NASA ICESat-2: Space-Borne LiDAR for Geological Education and Field Mapping of Aeolian Sand Dune Environments

Abstract

Satellites are launched frequently to monitor the Earth’s dynamic surface processes. For example, the Landsat legacy has thrived for the past 50 years, spanning almost the entire application spectrum of Earth Sciences. On the other hand, fewer satellites are launched with a single specific mission to address pressing scientific questions, e.g., the study of polar icecaps and their response to climate change using Ice Cloud and the Land Elevation Satellite (ICESat) program with ICESat-1 (decommissioned in 2009) and ICESat-2. ICESat-2 has been operational since 2018 and has provided unprecedented success in space-borne LiDAR technology. ICESat-2 provides exceptional details of topographies covering inland ice, snow, glaciers, land, inland waterbodies, and vegetation in three-dimensional (3D) space and time, offering the unique opportunity to quantify the Earth’s surface processes. Nevertheless, ICESat-2 is not well known to some other disciplines, e.g., Geology and Geomorphology. This study, for the first time, introduces the use of ICESat-2 in aeolian sand dune studies, purely from an ICESat-2 remote sensing data perspective. Two objectives are investigated. first, a simplified approach to understanding ICESat-2 data products along with their application domains. Additionally, data processing methods and software applications are briefly explained to unify the information in a single article. Secondly, the exemplified use of ICESat-2 data in aeolian sand dune environments is analyzed compared to global Digital Elevation Models (DEMs), e.g., Shuttle Radar Topography Mission (SRTM). Our investigation shows that ICESat-2 provides high-resolution topographic details in desert environments with significant improvements to the existing methods, thereby facilitating geological education and field mapping. Aeolian sand dune environments can be better understood, at present, using ICESat-2 data compared to traditional DEM-based methods.