Glacial acceleration is the largest source of uncertainty in sea-level-rise assessment, according to the Intergovernmental Panel on Climate Change. Of the different types of glacial acceleration, surging is the least understood. In this paper, we demonstrate how a combination of automated algorithms dedicated to analysis of two entirely different observation types - satellite altimetry from NASA’s ICESat-2 and satellite imagery from Planet SkySat - can aid in advancing glaciology, utilizing state-of-the art remote sensing /Earth observation technology. NASA’s Ice, Cloud and land Elevation Satellite ICESat-2, launched 15~September~2018, carries the first space-borne multi-beam micro-pulse photon counting laser altimeter system, the Advanced Topographic Laser Altimeter System (ATLAS). ATLAS observations are collected in three pairs of weak and strong beams with 0.7m nominal along-track spacing (under clear-sky conditions). The recording of the observations as a photon-point cloud requires a dedicated algorithm for identification of signal photons and determination of surface heights. As a solution, we developed the density-dimension algorithm for ice surfaces, the DDA-ice. ATLAS data analyzed with the DDA-ice allow determination of heights over heavily crevassed ice surfaces, which are characteristics of accelerating glaciers. The study presented here builds on a special multi-component data set, obtained through synoptic observations of an Arctic glacier system during surge (Negribreen, Svalbard): Airborne altimeter and image data collected during our ICESat-2 validation campaign, and SkySat image data from a special acquisition collected as part of NASA’s Commercial Smallsat Data Acquisitions Pilot program. These are complemented by WorldView (Maxar) and ESA Sentinel-1 data. With a spatial resolution of 0.7-0.86m, SkySat data and WorldView lend themselves to automated classification of crevasse types. Altogether, we obtain a characterization in 3 dimensions that allows discrimination of ice-surface types from surging glaciers (Negribreen) and continuously fast-moving and accelerating glaciers (Jakobshavn Isbrae) based on morphological characteristics.