Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature

Abstract

Ground measured component radiative temperatures are basic inputs for modelling energy and hydrological processes and for simulating land surface temperature (LST) as “viewed” by remote sensors. However, knowledge of factors affecting the component temperatures and about their potential for upscaling LST over sparsely vegetated surfaces with high heterogeneity is still lacking. Here, a MUlti-Scale Observation Experiment on land Surface temperature (MUSOES) was performed under HiWATER over an arid sparsely vegetated surface. Component temperatures were obtained with different instruments on multiple spatial scales; for LST upscaling, a three-dimensional scene model was employed for two forest stations (MFS and PFS) and a two-dimensional model for a shrub station (SUP). Results show that intrinsic characteristics contribute to the temperature variability between different components and even within a single component. Using a thermal infrared (TIR) imager at MFS, average temperature difference of 24.9 K between sunlit bare soil and tree canopy was found; different components exhibit different internal temperature differences at direction-level and pixel-level. Furthermore, illumination conditions, viewing directions, and instrument types significantly affected the measured component temperatures. The measurements of the TIR radiometer and the imager can deviate considerably (e.g. 14.9 K for sunlit bare soil at MFS). When the longwave radiometers were selected as target sensors, the component temperatures measured by the imager exhibit good potential for LST upscaling: the upscaled LST has MBD/RMSD values of 2.0 K/2.3 K at MFS and 2.0 K/2.5 K at PFS. The TIR radiometer’s measurements introduce large uncertainties into LST upscaling at MFS and PFS, but result in good accuracy at SUP, mainly due to its simpler land cover and surface structure. Findings from this study can benefit our understanding of factors affecting observations of component temperatures and the LST upscaling process and are, therefore, relevant for further studying the evaluation of satellite LST products.