Photogrammetric analysis of multispectral and thermal close-range images

Abstract

PhotogrammetryRemote sensing Multispectral images Thermal images Close-range Sensors capable of multispectral and thermal imaging beyond visible bands offer many analysis possibilities for environmental monitoring. Different sensor images constitute an important source of information especially in the fields of agriculture, forestry, geology and energy. Photogrammetric studies have been affected by this development in recent years and have been used in the production of multispectral and thermal models besides the RGB model. However, due to geometric and radiometric resolution differences, it is difficult to combine or evaluate models produced from different types of sensors. In this study, the three-dimensional test field images obtained with RGB, multispectral and thermal sensors were oriented and modeled photogrammetrically. The accuracies of the control points on the produced models were compared and discussed. When the results are examined, control point accuracy was obtained as almost similar as in the RGB model after the orientation based on automatic feature matching. Automatic feature detection and matching in thermal images were not robustly produced due to low geometric resolution. For this reason, manual measurements were performed in thermal images, and the photogrammetric orientation and adjustment process was done accordingly. The fused evaluation approach considering RGB, multispectral and thermal images in one photogrammetric model was also implemented and discussed.

3D Data Fusion for Historical Analyses of Heritage Buildings Using Thermal Images: The Palacio de Colomina as a Case Study

“…Therefore, in addition to the TIR acquisition, a complete terrestrial LiDAR survey was conducted. In fact, as reported in the previous section, although currently thermal images are increasingly used for 3D applications-for example, photogrammetric applications [29][30][31]-they are often not suitable for generating highly-detailed 3D surfaces due to their limited spatial resolution.…”

Integration of Thermal and RGB Data Obtained by Means of a Drone for Interdisciplinary Inventory

“…Thermography is wide remote-sensing data acquisition and processing technology, often applying photogrammetric methods of measurement and results presentation. The thermal sensors are used in different scales and from different distances: from closerange [1,2] that can also be mounted on robots and integrated with other sensors [3], on UAV [4,5], aircrafts or satellites [6]. Thermal information can be captured by different means: by passive methods like typical IRT (infrared thermography) [7][8][9], and active methods such as pulse IRT [10,11] and lock-in thermography [12,13].…”

“…(2) Thermographic and photogrammetric data integration are the second group, in particular using RGB sensors [40,[47][48][49][50][51][52], as well as smartphone sensors [53], depth cameras [54,55], RGB visual odometry data [56], multispectral [2,4,38], and hyperspectral data [16]. The presented research is another example of this group.…”

“…(2) Another solution is the co-registration of visual or LiDAR data with thermal data by specially selected or automatically found natural or marked points and other features. Points marked by coins can be used for thermal and RGB data fusion as well multispectral and RGB data [2]. Another method of marking the thermal control point is by using of circles of aluminum foil [64].…”

SFM-Based 3d Reconstruction of Heritage Assets Using Uav Thermal Images

“…Also, the possibility to directly exploit thermal images in consolidated photogrammetric workflows has been explored. In particular, different studies * Corresponding author aimed at testing a SfM (Structure-from-Motion) approach using TIR images, obtaining remarkable results (Akçay 2021;Dlesk et al 2018;Adamopoulos et al 2020). However, many issues connected to the co-registration of TIR and visible images still need to be solved and the development of a user-oriented data fusion strategy certainly represents an actual challenge (Javadnejad et al 2019).…”