Spatial analysis of the homogeneity of the land surface temperature in three Spanish test sites

Calibration and validation (cal/val) are key activities to test the data quality acquired from satellite-based instruments, as well as to report the accuracy of derived products such as the land surface temperature (LST). Calibration of thermal infrared (TIR) data and validation of LST products at low spatial resolution requires the identification of large and homogeneous areas, which is a difficult task. In this work, spatial and temporal homogeneity of LST was analysed over three Spanish regions: the agricultural area of Barrax, Doñana National Park, and Cabo de Gata Natural Park. For this purpose, very high spatial resolution (approximately 3 m) imagery acquired with the Airborne Hyperspectral Scanner (AHS) in the framework of different field campaigns and high–medium spatial resolution (approximately 100 m) imagery acquired with the Landsat-8 (L8) TIR sensor (TIRS) have been used to retrieve homogeneity of high–medium and low spatial resolution sensors, respectively. Different LST retrieval algorithms were applied to AHS and TIRS to compare the LST for a given pixel against the LST of neighbour pixels through the computation of the root mean square error (RMSE). The results obtained from the analysis of LST derived from AHS data over Barrax and Doñana test sites show that part of these regions have an RMSE lower than 1 K, which is consistent with the accuracy of the LST validation (between 0.5 and 1.5 K). The analysis of LST derived from the TIRS shows that some parts of Doñana and Cabo de Gata sites have a mean RMSE of 1 K over the period of a year, with maximal homogeneity in autumn and winter (lower than 1 K) and minimal in spring and summer (around 2 K). These results are lower than the accuracy of the LST validation (approximately 2 K). The results show the usefulness of these three test sites to perform cal/val activities for both low and high spatial resolution sensors. The methodology presented in this study also allows the identification of suitable areas for future cal/val activities.