scholarly journals A DATABASE OF THE CONTENT OF GEOLOGICAL MAPS (GEOMAP) AND THE COMPUTER-ASSISTED PRODUCTION OF THE GEOLOGICAL MAP 1: 50.000 OF AUSTRIA AS A MAJOR PART OF THE AUSTRIAN GEOLOGICAL INFORMATION SYSTEM

1993 ◽  
Vol 4 (3) ◽  
pp. 239-244
Author(s):  
Werner R. Janoschek ◽  
Gunther A. Pascher ◽  
Udo R. Strauss
Keyword(s):  
Information System ◽  
Major Part ◽  
Computer Assisted ◽  
Geological Maps ◽  
Geological Information ◽  
Geological Map

scholarly journals Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization

Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2443-2453 ◽  
Author(s):  
Samuele Segoni ◽  
Giulio Pappafico ◽  
Tania Luti ◽  
Filippo Catani
Keyword(s):  
Landslide Susceptibility ◽  
Characteristic Curve ◽  
Receiver Operator Characteristic Curve ◽  
Landslide Susceptibility Mapping ◽  
Susceptibility Assessment ◽  
Geological Maps ◽  
Geological Information ◽  
Susceptibility Model ◽  
Validation Procedure ◽  
Geological Map

AbstractThe literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been established. This point is crucial, especially when working on wide and complex areas, in which a detailed geological map needs to be reclassified according to more general criteria. In a study area in Italy, we tested different configurations of a random forest–based landslide susceptibility model, accounting for geological information with the use of lithologic, chronologic, structural, paleogeographic, and genetic units. Different susceptibility maps were obtained, and a validation procedure based on AUC (area under receiver-operator characteristic curve) and OOBE (out of bag error) allowed us to get to some conclusions that could be of help for in future landslide susceptibility assessments. Different parameters can be derived from a detailed geological map by aggregating the mapped elements into broader units, and the results of the susceptibility assessment are very sensitive to these geology-derived parameters; thus, it is of paramount importance to understand properly the nature and the meaning of the information provided by geology-related maps before using them in susceptibility assessment. Regarding the model configurations making use of only one parameter, the best results were obtained using the genetic approach, while lithology, which is commonly used in the current literature, was ranked only second. However, in our case study, the best prediction was obtained when all the geological parameters were used together. Geological maps provide a very complex and multifaceted information; in wide and complex area, this information cannot be represented by a single parameter: more geology-based parameters can perform better than one, because each of them can account for specific features connected to landslide predisposition.

An attempt to increase the geological information in landslide susceptibility mapping and sensitivity to different geological parameters

2020 ◽  
Author(s):  
Tania Luti ◽  
Samuele Segoni ◽  
Bimla Tamburini ◽  
Giulio Pappafico ◽  
Filippo Catani
Keyword(s):  
Landslide Susceptibility ◽  
Learning Algorithm ◽  
Input Parameter ◽  
Test Site ◽  
Landslide Susceptibility Mapping ◽  
Significant Information ◽  
Geological Maps ◽  
Lithostratigraphic Units ◽  
Geological Information ◽  
Geological Map

