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neighbor proximity analysis

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Journal Article
Journal: PALAIOS
Published: 01 August 2004
PALAIOS (2004) 19 (4): 396–407.
...LINDSEY R. LEIGHTON; CHRIS L. SCHNEIDER Abstract Time-averaging can be a major obstacle in reconstructing fine-scale ecological processes in the fossil record. This study presents a technique, Neighbor Proximity Analysis that attempts, despite time-averaging, to elucidate fine-scale ecological...
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Published: 01 August 2004
TABLE 2 —Data and results of the Neighbor Proximity Analysis for selected taxa from Unit 9, Rapid Member. Note that Spinatrypa ex hibited clustering as significant as that of colonial organisms (bryo zoans) and crinoid columnals
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FIGURE 2—Steps in Neighbor Proximity Analysis, illustrated by a hypothetical example. (A) Specimens are mapped on the bedding plane. (B) A grid is placed over the map, and the species of interest is point-counted. Grid spacing is designed to capture all specimens of the species of interest. (C) Neighbor connections (number of adjacent points with conspecific neighbors) are tallied. This example has two connections (four neighbors). This community, with 36 grid points and four Spinatrypa, is then randomly permuted for 10,000 iterations. The random communities generated four or more neighbors in 38.19% of the iterations; therefore, the hypothesis that the observed clustering is random cannot be rejected at the 95% confidence level. (D) Three connections (six neighbors); three Spinatrypa. Random communities produced six neighbors only 3.03% of the iterations; observed clustering is probably original biogenic clustering. (E) Two connections (four neighbors), but with a different geometry, and only three Spinatrypa. Random communities produced four or more neighbors 8.43% of the iterations. Random clustering cannot be rejected at 95% level of confidence, but can be rejected at 90%
Published: 01 August 2004
FIGURE 2 —Steps in Neighbor Proximity Analysis, illustrated by a hypothetical example. (A) Specimens are mapped on the bedding plane. (B) A grid is placed over the map, and the species of interest is point-counted. Grid spacing is designed to capture all specimens of the species of interest. (C
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Nearest‐neighbor clustering analysis performed on our enhanced seismicity catalog with ML≥0.5. Only epicenters are used, and the fractal dimension (df) is taken to be 1.6. (a) A joint 2D distribution of the rescaled time and rescaled distance. Each of the black dots represents the proximity of each event to a parent event. (b) Histogram of the nearest‐neighbor proximity distance with curves showing the two Gaussian distributions representing the two modes derived from the 1D Gaussian mixture model. (c) The average joint distribution of the rescaled time and rescaled distance derived from 100 catalogs created from reshuffling locations and magnitudes of independent events. The diagonal white dashed lines in panels (a) and (c) and the black vertical dashed line in panel (b) mark the mode separator (η0=10−3.05) used to perform binary classification of events into either independent or clustered. The color version of this figure is available only in the electronic edition.
Published: 05 September 2024
Figure 3. Nearest‐neighbor clustering analysis performed on our enhanced seismicity catalog with M L ≥ 0.5 . Only epicenters are used, and the fractal dimension ( d f ) is taken to be 1.6. (a) A joint 2D distribution of the rescaled time and rescaled distance. Each of the black
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(A) Results of nearest-neighbor spatial analysis of dike segment midpoints. Segments are binned in 20° increments then the number of nearby segment midpoints closer than either the mean dike length (0.4 km) or maximum dike length (4.3 km). Dashed lines refer to the average number of nearest neighbor distances closer than a particular threshold. CJDS—Chief Joseph dike swarm. (B) Dikes in central Wallowa Mountains colored in 20° bins. This illustrates the predominance of many dike segments of similar orientations in close proximity to one another.
Published: 14 May 2020
Figure 3. (A) Results of nearest-neighbor spatial analysis of dike segment midpoints. Segments are binned in 20° increments then the number of nearby segment midpoints closer than either the mean dike length (0.4 km) or maximum dike length (4.3 km). Dashed lines refer to the average number
Journal Article
Journal: AAPG Bulletin
Published: 01 February 2022
AAPG Bulletin (2022) 106 (2): 289–319.
