【摘要】 以福建省为研究区,利用环境星(HJ-1)CCD数据,选择并提取了与叶面积指数(LAI)关系密切的4种植被指数,即归一化比值植被指数(NDVI)、比值植被指数(RVI)、改进的土壤调节植被指数(mSAVI)及增强型植被指数(EVI),结合研究区内准同步马尾松LAI地面观测数据,通过研究各种指数与马尾松LAI之间的关系,选择与马尾松LAI相关最密切的RVI同实测LAI建立6种非线性回归模型,6种模型中以理查德模型建立的模型精度为最高,总体均值预报偏差相对误差为3.1%,并以此模型实现了福建省马尾松LAI遥感反演。更多还原

【Abstract】 Taking Fujian province as the research object and basing on the CCD data of HJ-1,four vegetation indices were selected which closely related to LAI. The selected indices included NDVI,RVI, mSAVI and EVI. Meanwhile,data synchronized with LAI of Pinus massoniana was obtained,and then the relationship between the indices and the LAI was built. At last,six kinds of the non-linear regression models,between the LAI of Pinus massoniana and the selected index RVI that most closely related to the LAI,was established. It was found that the model based on the Richards distribution function is the best and the relative error of the prediction of mean value is 3. 1%. Based on this model,the remote sensing inversion of the LAI of Pinus massoniana in Fujian province was implemented.更多还原