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An Algorithm for the Retrieval of High Temporal-Spatial Resolution Shortwave Albedo from Landsat-8 Surface Reflectance and MODIS BRDF
| Content Provider | MDPI |
|---|---|
| Author | Yang, Gang Wang, Jiyan Xiong, Junnan Yong, Zhiwei Ye, Chongchong Sun, Huaizhang Liu, Jun Duan, Yu He, Yufeng He, Wen |
| Copyright Year | 2021 |
| Description | Variations in surface physicochemical properties and spatial structures can prominently transform surface albedo which conversely influence surface energy balances and global climate, making it crucial to continuously monitor and quantify surface dynamics at fine scales. Here, we made two improvements to propose an algorithm for the simultaneous retrieval of 30-m Landsat albedo, based on the coupling of Landsat-8 and MODIS BRDF. First, two kinds of prior knowledge were added to disaggregate BRDF, including the Anisotropic Flat Index (AFX) and the Albedo-to-Nadir reflectance ratio (AN ratio), from MODIS scales into Landsat scales. Second, a simplified data fusion method was used to simulate albedo for the same, subsequent, or antecedent dates. Finally, we validated the reliability and correlations of the algorithm at six sites of the Surface Radiation (SURFRAD) budget network and intercompared the results with another algorithm called the ‘concurrent approach’. The results showed that the proposed algorithm had favorable usability and robustness, with a root mean square error (RMSE) of 0.015 (8%) and a mean bias of −0.005; while the concurrent approach had a RMSE of 0.026 (14%) and a mean bias of −0.018. The results emphasized that the proposed algorithm has captured subtle changes in albedo over a 16-day period. |
| Starting Page | 4150 |
| e-ISSN | 20724292 |
| DOI | 10.3390/rs13204150 |
| Journal | Remote Sensing |
| Issue Number | 20 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-10-16 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensing Surface Albedo High Temporal-spatial Resolution Landsat-8 Modis Brdf |
| Content Type | Text |
| Resource Type | Article |
