This study presents an automated method for the construction and spatialization of stratigraphic columns, facilitating the creation of maps of Stratigraphically Homogeneous Zones (SHZ). This approach integrates GIS tools with custom Python scripts, streamlining the manual process traditionally used in Seismic Microzonation (SM) studies according to Italian standards. Our method allows for rapid, scalable processing and provides a detailed geological model of near-surface stratigraphy, essential for land management and seismic risk assessment. We employed our scripts to automatically produce the map of SHZ in the test area of Cariati (Northern Calabria), demonstrating their effectiveness by accurately replicating and extending the manually-derived stratigraphic columns. Additionally, this procedure enhances accessibility to geological data by enabling subsurface insights through spatialized 1D stratigraphic information, while preserving the simplicity of 2D visualization. This advancement holds promise for broader applications in territorial planning and infrastructure development, supporting informed decision-making in various fields of geoscience and engineering.

‘Stratigraphically Homogeneous Zones’: automated construction and restitution procedure for engineering geology use

D'Agostino A.
;
Porchia A.;Tortorici G.;Pavano F.;Ortolano G.;Catalano S.
2025-01-01

Abstract

This study presents an automated method for the construction and spatialization of stratigraphic columns, facilitating the creation of maps of Stratigraphically Homogeneous Zones (SHZ). This approach integrates GIS tools with custom Python scripts, streamlining the manual process traditionally used in Seismic Microzonation (SM) studies according to Italian standards. Our method allows for rapid, scalable processing and provides a detailed geological model of near-surface stratigraphy, essential for land management and seismic risk assessment. We employed our scripts to automatically produce the map of SHZ in the test area of Cariati (Northern Calabria), demonstrating their effectiveness by accurately replicating and extending the manually-derived stratigraphic columns. Additionally, this procedure enhances accessibility to geological data by enabling subsurface insights through spatialized 1D stratigraphic information, while preserving the simplicity of 2D visualization. This advancement holds promise for broader applications in territorial planning and infrastructure development, supporting informed decision-making in various fields of geoscience and engineering.
2025
Northern Calabria
Python scripts
Engineering-Geological Units
Stratigraphically Homogeneous Zones
Seismic Microzonation
GIS Automation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/707629
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