6533b86cfe1ef96bd12c899d

RESEARCH PRODUCT

Study of Temperature Heterogeneities at Sub-Kilometric Scales and Influence on Surface–Atmosphere Energy Interactions

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The retrieval of land surface temperature (LST) from remote sensing techniques has been studied and validated during the past 40 years, leading to important improvements. Accurate LST values are currently obtained through measurements using medium resolution thermal infrared (TIR) sensors. However, the most recent review reports demonstrated that the future TIR LST products need to obtain reliable temperature values at a high spatial resolution (100 m or higher) to study temperature variations between different elements in a heterogeneous kilometric area. The launch of high-resolution TIR sensors in the near future requires studies of the temporal evolution and spatial heterogeneities of the elements in a mixed region. The present study analyzes the LST in a sub-kilometric highly heterogeneous area, combining the use of LST products from high-resolution TIR orbiting sensors with the LST maps created from a TIR camera onboard an unmanned aerial vehicle (UAV). The aim is to estimate the LST variability in a heterogeneous area containing different surfaces (roads, buildings, and grass), observed from different TIR sensors at different spatial resolutions, covering from the meter to the kilometer scales. Several results showed that variations in the LST up to 18 °C were identified with the UAV-TIR camera, and significant differences were also present in the LST products obtained from simultaneous overpasses of high-resolution satellite TIR sensors. A second objective of the study, due to the availability of the high-resolution LST fields, was to explore the thermal advection between different elements and determine if it correlates with the surface energy budget in the same area, thus indicating that this process is of importance for heterogeneous terrains at these scales. This paper also highlights the relevance of the UAV-TIR camera flight for future studies since it is not commonly used in TIR remote sensing but has substantial potential advantages.