Hyperspectral data analysis for subtropical tree species recognition

Author

Fung, Tung ; Ma, Fung Yan ; Siu, Wai Lok

Author_Institution

Dept. of Geogr., Chinese Univ. of Hong Kong, Shatin, Hong Kong

Volume

3

fYear

1998

fDate

6-10 Jul 1998

Firstpage

1298

Abstract

Hyperspectral data analysis is an important basic research arena for remote sensing. However, tree species in the tropical and subtropical environment are not commonly studied and reported. In this study, hyperspectral data are taken for 6 common tree species using a high spectral resolution spectrometer in the subtropical environment of Hong Kong. Data are taken from 400 to 900 nm. Using linear discriminant analysis reveals that these tree species can be recognized with an overall accuracy of %

Keywords

forestry; geophysical techniques; remote sensing; 400 to 900 nm; Acacia; Aleurites; Araucarua; Bauhinia; Casuariana; China; Cinnamomum; Dimocarpus; Ficus; Hong Kong; IR; Lophostemon; Melaleuca; Pinus elliottii; forestry; geophysical measurement technique; hyperspectral data analysis; hyperspectral remote sensing; infrared; linear discriminant analysis; multispectral remote sensing; optical method; subtropical tree species recognition; taxonomic identification; tree species; tropical forest; vegetation mapping; visible; Data analysis; Geography; Hyperspectral imaging; Hyperspectral sensors; Lamps; Libraries; Lighting; Master-slave; Remote sensing; Spectroscopy;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International

Conference_Location

Seattle, WA

Print_ISBN

0-7803-4403-0

Type

conf

DOI

10.1109/IGARSS.1998.691383

Filename

691383