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
Link To Document :
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