文献类型： 外文期刊

作者： Awais, Muhammad ¹ ; Li, Wei ¹ ; Hussain, Sajjad ³ ; Cheema, Muhammad Jehanzeb Masud ⁴ ; Li, Weiguo ⁶ ; Song, Rui ¹ ; Liu, Chenchen ¹ ;

作者机构： 1.Jiangsu Univ, Res Ctr Fluid Machinery Engn & Technol, Zhenjiang 212013, Jiangsu, Peoples R China

2.Jiangsu Univ, Sch Agr Equipment Engn, Zhenjiang 212013, Jiangsu, Peoples R China

3.King Abdulaziz Univ, Fac Meteorol Environm & Arid Land Agr, Dept Hydrol & Water Resources Management, Jeddah 21589, Saudi Arabia

4.PMAS Arid Agr Univ, Fac Agr Engn & Technol, Rawalpindi 46000, Pakistan

5.PMAS Arid Agr Univ, NCIB Project, Rawalpindi 46000, Pakistan

6.Jiangsu Acad Agr Sci, Inst Agr Informat, Nanjing 210014, Peoples R China

关键词： unmanned aerial vehicle; ArcGIS; thermal sensor; LST; orthomosaic; Landsat 8

期刊名称：AGRICULTURE-BASEL （ 影响因子：3.408； 五年影响因子：3.459 ）

ISSN：

年卷期： 2022 年 12 卷 2 期

页码：

收录情况： SCI

摘要： 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 (R-2 0.89, 0.90, root-mean-square error (RMSE) 1.07, 0.70 degrees C) than the Landsat LST accuracy (R-2 0.70, 0.73, (RMSE) 0.78 degrees 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.