Abstract
To monitor the entire earth system, several global land cover mapping products have been produced based on different remote sensing imagery (e.g., AVHRR, MODIS, SPOT, HJ-1), including UMD Land Cover, Global Land Cover 2000, GlobCover 2009 and GlobeLand30. However, the application potential of those products has not been fully explored at a provincial scale. The primary objective of this study is to compare and investigate the potential of these products in Anhui Province, China. The area and spatial consistency were used to evaluate the four datasets based on China’s GlobeLand 30 due to 30 m spatial resolution and the total accuracy of 83.51%. The Pearson’s correlation coefficient (R) and the percentage disagreement (PD) were used to evaluate the area consistency. The spatial similarity coefficient (O) was here adopted in order to verify the accuracy of spatial positions. A total of eight cover classes including cropland, woodland, grassland, shrubland, wetland, water bodies, artificial surfaces and bareland were reclassified and mapped to perform the intercomparison. The analysis results show that the PD of GlobCover 2009 is respectively 15.36% and −8.43% for “cropland” and “woodland”, while they are −20.20% and 2.10% for UMD. The “woodland” has better agreement percentage in comparison with “cropland”. The O of UMD is the worst of 69.25%, indicating that the spatial consistency is weak for “cropland”. Conversely, the O of GlobCover 2009 reaches up to 83.50%.
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Acknowledgements
The work presented here was supported Scientific Research Training Programme of Anhui University (ZLTS2015178), Anhui Provincial Science & Technology Project (1604a0702016) and Anhui Provincial Science and Technology Major Project (16030701091). The data set is provided by Environmental and Ecological Science Data Center for West China, National Natural Science Foundation of China (http://westdc.westgis.ac.cn).
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Ye, X., Zhao, J., Huang, L., Zhang, D., Hong, Q. (2017). A Comparison of Four Global Land Cover Maps on a Provincial Scale Based on China’s 30 m GlobeLand30. In: Yuan, H., Geng, J., Bian, F. (eds) Geo-Spatial Knowledge and Intelligence. GRMSE 2016. Communications in Computer and Information Science, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-10-3966-9_51
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DOI: https://doi.org/10.1007/978-981-10-3966-9_51
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