A radiance-based split-window algorithm for land surface temperature retrieval: Theory and application to MODIS data |
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| Institution: | 1. Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan, China;2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;3. Key Laboratory of Earth Observation Hainan Province, Sanya, China;4. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China;5. College of Resources Engineering, Longyan University, Longyan, China |
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| Abstract: | The split-window algorithm is the most commonly used method for land surface temperature (LST) retrieval from satellite data. Simplification of the Planck’s function, as an important step in developing the SWA, allows us to directly relate the radiance to the temperature toward solving the radiative transfer equation (RTE) set. In this study, Planck’s radiance relationship between two adjacent thermal infrared channels was modeled to solve the RTE set instead of simplification of the Planck’s function. A radiance-based split-window algorithm (RBSWA) was developed and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) data. The performance of the RBSWA was assessed and compared with three most common brightness temperature-based split-window algorithms (BTBSWAs) by using the simulated data and satellite measurements. Simulation analysis showed that the LST retrieval using RBSWA had a Root Mean Square Error (RMSE) of 0.5 K and achieved an improvement of 0.3 K compared with three BTBSWAs, and the LST retrieval accuracy using RBSWA was better than 1.5 K considering uncertainties in input parameters based on the sensitivity analysis. For application of RBSWA to MODIS data, the results showed that: 1) comparison between LST from MODIS LST product and LST retrieved using RBSWA showed a mean RMSE of 1.33 K for 108 groups of MODIS image covering continental US, which indicates RBSWA is reliable and robust; 2) when using the measurements from US surface radiation budget network as real values the RMSE of the RBSWA algorithm was 2.55 K and was slightly better than MODIS LST product; and 3) through the cross validation using Advanced Spaceborne Thermal Emission and Reflection Radiometer LST product, the RMSE of the RBSWA algorithm was 2.23 K and was 0.28 K less than that of MODIS LST product. We conclude that the RBSWA for LST retrieval from MODIS data can attain a better accuracy than the BTBSWA. |
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| Keywords: | Land surface temperature Split-window algorithm Simplification of Planck’s function MODIS |
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