Agglomerative hierarchical clustering of airborne electromagnetic data for multi-scale geological studies

Dumont, Marc; Reninger, Pierre-Alexandre; Pryet, Alexandre; Martelet, Guillaume; Aunay, Bertrand; Join, Jean-Lambert

doi:10.1016/j.jappgeo.2018.06.020

Cited by 22 publications

(16 citation statements)

References 30 publications

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“…Many studies reported methods, approaches and algorithm to better process and model data aimed at highlighting phenomena. Examples of various methods of statistical data analysis include data visualization, regressions, correlation, inference (Roberts et al, 2019;Lemenkova, 2019d), velocity modeling using grid based travel-time calculation method (Fujie et al, 2006), regression analysis of variables (Lemenkova, 2019c), factor analysis (Tucker, 1964;Lemenkova, 2018c), clustering and data grouping (Dumont et al, 2018;Lemenkova, 2019h). As for data instruments, examples of application include R programming language (Kotov & Pälike, 2017Lemenkova, 2018a), Python programming language (Yu et al, 2019;Lemenkova, 2019b), SPSS Statistics (Lemenkova, 2019e), Gretl (Lemenkova, 2019d).…”

Section: Discussionmentioning

confidence: 99%

Gebco Gridded Bathymetric Datasets for Mapping Japan Trench Geomorphology by Means of GMT Scripting Toolset

Lemenkova¹

2020

Geodesy and Cartography

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The study investigated geomorphology of the Japan Trench located east of Japan, Pacific Ocean. A high-resolution GEBCO Gridded Bathymetric Dataset was used for modeling, mapping and visualization. The study aimed to compare and analyse variations in the geomorphic structures of the two parts of the trench and to visualize variations in the geological, geophysical and bathymetric settings. Technically, the cartographic work was performed using scripting based on the Generic Mapping Toolset (GMT). Modelled cross-sectioning orthogonal profiles transecting the trench in a perpendicular direction were automatically digitized and graphed in the two segments. The results of the bathymetric analysis shown that the southern part is shallower: with deeper values in absolute (139 samples between –7000 to –8000 m) and statistical records (the most frequent values are within –5500 to –5800 m) comparing to the northern segment (–5300 to –5500 m). The geomorphological analysis shows a more complicated relief in the northern part of the trench, which has a higher seismic activity. The southern part has a gentler slope on the Honshu island side. The geoid modeling along the trench ranges in 0–20 mGal. The highest values are recorded by the Honshu Island (>40 mGal). The rest of the area has rather moderate undulations (20–40 mGal). The free-air marine gravity of the Sea of Japan is <40 mGal. The results include 2D and 3D graphical models, thematic cartographic maps, spatial and statistical analysis of the Japan Trench geomorphology. Tested GMT functionality can be applied to future regional bathymetric modeling of the ocean trenches. All presented maps and graphs are made using GMT scripting toolset.

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Section: Discussionmentioning

confidence: 99%

Gebco Gridded Bathymetric Datasets for Mapping Japan Trench Geomorphology by Means of GMT Scripting Toolset

Lemenkova¹

2020

Geodesy and Cartography

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“…Hiyerarşik kümeleme yöntemi her ne kadar birbirinden mutlak olarak ayrılmış kümeler yaratmaya çalışmasa da (Dumont et al 2018), HK'de elde edilen dendrogram optimal küme sayısının belirlenmesine yardımcı olabilir. Fakat dendrogramın kesme yüksekliğine karar vermek zorlu bir süreçtir (Li et al 2018, Govender andSivakumar 2020).…”

Section: çAlışma Alanıunclassified

“…(2018), kesme noktasını belirlemek için x ekseninde küme sayıları ve y ekseninde kümeler arası mesafelerin olduğu bir çizgi grafik kullanmıştır. Bu çalışmada kesme yüksekliğinin seçimi, grafikte eğiminin azalmaya başladığı nokta (dirsek formasyonu) olarak belirlenmiştir (Dumont, Reninger et al 2018).…”

