Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data

The extensive requirement of land surface temperature (LST) for environment al studies and management activities of the Earth's resources has made the remote sensing of LST an important academic topic during the last two decad es. Many studies have been devoted to establishing the methodology for the retrieval of LST from channels 4 and 5 of Advanced Very High Resolution Rad iometer (AVHRR) data. Various split-window algorithms have been reviewed an d compared in the literature to understand their differences. Different alg orithms differ in both their forms and the calculation of their coefficient s. The most popular form of split-window algorithm is T-s = T-4 + A(T-4 - T -5) + B, where T-s is land surface temperature, T-4 and T-5 are brightness temperatures of AVHRR channels 4 and 5, A and B are coefficients in relatio n to atmospheric effects, viewing angle and ground emissivity. For the actu al determination of the coefficients, no matter the complexity of their cal culation formulae in various algorithms, only two ways are practically appl icable, due to the unavailability of many required data on atmospheric cond itions and ground emissivities in situ satellite pass. Ground data measurem ents can be used to calibrate the brightness temperature obtained by remote sensing into the actual LST through regression analysis on a sample repres enting the studied region. The other way is standard atmospheric profile si mulation using computer software such as LOWTRAN 7. Ground emissivity has a considerable effect on the accuracy of retrieving LST from remote sensing data. Generally, it is rational to assume an emissivity of 0.96 for most gr ound surfaces. However, the difference of ground emissivity between channel s 4 and 5 also has a significant impact on the accuracy of LST retrieval. B y combining the data of AVHRR channels 3, 4 and 5, the difference can be di rectly calculated from remote sensing data. Therefore, much more study is r equired on how to accurately determine the coefficients of split-window alg orithms in the application of remote sensing to examine LST change and dist ribution in the real world.