Comprehensive Strip Based Lineament Detection Method (COSBALID) from point-like features: a GIS approach

Arcasoy, Arda; Toprak, Vedat; Kaymakçı, Nuretdin

doi:10.1016/j.cageo.2003.09.004

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…The CAVP exhibits many spectacular volcanic landscapes including Miocene-Pliocene widespread ignimbrites (e.g., Aydar et al, 2012), various types of Miocene-Quaternary polygenetic volcanoes (e.g., Hasandağ and Erciyes stratovolcanoes, Keçikalesi and Acıgöl calderas) and hundreds of Quaternary monogenetic volcanoes (Toprak, 1998;Arcasoy, 2001;Arcasoy et al, 2004). These are typically in the form of scoria cones with smaller numbers of lava domes, maars, and tuff rings.…”

Section: Introductionmentioning

confidence: 99%

“…Inset map showing the Neogene-Quaternary volcanics in the Anatolia (compiled from MTA 1/500000 scale geological maps) and the geographic location of the CAVP (modified after Uslular and Gençalioğlu-Kuşcu, 2019b and references therein); B. Distribution of Quaternary monogenetic vents in the CAVP (modified afterToprak, 1998;Arcasoy et al, 2004) displayed on a shaded digital elevation model (ALOS 3D World, 30 m x 30 m resolution). Fault dataset (compiled fromPasquare et al, 1988;Toprak and Göncüoglu, 1993;Dhont et al, 1998;…”

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confidence: 99%

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Morphological and multivariate statistical analysis of quaternary monogenetic vents in the Central Anatolian Volcanic Province (Turkey): Implications for the volcano-tectonic evolution

Uslular

Corvec²,

Mazzarini

et al. 2021

Journal of Volcanology and Geothermal Research

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Morphological and multivariate statistical analysis of quaternary monogenetic vents in the Central Anatolian Volcanic Province (Turkey): Implications for the volcano-tectonic evolution

Uslular

Corvec²,

Mazzarini

et al. 2021

Journal of Volcanology and Geothermal Research

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“…In other words, vent alignments can represent areas of magma focusing or structural weaknesses, along which volcanism returns in repeated episodes (e.g., Kear 1964;Le Corvec et al 2013;Morfulis et al 2020;Sieron et al 2021). Several methods have been developed to identify orientations in volcanic fields, including: two-point azimuth techniques (Lutz 1986;Lutz and Gutmann 1995;Bleacher et al 2009;Richardson et al 2013), spatial transform methods (e.g., Hough's transform ;Connor 1990;Connor et al 1992;Von Veh and Németh 2009), and strip methods (Zhang and Lutz 1989; Arcasoy et al 2004). In our study, we focused on the nearest neighbor azimuth method of Cebriá et al (2011) using the Thomson and Lang (2016) Matlab tool (e.g., Grosse et al 2020;Morfulis et al 2020).…”

Section: Alignment Analysismentioning

confidence: 99%

Spatio-temporal forecasting of future volcanism at Harrat Khaybar, Saudi Arabia

et al. 2022

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The 180,000 km2 of Arabian lava fields (“harrats” in Arabic) form one of the largest distributed basaltic provinces in the world. The most recent eruption in 1256 AD, on the outskirts of Medina, as well as shallow dike emplacement in 2009, ~ 200 km northeast of the city, suggest future volcanic threat to this area. Harrat Khaybar (~ 1.7 Ma to present) is one of the largest and most compositionally diverse Arabian lava fields; it is located ~ 137 km northeast of Medina and covers ~ 14,000 km2. Here, we present a new eruption event record and the first estimation of future potential locations and timing of volcanism in Harrat Khaybar. Volcanic vents and eruptive fissures were mapped using remote sensing and field studies, and categorized into a geospatial database, complemented by 16 new 40Ar/39Ar ages. Our analysis reveals that Harrat Khaybar developed over five eruptive phases, where vent locations over time focus towards the central axis forming a broad N-S trend, with a central group concentrated along an axis of the regional Makkah-Madinah-Nafud (MMN) line and wider spatial dispersion between vents outwards from there. For the whole field, we estimate a long-term average recurrence rate of ~ 2.3 eruptions per 10 kyr assuming a Poisson distribution for inter-event times, which indicates that Harrat Khaybar would belong to a global group of highly active distributed volcanic fields. Our analysis also reveals that the field likely had a “flare-up” period between 450 and 300 ka where the vast majority of eruptions occurred, with ~ 18 eruptions per 10 kyr. After this intense period, eruption rates fell to < 2 eruptions per 10 kyr. Based on our findings, we estimate cumulative probabilities of 1.09 and 16.3% as lower and upper bounds of at least one eruption occurring over the next 100 years somewhere in Harrat Khaybar, with the highest probabilities within the central axis region, in particular around Jabal Qidr, Bayda and Abyad.

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“…Monte Carlo simulations of random points provide the estimate of the significance in [52] while a binomial model is used in [3]. A set of heuristics are added in [4]. The method in [18] also applies the strip method with a Poisson model, but the density is estimated locally.…”

Section: Introductionmentioning

confidence: 99%

A Contrario 2D Point Alignment Detection

Lezama

Morel

Randall

et al. 2015

IEEE Trans. Pattern Anal. Mach. Intell.

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In spite of many interesting attempts, the problem of automatically finding alignments in a 2D set of points seems to be still open. The difficulty of the problem is illustrated here by very simple examples. We then propose an elaborate solution. We show that a correct alignment detection depends on not less than four interlaced criteria, namely the amount of masking in texture, the relative bilateral local density of the alignment, its internal regularity, and finally a redundancy reduction step. Extending tools of the a contrario detection theory, we show that all of these detection criteria can be naturally embedded in a single probabilistic a contrario model with a single user parameter, the number of false alarms. Our contribution to the a contrario theory is the use of sophisticated conditional events on random point sets, for which expectation we nevertheless find easy bounds. By these bounds the mathematical consistency of our detection model receives a simple proof. Our final algorithm also includes a new formulation of the exclusion principle in Gestalt theory to avoid redundant detections. Aiming at reproducibility, a source code and an online demo open to any data point set are provided. The method is carefully compared to three state-of-the-art algorithms and an application to real data is discussed. Limitations of the final method are also illustrated and explained.

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Comprehensive Strip Based Lineament Detection Method (COSBALID) from point-like features: a GIS approach

Cited by 9 publications

References 8 publications

Morphological and multivariate statistical analysis of quaternary monogenetic vents in the Central Anatolian Volcanic Province (Turkey): Implications for the volcano-tectonic evolution

Morphological and multivariate statistical analysis of quaternary monogenetic vents in the Central Anatolian Volcanic Province (Turkey): Implications for the volcano-tectonic evolution

Spatio-temporal forecasting of future volcanism at Harrat Khaybar, Saudi Arabia

A Contrario 2D Point Alignment Detection

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