Steep topographic reliefs and heavy vegetation severely limit visibility when examining geological structures and surface deformations in the field or when detecting these features with traditional approaches, such as aerial photography and satellite imagery. However, a light detection and ranging (LiDAR)-derived digital elevation model (DEM), which is directly related to the bare ground surface, is successfully employed to map topographic signatures with an appropriate scale and accuracy and facilitates measurements of fine topographic features. This study demonstrates the efficient use of 1-m-resolution LiDAR for tectonic geomorphology in forested areas and to identify a fault, a deep-seated landslide, and the regional cleavage attitude in southern Taiwan. Integrated approaches that use grayscale slope images, openness with a tint color slope visualization, the three-dimensional (3D) perspective of a red relief image map, and a field investigation are employed to identify the aforementioned features. In this study, the previously inferred Meilongshan Fault is confirmed as a NE–SW-trending, eastern dipping thrust with at least a 750 m-wide deformation zone. The site where future paleoseismological studies should be performed has been identified, and someone needs to work further on this site. Signatures of deep-seated landslides, such as double ridges, trenches, main escarpments, and extension cracks, are successfully differentiated in LiDAR DEM images through the use of different visualization techniques. Systematic parallel and continuous lineaments in the images are interpreted as the regional cleavage attitude of cleavage, and a field investigation confirms this interpretation.

The Tsaoling Landslide in Taiwan has captured attentions of researchers worldwide due to its frequent catastrophic failure and distinctive features. Thanks to the launch of TerraSAR-X/TanDEM-X (TSX/TDX) constellation, retrieval of global DEM with high spatial resolution and accuracy becomes possible, which is extremely useful for the study of natural hazards (e.g., landslides) globally. We attempt here for the first time to track recent landslide movements in Tsaoling Taiwan by analyzing DEM time series reconstructed from TSX/TDX image pairs. Quality improvement of InSAR derived DEM through an iterated differential operation is addressed during the data processing. Five cliffs and the Chingshui River are selected to determine the spatial pattern of morphologic changes of the landslide. The results show that: (a) A large amount of collapses occurred on dip slopes in the period from 2011 to 2014 and on surrounding debris deposits during the rainy seasons; (b) The average recession rate of the Chunqui Cliff decreased from 24.4 m/yr to 19.6 m/yr compared with the result between 1999 and 2009; (c) The Tsaoling Landslide has lost 6.90 ×106 m³ of soil from November of 2011 to April of 2014, which shows a positive correlation of 0.853 with rainfall; (d) The Chingshui River is undergoing a gradual bed erosion with a volumes of 1.84 ×106 m³.

In Taiwan, landslides pose serious threats to local residents and infrastructures each year due to high mountain relief and distinct seasonal precipitation distribution. Interferometric synthetic aperture (InSAR) provides a powerful tool to map terrain motion and characterize the failure mechanism of unstable slopes. However, it is challenging for the conventional InSAR technique to obtain reliable landslide information in mountainous regions because of insufficient coherent measurements and signal confusion caused by vegetation coverage and rugged terrain. In this study, we adopt an optimized multi-temporal InSAR (MTInSAR) approach to analyze the surface displacement of an artificial side slope along Freeway No. 3, where a catastrophic landslide failure occurred on 25 April 2010, in northern Taiwan. To increase the spatial extent of the deformation signal, we integrate information from both persistent scatterers (PSs) and distributed scatterers (DSs). Topographic residual and height-dependent atmospheric delays are corrected by a component-based method and joint model estimation, respectively. The results reveal the existence of slope movement with a rate of about −30 mm/year prior to the landslide failure. Further analysis shows that the temporal behaviors of downslope movement are correlated with local precipitation. The study demonstrates the need to continuously monitor and verify the stability of artificial slopes to prevent and minimize the probability of a similar landslide occurrence in the future.

This study uses three periods of airborne laser scanning (ALS) digital elevation model (DEM) data to analyze the short-term erosional features of the Tsaoling landslide triggered by the 1999 Chi-Chi earthquake in Taiwan. Two methods for calculating the bedrock incision rate, the equal-interval cross section selection method and the continuous swath profiles selection method, were used in the study after nearly ten years of gully incision following the earthquake-triggered dip-slope landslide. Multi-temporal gully incision rates were obtained using the continuous swath profiles selection method, which is considered a practical and convenient approach in terrain change studies. After error estimation and comparison of the multi-period ALS DEMs, the terrain change in different periods can be directly calculated, reducing time-consuming fieldwork such as installation of erosion pins and measurement of topographic cross sections on site. The gully bedrock incision rate calculated by the three periods of ALS DEMs on the surface of the Tsaoling landslide ranged from 0.23 m/year to 3.98 m/year. The local gully incision rate in the lower part of the landslide surface was found to be remarkably faster than that of the other regions, suggesting that the fast incision of the toe area possibly contributes to the occurrence of repeated landslides in the Tsaoling area.

The mining industry, which encompasses national resource management, environmental and ecological impacts, is becoming increasingly important to sustainable development policies. Digital Terrain Model (DTM) provides a spatial distribution of numerical terrain features and the ways in which the model can be constructed and mapped have evolved through a variety of technologies, including aerial photography, airborne LiDAR and drone mapping, DTM can be subdivided into Digital Surface Model (DSM) and Digital Elevation Model (DEM). This study therefore proposes to integrate multi-technology DTMs with terrain metrology analysis to accurately define the land use profile of a mine site over time to provide transparent land use information and monitor environmental changes. In addition to estimating assessment of the mine site is investigated, and vertical accuracy analysis based on spatial grid sampling and the 2018 airborne LiDAR DEM is conducted to assess the error between data to calculate surface volume variation and demonstrate elevation profile changes. According to the results of the accuracy analysis, the 2003 aerial photography DTM showed a larger average error of -0.19 m with a standard deviation of ±1.71 m compared to the airborne radar and UAV; the 2015 airborne radar DEM showed an average error of 0.00 m with a standard deviation of ±0.11 m; and the 2022 UAV DSM showed an average error of 0.00 m with a standard deviation of ±0.10 m. Aerial photographic DTMs can demonstrate the early geomorphology of the study area; airborne LIDAR DEMs can present a wide range of high-precision and high-resolution topographic information features that can penetrate vegetation; and UAV DSMs can reflect regional surface changes, such as mining volume variation in open pit mines.