增强遗产海洋颜色气溶胶模型以增强内陆和近岸沿海水域的遥感的数据表

在内陆和近岸海域，利用卫星遥感技术监测水体组成面临着巨大挑战，这主要源于大气校正（AC）框架中缺乏具有代表性的大陆气溶胶模型所带来的不确定性。本研究旨在通过扩展现有的海洋色彩气溶胶模型，以提高对这些区域水体特性的遥感监测能力。我们分析了全球AERONET（气溶胶罗伯逊网络）的测量数据，利用先进的分类技术，构建了一系列新的气溶胶模型，并评估了这些模型在提升遥感反射率（Rrs）反演精度方面的效果。

Inland and coastal waters face significant challenges in water constituent monitoring via satellite remote sensing, which mainly stem from uncertainties introduced by the lack of representative continental aerosol models within the atmospheric correction (AC) framework. This study aims to improve the remote sensing monitoring capability of water properties in these regions by expanding existing ocean color aerosol models. We analyzed global AERONET (Aerosol Robotic Network) measurement data, developed a series of new aerosol models using advanced classification techniques, and evaluated the performance of these models in improving the inversion accuracy of remote sensing reflectance (Rrs).