrepancies among the five data sets in China. All of the compared data sets were aggregated to consistent spatial resolution and extent, along with a 12-class thematic classification schema; intercomparisons among five datasets and each with reference data GLCD-2005 were performed. Results show reasonable agreement across the five data sets over China in terms of the dominating land cover types like Grassland and Cropland; while discrepancies of Forest classes, particularly Shrubland and Wetland among them are great. Additionally, GLC2000 has the highest agreement with GLCD-2005; MODIS LC gets the highest map-specific consistency compared with others; whereas UMd has the lowest agreement with GLCD-2005, but also has the lowest map-specific consistency. View Full-Text
Keywords: land cover; per-pixel comparison; agreement; consistency; China land cover; per-pixel comparison; agreement; consistency; China
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Bai, Y.; Feng, M.; Jiang, H.; Wang, J.; Zhu, Y.; Liu, Y. Assessing Consistency of Five Global Land Cover Data Sets in China. Remote Sens. 2014, 6, 8739-8759.

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