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Open AccessArticle

Four-band Thermal Mosaicking: A New Method to Process Infrared Thermal Imagery of Urban Landscapes from UAV Flights

by Yichen Yang 1,2 and Xuhui Lee 1,2,*
1
Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China
2
Yale School of Forestry & Environmental Studies, Yale University, 195 Prospect Street, New Haven, CT 06511, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(11), 1365; https://doi.org/10.3390/rs11111365
Received: 21 April 2019 / Revised: 25 May 2019 / Accepted: 4 June 2019 / Published: 6 June 2019
Unmanned aerial vehicles (UAVs) support a large array of technological applications and scientific studies due to their ability to collect high-resolution image data. The processing of UAV data requires the use of mosaicking technology, such as structure-from-motion, which combines multiple photos to form a single image mosaic and to construct a 3-D digital model of the measurement target. However, the mosaicking of thermal images is challenging due to low lens resolution and weak contrast in the single thermal band. In this study, a novel method, referred to as four-band thermal mosaicking (FTM), was developed in order to process thermal images. The method stacks the thermal band obtained by a thermal camera onto the RGB bands acquired on the same flight by an RGB camera and mosaics the four bands simultaneously. An object-based calibration method is then used to eliminate inter-band positional errors. A UAV flight over a natural park was carried out in order to test the method. The results demonstrated that with the assistance of the high-resolution RGB bands, the method enabled successful and efficient thermal mosaicking. Transect analysis revealed an inter-band accuracy of 0.39 m or 0.68 times the ground pixel size of the thermal camera. A cluster analysis validated that the thermal mosaic captured the expected contrast of thermal properties between different surfaces within the scene. View Full-Text
Keywords: unmanned aerial vehicle; structure-from-motion; four-band thermal mosaicking; positional error; object-based calibration; transect analysis; cluster analysis unmanned aerial vehicle; structure-from-motion; four-band thermal mosaicking; positional error; object-based calibration; transect analysis; cluster analysis
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Yang, Y.; Lee, X. Four-band Thermal Mosaicking: A New Method to Process Infrared Thermal Imagery of Urban Landscapes from UAV Flights. Remote Sens. 2019, 11, 1365.

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