3D reconstruction of complex geological bodies: Examples from the Alps

Zanchi, Andréa; Salvi, F.; Zanchetta, Stefano; Sterlacchini, Simone; Guerra, Graziano

doi:10.1016/j.cageo.2007.09.003

Cited by 104 publications

(48 citation statements)

References 17 publications

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“…Georeferencing is a first step before starting geomodeling, whereby all available information is combined and organized in a common coordinate system (e.g., Culshaw 2005; Kaufman and Martin 2008;Zanchi et al 2009), see Fig. 1(A).…”

Section: Management and 3d Visualization Of Earth Datamentioning

confidence: 99%

“…This paper is mostly based on our experience of teaching 3D structural modeling with the Gocad® geomodeling software; however, most general rules provided here should be applicable to other software platforms. Additional insight on surface-based 3D structural modeling methods is also available from de Kemp and Sprague (2003), Dhont et al (2005), Fernández et al (2004), Gjøystdal et al (1985), Groshong (2006), Kaufman and Martin (2008), Lemon and Jones (2003), Mallet (1997Mallet ( , 2002, Sprague and de Kemp (2005), Turner (1992), Wycisk et al (2009), Wu et al (2005, Zanchi et al (2009). After a rapid overview of the typical data available in a 3D modeling project (Sect.…”

Section: Introductionmentioning

confidence: 99%

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Surface-Based 3D Modeling of Geological Structures

et al. 2009

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Building a 3D geological model from field and subsurface data is a typical task in geological studies involving natural resource evaluation and hazard assessment. However, there is quite often a gap between research papers presenting case studies or specific innovations in 3D modeling and the objectives of a typical class in 3D structural modeling, as more and more is implemented at universities. In this paper, we present general procedures and guidelines to effectively build a structural model made of faults and horizons from typical sparse data. Then we describe a typical 3D structural modeling workflow based on triangulated surfaces. Our goal is not to replace software user guides, but to provide key concepts, principles, and procedures to be applied during geomodeling tasks, with a specific focus on quality control. Electronic supplementary materialThe online version of this article (http://dx

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Section: Management and 3d Visualization Of Earth Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Surface-Based 3D Modeling of Geological Structures

et al. 2009

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“…For these reasons, remote sensing technologies are experiencing a rapid development and are being widely applied to enhance geological analysis of rock slopes. Aerial and Terrestrial Laser Scanning (ALS, TLS) are commonly used and constitute efficient remote sensing technologies for geological studies [Zanchi et al, 2009;Buckley et al, 2008Buckley et al, , 2010Jaboyedoff et al, 2012;Abellan et al, 2014]. The potential of LiDAR-derived topographic models has been demonstrated in different geological domains such as: structural characterization [Slob and Hack, 2004;Kemeny et al, 2006;Haneberg, 2007;Jaboyedoff et al, 2007;Sturzenegger and Stead, 2009;Sturzenegger et al, 2011;Gigli and Casagli, 2011;Lato et al, 2012], landslide monitoring [Rosser et al, 2007;Oppikofer et al, 2008;Stock et al, 2012] and 3D folds and layers reconstruction [Zanchi et al, 2009;Jones et al, 2009;De Donatis et al, 2009].…”

Section: Introductionmentioning

confidence: 99%

“…Aerial and Terrestrial Laser Scanning (ALS, TLS) are commonly used and constitute efficient remote sensing technologies for geological studies [Zanchi et al, 2009;Buckley et al, 2008Buckley et al, , 2010Jaboyedoff et al, 2012;Abellan et al, 2014]. The potential of LiDAR-derived topographic models has been demonstrated in different geological domains such as: structural characterization [Slob and Hack, 2004;Kemeny et al, 2006;Haneberg, 2007;Jaboyedoff et al, 2007;Sturzenegger and Stead, 2009;Sturzenegger et al, 2011;Gigli and Casagli, 2011;Lato et al, 2012], landslide monitoring [Rosser et al, 2007;Oppikofer et al, 2008;Stock et al, 2012] and 3D folds and layers reconstruction [Zanchi et al, 2009;Jones et al, 2009;De Donatis et al, 2009]. Classification of intensity derived from terrestrial LiDAR point clouds was achieved in several geomorphological contexts [Brodu and Lague, 2012] and rock type characterization was successfully performed [Bellian et al, 2005;Franceschi et al, 2009Franceschi et al, , 2011Burton et al, 2011;Buckley et al, 2008Buckley et al, , 2010Campos Inocencio et al, 2014].…”

Section: Introductionmentioning

confidence: 99%

Geological mapping and fold modeling using Terrestrial Laser Scanning point clouds: application to the Dents-du-Midi limestone massif (Switzerland)

Matasci

Carrea

Abellán

et al. 2015

European Journal of Remote Sensing

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Geological mapping in vertical rock faces is extremely challenging because of access difficulties and limited possibilities of recognition, localization and measurement of features at large distance with traditional tools. Moreover, vertical areas can be of primary interest since they often display good quality outcrops and relevant geological information. This study focuses on the detailed remote identification of rock types and fold structures using intensity values acquired by Terrestrial Laser Scanning. A correction of the intensity is proposed proportional to the square of the range and to the cosine of the incidence angle. Furthermore, two methods of remote lithological mapping in 3D have been developed using a manual and a semi-automatic approach. Both delivered good results that are consistent with the spatial distribution of rock-types and allowed us to generate an accurate 3D lithological map of Dents-du-Midi massif (Valais, Swiss Alps). The bedding orientation near the hinge of a Km scale fold was measured on LiDAR data in order to define the fold axis. Then, the result was used to build a model of the hinge in 3D.

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“…GOCAD is a sophisticated tool to model complex geological structures; see for example Zanchi et al (2009). It can be used as a pre-processor to display hydrogeological simulation models to acquire and assess information on the heterogeneity of aquifer systems.…”

Section: Modeling Tools and Site Descriptionmentioning

confidence: 99%

GO2OGS 1.0: a versatile workflow to integrate complex geological information with fault data into numerical simulation models

et al. 2015

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Abstract. We offer a versatile workflow to convert geological models built with the Paradigm ™ GOCAD © (Geological Object Computer Aided Design) software into the opensource VTU (Visualization Toolkit unstructured grid) format for usage in numerical simulation models. Tackling relevant scientific questions or engineering tasks often involves multidisciplinary approaches. Conversion workflows are needed as a way of communication between the diverse tools of the various disciplines. Our approach offers an open-source, platform-independent, robust, and comprehensible method that is potentially useful for a multitude of environmental studies. With two application examples in the Thuringian Syncline, we show how a heterogeneous geological GO-CAD model including multiple layers and faults can be used for numerical groundwater flow modeling, in our case employing the OpenGeoSys open-source numerical toolbox for groundwater flow simulations. The presented workflow offers the chance to incorporate increasingly detailed data, utilizing the growing availability of computational power to simulate numerical models.

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3D reconstruction of complex geological bodies: Examples from the Alps

Cited by 104 publications

References 17 publications

Surface-Based 3D Modeling of Geological Structures

Surface-Based 3D Modeling of Geological Structures

Geological mapping and fold modeling using Terrestrial Laser Scanning point clouds: application to the Dents-du-Midi limestone massif (Switzerland)

GO2OGS 1.0: a versatile workflow to integrate complex geological information with fault data into numerical simulation models

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