DocumentCode
1825564
Title
Research on New Classification Methods of Remote Sensing of Mass Ingredient without Vegetation of Hei Shan Gorge in Yellow River Basin
Author
Wang Shudong ; Wang Xiaohua
Author_Institution
Sch. of Geogr. & Remote Sensing Sci., Beijing Normal Univ., Beijing, China
Volume
2
fYear
2009
fDate
18-20 Aug. 2009
Firstpage
693
Lastpage
696
Abstract
Method of normalized spectrum was presented for problem-saving of spectral complexity and separating capacity, which were used to differ prtrous mountain from exposed soil and desert. Using the method, normalized spectral index (NSI) was established; then, the preous mountain index (RMI) was created; finally, we established desert-exposed soil difference model (DS-Def). The above results indicated that the precision is higher than traditional classification. But the method is too complex to extract the information quickly, so we selected above sensitive factors as new bands to classify mass ingredient in non-vegetation area using supervise classification. The result indicted that the method is relatively simple and effective.
Keywords
remote sensing; rivers; soil; Hei Shan Gorge; Yellow River basin; desert-exposed soil difference model; mass ingredient; normalized spectral index; normalized spectrum method; remote sensing; rock mountain index; spectral complexity; supervise classification; Area measurement; Data mining; Image analysis; Information analysis; Remote sensing; Rivers; Satellites; Soil measurements; Spectral analysis; Vegetation; classification method; heterogeneous underlying surface; soil erosion; spectrum and texture;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location
Xian
Print_ISBN
978-0-7695-3744-3
Type
conf
DOI
10.1109/IAS.2009.186
Filename
5284229
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