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Remote Sens. 2015, 7(8), 10589-10606; doi:10.3390/rs70810589

Validation of Land Cover Maps in China Using a Sampling-Based Labeling Approach

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
Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
5
General Staff Information Center of Surveying and Mapping, Beijing 100088, China
*
Author to whom correspondence should be addressed.
Academic Editors: Giles M. Foody, Parth Sarathi Roy and Prasad S. Thenkabail
Received: 17 July 2015 / Revised: 30 July 2015 / Accepted: 12 August 2015 / Published: 18 August 2015
View Full-Text   |   Download PDF [1344 KB, uploaded 18 August 2015]   |  

Abstract

This paper presents a rigorous validation of five widely used global land cover products, i.e., GLCC (Global Land Cover Characterization), UMd (University of Maryland land cover product), GLC2000 (Global Land Cover 2000 project data), MODIS LC (Moderate Resolution Imaging Spectro-radiometer Land Cover product) and GlobCover (GLOBCOVER land cover product), and a national land cover map GLCD-2005 (Geodata Land Cover Dataset for year 2005) against an independent reference data set over China. The land cover reference data sets in three epochs (1990, 2000, and 2005) were collected on a web-based prototype system using a sampling-based labeling approach. Results show that, in China, the highest overall accuracy is observed in GLCD-2005 (72.3%), followed by MODIS LC (68.9%), GLC2000 (65.2%), GlobCover (57.7%) and GLCC (57.2%), while UMd has the lowest accuracy (48.6%); all of the products performed best in representing “Trees” and “Others”, well with “Grassland” and “Cropland”, but problematic with “Water” and “Urban” across China in general. Moreover, in respect of GLCD-2005, there are significant accuracy differences across seven geographical locations of China, ranging from 46.3% in the Southwest, 77.5% in the South, 79.2% in the Northwest, 80.8% in the North, 81.8% in the Northeast, 82.6% in the Central, to 89.0% in the East. This study indicates that a regionally focused land cover map would in fact be more accurate than extracting the same region from a globally produced map. View Full-Text
Keywords: land cover; reference data; stratified sampling; visual interpretation; validation land cover; reference data; stratified sampling; visual interpretation; validation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bai, Y.; Feng, M.; Jiang, H.; Wang, J.; Liu, Y. Validation of Land Cover Maps in China Using a Sampling-Based Labeling Approach. Remote Sens. 2015, 7, 10589-10606.

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