Optimal Digital Elevation Models (DEMs) from multiple data sources, and topography analysis sensitivity for improved volcano hazard assessment

Digital elevation models (DEMs) are now widely used for hazard assessment of volcanic mass flows, e.g., lava flows, pyroclastic flows, lahars. Rapid development of satellite, airborne and ground-based remote sensing techniques have increased the availability of DEM products of higher resolution and better accuracy. Volcanic areas with rugged terrains and dense vegetation remain challenging targets for such DEMs, but are critical for proper volcanic hazard assessments. Recent advances in our understanding of the dynamics of volcanic mass flows have pointed out the strong dependence on local topography. Geomorphic analysis of volcanic terrains can improve hazard assessment of volcanic mass flows, but requires high-resolution and up-to-date DEMs.

We use GIS-based python algorithms to perform geomorphic analyses of volcanic terrains on DEMs of increasing resolution to test for sensitivity. We include satellite-derived DEMs, as well as information from Terrestrial Radar Interferometry (TRI) and optical Structure from Motion (SfM) in our analysis. We evaluate the relationship between various topographic features and the extent of volcanic mass flows using historical eruptions. We discuss the main sources of errors and uncertainties in DEMs, and show that combining DEMs from different data sources and resolutions can be an optimal approach. Our goal is a step-by-step semi-automated process of geomorphic analyses of active volcanoes for a rapid recognition of potential areas at risk for volcanic mass flows, and to ultimately generate optimal DEMs and improve hazard assessment.