<p>Geological maps convey different and multifaceted information including lithology, age, tectonism and so on. This complex information is not fully exploited in landslide susceptibility (LS) studies, as a single parameter is usually derived from the geological map of the study area (e.g. the area is divided into lithological or lithostratigraphic or geological units). The aim of this work is testing different approaches to extract significant information from geological maps, creating different parameterizations, and analyzing the sensitivity of a LS model to these variations.</p><p>Our test site is a 3100 km<sup>2</sup> wide area in Tuscany (Italy) characterized by a very complex geological setting. A 1:10000 scale geological map subdivides the area into 194 different lithostratigraphic units. This map was reclassified according to different criteria, creating 6 different parameters derived from the same geological map: lithology (6 lithological classes), age of deposition (the area was subdivided into 6 chronological units), paleogeography (6 units were differentiated on the basis of their environment of formation), genesis of the bedrock (5 classes accounted for the mechanism of formation of the outcropping rock/terrain), broad tectonic domain (the mapped elements were grouped into 5 broad structural units accounting for their tectonic history), detailed tectonic domain (same as before but with a more detailed subdivision into 10 classes).</p><p>Some of these parameters have already been used in LS studies, others have been used here for the first time; however, all of them have some connections with landslide predisposition. These parameters were used (one by one and altogether) to run seven times a landslide susceptibility model based on the widely used random forest machine learning algorithm. The model configurations and resulting maps were evaluated in terms of AUC(Area Under Curve) and OOBE(out of bag error): while the former expresses the forecasting effectiveness of each configuration, the latter expresses, among a single configuration, the importance of each input parameter.</p><p>We discovered that the results are very sensitive to the approach used to consider geology in the susceptibility assessment, with AUC values ranging from 63.5% (using chronological units) to 70.0% (using genetic units) and 75.2% (using all the geology-derived parameters simultaneously). These results are in line with OOBE statistics, which showed a similar relative importance of the geologically-driven parameters.</p><p>These outcomes can to assist future landslide susceptibility studies for different reasons:</p><p>(i)at least in our study area, lithology, which is commonly used in LS, did not provide the best results;</p><p>(ii)as geological maps provide multifaceted information, a single classification approach cannot fully grasp this complexity; therefore, the best results can be obtained using different geology-based parameters simultaneously, because each of them can account for specific features connected to landslide predisposition (to our knowledge, a similar approach has never been attempted before in LS literature).</p><p>(iii)When using thematic maps to feed LS models, it is important to fully understand the nature and the meaning of the information provided by the geology-related maps: results are very sensitive to this kind of information and the interpretation of the results should take it into account.</p>

scholarly journals Geology and geophysics at the archeological park of Vulci (central Italy)

2014 ◽  
Vol 57 (1) ◽  
Author(s):  
Marco Marchetti ◽  
Vincenzo Sapia ◽  
Adriano Garello ◽  
Donatella De Rita ◽  
Alessandra Venuti
Keyword(s):  
Electrical Resistivity ◽  
Magnetic Susceptibility ◽  
Cultural Heritage ◽  
Central Italy ◽  
Geophysical Methods ◽  
Archaeological Sites ◽  
Local Authorities ◽  
Resistivity Tomography ◽  
Geological Information ◽  
Geological Map

<p>The Vulci archeological site was object of interest by the Soprintendenza ai beni culturali dell’Etruria meridionale (Italian government department responsible for southern Etruria’s cultural heritage) since the beginning of the 20th century. In 2001, the Ministero dei Beni Culturali (Italian ministry of cultural heritage) along with the local authorities, opened a natural-archeological park. In this area, it lies most of the ancient Etruscan city of Velch (today known by its Latin name, Vulci) including the Osteria Necropolis that is the object of this study. Recently, new archaeological excavations were made and the local authorities needed major geological information about the volcanic lithotypes where the Etruscans used to build their necropolis. The aim of this study is to define the geological and geophysical characteristics of the rock lithotypes present in the Vulci park. For this purpose, a geological map of the area (1:10000) has been realized. Moreover, two different geophysical methods were applied: measurements of magnetic susceptibility and electrical resistivity tomography. Magnetic susceptibility analyses clearly identify magnetic contrasts between different lithotypes; the characteristics of the pyroclastic flow that originated the Sorano unit 2 and its vertical facies variations are well recorded by this parameter that along with lithostratigraphic observations provides information about the depositional conditions. Two electrical resistivity tomographies were performed, which show the Sorano unit 2 thickness to be of c. 7 m with resistivity values ranging from 200 to 400 Ω·m. This kind of multidisciplinary approach resulted to be suitable to study this type of archaeological sites, revealing that areas characterized by a relevant thickness and wide areal extension of volcanic lithotypes can be a potential site where Etruscans might have excavated their necropolis.</p>

scholarly journals The value of urban trails, statuary and installations for Geoscience education: uses and abuses from the north of England and further afield

2018 ◽  
Vol 14 (3) ◽  
pp. 277-281
Author(s):  
Phillip J. Murphy ◽  
Elizabeth Murphy
Keyword(s):  
Building Stone ◽  
Educational Resources ◽  
Geoscience Education ◽  
Web Based ◽  
The North ◽  
Geological Maps ◽  
Geological Map ◽  
The Right ◽  
Education Resource ◽  
City Park

