Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index

被引:157
作者
Pu, RL [1 ]
Gong, P
Biging, GS
Larrieu, MR
机构
[1] Univ Calif Berkeley, CAMFER, Berkeley, CA 94720 USA
[2] Secretaria Agr Ganaderia Pesca & Alimentac, Proyecto Forestal Desarrollo, RA-1063 Buenos Aires, DF, Argentina
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2003年 / 41卷 / 04期
关键词
Hyperion; leaf area index; red-edge position; red well position;
D O I
10.1109/TGRS.2003.813555
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
A correlation analysis was conducted between I forest leaf area index (LAI) and two red edge parameters: red edge position (REP) and red well position (RWP), extracted from reflectance image retrieved from Hyperion data. Field spectrometer data and LAI measurements were collected within to days, after the Earth Observing One satellite passed over the study site in the Patagonia region of Argentina. The two, red edge parameters were extracted with four. approaches; four-point interpolation, polynomial fitting, Lagrangian technique, and inverted-Gaussian (IG) modeling. Experimental results indicate that the four-point approach is the most practical and suitable method for extracting the two red edge parameters from Hyperion data because only four bands and a. simple interpolation computation are needed. The polynomial fitting approach is a direct method and has its practical value it hyperspectral data are available. However, it requires more computation time. The Lagrangian method is applicable only if the first derivative spectra are available; thus, it is not suitable to multispectral remote sensing, The IG approach needs further testing and refinement for Hyperion data.
引用
收藏
页码:916 / 921
页数:6
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