郑姚闽等:A method for alpine wetland delineation and features of border: Zoig Plateau, China
被阅读 55 次
2017-10-19
A method for alpine wetland delineation and features of border: Zoig Plateau, China
作者:Zheng, YM (Zheng Yaomin)[ 1 ] ; Niu, ZG (Niu Zhenguo)[ 1 ] ; Gong, P (Gong Peng)[ 2,3 ] ; Li, MN (Li Mengna)[ 1 ] ; Hu, LL (Hu Lile)[ 4 ] ; Wang, L (Wang Lei)[ 5 ] ; Yang, YX (Yang Yuxiang)[ 6 ] ; Gu, HJ (Gu Hai-jun)[ 7 ] ; Mu, JR (Mu Jinrong)[ 8 ] ; Dou, GJ (Dou Gejia)[ 8 ]  ; Xue, H (Xue Hui)[ 8 ] ; Wang, L (Wang Lin)[ 8 ] ; Li, H (Li Hua)[ 9 ] ; Dou, GJ (Dou Gejie)[ 10 ] ; Dang, ZCR (Dang Zhicairang)[ 10 ] 
CHINESE GEOGRAPHICAL SCIENCE
卷: 27  期: 5  页: 784-799
DOI: 10.1007/s11769-017-0897-3
出版年: OCT 2017
 
摘要
Accurate wetland delineation is the basis of wetland definition and mapping, and is of great importance for wetland management and research. The Zoig Plateau on the Qinghai-Tibet Plateau was used as a research site for research on alpine wetland delineation. Several studies have analyzed the spatiotemporal pattern and dynamics of these alpine wetlands, but none have addressed the issues of wetland boundaries. The objective of this work was to discriminate the upper boundaries of alpine wetlands by coupling ecological methods and satellite observations. The combination of Landsat 8 images and supervised classification was an effective method for rapid identification of alpine wetlands in the Zoig Plateau. Wet meadow was relatively stable compared with hydric soils and wetland hydrology and could be used as a primary indicator for discriminating the upper boundaries of alpine wetlands. A slope of less than 4.5A degrees could be used as the threshold value for wetland delineation. The normalized difference vegetation index (NDVI) in 434 field sites showed that a threshold value of 0.3 could distinguish grasslands from emergent marsh and wet meadow in September. The median normalized difference water index (NDWI) of emergent marsh remained more stable than that of wet meadow and grasslands during the period from September until July of the following year. The index of mean density in wet meadow zones was higher than the emergent and upland zones. Over twice the number of species occurred in the wet meadow zone compared with the emergent zone, and close to the value of upland zone. Alpine wetlands in the three reserves in 2014 covered 1175.19 km(2) with a classification accuracy of 75.6%. The combination of ecological methods and remote sensing technology will play an important role in wetland delineation at medium and small scales. The correct differentiation between wet meadow and grasslands is the key to improving the accuracy of future wetland delineation.
 
通讯作者地址: Niu, ZG (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
通讯作者地址: Gong, P (通讯作者)
Tsinghua Univ, Inst Global Change Studies, Key Lab Earth Syst Modeling, Minist Educ,Ctr Earth Syst Sci, Beijing 100084, Peoples R China.
通讯作者地址: Gong, P (通讯作者)
Beijing Normal Univ, Joint Ctr Global Change Studies, Coll Global Change & Earth Syst Sci GCESS, Beijing 100875, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Tsinghua Univ, Inst Global Change Studies, Key Lab Earth Syst Modeling, Minist Educ,Ctr Earth Syst Sci, Beijing 100084, Peoples R China
[ 3 ] Beijing Normal Univ, Joint Ctr Global Change Studies, Coll Global Change & Earth Syst Sci GCESS, Beijing 100875, Peoples R China
[ 4 ] Chinese Res Inst Environm Sci, Beijing 100012, Peoples R China
[ 5 ] World Wide Fund Nat China, Beijing 100006, Peoples R China
[ 6 ] Wildlife Management Bur Gansu Prov, Lanzhou 730050, Gansu, Peoples R China
[ 7 ] Wetland Management Ctr Sichuang Prov, Chengdu 610081, Sichuan, Peoples R China
[ 8 ] Gansu Gahai Zecha Natl Reserve Adm, Chengdu 747200, Gansu, Peoples R China
[ 9 ] Sichuan Zoige Wetland Natl Reserve Adm, Sichuan 624500, Sichuang, Peoples R China
[ 10 ] Gansu First Meander Yellow River Natl Reserve Adm, Sichuan 747300, Gansu, Peoples R China