J. Levy

The availability of remote sensing imagery at high spatiotemporal resolutions presents the opportunity to monitor the surface motion of rock glaciers, a key constraint for characterizing the dynamics of their evolution. In this paper, we investigate four North American rock glaciers by automatically measuring their horizontal surface displacement using photogrammetric data acquired with crewed and uncrewed aircraft along with orbital spacecraft over monitoring periods of up to eight years. We estimate vertical surface changes on these rock glaciers with photogrammetrically generated digital elevation models (DEM) and digitized topographic maps. Uncertainty analysis shows that the imagery with the highest resolution and most precise positioning have the best performance when used with the automated change detection algorithm. This investigation produces gridded velocity fields over the entire surface area of each study site, from which we estimate the age of rock glacier formation using along-flow velocity integration. Though the age estimates vary, the ice within the modern extent of these landforms began flowing between 3000 and 7000 years before present, postdating the last glacial maximum. Surface elevation change maps indicate present-day thinning at the lower latitude/higher elevation sites in Wyoming, while the higher latitude/lower elevation sites in Alaska exhibit relatively stable surface elevations.

Boulder‐sized clasts are common on the surface of Mars, and many are sufficiently large to be resolved by the high resolution imaging science experiment (HiRISE) camera aboard the Mars reconnaissance orbiter. The size, number, and location of boulders on the surface and their spatial distribution can reveal the processes that have operated on the surface, including boulder erosion, burial, impact excavation, and other mechanisms of boulder transport and generation. However, quantitative analysis of statistically significant boulder populations, which could inform these processes, entails prohibitively laborious manual segmentation, granulometry, and morphometry measurements over large areas. Here, we develop, describe, and validate an automated tool to locate and measure boulders on the Martian surface: the Martian Boulder Automatic Recognition System (MBARS). Our open‐source Python‐based toolkit automatically measures boulder diameter and height in HiRISE images enabling rapid and accurate assessments of boulder populations. We compare our algorithm with existing boulder‐counting methods, manual analyses, and objects of known size to verify accuracy and precision. Additionally, we test how MBARS quantitatively characterizes boulders around an impact crater in the Martian northern lowlands. We compare this to previous work on rock excavation during impact cratering using manually counted boulders around lunar craters.