A hybrid inversion method for mapping leaf area index from MODIS data: experiments and application to broadleaf and needleleaf canopies
A hybrid inversion method for mapping leaf area index from MODIS data: experiments and application to broadleaf and needleleaf canopies
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DOI：
10.1016/j.rse.2004.11.001
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发表时间：
2005-02
影响因子：
13.5
通讯作者：
H. Fang;S. Liang
中科院分区：
文献类型：
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作者：
H. Fang;S. Liang
叶面积指数(LAI)是各种陆面过程模式所需的重要变量。它是从中分辨率成像光谱仪(MODIS)数据使用查找表(LUT)方法在业务上产生的，但反演精度仍需显著提高。在这项研究中，我们提出了一种替代方法，它结合了辐射传递(RT)模拟和非参数回归方法。研究了两种非参数回归方法(即神经网络和投影寻踪回归)。根据针对两大生物群类别(阔叶和针叶植被)进行的辐射传输模拟，构建了一个综合数据库。在参数化过程中使用了一种新的土壤反射指数(SRI)和解析模拟的叶片光学特性。该算法在两个地点进行了测试，一个在美国马里兰州的中纬度温带农业区，另一个在加拿大的北方森林地点，并准确地估计了叶面积指数。将得到的LAI图与MODIS科学团队和ETM+数据进行了比较。对于阔叶林、针叶林和其他覆盖类型，MODIS标准叶面积指数产品与我们的结果一致，但由于复杂的生物群类型，高估了2.0-3.0的阔叶林。
Leaf area index (LAI) is an important variable needed by various land surface process models. It has been produced operationally from the Moderate Resolution Imaging Spectroradiometer (MODIS) data using a look-up table (LUT) method, but the inversion accuracy still needs significant improvements. We propose an alternative method in this study that integrates both the radiative transfer (RT) simulation and nonparametric regression methods. Two nonparametric regression methods (i.e., the neural network [NN] and the projection pursuit regression [PPR]) were examined. An integrated database was constructed from radiative transfer simulations tuned for two broad biome categories (broadleaf and needleleaf vegetations). A new soil reflectance index (SRI) and analytically simulated leaf optical properties were used in the parameterization process. This algorithm was tested in two sites, one at Maryland, USA, a middle latitude temperate agricultural area, and the other at Canada, a boreal forest site, and LAI was accurately estimated. The derived LAI maps were also compared with those from MODIS science team and ETM+ data. The MODIS standard LAI products were found consistent with our results for broadleaf crops, needleleaf forest, and other cover types, but overestimated broadleaf forest by 2.0–3.0 due to the complex biome types.