Abstract
ABSTRACTThe first long-term Land Surface Temperature (LST) maps for the Peninsular Spain at annual and seasonal time scales for 1981–2015 is presented in this work. A robust protocol for correcting and calibrating NOAA-AVHRR images and computing LST datasets at the spatial resolution of 1.1 km has been used. Simultaneously, maximum air temperature (Tmax) maps at the same spatial resolution have been produced using data from meteorological stations. The comparison between the two datasets resulted in statistically significant spatial correlations at annual and seasonal scales. Finally, the Normalized Difference Vegetation Index (NDVI) data were also compared with the obtained LST datasets and the results showed significant negative correlations between the two variables, especially in summer.
Highlights
Climate change processes are demanding high spatial and temporal observational datasets for the evaluation of climate models and the interaction of the climate with natural elements (Hofstra, Haylock, New, Jones, & Frei, 2008)
The spatial distribution of the Land Surface Temperature (LST) is highly controlled by the relief disposition, with low LST recorded in the different topographic chains
This study develops a long-term database (1981–2015) of LST at a high spatial resolution (1.1 km2) from the set of NOAA-AVHRR images available in the Peninsular Spain, which were obtained after processing the thermal infrared bands (4 and 5) using a split-window algorithm
Summary
Climate change processes are demanding high spatial and temporal observational datasets for the evaluation of climate models and the interaction of the climate with natural elements (Hofstra, Haylock, New, Jones, & Frei, 2008). Minimum and maximum air temperature and total precipitation are the most commonly used gridded climate variables, there are still other key climate parameters to be derived from either ground-based stations or satellite observations. Among these parameters, Land Surface Temperature (LST) is an essential environmental variable, which is a direct driving force of turbulent heat fluxes and long-wave radiation exchanges (Maurer, Wood, Adam, Lettenmaier, & Nijssen, 2002; Nishida, Nemani, Running, & Glassy, 2003). There are larger problems to retrieve LST given the diversity of land cover types with different emissivity (Becker & Li, 1990; Qin, Dall, Karni, & Berliner, 2001; Sobrino, Raissouni, & Li, 2001), land cover changes (Jin & Liang, 2006), etc
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
