农业工程学报2012，Vol.28Issue(10)：172-176,5.DOI:10.3969/j.issn.1002-6819.2012.10.027
利用HJ-1-A/B CCD2数据反演冬小麦叶面积指数
Retrieving leaf area index of winter wheat using HJ-1-A/B CCD2 data
摘要
Abstract
Leaf area index (LAI) is one of the most important biophysical parameters of crop and other land surface vegetation. In order to improve the accuracy of retrieving leaf area index of winter wheat using HJ CCD data, the accuracy of different vegetation indices and regression models were compared and analyzed from the aspects of growth stages on the basis of five common vegetation indices including NDVI (normalized difference vegetation index), EV1 (enhanced vegetation index), EVI2 (two-bands enhanced vegetation index), RVI (ratio vegetation index) and SAVI (soil adjusted vegetation index) and three common regression models. The results showed that LAI and all five vegetation indices had good correlative relationship except at reproductive growth stage. Exponential and linear regression model were the best regression models for the whole growth stage and the vegetative stage, respectively. EVI performed better than other four indices when simulated at the whole growth stage (R2=0.9348), and SAVI was the best index for LAI retrieving at vegetative growth stage (R2=0.9404). This paper provides the reference for LAI inversion by vegetation index of winter wheat.关键词
遥感/植被/模型/环境减灾小卫星/叶面积指数反演/冬小麦Key words
remote sensing/ vegetation/ models/ HJ satellites/ leaf area index retrieving/ winter wheat分类
农业科技引用本文复制引用
赵虎,裴志远,马尚杰,王连林,马志平..利用HJ-1-A/B CCD2数据反演冬小麦叶面积指数[J].农业工程学报,2012,28(10):172-176,5.基金项目
国防科工委HJ-1卫星数据应用研究专题(2009A02A0100),农业部规划设计研究院自选课题(201104) （2009A02A0100）
