李丛丛等:A Circa 2010 Thirty Meter Resolution Forest Map for China
被阅读 1032 次
2014-08-12

A Circa 2010 Thirty Meter Resolution Forest Map for China
作者:Li, CC (Li, Congcong)[ 1,2 ] ; Wang, J (Wang, Jie)[ 3 ] ; Hu, LY (Hu, Luanyun)[ 4 ] ; Yu, L (Yu, Le)[ 4 ] ; Clinton, N (Clinton, Nicholas)[ 4 ] ; Huang, HB (Huang, Huabing)[ 3 ] ; Yang, J (Yang, Jun)[ 4 ] ; Gong, P (Gong, Peng)[ 3,4,5,6 ]
REMOTE SENSING
卷: 6  期: 6  页: 5325-5343
DOI: 10.3390/rs6065325
出版年: JUN 2014

摘要
This study examines the suitability of 30 m Landsat Thematic Mapper (TM), 250 m time-series Moderate Resolution Imaging Spectrometer (MODIS) Enhanced Vegetation Index (EVI) and other auxiliary datasets for mapping forest extent in China at 30 m resolution circa 2010. We calculated numerous spectral features, EVI time series, and topographical features that are helpful for forest/non-forest distinction. In this research, extensive efforts have been made in developing training samples over difficult to map or complex regions. Scene by scene quality checking was done on the initial forest extent results and low quality results were refined until satisfactory. Based on the forest extent mask, we classified the forested area into 6 types (evergreen/deciduous broadleaf, evergreen/deciduous needleleaf, mixed forests, and bamboos). Accuracy assessment of our forest/non-forest classification using 2195 test sample units independent of the training sample indicates that the producer's accuracy (PA) and user's accuracy (UA) are 92.0% and 95.7%, respectively. According to this map, the total forested area in China was 164.90 million ha (Mha) circa 2010. It is close to the forest area of 7th National Forest Resource Inventory with the same definition of forest. The overall accuracy for the more detailed forest type classification is 72.7%.

通讯作者地址: Gong, P (通讯作者)
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China
[ 3 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
[ 4 ] Tsinghua Univ, Minist Educ Key Lab Earth Syst Modeling, Ctr Earth Syst Sci, Beijing 100084, Peoples R China
[ 5 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
[ 6 ] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA