1,721,028 research outputs found
Probabilistic modelling of uncertainties in earthquake-induced landslide hazard assessment
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SIGNUM: A Matlab, TIN-based landscape evolution model
No full textSeveral numerical landscape evolution models (LEMs) have been developed to date, and many are available as open source codes. Most are written in efficient programming languages such as Fortran or C, but often require additional code efforts to plug in to more user-friendly data analysis and/or visualization tools to ease interpretation and scientific insight. In this paper, we present an effort to port a common core of accepted physical principles governing landscape evolution directly into a high-level language and data analysis environment such as Matlab. SIGNUM (acronym for Simple Integrated Geomorphological Numerical Model) is an independent and self-contained Matlab, TIN-based landscape evolution model, built to simulate topography development at various space and time scales. SIGNUM is presently capable of simulating hillslope processes such as linear and nonlinear diffusion, fluvial incision into bedrock, spatially varying surface uplift which can be used to simulate changes in base level, thrust and faulting, as well as effects of climate changes. Although based on accepted and well-known processes and algorithms in its present version, it is built with a modular structure, which allows to easily modify and upgrade the simulated physical processes to suite virtually any user needs. The code is conceived as an open-source project, and is thus an ideal tool for both research and didactic purposes, thanks to the high-level nature of the Matlab environment and its popularity among the scientific community. In this paper the simulation code is presented together with some simple examples of surface evolution, and guidelines for development of new modules and algorithms are proposed. © 2011 Elsevier Ltd
Evaluating earthquake-triggered landslide hazards at basin scale. The example of the upper sele river valley
No full textInvestigating valley spacing dynamics in linear mountain fronts through terrain numerical modeling
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The Use of DEM-Based Approaches to Derive a Priori Information on Flood-Prone Areas
No full textKnowing the location and the extent of areas exposed to floods is the most basic information needed for planning flood management strategies. Unfortunately, a complete identification of these areas is still lacking in many countries. Recent studies have highlighted that a significant amount of information regarding the inundation process is already contained in the structure and morphology of a river basin. Therefore, several geomorphic approaches have been proposed for the delineation of areas exposed to flood inundation using DEMs. Such DEM-based approaches represent a useful tool, characterized by low cost and simple data requirements, for a preliminary identification of the flood-prone areas or to extend flood hazard mapping over large areas. Moreover, geomorphic information may be used as external constraint in remote-sensing algorithms for the identification of inundated areas during or after a flood event
Use of scaling information for stochastic atmospheric absolute phase screen retrieval
No full textScaling information is an important tool for the description of natural processes. Many applications of SAR (differential) interferometry lead to a set of sparse phase measurements, e.g. the monitoring of permanent scatterers. In this case, the atmospheric phase screen component of a given SAR image can be estimated over the PS sparse grid. Usually such data have to be unwrapped and then interpolated on a regular grid. We investigate the utility of the scaling information, valid for atmospheric phase screen data, in the process of unwrapping a set of sparse measurements. We show how the power-law behaviour of the data variogram can be used as an a priori constraint for optimization through techniques such as simulated annealing. The results are interpreted in view of operational applications to real data
Land-cover classification-based persistent scatterers identification for peri-urban applications
No full textWe illustrate, through a sample application to a difficult landslide test site, the use of a novel method to detect potentially stable objects in Persistent Scatterers SAR Interferometry (PSI). Conventional PSI processing involves selecting first-guess potential stable objects, called PS Candidates (PSC), through thresholding of the amplitude dispersion index. This method can lead, in applications to scenes characterized by scarce urbanization, to very low PSC numbers, insufficient for a successful subsequent phase analysis if their spatial distribution is very sparse. Our classification-based approach relies on the proven fact that urban areas are more likely to contain PS pixels than any other land-cover class. Therefore, using pixels belonging to the urban land-cover class as PSC is a convenient way of increasing the number of initial fiducial points while keeping false alarm probabilities to reasonable levels. Results show that PSC belonging to the urban class, selected through simple external classification algorithms, lead to more consistent results for the final PS, both in terms of spatial density, and of reliability of displacement series
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