安徽农业科学Issue(2)：907-910,4.
基于CHRIS/PROBA的植被叶面积指数估算模型研究
Estimation Models of Leaf Area Index (LAI) Based on Remote Sensing Image of CHRIS/PROBA
摘要
Abstract
The ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) was used for providing space borne imaging spectrometer and multiangular data to assess the LAI. Five spectral vegetation indices (VI) were derived from CHRIS-PROBA image, including normalized difference vegetation index (NDVI), perpendicular vegetation index (PVI), modified soil adjusted vegetation index (MSAVI), ratio vegetation index (RVI), atmospheric resistance vegetation index(ARVI). Three hundreds LAI-VI correlation models were established. The VI-LAI correlation coefficients varied greatly across vegetation, vegetation indices, as well as image angular. In all models, from the perspective of angular, the best model is 0° image,R2 =0. 591 ,RMSE =0. 650, the worst model is -55° image,R2 = 0. 551 ,RMSE =0.821, from the perspective vegetation types, the best model is coniferous forest, followed by the broadleaf forests, shrubs, coniferous forests and grasslands, from the types of vegetation model, exponential model is better than one regression model, from the perspective vegetation index, the best model is PVI, followed by MSAVI, NDVI, RVI, ARVI.关键词
多角度/高光谱/植被指数/叶面积指数/模型Key words
Multi-angular/ Hyperspectral/ Vegetation index/ LAI/ Model分类
农业科技引用本文复制引用
曹建军,顾祝军,徐建华,刘永娟..基于CHRIS/PROBA的植被叶面积指数估算模型研究[J].安徽农业科学,2013,(2):907-910,4.基金项目
国家自然科学基金项目(41071281) （41071281）
江苏省高校自然科学研究项目(10KJD170005). （10KJD170005）
