The Hi-GLASS all-wave daily net radiation product: Algorithm and product validation

作者：Bo Jiang, Jiakun Han, Hui Liang, Shunlin Liang, Xiuwan Yin, Jianghai Peng, Tao He, Yichuan Ma · 发表于：Science of Remote Sensing · 年份：2023 · DOI：10.1016/j.srs.2023.100080 · 被引用次数：18 · 研究领域：Atmospheric and Environmental Gas Dynamics、Atmospheric Ozone and Climate、Meteorological Phenomena and Simulations

The surface net radiation ( R n ) represents the balance of the radiative budget on the land surface and drives many physical and biological processes. An accurate and long-term product for global daily coverage of R n at a high spatial resolution is needed for a variety of applications at regional and local scales. This study proposes two algorithms, called the downward shortwave radiation (DSR)-based algorithm and the top-of-atmosphere (TOA)-based algorithm, to estimate R n by using Landsat data. The DSR-based algorithm consists of three conditional models, and was developed based on the analysis of the relationship between R n and shortwave radiation as well as ancillary information from ground measurements and various datasets. The TOA-based algorithm was developed by linking R n to TOA observations from Landsat sensors and ancillary information. The two algorithms were developed by using the random forest method. The results of their validation against ground measurements showed that the DSR-based algorithm outperformed the TOA-based algorithm in terms of accuracy, with a determination coefficient (R 2 ) of 0.93, root-mean-squared error (RMSE) of 17.58 Wm −2 , and bias of −4.27 Wm −2 . It was stable under various conditions. We then applied the DSR-based algorithm to generate a product of the global daily R n , called the High-resolution (Hi)- Global LAnd Surface Satellite (GLASS), from 2013 to 2018 at a spatial resolution of 30 m under a clear sky based on remotely sens...