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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2,784
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4,185
146
211
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PDF: 970
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Total: 4,185
BibTeX: 146
EndNote: 211
Views and downloads (calculated since 09 Feb 2023)
Cumulative views and downloads
(calculated since 09 Feb 2023)
Total article views: 2,441 (including HTML, PDF, and XML)
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1,721
374
346
2,441
73
138
HTML: 1,721
PDF: 374
XML: 346
Total: 2,441
BibTeX: 73
EndNote: 138
Views and downloads (calculated since 11 Oct 2024)
Cumulative views and downloads
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Total article views: 1,744 (including HTML, PDF, and XML)
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1,063
596
85
1,744
73
73
HTML: 1,063
PDF: 596
XML: 85
Total: 1,744
BibTeX: 73
EndNote: 73
Views and downloads (calculated since 09 Feb 2023)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 4,185 (including HTML, PDF, and XML)
Thereof 4,075 with geography defined
and 110 with unknown origin.
Total article views: 2,441 (including HTML, PDF, and XML)
Thereof 2,369 with geography defined
and 72 with unknown origin.
Total article views: 1,744 (including HTML, PDF, and XML)
Thereof 1,706 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...
