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首页»科研成果» 2014
徐玥与合作者在SCIENCE CHINA-EARTH SCIENCES发表论文
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A 30 meter land cover mapping of China with an efficient HU LuanYun1, CHEN YanLei2, XU Yue3, ZHAO YuanYuan1, YU Le1, WANG Jie4 & GONG Peng1,2,4,5* 1 Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China; 2 Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720-3114, USA; 3 College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; 4 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, and Beijing Normal University, Beijing 100101, China; 5 Joint Center for Global Change Studies, Beijing 100875, China ABSTRACT Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised classification approaches. This article used a fast clustering method—Clustering by Eigen Space Transformation (CBEST) to produce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clustered by combining CBEST and K-means in each pre-defined ecological zone (50 in total for China). Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test samples indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products (i.e., Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC) and GlobCover 2009) also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types. KEY WORDS: land cover, mapping, cluster, Landsat TM, CBEST PUBLISHED BY: SCIENCE CHINA-EARTH SCIENCES, 2014, 57 (10): 2293-2304 SOURCE: http://link.springer.com/article/10.1007/s11430-014-4917-1 |
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