Integrating UAV and Ground Panoramic Images for Point Cloud Analysis of Damaged Building

The effectiveness of damaged building investigation relies on rapid data collection, while jointly applying an unmanned aerial vehicle (UAV) and a backpack panoramic imaging system can quickly and comprehensively record the damage status. Meanwhile, integrating them for generating complete3-D point clouds (3DPCs) is important for further assisting the 3-D measurement of the damaged areas. During the 2016 Meinong earthquake (Taiwan), the system collected multiview aerial images (MVAIs) and ground panoramic images of two collapsed buildings. However, due to the spatial offsets of thespherical camera result in nonideal panoramic images (NIPIs), an appropriate spherical radius has to be chosen to reduce the distance-related stitching errors. In order to evaluate the impact of using NIPIs for 3-D mapping, the geometric accuracy of the 3-D scene reconstruction (3DSR) and usability of the3DPCs were assessed. This study introduces the stitching errors of panoramic images, uses sky masks for successful 3DSR, and obtains clean point clouds. It then analyzes the usability of point clouds that were obtained from only NIPIs, only MVAIs, and their integration. The analysis shows that NIPIs have more rapid processing efficiency than their unstitched original images and can increase the completeness of point clouds at the building’slower floor, while MVAIs can reduce the stitching errors of NIPIs to an acceptable range. Therefore, integrating both images is necessary to achieve rapid and complete point cloud generation

The Geomorphometry of Rainfall-Induced Landslides in Taiwan Obtained by Airborne Lidar and Digital Photography

Non

A Semi-Automatic Image-Based Close Range 3D Modeling Pipeline Using a Multi-Camera Configuration

sensor

Determination of potential secondary lahar hazard areas based on pre-and post-eruption UAV DEMs: Automatic identification of initial lahar starting points and supplied lahar volume

Secondary lahars, generated after volcanic eruptions, may pose significant threats to life and infrastructure. Secondary lahars typically develop from ash deposits and other volcanic debris that remobilize downstream via intense rainfall. The lahar inundation zone after eruptions must be predicted to minimize the impact. This prediction can be modeled based on digital elevation models (DEMs) and two parameters associated with lahar simulations: the lahar starting point (LSP), which indicates the potential locations at which a lahar flow may initiate, and supplied lahar volume (SLV), which is the lahar volume corresponding to each LSP. These parameters are typically determined by assumptions based on past lahar events, which may be unrealistic and often misinterpreted in the inundation prediction. To address this problem, this paper proposes an automated method to estimate the LSP and SLV based on pre-and post-eruption DEMs generated by unmanned aerial vehicle (UAV) images and simulate the inundation zone using the LAHARZ model. The study site is located in the southeast region of Mount Agung (Indonesia), and the objective is to mitigate the potential secondary lahar hazard after the 2017–2019 eruption crisis. Results show that the parameter estimations using the high-resolution UAV DEM and LAHARZ produce a realistic lahar simulation, with a satisfactory similarity of 82%, as verified against the lahar footprint. Moreover, we compare the results with those obtained using TerraSAR-X DEM and demonstrate the importance of using a detailed UAV DEM to avoid underestimating the lahar runout and ensure that the simulated inundation zones mimic real lahars

Post-Eruption Lava Dome Emplacement Measured by UAV Photogrammetry: An Investigation One Year After The 2017-2019 MT. Agung Eruptions

We present an observation of morphological changes at Mt. Agung lava dome one year after the 2017-2019 eruption crisis using UAV-photogrammetry method. Five time-series UAV datasets involve the images collected during the crisis period and the newest data collection (July 16, 2020) were used to provide a detailed investigation of the changes in morphology inside the crater and land cover on the surrounding slopes. The digital surface models (DSMs) generated by structure-from-motion (SfM) with multi-view stereo (MVS) algorithm were used to quantify the dome growth, the surface emplacement, and the actual remaining deposited material eruption surrounding the summit. Analysis of the last two series orthoimages indicates that the crater surface's texture remarkably unchanged one year after the eruption crisis (the dome still presents rough surfaces that resemble small stones and sand). According to the DSMs difference, it is evident that there were no considerable surface displacements inside the dome. It implies that no significant magma pressure accumulation occurring the dome. However, we found a small-scale growth in the central dome, which has increased the dome height up to 2 m and inflate the dome with a volume of 45,950 m3. We have also observed a new lava lake (e.g., compound lava) with an area of 9,166 m2 in the southeast of the dome edge. This new lava lake uplifts the surface up to 29 m and translated to a 79,623 m3 additional volume. Meanwhile, the depression areas surrounding the central dome were observed with a depth between 0.5 and 4 m. The amount of material deposited on the volcano's summit was identified with a total volume of 2.93 × 106 m3. This remaining deposited volume could be a potential lahar in the future. The ability to measure spatial and time-series of the lava dome changes from SfM-UAV, therefore, provides effective, detailed, and sometimes sole means of observing and quantifying dome surface emplacement in the period of before, during and after eruptions. © 2022. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. All rights reserved