Many existing techniques for estimating the optical properties of a body of water directly from a hyperspectral remote sensing spectrum are based on the idea of ‘spectral matching’ – that is, input parameters in a forward model are systematically varied until the measured and modelled spectra are sufficiently similar. This is usually done by using numerical optimization methods with a simplified forward model, or by precomputing a large library of spectra with a more realistic model, and then searching the library for the best match. In this letter, we show that is possible to combine the two approaches by using a full radiative transfer model in an optimization routine. We include results of running the algorithm on both simulated and measured data.

许多直接用于从高光谱遥感光谱估算水体光学特性的现有技术都是基于“光谱匹配”的思想的，也就是说，正向模型中的输入参数会系统地变化，直到测量和建模的光谱被改变为止。足够相似。通常，这可以通过使用具有简化前向模型的数值优化方法来完成，或者通过使用更现实的模型来预先计算大型光谱库，然后在该库中搜索最佳匹配来完成。在这封信中，我们表明可以通过在优化例程中使用完整的辐射传输模型来组合这两种方法。我们包括在模拟和测量数据上运行算法的结果。