ICESat-2, SkySat, WorldView and Sentinel: Automated Extraction of High-Resolution Spatial Information for Investigation of Surging and Fast-Moving Glaciers
Journal Article
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.
