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标题：Annual dynamics of global land cover and its long-term changes from 1982 to 2015
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作者：Liu, Han ; Gong, Peng ; Wang, Jie 等
期刊名称：Earth System Science Data Discussions
电子版ISSN：1866-3591
出版年度：2020
卷号：12
期号：2
页码：1217-1243
DOI：10.5194/essd-12-1217-2020
语种：English
出版社：Copernicus Publications
摘要：Land cover is the physical material at the surface of the Earth. As the cause and result of global environmental change, land coverchange (LCC) influences the global energy balance and biogeochemical cycles.Continuous and dynamic monitoring of global LC is urgently needed. Effectivemonitoring and comprehensive analysis of LCC at the global scale are rare.With the latest version of GLASS (Global Land Surface Satellite) CDRs(climate data records) from 1982 to 2015, we built the first record of34-year-long annual dynamics of global land cover (GLASS-GLC) at 5 kmresolution using the Google Earth Engine (GEE) platform. Compared to earlierglobal land cover (LC) products, GLASS-GLC is characterized by high consistency, moredetail, and longer temporal coverage. The average overall accuracy for the34 years each with seven classes, including cropland, forest, grassland,shrubland, tundra, barren land, and snow/ice, is 82.81 % based on 2431test sample units. We implemented a systematic uncertainty analysis andcarried out a comprehensive spatiotemporal pattern analysis. Significantchanges at various scales were found, including barren land loss andcropland gain in the tropics, forest gain in the Northern Hemisphere, andgrassland loss in Asia. A global quantitative analysis of human factorsshowed that the average human impact level in areas with significant LCC wasabout 25.49 %. The anthropogenic influence has a strong correlation withthe noticeable vegetation gain, especially for forest. Based on GLASS-GLC,we can conduct long-term LCC analysis, improve our understanding of globalenvironmental change, and mitigate its negative impact. GLASS-GLC will befurther applied in Earth system modeling to facilitate research on globalcarbon and water cycling, vegetation dynamics, and climate change. TheGLASS-GLC data set presented in this article is available athttps://doi.org/10.1594/PANGAEA.913496 (Liu et al., 2020).