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RSS FeedsRemote Sensing, Vol. 12, Pages 288: Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data (Remote Sensing)

 
 

15 january 2020 18:00:21

 
Remote Sensing, Vol. 12, Pages 288: Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data (Remote Sensing)
 


The accuracy of land surface temperatures (LSTs) acquired by an unmanned aerial vehicle (UAV) was verified by comparison with in-situ LSTs of various land cover materials at the Changwon National University Campus, Changwon City, South Korea. UAV imaging and in-situ measurements were performed on July 31st and August 2nd, 2019. During the in-situ measurements, LST was measured at 160 points using an infrared thermometer. The linear regression model between the UAV and in-situ measurements exhibited a very high correlation on both days, with R2 values greater than 0.7004. The root mean square error (RMSE), however, was 4.030 °C on July 31st and 5.446 °C on August 2nd, and it also varied depending on the land cover type. These results may depend on various factors, such as the field of view and performance of the TIR (Thermal infrared radiance) camera, as well as the weather and atmospheric conditions. Accurately diagnosing the thermal characteristics of urban areas based on the spatial elements can be used to accurately analyze the thermal characteristics of urban areas and to make effective policy decisions. Techniques for verifying and improving the accuracy of UAV TIR LST data for various land cover materials are required to enable precise investigation of the thermal characteristics of urban areas.


 
216 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 12, Pages 292: A Full-Waveform Airborne Laser Scanning Metric Extraction Tool for Forest Structure Modelling. Do Scan Angle and Radiometric Correction Matter? (Remote Sensing)
Remote Sensing, Vol. 12, Pages 287: Spatiotemporal Dynamics and Driving Forces of Urban Land-Use Expansion: A Case Study of the Yangtze River Economic Belt, China (Remote Sensing)
 
 
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