...Nigel E. Cross; Sunil K. Singh; Abdulmohsen Al-Enezi; Sayed Behbehani ABSTRACT An integrated sedimentological and sequence stratigraphic analysis of the mixed carbonate and clastic Albian Mauddud Formation in the Bahrah and Sabiriyah fields provides an improved understanding of this important...
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Journal Article
Published: 01 March 2019
Russ. Geol. Geophys. (2019) 60 (3): 267–286.
...–525 Ma. The results of our study and the performed analysis of available geological data on the Argun terrane and neighboring Transbaikalia and Southeastern Asia territories point to the fallacy of previous arguments about the Amur composite microcontinent as a single tectonic unit, whose collision...
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Journal Article
Journal: Lithosphere
Publisher: GSW
Published: 01 October 2016
Lithosphere (2016) 8 (5): 519–532.
... neighbors during deposition. The polydeformed nature of the Murmac Bay Group, however, presents challenges in determining detailed stratigraphic relationships in the upper succession, which lacks distinct marker beds. Provenance analysis from detrital zircon geochronology provides one strategy...
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Series: SEPM Short Course Notes
Published: 01 January 2010
DOI: 10.2110/sepmscn.054.001
EISBN: 9781565763364
... trends are defined when separation distance is plotted against the variance in water depth atop each sandbar for the three areas (Fig. 49 ). Here, sandbars that have a neighbor in close proximity show the greatest variance in depth. More separated sandbars have a distinctly lower variance in water depth...
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Journal Article
Published: 01 October 2020
Italian Journal of Geosciences (2020) 139 (3): 436–449.
... m 2 , with a maximum depth of 7 m and located on the distal deposits of the Alban Hills Volcanic District in an area named “Acqua Bullicante” (i.e. Bubbling Water), where degassing phenomena were historically recorded. The proximity of this volcanic district motivated the study on Lake Bullicante...
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Journal Article
Journal: Geosphere
Published: 27 July 2017
Geosphere (2017) 13 (5): 1640–1663.
...T.L. Carley; C.F. Miller; O. Sigmarsson; M.A. Coble; C.M. Fisher; J.M. Hanchar; A.K. Schmitt; R.C. Economos Abstract Breiðuvík and Kækjuskörð are two neighboring extinct eruptive centers in the East Fjords of Iceland. Together, they compose the second-largest volume of silicic rock in the country...
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Journal Article
Published: 01 March 2003
Bulletin de la Société Géologique de France (2003) 174 (2): 125–140.
...Patrick Bachèlery; Bernard Robineau; Michel Courteaud; Cécile Savin Abstract The Saint-Gilles breccias, on the western flank of Piton des Neiges volcano, are clearly identified as debris avalanche deposits. A petrographic, textural and structural analysis of the breccias and inter-bedded...
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Examples of texture classes in the map view based on depth or surface slice along with regular seismic characters in the cross sectional view (see text for explanation). In areas with flat beds (A, B, C), depth slicing provides an efficient and interactive means of viewing facies changes. In areas with structural dip (D), stratal slicing using a picked surface is required to provide more robust facies analysis because depth slicing may not be chronostratigraphically contiguous in such areas. (A) A meandering channel filled with sand. Notice the textural differences between the channel fill and the neighboring shale, the erosional base of the channel, and the convex-upward reflection geometry. (B) A channel-fan system showing the variability in width, morphology, channel-fill geometry, aspect ratio, and sinuosity from the proximal (erosional) to the distal (depositional) part of the system. (C) A channel-levee system with significant across- and along-axis variability in facies. Notice the concave-upward reflection geometry of the channel fill that contrasts with the convex-upward reflection geometry of other channel-fill deposits, indicating spatial and temporal variability in facies of the turbidite system. (D) A mass-transport complex (MTC) that features frontal cuspate and flanking linear edges. Arrows indicate the mass-transport direction, and curved lines denote cuspate (map view) faults induced by the mass transport of slope-forming sediments.
