Abstract
Remotely-sensed data are a source of rich information and are valuable for precision agricultural tasks such as soil quality, plant disease analysis, crop stress assessment, and allowing for better management. It is necessary to validate the accuracy of land surface temperature (LST) that is acquired from an unmanned aerial vehicle (UAV) and satellite-based remote sensing and verify these data by a comparison with in situ LST. Comprehensive studies at the field scale are still needed to understand the suitability of UAV imagery and resolution, for which ground measurement is used as a reference. In this study, we examined the accuracy of surface temperature data that were obtained from a thermal infrared (TIR) sensor placed on a UAV. Accordingly, we evaluated the LST from the Landsat 8 satellite for the same specific periods. We used contact thermometers to measure LSTs in situ for comparison and evaluation. Between 18 August and 2 September 2020, UAV imagery and in situ measurements were carried out. The effectiveness of high-resolution UAVs imagery and of Landsat 8 imagery was evaluated by considering a regression and correlation coefficient analysis. The data from the satellite photography was compared to the UAV imagery using statistical metrics after it had been pre-processed. Ground control points (GCPs) were collected to create a rigorous geo-referenced dataset of UAV imagery that could be compared to the geo-referenced satellite and aerial imagery. The UAV TIR LST showed higher accuracy (R2 0.89, 0.90, root-mean-square error (RMSE) 1.07, 0.70 °C) than the Landsat LST accuracy (R2 0.70, 0.73, (RMSE) 0.78 °C). The relationship between LST and the available soil water content (SWC) was also observed. The results suggested that the UAV-SMC correlation was negative (−0.85) for the image of DOY 230, while this value remains approximately constant (−0.86) for the DOY 245. Our results showed that satellite imagery that was coherent and correlated with UAV images could be useful to assess the general conditions of the field while the UAV favors localized circumscribed areas that the lowest resolution of satellites missed. Accordingly, our results could help with urban area and environmental planning decisions that take into account the thermal environment.
Highlights
Land surface temperature (LST) is directly linked with many areas, i.e., land use and land cover (LULC), climate change, hydrological, geophysical, and urban management [1]
This research work is useful for developing countries, where agriculture is the primary source of income
We evaluated the accuracy of the unmanned aerial vehicle (UAV) thermal infrared (TIR) land surface temperature (LST) and Landsat 8 TIR LST by calculating the in situ LST for each day
Summary
Land surface temperature (LST) is directly linked with many areas, i.e., land use and land cover (LULC), climate change, hydrological, geophysical, and urban management [1]. LST is a crucial parameter for the physical description of surface energy and water balance processes [3]. This important component has been demonstrated in numerous thermal infrared-based investigations and applications, such as vegetation monitoring [4], agriculture [5], hydrological modelling [6,7], monitoring of land use changes in wetlands, and evapotranspiration [8]. The most commonly used indices are normalized difference vegetation index (NDVI), LST, soil-adjusted vegetation index (SAVI), and modified SAVI Such indices have been widely used to estimate the LULC, changes in vegetation, surface soil moisture (SM), and evapotranspiration. The accurate measurement of such variables (i.e., LST and SM) is a difficult and challenging task due to traditional field calculation methods [2,16]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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.
