遥感提取植物生理参数LAI/FPAR的研究进展与应用

植物生理参数LAI/FPAR是2个重要的陆地特征参量。利用遥感光谱模型并结合地面验证是提取区域尺度的LAI/FPAR最有效的途径。提取LAI/FPAR的模型主要有光谱指数模型和辐射传输模型两类,经过精确的辐射标定和大气纠正的遥感数据可以得到较高精度的LAI/FPAR数据。影响LAI/FPAR精度的因素很多,其中主要因素是像元的异质性、植被类型和物候期等。LAI/FPAR与作物产量有更直接的关系,也是大量作物生长模型的基础,利用这些参数可以实现真实的作物产量预测,特别是开展全球尺度的单产预测。

OVERVIEW OF LAI/FPAR RETRIEVAL FROM REMOTELY SENSED DATA

Vegetation biophysical variables, LAI and FPAR, are the most important terrestrial properties. For acquiring these variables in local scale, the most effective approach is by remote sensing models combined with the ground-based validation. Spectral index model and radiant transmission model are two kinds of key methods. Through the precise radiometric and atmospheric correction, it is possible to obtain the LAI/FPAR products with a high accuracy. There are several factors influencing the accuracy of these products, such as the pixel heterogeneity, vegetation types and growing seasons. LAI and FPAR have the compact relationship with crop yield and they are also the basic variables of many crop growth models. Using them could realize the true yield prediction, especially for estimating the production in the global scale.