Study on hyperspectral remote sensing estimation models about aboveground fresh biomass of rice

Xiuzhen Wang; Jingfeng Huang; Yunmei Li; Renchao Wang

doi:10.1117/12.557403

9 November 2004 Study on hyperspectral remote sensing estimation models about aboveground fresh biomass of rice

Xiuzhen Wang, Jingfeng Huang, Yunmei Li, Renchao Wang

Proceedings Volume 5544, Remote Sensing and Modeling of Ecosystems for Sustainability; (2004) https://doi.org/10.1117/12.557403
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

The data for this study was collected from two-year (1999 and 2000) field experiments that based on different artificial nitrogen treatments. Linear, non-linear and stepwise multiple regression analysis were adopted for modeling The data in 1999 was utilized as training sample for modeling hyperspectra remote sensing estimation of rice aboveground fresh biomass, and the data in 2000 was evaluated and tested the models' predictive accuracy. Results of fitness analysis between hyperspectral variables and rice aboveground fresh biomass indicate that some hyperspectral characteristic variables and their combinations are closely correlated to aboveground biomass, such as red edge wavelength (λr),maximum reflectivity in green region, minimum reflectivity in red region, and the vegetation index based on the sum of first derivative spectral reflectance in blue region and that in red region. Determining the highest correlated wavebands and the best-fitting variables for raw spectra, first derivative spectra and hyperspectral characteristic variables through stepwise multiple regressions, and the results reveal that the relationship between the first derivative spectra and rice aboveground biomass is much clearer and simpler when compared with the rest. The best model for rice aboveground biomass estimation is based on the ration vegetation indices that calculated with the sum of the first derivative spectra reflectance in blue region and that in red region.

Citation Download Citation

Xiuzhen Wang, Jingfeng Huang, Yunmei Li, and Renchao Wang "Study on hyperspectral remote sensing estimation models about aboveground fresh biomass of rice", Proc. SPIE 5544, Remote Sensing and Modeling of Ecosystems for Sustainability, (9 November 2004); https://doi.org/10.1117/12.557403

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available