Published: 01 December 2007
and the neighboring shale, the erosional base of the channel, and the convex-upward reflection geometry. (B) A channel-fan system showing the variability in width, morphology, channel-fill geometry, aspect ratio, and sinuosity from the proximal (erosional) to the distal (depositional) part of the system. (C
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Workflow followed for the reconstruction of the turbidite systems in the Ainsa basin. (a) The main source of data was geological mapping and outcrop interpretations. (b) Field data were digitized onto the digital terrain model draped with the corresponding ortophotograph. (c) Geometrical analysis of 3-D map traces yielded bedding attitudes and stratigraphic separation between stratigraphic units that make it possible to define a 3-D dip-domain model of the area. (d–f) To reconstruct individual structural reference horizons, planes with the attitude of the defined dip domains are anchored at the map trace of the horizon and extended to their intersection with neighboring dip domains. Data from other horizons are projected onto the horizon under construction to constrain its geometry at depth and above surface. Continued. (g) The result is a 3-D TIN (triangulated irregular network) surface that defines the structure of the Buil syncline. (h) This structural reference horizon is flattened by flexural slip, leaving all the accompanying data in syndepositional state. (i) Sedimentary body boundaries are reconstructed by linking distal and proximal outcrops of the same bodies, constraining the shape with paleoflow information, and generating TIN surfaces (yellow surface) to represent the SBB. (j) The SBB reconstructed in syndepositional state (pink and brown surfaces below) are deformed to their present-day geometry (above) by deforming the structural reference surface (translucent surface) back to its original state.
Published: 01 August 2004
analysis of 3-D map traces yielded bedding attitudes and stratigraphic separation between stratigraphic units that make it possible to define a 3-D dip-domain model of the area. (d–f) To reconstruct individual structural reference horizons, planes with the attitude of the defined dip domains are anchored
Journal Article
Published: 10 April 2025
Bulletin of the Seismological Society of America (2025)
... data and makes more nuanced selections of background and clustered events when applied to real seismicity. Although the vast majority of the SML technique’s predictive power appears to lie within the NND values of the “first” nearest neighbors, a machine learning analysis reveals that predictive...
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Journal Article
Journal: PALAIOS
Published: 01 August 2004
PALAIOS (2004) 19 (4): 313–315.
... . Leighton , L.R. 2003 . Morphological response of prey to drilling predation in the Middle Devonian :: Palaeogeography, Palaeoclimatology, Palaeoecology , v. 201 , p. 221 – 234 . Leighton , L.R. , and Schneider , C. , 2004 . Neighbor Proximity Analysis, a technique for assessing...
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Journal Article
Published: 01 January 2025
Russ. Geol. Geophys. (2025) 66 (1): 118–126.
... of objects from the training set. This method does not have a training stage. The forecast result is calculated on the basis of selecting the most similar elements in the training dataset pairs. Due to the high degree of freedom and smoothness of the proximity field, the nearest neighbor method is less...
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Journal Article
Published: 22 September 2021
Seismological Research Letters (2022) 93 (1): 386–401.
... clustering of earthquakes in southern California. Figure  3a shows the time–latitude projection of all 8140 events with M ≥ 3 in the catalog. Figure  3b only includes the 50% (4083) least clustered events based on the nearest‐neighbor earthquake proximity discussed in Zaliapin and Ben‐Zion (2020...
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Journal Article
Published: 05 September 2024
Seismological Research Letters (2025) 96 (1): 130–146.
...Figure 3. Nearest‐neighbor clustering analysis performed on our enhanced seismicity catalog with M L ≥ 0.5 . Only epicenters are used, and the fractal dimension ( d f ) is taken to be 1.6. (a) A joint 2D distribution of the rescaled time and rescaled distance. Each of the black...
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Journal Article
Published: 12 March 2025
Seismological Research Letters (2025)
... of this figure is available only in the electronic edition. To further understand potential driving mechanisms of the earthquake sequences, we performed a nearest‐neighbor‐clustering analysis ( Zaliapin and Ben‐Zion, 2013a ). This analysis is particularly useful to distinguish tectonic, human‐induced...
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