In this study, six different periods of digital terrain model (DTM) data obtained from various flight vehicles by using the techniques of aerial photogrammetry, airborne LiDAR (ALS), and unmanned aerial vehicles (UAV) were adopted to discuss the errors and applications of these techniques. Error estimation provides critical information for DTM data users. This study conducted error estimation from the perspective of general users for mountain/forest areas with poor traffic accessibility using limited information, including error reports obtained from the data generation process and comparison errors of terrain elevations. Our results suggested that the precision of the DTM data generated in this work using different aircrafts and generation techniques is suitable for landslide analysis. Especially in mountainous and densely vegetated areas, data generated by ALS can be used as a benchmark to solve the problem of insufficient control points. Based on DEM differencing of multiple periods, this study suggests that sediment delivery rate decreased each year and was affected by heavy rainfall during each period for the Meiyuan Shan landslide area. Multi-period aerial photogrammetry and ALS can be effectively applied after the landslide disaster for monitoring the terrain changes of the downstream river channel and their potential impacts.

Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne lidar, were used in this study to decipher the morphological features of obscure landslides in volcanic regions and how the observed features may be used for understanding landslide occurrence and potential hazard. A morphological reconstruction method was proposed to assess landslide morphology based on the dome-shaped topography of the volcanic edifice and the nature of its morphological evolution. Two large-scale landslides in the Tatun volcano group in northern Taiwan were targeted to more accurately characterize the landslide morphology through airborne lidar and UAS-derived digital terrain models and images. With the proposed reconstruction method, the depleted volume of the two landslides was estimated to be at least 820 ± 20 × 10⁶ m³. Normal faulting in the region likely played a role in triggering the two landslides, because there are extensive geological and historical records of an active normal fault in this region. The subsequent geomorphological evolution of the two landslides is thus inferred to account for the observed morphological and tectonic features that are indicative of resulting in large and life-threatening landslides, as characterized using the recent remote sensing techniques.

Kueishantao (KST) is a small offshore volcanic island located at the southernmost part of the Okinawa Trough. In this study, we conducted a detailed mapping incorporating the new high resolution LiDAR DTM laser scanning device to accurately construct a volcanic sequence. A new 1/5000 geological map was established. One primary volcanic cone, composed of layers of both lava flows and pyroclastic rocks constituted the major edifice of KST. The other minor volcanic cone, which consists of volcanic lapillis and blocks, is seated to the east of the main cone. The escarped and nearly straight coast in the southern part of the KST indicates that the volcano suffered a large post-volcanic edifice collapse erasing nearly one half of the volume of both volcanic cones. The increase in the abundance of the xenoliths of sedimentary rocks from the lower to the upper part of the volcanic sequence indicates that the formation of volcanic rocks of the KST involved an intensification of crustal contamination. The possibility of volcanic eruption can not be excluded in the future based on the present thermolu¬minescene age data of 7 ka. The associated eruptive ash fall and tsunami induced by the further collapse of the KST volcanic edifice might have great influence to the adjacent inland. Thus, long-term monitoring of volcanic activities around KST should be required for future hazard assessments