The origins, uses and fates of a number of purpose built urban educational resources sited in the north of England are reviewed. These include walk on geological maps, building stone trails, a church gate and landscaping in a city park. A geological trail in the municipal cemetery of Rochdale dating from 1855 is a candidate for the oldest purpose made geological education trail in the world and the most recent educational resource was built in 2015. The destruction of a walk on geological map of England and Wales in 2004 shows that such valuable geoscience educational resources are in need of protection. A range of educational uses of these resources are suggested. Comparison is made with similar resources in London, both statuary and web based, and ways to ensure their preservation and continued educational use are suggested. This study shows that a geoscience education resource, if sited in the right place and looked after, can be an exciting and inspirational education resource in regular use for over half a century.

scholarly journals Automated geological map deconstruction for 3D model construction using <i>map2loop</i> 1.0 and <i>map2model</i> 1.0

2021 ◽  
Vol 14 (8) ◽  
pp. 5063-5092
Author(s):  
Mark Jessell ◽  
Vitaliy Ogarko ◽  
Yohan de Rose ◽  
Mark Lindsay ◽  
Ranee Joshi ◽  
...  
Keyword(s):  
Data Extraction ◽  
Regional Scale ◽  
3D Modelling ◽  
Stochastic Simulations ◽  
Model Construction ◽  
Conceptual Information ◽  
Geological Maps ◽  
Information Studies ◽  
Geological Map ◽  
Positional Data

Abstract. At a regional scale, the best predictor for the 3D geology of the near-subsurface is often the information contained in a geological map. One challenge we face is the difficulty in reproducibly preparing input data for 3D geological models. We present two libraries (map2loop and map2model) that automatically combine the information available in digital geological maps with conceptual information, including assumptions regarding the subsurface extent of faults and plutons to provide sufficient constraints to build a prototype 3D geological model. The information stored in a map falls into three categories of geometric data: positional data, such as the position of faults, intrusive, and stratigraphic contacts; gradient data, such as the dips of contacts or faults; and topological data, such as the age relationships of faults and stratigraphic units or their spatial adjacency relationships. This automation provides significant advantages: it reduces the time to first prototype models; it clearly separates the data, concepts, and interpretations; and provides a homogenous pathway to sensitivity analysis, uncertainty quantification, and value of information studies that require stochastic simulations, and thus the automation of the 3D modelling workflow from data extraction through to model construction. We use the example of the folded and faulted Hamersley Basin in Western Australia to demonstrate a complete workflow from data extraction to 3D modelling using two different open-source 3D modelling engines: GemPy and LoopStructural.

A synthetic geological information system and its application to xiangjiaba hydropower station

2004 ◽  
Vol 41 ◽  
pp. 273-279
Author(s):  
Pan Wei ◽  
Liu Daan ◽  
Yang Zhifa ◽  
Zeng Qianbang ◽  
Ye Siyuan ◽  
...  
Keyword(s):  
Information System ◽  
Hydropower Station ◽  
Geological Information

THE EVOLUTION OF GEOLOGICAL MAPS OF LOWER SILESIA ON THE EXAMPLE OF THE KARKONOSZE-IZERA BLOCK

2016 ◽  
pp. 0-0
Author(s):  
Stanisław WOŁKOWICZ
Keyword(s):  
20Th Century ◽  
19Th Century ◽  
Geological Mapping ◽  
Geological Maps ◽  
Geological Map ◽  
The 19Th Century ◽  
Lower Silesia

The paper presents the development of the geological mapping of in the Sudetes and Lower Silesia, starting from issuing in 1791 the first geological map of the Karkonosze Mountains, developed by J. Jirasek and issued in 1791, through maps of L. von Buch, C. von Raumer and A. Kaluža from the beginning of the 19th century, through and numerous editions of atlases published throughout the 19th century, ending with the detailed maps produced at the scale of 1 : 25,000 in at the beginning of the 20th century. The latter maps were the basis for the geological maps prepared after 1945.

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