玉米冠层FPAR的高光谱遥感估算研究--基于PCA方法及近、短波红外波段

A STUDY OF CORN FPAR ESTIMATION FROM HYPERSPECTRAL DATA BASED ON PCA APPROACH AND NEAR-INFRARED SHORTWAVE BANDS

光合有效辐射分量(Fraction of Photosynthetically Active Radiation,FPAR)是进行生态系统功能和全球变化研究的重要参数,准确估算FPAR具有重要意义。通过对野外实测玉米高光谱数据和光合有效辐射数据的分析,探讨了主成分分析方法在高光谱信息提取及估算玉米冠层FPAR参数方面的可行性,在此基础上,结合植被指数验证FPAR估算效果,分析近红外及短波红外高光谱数据在FPAR估算方面的应用潜力。

Fraction of Photosynthetically Active Radiation （FPAR） is a key parameter in the study of such topics as ecological system function and global changes, and hence it is important to estimate FPAR accurately. Based on an analysis of hyperspectral and photosynthetical active radiation data of the corn, this paper studied the feasibility of Principal Component Analysis （PCA） for hyperspectral information extraction and corn canopy FPAR estimation, and analyzed the potential of near - shortwave infrared hyperspectral data for FPAR estimation. The results show that the PCA method can be used effectively to compress hyperpsectral information, and will give a better performance than vegetation indices for FPAR estimation. Near - infrared and shortwave band hyperspectral reflectance has a great potential for estimating FPAR and hence can help improve the precision of FPAR estimation.