中文摘要：

【目的】叶面积指数（LAI）是描述植物冠层结构、群落生长分析和陆地生态系统研究的重要参数，提高叶面积指数的估算精度是遥感工作者的重要研究方向之一。【方法】通过不同氮素营养水平的水稻小区实验，利用2004年中稻高光谱反射率数据，模拟中等分辨率成像光谱仪（MODIS）前四个通道，提出包含蓝、绿、红和近红外四个谱段的调节型归一化植被指数ANDVI（adjusted-normalized difference vegetation index）。对ANDVI和归一化植被指数NDVI（normalized difference vegetation index）、增强型植被指数EVI（enhanced vegetation index）、绿波比值指数GRI（green ratio index）、红边比值指数RRI（red-edge ratio index）等5个光谱植被指数与水稻LAI的相关关系进行了分析。利用2004年晚稻试验数据，对与LAI相关关系较好的ANDVI进行验证。【结果】ANDVI指数模型预测效果最好，均方根误差为1.771，估算精度达到63.1%。【结论】说明ANDVI具有进行在大面积范围内监测水稻LAI的能力。

英文摘要：

[Objective] Leaf area index （LAI） is an important parameter for describing vegetation canopy structure and community development condition in the terrestrial ecosystem. To improve the estimation accuracy of leaf area index is the main research direction for the remote sensed scholars. [Method] In this study the mid and late maturing rice at the different nitrogen fertilizer level was planted in 2004 yr, and the hyperspectral canopy reflectance of mid rice was obtained. The front four bands of Moderate Resolution Imaging Spectrometer （MODIS） （i.e. red,near-infrared,blue and green regions） were simulated to develop, and the adjusted-normalized difference vegetation index （ANDVI）. A comparison of ANDVI with other VIs, such as Normalized Difference Vegetation Index （NDVI）, enhanced Vegetation Index （EVI）, Green Ratio Index （GRI） and Red-edge Ratio Index （RRI） for estimation of LAI was made. The efficiency of ANDVI was validated with the hyperspectral canopy reflectance data of late maturing rice in 2004. [ Result ] Results show that the estimation precision of exponential equation of ANDVI was 63.1%, the root mean square error was 1.771, [ Conclusion ] and ANDVI has the potential of monitoring LAI in an extensive area.