The applications of high-spatial-resolution satellite data have been increasing in recent years owing to improvements in sensor techniques, and the errors in estimated parameters induced by ignoring topographic effects are increasingly stressed because their effects are important for parameter retrieval from high-spatial-resolution satellite observations. A coupled surface-atmosphere model is employed to develop a two-step multiparameter estimation scheme to simultaneously estimate multiple parameters (leaf area index, LAI; aerosol optical depth, AOD; photosynthetically active radiation, PAR; incident shortwave radiation, ISR; surface albedo, and fraction of absorbed photosynthetically active radiation, FAPAR) from long-term Landsat 4–8 top-of-atmosphere (TOA) observations. First, the influential parameters of the coupled model are retrieved through optimization retrieval strategies. Then, these estimated parameters are entered into the coupled model to compute the PAR, ISR, surface reflectance, surface albedo, and FAPAR. Validation of this scheme with in situ measurements from 57 sites demonstrates that it can successfully estimate multiple parameters from Landsat TOA data, with root mean square errors (RMSEs) of LAI, AOD, FAPAR, visible albedo, shortwave albedo, PAR, and ISR of 0.69, 0.16, 0.13, 0.034, 0.047, 26.80, and 64.28 W/m ² , respectively. In the two-step multiparameter estimation scheme, atmospheric and topographic corrections of satellite observations are avoided because the atmospheric and topographic effects are incorporated, and the surface anisotropy is also effectively considered. In addition, by using the two-step multiparameter estimation scheme, physical connections among the multiple parameters are ensured since they are estimated from the same physical model.

中文翻译：

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基于地形考虑的 Landsat 观测的多参数估计

近年来，由于传感器技术的进步，高空间分辨率卫星数据的应用越来越多，忽略地形效应引起的估计参数误差越来越受到重视，因为它们的影响对于从高空间分辨率的参数检索中具有重要意义。分辨率卫星观测。采用耦合地表大气模型开发两步多参数估计方案，以同时估计多个参数（叶面积指数，LAI；气溶胶光学深度，AOD；光合有效辐射，PAR；入射短波辐射，ISR；表面反照率，和来自长期 Landsat 4-8 大气顶 (TOA) 观测的吸收光合有效辐射的分数 (FAPAR)。第一的，通过优化检索策略检索耦合模型的影响参数。然后，将这些估计参数输入耦合模型以计算 PAR、ISR、表面反射率、表面反照率和 FAPAR。验证这个方案来自 57 个站点的原位测量表明，它可以成功地估计 Landsat TOA 数据的多个参数，LAI、AOD、FAPAR、可见反照率、短波反照率、PAR 和 ISR 的均方根误差 (RMSE) 为 0.69、0.16、0.13 、0.034、0.047、26.80 和 64.28 W/m ² 分别。在两步多参数估计方案中，由于结合了大气和地形效应，避免了卫星观测的大气和地形校正，也有效地考虑了地表各向异性。此外，通过使用两步多参数估计方案，确保了多个参数之间的物理联系，因为它们是从同一物理模型中估计出来的。