Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8

Abstract

Thermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area thermal attribute mapping. In order to merge 3D RGB data and 3D thermal data, registration is conducted in four steps: First, thermal and RGB point clouds are generated independently by applying structure from motion (SfM) photogrammetry to both the thermal and RGB imagery. Next, a coarse point cloud registration is performed by the support of georeferencing data (global positioning system, GPS). Subsequently, a fine point cloud registration is conducted by octree-based iterative closest point (ICP). Finally, three different texture mapping strategies are compared. Experimental results showed that the global image pose refinement outperforms the other two strategies at registration accuracy between thermal imagery and RGB point cloud. Potential building thermal leakages in large areas can be fast detected in the generated texture mapping results. Furthermore, a combination of the proposed workflow and the oblique airborne system allows for a detailed thermal analysis of building roofs and facades.

Precise 3D extraction of building roofs by fusion of UAV-based thermal and visible images

“…In this study, a visible camera and a thermal camera are used in two separate flights, which are more cost-effective tools than research using laser scanners or multi-camera systems such as Lin et al (2020) research, which used four thermal and four visible cameras. López-Fernández et al (2015) and Javadnejad et al (2020) used the dualcamera system, which cannot have separate flights from the area with a thermal and visual camera, as the best shooting time for a thermal camera may be different from the visible one.…”

“…The position of the corresponding points from the visible images was mapped to the visible point cloud and, through the intersection with the thermal images, the position of the features was corrected and precise registration was made. Lin et al (2020) used four visible and four thermal cameras to cover a large-scale area. They proposed three different texture mapping methods, and global image pose refinement outperformed the other strategies.…”

Mining Exploration with UAV, Low-Cost Thermal Cameras and GIS Tools—Application to the Specific Case of the Complex Sulfides Hosted in Carbonates of Udías (Cantabria, Spain)

“…The set of images from the flight have to be processed according to the principles of photogrammetry; that is, what might be called "modern photogrammetry", which uses software based on Structure-from-Motion (SfM) algorithms, and automatic image correlation to generate products that allow the results to be interpreted. Regarding the generation of thermal models, some authors have tried to classify the methodologies into categories [46][47][48]. However, when starting from thermal images, the methods can be divided into only three main categories: thermal 2D-image modeling [49], thermal image mapping in existing 3D models [50,51] and a combination of RGB and thermal images [52][53][54].…”

Thermal and visual remote sensing of residential buildings by UAV

“…Identifying the location of potential defects can help operators define the causes and planning the best type of intervention. In this context, several studies are focused on the fusion of thermal imagery with 3D digital reconstructions to integrate thermal and geometrical data [2,3,7,8].…”