DocumentCode :
2952558
Title :
Based on TM Image Extraction Method of Pinus sylvestris var. mongolica Forests Indexes in Honghuaerji
Author :
Yang Fan ; Hou Enke
Author_Institution :
Coll. of Geol. & Environ., Xian Univ. of Sci. & Technol., Xian, China
fYear :
2011
fDate :
30-31 July 2011
Firstpage :
1
Lastpage :
3
Abstract :
MONGOLICA forests is composed of HONGHUAERJI one of the main vegetation, MONGOLICA in the region after long-term impact of natural succession and human activities, pine forests in the formation of a unique, extremely valuable research and ecological value. MONGOLICA forests in the region has been listed as a national nature reserve and seed base. Applications in remote sensing, vegetation indices have been widely used for qualitative and quantitative evaluation of vegetation cover and its growth activity. This paper remote sensing images, the use of ERDAS software to extract pine forests in vegetation indices, including the following steps: data preprocessing and image cropping; selection and extraction of vegetation index; non-supervisory classification and category were merging. Finally, after a comprehensive solution into plans found that the use of vegetation index image extraction TM successful, the plan can be good to reflect MONGOLICA forests and other vegetation cover conditions for the development and pine forests in the area provide a good basis for protection.
Keywords :
forestry; image classification; vegetation mapping; Honghuaerji; Pinus Sylvestris var. Mongolica forests index; TM image extraction; data preprocessing; image cropping; nonsupervisory classification; pine forests; remote sensing; vegetation cover; vegetation index; Analytical models; Data mining; Indexes; Monitoring; Remote sensing; Software; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0859-6
Type :
conf
DOI :
10.1109/ICCASE.2011.5997585
Filename :
5997585
Link To Document :
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