Integrating LiDAR and SfM data from ground-based, unmanned (UAV) and manned aerial platforms to estimate sediment budgets for aeolian dunefields

Sediment budgets are important for understanding landscape evolution as related to climate, weather, and sediment dynamics on Earth and other planets. Aeolian dunefield sediment budgets are defined by the difference between the amount of sediment entering and leaving a dunefield over a period of time. Change detection of repeat topographic datasets derived from LiDAR or photogrammetric point cloud data provides estimates of changes in sediment storage and thus inference to sediment influx and/or efflux. Drawing specific examples from our research in the Grand Canyon region, Arizona, USA, we describe the use of LiDAR and photogrammetrically derived point cloud data from ground-based and airborne sensors including manned and unmanned aerial vehicles (UAV; drones) to characterize changes in dunefield sediment storage at high spatial resolution. We also discuss the synergistic use of airborne- and satellite-based multispectral imagery to scale the high resolution observations of changes in sediment storage to larger geographic extents within river valleys and plateaus. The multi-sensor, multi-scale, and multi-temporal remote sensing approaches that we demonstrate are likely to be broadly applicable in other Earth and planetary environments.