Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Rover data can provide important constraints on the possible origin of wind‐related martian features that have been termed “Transverse Aeolian Ridges” (TARs). The large aeolian bedform traversed by Curiosity at Dingo Gap has a planform and albedo similar to members of nearby TAR fields, so that the crossing at Dingo Gap revealed the surface characteristics of a small TAR. Mars Hand Lens Imager images documented 1–2 mm diameter, well‐rounded particles on the Dingo Gap bedform, along with numerous images obtained from the Mastcam, Hazcam, and Navcam science and engineering cameras on the rover. These images confirm that this feature (and, by extension, all small TARs) can be considered a megaripple whose surface is coated by rounded particles that are too large to be set into motion through saltation, but they may be induced to roll (creep) along the surface by the impact of saltating sand grains (a characteristic of megaripples on Earth). The images also confirm that a bimodal wind was present here, a condition that could have contributed to the symmetrical profile of the bedform. The bearing strength at Dingo Gap was better than that of the Purgatory megaripple that trapped Opportunity for several weeks, so that all megaripples should not be automatically presumed to represent a trafficability hazard for a rover.

Finely resolved geodetic data provide an opportunity to assess the extent and morphology of crevasses and their change over time. Crevasses have the potential to bias geodetic measurements of elevation and mass change unless they are properly accounted for. We developed a framework that automatically maps and extracts crevasse geometry and masks them where they interfere with surface mass-balance assessment. Our study examines airborne light detection and ranging digital elevation models (LiDAR DEMs) from Haig Glacier, which is experiencing a transient response in its crevassed upper regions as the glacier thins, using a self-organizing map algorithm. This method successfully extracts and characterizes ~1000 crevasses, with an overall accuracy of 94%. The resulting map provides insight into stress and flow conditions. The crevasse mask also enables refined geodetic estimates of summer mass balance. From differencing of September and April LiDAR DEMs, the raw LiDAR DEM gives a 9% overestimate in the magnitude of glacier thinning over the summer: −5.48 m compared with a mean elevation change of −5.02 m when crevasses are masked out. Without identification and removal of crevasses, the LiDAR-derived summer mass balance therefore has a negative bias relative to the glaciological surface mass balance.