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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4,336
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PDF: 1,029
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Total: 4,336
BibTeX: 168
EndNote: 226
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Cumulative views and downloads
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Total article views: 2,533 (including HTML, PDF, and XML)
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1,771
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2,533
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HTML: 1,771
PDF: 411
XML: 351
Total: 2,533
BibTeX: 78
EndNote: 152
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Total article views: 1,803 (including HTML, PDF, and XML)
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1,100
618
85
1,803
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HTML: 1,100
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Total: 1,803
BibTeX: 90
EndNote: 74
Views and downloads (calculated since 09 Feb 2023)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 4,336 (including HTML, PDF, and XML)
Thereof 4,227 with geography defined
and 109 with unknown origin.
Total article views: 2,533 (including HTML, PDF, and XML)
Thereof 2,462 with geography defined
and 71 with unknown origin.
Total article views: 1,803 (including HTML, PDF, and XML)
Thereof 1,765 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...
