title: A method to estimate land surface temperature from Meteosat Second Generation data using multi-temporal data.
abstract: Land surface temperature (LST) is key parameters in the interaction of land-atmosphere system. This paper proposed a method to inverse LST from multi-temporal thermal infrared remote sensing data based on the theory of split-window algorithm and diurnal temperature cycle model. The new method was validated by a diurnal brightness temperatures data sets corresponding to MSG2-SEVIRI, which was simulated by the atmospheric radiative transfer model MODTRAN 4 with several input parameters under clear sky, including near surface air temperature, atmospheric water, surface temperature and emissivity, and viewing angles, and result showed the root mean square error (RMSE) of LST reaches 1.2K for simulated data and most errors are within ± 2K with accurate parameters input. At the same time, comparison of LST estimated using the proposed method from MSG2-SEVIRI data with that from MOD11B1 V5 product displayed that the RMSE equals to 3.0K and most errors are distributed within ± 6K. But, the method is proposed under no cloudy condition and is tested only in mid-latitude and daytime; more validation should be made in different areas and atmospheric conditions.
authors: Xiaoyu
authors: X
authors: Zhang
authors: Lingling
authors: L
authors: Li
mesh_terms: D000465:Algorithms; D018534:Earth, Planet; D009391:Nephelometry and Turbidimetry / Q000379:methods*; D058998:Remote Sensing Technology / Q000379:methods*; D018531:Spacecraft; D013696:Temperature; D013817:Thermography / Q000379:methods*