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

dc.contributor.authorBai, Yan
dc.contributor.authorFeng, Min
dc.contributor.authorJiang, Hao
dc.contributor.authorWang, Juanle
dc.contributor.authorLiu, Yingzhen
dc.date.accessioned2024-01-10T19:10:49Z
dc.date.available2024-01-10T19:10:49Z
dc.date.issued2015-08-18
dc.description.abstractThis 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.
dc.description.urihttps://doi.org/10.3390/rs70810589
dc.identifierhttps://doi.org/10.13016/dspace/00bi-xtao
dc.identifier.citationBai, 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.
dc.identifier.urihttp://hdl.handle.net/1903/31566
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isAvailableAtCollege of Behavioral & Social Sciencesen_us
dc.relation.isAvailableAtGeographyen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.subjectland cover
dc.subjectreference data
dc.subjectstratified sampling
dc.subjectvisual interpretation
dc.subjectvalidation
dc.titleValidation of Land Cover Maps in China Using a Sampling-Based Labeling Approach
dc.typeArticle
local.equitableAccessSubmissionNo

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