Thermal infrared cameras sense the temperature information of sensed scenes. With the development of UASs (Unmanned Aircraft Systems), thermal infrared cameras can now be carried on a quadcopter UAV (Unmanned Aircraft Vehicle) to appropriately collect high-resolution thermal images for volcanic geothermal monitoring in a local area. Therefore, the quadcopter UAS used to acquire thermal images for volcanic geothermal monitoring has been developed in Taiwan as part of this study to overcome the difficult terrain with highly variable topography and extreme environmental conditions. An XM6 thermal infrared camera was employed in this thermal image collection system. The Trimble BD970 GNSS (Global Navigation Satellite System) OEM (Original Equipment Manufacturer) board was also carried on the quadcopter UAV to gather dual-frequency GNSS observations in order to determine the flying trajectory data by using the Post-Processed Kinematic (PPK) technique; this will be used to establish the position and orientation of collected thermal images with less ground control points (GCPs). The digital surface model (DSM) and thermal orthoimages were then produced from collected thermal images. Tests conducted in the Hsiaoyukeng area of Taiwan’s Yangmingshan National Park show that the difference between produced DSM and airborne LIDAR (Light Detection and Ranging) data are about 37% between −1 m and 1 m, and 66% between −2 m and 2 m in the area surrounded by GCPs. As the accuracy of thermal orthoimages is about 1.78 m, it is deemed sufficient for volcanic geothermal monitoring. In addition, the thermal orthoimages show some phenomena not only more globally than do the traditional methods for volcanic geothermal monitoring, but they also show that the developed system can be further employed in Taiwan in the future.

In conducting land boundary verification surveys in digitalized cadastral areas in Taiwan, possible parcel points must be surveyed. These points are employed in the overlap analysis and map registration of possible parcel points and digitalized cadastral maps to identify the coordinates of parcel points. Based on the computed horizontal distance and angle between control points and parcel points, parcels are staked out using ground surveys. Most studies survey possible parcel points using ground surveys with, for example, total stations. Compared with ground surveys, UAV (Unmanned Aerial Vehicle) aerial photogrammetry can provide more possible parcel points. Thus, an overlap analysis of digitalized cadastral maps, combined with the collection of possible parcel points, will be more comprehensive. In this study, a high-quality-medium format camera, with a 55 mm focal length, was carried on a rotary UAV to take images, with a 3 cm ground sampling distance (GSD), flying 300 m above the ground. The images were taken with an 80% end-lap and side-lap to increase the visibility of the terrain details for stereo-mapping. According to the test conducted in this study, UAV aerial photogrammetry can accurately provide supplementary control points and assist in the boundary verification of digitalized cadastral areas in Taiwan.

The cadastral detail data is used for overlap analysis with digitized graphic cadastral maps to solve the problem of inconsistencies between cadastral maps and the current land situation. This study investigated the feasibility of a handheld LiDAR scanner to collect 3D point clouds in an efficient way for a detail survey in urban environments with narrow and winding streets. Then, urban detail point clouds were collected by the handheld LiDAR scanner. After point cloud filtering and the ranging systematic error correction that was determined by a plane-based calibration method, the collected point clouds were transformed to the TWD97 cadastral coordinate system using control points. The land detail line data were artificially digitized and the results showed that about 97% error of the digitized detail positions was less than 15 cm compared to the check points surveyed by a total station. The results demonstrated the feasibility of using a handheld LiDAR scanner to perform an urban cadastral detail survey in digitized graphic areas. Therefore, the handheld LiDAR scanner could be used for the production of the detail lines for urban cadastral detail surveying for digitized cadastral areas in Taiwan.

The airborne LIDAR scanning system is a whole new surveying technique that captures extremely detailed and abundant terrain surface information. Terrain information is implied in airborne LIDAR data. Roof points are especially important in airborne LIDAR data for 3‐D building reconstruction. The key point for automatically and reliably extracting roof points from airborne LIDAR data is how to exclude irrelevant non‐roof points. Robust estimation is a theory about how to remove blunders from observations. If the non‐roof points are viewed as blunders, it is possible to develop an algorithm to acquire the roof points, based on robust estimation theory. This paper will therefore study how to develop an algorithm to acquire those roof LIDAR points and remove irrelevant non‐roof LIDAR points, based on robust estimation theory. Problems relevant to the proposed algorithm will be investigated in this study through experiments in order to understand the feasibility of the proposed algorithm and to further develop an automatic algorithm to extract roof points from airborne LIDAR data.

Unmanned Aircraft Systems (UASs) can collect high resolution and high quality images for local mapping. If the highly accurate GPS flying trajectory of a UAS is collected, it can support bundle adjustment aerial triangulation (AT) of UAS images and reduce the demands on ground control points (GCPs). This study installs a Trimble BD970 GNSS OEM on a fixed-wing UAS for capturing highly accurate GPS data by using a Virtual Base Station (VBS) RTK GPS technique for AT. Meanwhile, the GPS antenna-camera offset is resolved by stripwise linear drift parameters introduced in GPS observation equations, while performing bundle adjustment for AT. Additionally, self-calibration bundle adjustment is used in VBS RTK GPS-assisted AT to solve incomplete camera parameters calibrated by a close-range photogrammetric approach. The results show that the AT accuracy of fixed-wing UAS images collected with a 24 mm focal-length Canon EOS 5D Mark II camera at a flying height of 550 m above ground level is 0.21 m in planimetry and 0.22 m in height using two cross strips with two full GCPs at each corner of the block. The RMSE of check points from stereoscopic viewing can reach 0.27 m in planimetry and 0.24 m in height. The test results show that the accuracy of VBS RTK GPS-assisted bundle adjustment with self-calibration for the AT of fixed-wing UAS image can be used for updating local 1/5000 topographic maps in Taiwan.

A plane-based dynamic calibration method had been proposed by the previous study for the GeoSLAM ZEB Horizon handheld LiDAR scanner. Only one preliminary test was presented. Therefore, three datasets in a calibration field were collected in this study on different dates and at different times on the same date to investigate the efficiency of the proposed calibration approach and calibration results. The calibration results for these three datasets showed that all average residuals were closer to 0, and all a posterior unit weight standard deviations of the adjustment were also significantly reduced after calibration. Moreover, the RMSE (root mean square error) of the check planes was improved by about an average of 32.61%, 28.44%, and 14.7%, respectively, for the three datasets. The improvement was highly correlated with the quality of the calibration data. The RMSE differences of all check planes using calibration data collected on different dates and at different times on the same date for calibration was about 1–2 cm and less than 1 mm, respectively. There was no difference in the calibration results, demonstrating the efficiency of the proposed calibration approach and the calibration results during the two different dates.