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 are...
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MDPI AG
2025-04-01
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| author | João Carvalho Ruben Dias José Borges Lídia Quental Bento Caldeira |
| author_facet | João Carvalho Ruben Dias José Borges Lídia Quental Bento Caldeira |
| author_sort | João Carvalho |
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| description | 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 V<sub>s30</sub> 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 V<sub>s30</sub> 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. |
| format | Article |
| id | doaj-art-25c53f329f114792a30d70ad5f00c19a |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-25c53f329f114792a30d70ad5f00c19a2025-08-20T02:28:25ZengMDPI AGRemote Sensing2072-42922025-04-01178137610.3390/rs17081376Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing DataJoão Carvalho0Ruben Dias1José Borges2Lídia Quental3Bento Caldeira4National Laboratory for Energy and Geology, Estrada da Portela, Apartado 7586, Alfragide, 2610-999 Amadora, PortugalNational Laboratory for Energy and Geology, Estrada da Portela, Apartado 7586, Alfragide, 2610-999 Amadora, PortugalPhysics Department of Évora University and Center for Sci-Tech Research in Earth System and Energy—CREATE, Évora University, 7004-671 Évora, PortugalNational Laboratory for Energy and Geology, Estrada da Portela, Apartado 7586, Alfragide, 2610-999 Amadora, PortugalPhysics Department of Évora University and Center for Sci-Tech Research in Earth System and Energy—CREATE, Évora University, 7004-671 Évora, PortugalThe 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 V<sub>s30</sub> 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 V<sub>s30</sub> 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.https://www.mdpi.com/2072-4292/17/8/1376seismic hazardLower Tagus ValleyV<sub>S30</sub>soil classificationseismic refractionseismic noise |
| spellingShingle | João Carvalho Ruben Dias José Borges Lídia Quental Bento Caldeira Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data Remote Sensing seismic hazard Lower Tagus Valley V<sub>S30</sub> soil classification seismic refraction seismic noise |
| title | Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data |
| title_full | Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data |
| title_fullStr | Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data |
| title_full_unstemmed | Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data |
| title_short | Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data |
| title_sort | soil classification maps for the lower tagus valley area portugal using seismic geological and remote sensing data |
| topic | seismic hazard Lower Tagus Valley V<sub>S30</sub> soil classification seismic refraction seismic noise |
| url | https://www.mdpi.com/2072-4292/17/8/1376 |
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