遥感数据lai / fpar检索综述

Wu Bing-fang, Zeng Yuan, Huang Jin-liang
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引用次数: 15

摘要

植被生物物理变量LAI和FPAR是最重要的陆地特征。在局部尺度上获取这些变量,最有效的方法是将遥感模型与地面验证相结合。光谱指数模型和辐射透射模型是两种关键的方法。通过精确的辐射和大气校正,可以获得精度较高的LAI/FPAR产品。这些产品的精度受到像元异质性、植被类型和生长季节等因素的影响。LAI和FPAR与作物产量关系密切,是许多作物生长模型的基本变量。利用它们可以实现真实的产量预测,特别是在全球范围内的产量估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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