Assessing Rice Chlorophyll Content with Vegetation Indices from Hyperspectral Data
Leaf chlorophyll content is not only an important biochemical para-meter for determinating the capacity of rice photosynthesis, but also a good in-dicator of crop stress, nutritional state. Due to the reliable, operational and non-destructive advantages, hyperspectral remote sensing plays a significant role for assessing and monitoring chlorophyll content. In the study, a few of typical ve-getation indices (VI) with the combination of 670nm and 800nm band reflectance. Normalized Difference Vegetation Index (NDVI), Modified Simple Ra-tio index (MSR), Modified Chlorophyll Absorption Ratio Index (MCARI), Transformed Chlorophyll Absorption Ratio Index (TCARI), and Optimized Soil-Adjusted Vegetation Index (OSAVI) are modified by using 705nm and 750nm band reflectance so as to reduce the effect of spectral saturation in 660-680nm absorptive band region, and then used to assess the rice chlorophyll con-tent. The result shows that the five mentioned VIs have better correlation with rice chlorophyll content while using 705nm and 750nm. In addition, in the study the Weight optimization combination (WOC) principle is utilized to fur-ther assess the capacity of the five modified VIs for estimating rice chlorophyll content, it is proved that OSAVI and MSR display the better performance.
Chlorophyll Content Vegetation Indices Weight Optimization Combination Hyperspectral Remote Sensing
Xingang Xu Xiaohe Gu Xiaoyu Song Cunjun Li Wenjiang Huang
National Engineering Research Center for Information Technology in Agriculture,P.O. Box 2449-26, Beijing 100097, P.R. China
国际会议
南昌
英文
296-303
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）