应用遥感数据反演针叶林有效叶面积指数

Retrieving effective leaf area index of conifer forests using Landsat TM images.

以红壤丘陵典型区千烟洲及其周边为研究区,利用陆地卫星TM图像数据和同期野外实测的37个针叶林样地有效叶面积指数数据,分析了遥感植被指数与湿地松、杉木林、马尾松和针叶林总体之间的相关关系,进而分别建立了遥感植被指数与不同林型针叶林有效叶面积指数间的线性与非线性回归模型.研究表明,遥感植被指数与不同林型针叶林有效叶面积指数存在较好的相关性,但不同林型之间的相关系数存在一定差异;所建立的针叶林有效叶面积指数遥感反演模型以三次曲线回归方程拟合精度最高.

The normalized difference vegetation index( NDVI ), from Landsat TM data was correlated to ground based measurements of effective leaf area index( LAI ) obtained from 37 sampling sites of conifer forests including slash pine( Pinus elliottii ), Chinese fir (Cuninghamia lanceolata ) and Masson pine( Pinus massoniana ) located in Qianyanzhou Agricultural Station and its nearby areas in red soil hilly region is outheastern China's Jiangxi Province. The monadic linear regression models and the non linear regression models were established for determining the relations between NDVI and effective LAI . It is found that there is an obvious correlation among NDVI and conifer forests, but the correlation coefficients show the difference in the different types of forests. In addition, the cubic equations are the best in the different forms of the regression models for retrieving effective LAI of conifer forests using Landsat TM images in red soil hilly region.