Abstract
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.
Highlights
For the last two decades, permanent Global Positioning System (GPS) and geodetic control networks have been widely used for analyzing and monitoring crustal deformations [1]
The implementation of a hierarchical methodology for topographic and morphologic modeling of terrain surface representations was presented. This includes the development of an original algorithm for identifying the topographic skeletal structure, the implementation of a robust ranking registration process and an improved constrained-Iterative Closest Point (ICP) matching algorithm
This comprehensive framework enables proper definition, modeling and monitoring of the completely different databases’ spatial local interrelations, which by nature exist of varied-scale discrepancies. This ‘from global to local’ process validates that the mutual modeling is able to quantify both global and local spatial relations, as well as irregularities, preserving the topology, geometry and morphology of features existing in the series of the terrain databases. This novel hierarchical co-modeling enables the implementation of a comparison process for a given series of topographic databases, each acquired at a different time
Summary
For the last two decades, permanent Global Positioning System (GPS) and geodetic control networks have been widely used for analyzing and monitoring crustal deformations [1] These networks provide a series of accurate positional measures that cover the analyzed area, providing a time-continuous infrastructure enabling the tracking and studying of landform (seismic, geomorphologic) activities (e.g., [2,3]). The entire analysis is based only on discrete distant points, while assuming that the surrounding area, i.e., the GPS station footprint, experienced similar behaviors and trends (e.g., [4,5]) This assumption is not always correct, as different physical constraints, such as geology, may have a certain effect on the terrain’s seismic behavior. Since developing regions do not always have the means to establish such monitoring systems [6], an alternative form of such temporal infrastructure that is feasible and practical to establish, which still produces qualitative analysis measures, should be considered
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