An integrated classification strategy of hyperspectral imaging spectrometer data

Author

Cui, Linli ; Fan, Wenyi ; Zhao, Zhongming ; Shi, Jun ; Peng, Ling

Author_Institution

Inst. of Remote Sensing Applications, Chinese Acad. of Sci., Beijing, China

Volume

5

fYear

2004

fDate

20-24 Sept. 2004

Firstpage

3283

Abstract

It is one of the hotspots to apply the advanced remote sensing data and processing techniques to monitor the desertification. Some monitor factors, such as vegetation, sand and soil moisture, were identified by use of the OMIS-I hyperspectral data individually and its integration with the 7_th band of ETM data in this study. The results indicate that the former has a high identification precision in vegetation and sand, but in soil moisture it is not well because of the influence of upper vegetation; this can been greatly improved in the latter and the overall identification precision is higher than the former.

Keywords

geophysical signal processing; hydrological techniques; image classification; moisture measurement; sand; soil; terrain mapping; vegetation mapping; 7_th band; China; ETM data; Inner Mongolia Autonomous Region; Ke´erqing; Namaqi; OMIS-I hyperspectral data; Zhelimu; data processing techniques; desertification monitoring; hyperspectral imaging spectrometer data; integrated classification strategy; remote sensing data; sand; soil moisture; vegetation; Data mining; Forestry; Hyperspectral imaging; Hyperspectral sensors; Pixel; Remote monitoring; Remote sensing; Soil moisture; Spectroscopy; Vegetation mapping;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International

Print_ISBN

0-7803-8742-2

Type

conf

DOI

10.1109/IGARSS.2004.1370403

Filename

1370403