School of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK 73019, USA
Yuanwei Qin
School of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK 73019, USA
Jinwei Dong
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Geli Zhang
College of Land Science and Technology, China Agricultural University, Beijing 100193, China
Xuebin Yang
School of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK 73019, USA
Xiaocui Wu
Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Chandrashekhar Biradar
Center for International Forestry Research (CIFOR) and World Agroforestry Center (ICRAF), Asia Continental Program, New Delhi, India
Yang Hu
School of Ecology and Environment, Ningxia University, Yinchuan 750021, China
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Cumulative views and downloads
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Total article views: 2,389 (including HTML, PDF, and XML)
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1,694
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2,389
68
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HTML: 1,694
PDF: 352
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Total: 2,389
BibTeX: 68
EndNote: 130
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1,049
585
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1,717
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HTML: 1,049
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Total: 1,717
BibTeX: 71
EndNote: 73
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Cumulative views and downloads
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Total article views: 4,106 (including HTML, PDF, and XML)
Thereof 3,998 with geography defined
and 108 with unknown origin.
Total article views: 2,389 (including HTML, PDF, and XML)
Thereof 2,319 with geography defined
and 70 with unknown origin.
Total article views: 1,717 (including HTML, PDF, and XML)
Thereof 1,679 with geography defined
and 38 with unknown origin.
Existing satellite-based forest maps have large uncertainties due to different forest definitions and mapping algorithms. To effectively manage forest resources, timely and accurate annual forest maps at a high spatial resolution are needed. This study improved forest maps by integrating PALSAR-2 and Landsat images. Annual evergreen and non-evergreen forest-type maps were also generated. This critical information supports the Global Forest Resources Assessment.
Existing satellite-based forest maps have large uncertainties due to different forest...