Section: çAlışma Alanıunclassified

“…Bu seçim, gerekli ayrıntı düzeyiyle tutarlı olmalı ve ayrıca kümeler arasındaki mesafenin en aza indirilmiş olması göz önünde bulundurmalıdır. Kesme mesafesi ne kadar yüksek olursa, kümeler içindeki heterojenlik o kadar fazla olur (Dumont et al 2018). Bir analistin veri setinde kaç küme bulması gerektiğine dair kesin bir cevap yoktur, önemli olan konu bu kümeler ile ne yapılacağıdır (Haynes 2012).…”

Section: şEkil 4 Mesafe Matrisiunclassified

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Havzaların Benzerliklerini Tanımlamada Alternatif Bir Yaklaşım: Hiyerarşik Kümeleme Yöntemi Uygulaması

Aytaç

2021

Afyon Kocatepe University Journal of Sciences and Engineering

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Machine learning methods have widespread their use and strengthened their places in many areas. These procedures can be divided into three main branches as supervised, unsupervised, and reinforced learning and assist researchers to find connections in the data that cannot be seen or in situations that require long-term computation. Unsupervised methods are used to discover patterns or structures in data which does not have any labels. The hierarchical clustering process is one of the leading unsupervised methods. This study is an alternative approach to the process we used in defining the similarities of basins. The advantages of the proposed method are; reveals the relations between all basins, is less sensitive to noise in the data set, is more useful in applications with fewer basins, and is flexible in ensuring intra-cluster consistency. Some basins located in the north of Turkey based on their hydrological response units (HRU) images were hierarchically clustered and found out that and the two basins most similar to each other are the Ereğli and Çaykıyı catchments. A distance matrix was prepared to reveal the relations of the basins. Besides, to create independent clusters, four different statistical approaches were used to select the cut-off height of the dendrogram. To stay within the cluster numbers suggested by statistical methods and to ensure cluster homogeneity, 6 separate clusters were created. The distribution of the catchments depending on the clusters was illustrated. This study provides an alternative perspective for the clustering of basins based on HRU images.

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“…Airborne electromagnetics (AEM) provides information on lithology and regolith over large surfaces and/or hard-to-access areas [36][37][38][39][40]. It is able to provide plentiful pseudo-3D information about geological structures reaching a few hundred meters [41,42] and has been successfully used in many environmental studies [30,[43][44][45][46][47] particularly in volcanic settings. AEM is therefore useful to analyze the internal structure of large landslides [48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Airborne Electromagnetics to Improve Landslide Knowledge in Tropical Volcanic Environments

2021

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Caribbean areas are particular volcanic territories in tropical environments. These territories juxtapose several landslide-prone areas with different predisposing factors (poorly consolidated volcanic materials, superimposition of healthy materials on highly weathered materials, high heterogeneity of thicknesses, etc.). In these environments, where rapid development of slopes and land use changes are noticeable, it is necessary to better characterize these unstable phenomena that cause damage to infrastructure and people. This characterization has to be carried out on the materials as well as on the initiation conditions of the phenomena and requires complementary investigations. This study, focusing on La Martinique, proposes a landslide analysis methodology that combines new information about landslide-prone materials acquired by an airborne electromagnetics survey with a physical-based model. Once the data are interpreted and compared with field observations and previous data, a geological model is produced and introduced into the physical model to test different instability scenarios. The results show that geophysical investigations (i) improve the knowledge of the internal structure of landslides and surficial formations, (ii) specify the spatial limits of the materials that are sensitive to landslides, and (iii) give a better understanding of landslide initiation conditions, particularly hydrogeological triggering conditions.

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Agglomerative hierarchical clustering of airborne electromagnetic data for multi-scale geological studies

Cited by 22 publications

References 30 publications

Gebco Gridded Bathymetric Datasets for Mapping Japan Trench Geomorphology by Means of GMT Scripting Toolset

Gebco Gridded Bathymetric Datasets for Mapping Japan Trench Geomorphology by Means of GMT Scripting Toolset

Havzaların Benzerliklerini Tanımlamada Alternatif Bir Yaklaşım: Hiyerarşik Kümeleme Yöntemi Uygulaması

Airborne Electromagnetics to Improve Landslide Knowledge in Tropical Volcanic Environments

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