Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data

The Lower Tagus Valley (LTV) region has the highest population density in Portugal, with over 3.7 million people living in the region. It has been struck in the past by several historical earthquakes, which caused significant economic and human losses. For a proper seismic hazard evaluation, the area needs detailed Vs30 and soil classification maps. Previously available maps are based on proxies, or an insufficient number of velocity measurements followed by coarse geological generalizations. The focus of this work is to significantly improve the available maps. For this purpose, more than 90 new S-wave seismic velocities measurements obtained from seismic refraction and seismic noise measurements, doubling the number used in previously available maps, are used to update available Vs30 and soil classification maps. The data points are also generalized to the available geological maps using local lithostratigraphic studies and, for the first time, satellite images of this area. The results indicate that lithological and thickness changes within each geological formation prevent a simple generalization of geophysical data interpretation based solely on geological mapping. The maps presented here are the first attempt to produce maps at a scale larger than 1:1,000,000 in Portugal, with direct shear wave velocity measurements. A tentative approach to produce more detailed maps using machine learning was also carried out, presenting promising results. This approach may be used in the future to reduce the number of shear wave measurements necessary to produce detailed maps at a finer scale.

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Publication Details

Journal
Remote Sensing
Published
2025-04-11
DOI
https://doi.org/10.3390/rs17081376
Primary Topic
earthquake and tectonic studies
Type
article
Field-Weighted Citation Impact
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article

Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data

Lídia Quental, R. Dias, Bento Caldeira, J. Carvalho et al.
Remote Sensing
earthquake and tectonic studies
article

Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data

Lídia Quental, R. Dias, Bento Caldeira, J. Carvalho, José Fernando Borges
article en

Abstract

The Lower Tagus Valley (LTV) region has the highest population density in Portugal, with over 3.7 million people living in the region. It has been struck in the past by several historical earthquakes, which caused significant economic and human losses. For a proper seismic hazard evaluation, the area needs detailed Vs30 and soil classification maps. Previously available maps are based on proxies, or an insufficient number of velocity measurements followed by coarse geological generalizations. The focus of this work is to significantly improve the available maps. For this purpose, more than 90 new S-wave seismic velocities measurements obtained from seismic refraction and seismic noise measurements, doubling the number used in previously available maps, are used to update available Vs30 and soil classification maps. The data points are also generalized to the available geological maps using local lithostratigraphic studies and, for the first time, satellite images of this area. The results indicate that lithological and thickness changes within each geological formation prevent a simple generalization of geophysical data interpretation based solely on geological mapping. The maps presented here are the first attempt to produce maps at a scale larger than 1:1,000,000 in Portugal, with direct shear wave velocity measurements. A tentative approach to produce more detailed maps using machine learning was also carried out, presenting promising results. This approach may be used in the future to reduce the number of shear wave measurements necessary to produce detailed maps at a finer scale.

Remote SensingVol. 17(8)
University of Évora (PT), National Laboratory of Energy and Geology (PT)
Openalex Percentile: Top 89%
earthquake and tectonic studies
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