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Land surface temperature and emissivity separation (TES) is a key problem in thermal infrared remote sensing. Many TES algorithms have been proposed and validated on natural surface materia...

In this article, great efforts are focused on the temperature and emissivity separation (TES) from hyperspectral thermal infrared data. Instead of proposing a new TES method, several published TES ...

A novel satellite cross-calibration method is proposed using image pairs with large view zenith angle observations. Previous studies on cross calibration have focused primarily on image pairs with ...

Land surface temperature (LST) is a key parameter in the physics of land surface processes on a regional and global scale, as it combines the results of all surface–atmospheric interactions and ene...

Land surface temperature LST and land surface emissivity LSE are two key parameters in global climate study. This article aims to cross-validate LST/LSE products retrieved from data of the Spinning Enhanced Visible and Infrared Imager SEVIRI on board the first geostationary satellite, Meteosat Second Generation MSG, with Moderate Resolution Imaging Spectroradiometer MODIS LST/LSE version 5 products over the Iberian Peninsula and over Egypt and the Middle East. Besides time matching, coordinate matching is another requirement of the cross-validation. An area-weighted aggregation algorithm was used to aggregate SEVIRI and MODIS LST/LSE products into the same spatial resolution. According to the quality control QC criterion and the view angle, the cross-validation was completed under clear-sky conditions and within a view angle difference of less than 5° for the two instruments to prevent land surface anisotropic effects. The results showed that the SEVIRI LST/LSE products are consistent with MODIS LST/LSE products and have the same trend over the two study areas during both the daytime and the night-time. The SEVIRI LST overestimates the temperature by approximately 1.0 K during the night-time and by approximately 2.0 K during the daytime compared to MODIS products over these two study areas. The SEVIRI LSE underestimates by about 0.015 in 11 μm and by about 0.025 in 12 μm over the Iberian Peninsula. However, both LSEs agree and show a difference of less than 0.01 over Egypt and the Middle East.

Methods for retrieving subpixel fire temperature and fire area have been developed over several years, but the retrieval accuracies of these methods require further improvement. In this study, a channel of the Moderate Resolution Imaging Spectroradiometer MODIS sensor centred at 2.1 μm and associated with the MODIS 4.0 2.1 μm channel is used to retrieve the temperature and area of fires. To test the feasibility of using the 2.1 μm channel for retrieval, the fire contribution ratios of MODIS 2.1, 4.0 and 11.0 μm channels are first examined using simulated surface radiance. Considering the difficulties in obtaining real-time validation data and in evaluating the retrieval accuracies, simulated MODIS data are used for this study. A modified method, which combines MODIS 2.1 and 4.0 μm channels, is introduced and described in detail. Compared with the traditional method, which utilizes a combination of 4.0 and 11.0 μm channels Dozier 1981, the results show that the 2.1 μm channel is more sensitive to active fires and the large area of fires than the 11.0 μm channel, but is less sensitive to smouldering fires and small fires. The modified method that we propose has better performance and higher accuracy in active fires temperature ≥ 800 K and in large fires area ≥ 0.5%. However, the traditional method is more accurate for smouldering fires and small fires. Finally, a sensitivity analysis is performed to estimate the uncertainty in assessing fire temperature and area. Experimental results indicate that under realistic conditions fire temperatures of approximately 1000 K and a fire fractional area greater than 0.005, the retrieval errors for fire temperature and fire area are ±35 K and 20%, respectively.