Estimation of Land Surface Temperature for a 1-km AVHRR Time Series

Abstract:

In order to re-process DLRs 1km AVHRR data archive to different geophysical and descriptive parameters of the land surface and the atmosphere, a series of scientific data processors are being developed in the framework of the TIMELINE project. The archive of DLR ranges back to the 80ies. One of the data processors is SurfTemp, which processes L2 LST and emissivity datasets from AVHRR L1b data. The development of the data processor included the selection of procedures suitable for time series processing, including mono-window and split window algorithms. The selection is based on a round robin approach, in which selected mono-window and split window algorithms are tested on the basis of TOA radiance/LST pairs, which were generated using a radiative transfer model. The algorithm comparison includes measures of precision, as well as the sensitivity of a method to the accuracy of its input data. The results of the round robin are presented, as well as the implementation of selected algorithms into SurfTemp. Further, first validation results are shown.