Abstract
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.
Highlights
Unmanned aerial vehicles (UAVs) have become a reliable observation platform for environmental remote sensing applications, including wildfire mapping [1,2], atmospheric studies [3,4,5], precision agriculture [6,7,8] and plant identification [9,10,11]
Even though the thermal mosaicking without geotag can be successful, it is still challenging to Remote Sens. 2019, 11, 1365 register, with sufficient positional accuracy, the thermal mosaic to the RGB imagery of the same target for proper interpretation of the former [29]. Motivated by these challenges and the importance of thermal mosaicking, this work aims to design a novel method, referred to as the four-band thermal mosaicking (FTM), in order to process thermal images acquired by a UAV, with three goals in mind: 1. The method overcomes the difficulty of mosaicking low-resolution, single-band thermal imagery
By selecting control points in the RGB orthomosaic, the thermal 3o.r1t.hIommagoesaOicrtihsogmeoosraeifcesrenced along the way (Figure 3)
Summary
Unmanned aerial vehicles (UAVs) have become a reliable observation platform for environmental remote sensing applications, including wildfire mapping [1,2], atmospheric studies [3,4,5], precision agriculture [6,7,8] and plant identification [9,10,11]. Compared to the traditional remote sensing platforms such as satellites and manned aircrafts, which have low spatiotemporal resolutions and high operational costs [12], light-weight UAVs are less costly and more flexible. Lucieer et al mapped the landslide displacement using high-resolution and multi-temporal UAV photos [16]. The landscape of an urban area can be investigated in detail with the acquisition of multi-band UAV imagery [18], which can yield more valuable information than satellite imagery
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