Landform Monitoring and Warning Framework Based on Time Series Modeling of Topographic Databases

Global Positioning System (GPS) and geodetic control networks are used today for analyzing and monitoring time-dependent crustal deformations, providing a series of accurate positional measurements to deliver information on positional changes and deformations that have occurred. Still, such networks present a low-resolution dispersal of positional measures, and do not take into account various physical constraints that affect the terrain’s seismic behavior. An alternative form of spatio-temporal infrastructure that is feasible and practical to establish might involve the use of Digital Terrain Model (DTM) databases. These databases use higher positional resolutions, and are exhibiting an increasing level of positional and height accuracy. Still, when comparing temporal DTMs, the separation of actual physical phenomena from data-related ambiguities is essential in the framework of spatio-temporal analysis. This paper proposes the use of a hierarchical co-modeling of different DTM databases for the task of landform monitoring. Analyses showed promising results, pointing to the feasibility of the proposed methodology in monitoring and quantifying topographic-related spatio-temporal phenomena, such as landslides and change detection, thus facilitating a reliable and precise landform monitoring and warning framework for geomorphodynamic analyses.