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Open AccessArticle

Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data

1
Institute of Industrial Technology, Changwon National University, 20 Changwondaehak-ro Uichang-gu Changwon-si, Gyeongsangnam-do 641-773, Korea
2
School of Civil, Environmental and Chemical Engineering, Changwon National University, 20 Changwondaehak-ro Uichang-gu Changwon-si, Gyeongsangnam-do 641-773, Korea
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(2), 288; https://doi.org/10.3390/rs12020288
Received: 25 November 2019 / Revised: 8 January 2020 / Accepted: 14 January 2020 / Published: 15 January 2020
(This article belongs to the Section Remote Sensing Image Processing)
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 31 July and 2 August 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 31 July and 5.446 °C on 2 August 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. View Full-Text
Keywords: UAV; land surface temperature; Remote Sensing; urban heat island; land cover UAV; land surface temperature; Remote Sensing; urban heat island; land cover
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Song, B.; Park, K. Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data. Remote Sens. 2020, 12, 288.

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