Study on Hyperspectral Remote Sensing Estimation Models for the Ground Fresh Biomass of Rice
WANG Xiu-Zhen 1 HUANG Jing-Feng 2 LI Yun-Mei 3 WANG Ren-Chao 2 ( 1 Institute Zhejiang Meteorology, Hangzhou, Zhejiang 310004; 2 Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou, Zhejiang 310029; 3 The College of Geography Science, Nanjing Normal University, Nanjing, Jiangsu 210097,China)
This study was based on the rank difference of the nitrogenous nutrition level by the man-made style through two years rice farm experiment about the difference of the nitrogenous nutrition level. Using linear and non-linear and stepwise multiple regression methods, whose precision had been evaluated and tested on the basis of the experiment data in 2000 acted as train sample, the estimate models for ground fresh biomass of rice was built on the basis of the experiment data in 1999 acted as train sample and evaluated and validated. The results showed that there were some relationships between the characteristic variables of hyperspectra (such as the green peak or red valley of reflectivity or red edge position or sum of 1 st derivative value within red edge ( SD r) and the blue edge ( SD b) or their vegetation indices) and about ground fresh biomass. Based on the results of precision analysis, the model in which the ratio vegetation indices consisted of sum of 1 st derivative value within red edge ( SD r) and the blue edge ( SD b) as variables was the best one of estimating about ground fresh biomass of rice by hyperspectra.