DocumentCode :
479808
Title :
Automated Estimation of Vegetation Fraction Based on Landsat TM/ETM+ Imagery
Author :
Yang, Shengmei ; Zhang, Qiuwen ; Li, Wenbo
Author_Institution :
Hubei Key Lab. of Digital Watershed Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
891
Lastpage :
894
Abstract :
Vegetation fraction is mainly associated with the living environment of human being. Forest canopy density (FCD) model and sub-pixel model are applied to automatically estimate the vegetation fraction in Qingjiang river basin. FCD model uses the vegetation bare-soil shadow index (VBSI). The sub-pixel model method applies the normalized difference vegetation index (NDVI) based on the dimidiate pixel algorithm. The vegetation fraction of Qingjiang river area is estimated based on the Landsat enhanced thematic mapper (ETM+) imagery with the ENVI 4.0 and the EARDAS 8.7 image software. Results indicate that the estimate accuracy of two models exceeds 75%. Both the FCD model and the sub-pixel model are reliable to extract the vegetation fraction. The information of this study is useful for further study on the vegetation fraction automated estimation, especially in mountainous area.
Keywords :
satellite communication; vegetation mapping; EARDAS 8.7 image software; ENVI 4.0; FCD model; Landsat TM-ETM+ imagery; Qingjiang river basin; automated vegetation fraction estimation; dimidiate pixel algorithm; enhanced thematic mapper; forest canopy density model; normalized difference vegetation index; subpixel model; vegetation bare-soil shadow index; Biological system modeling; Bismuth; Computer science; Infrared spectra; Large-scale systems; Remote sensing; Rivers; Satellites; Soil; Vegetation mapping; Qingjiang River Basin; automated estimation; image-processing; landsat TM/ETM+; remote sensing; vegetation fraction; vegetation index;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.1337
Filename :
4721893
Link To Document :
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