Collecting and Handling Point Pattern Data

2015 ◽  
pp. 67-98
Keyword(s):  
Point Pattern

scholarly journals Does fluvial channel-belt clustering predict net sand to gross rock volume? Architectural metrics and point-pattern analysis of a digital outcrop model

2019 ◽  
Vol 89 (11) ◽  
pp. 1109-1126
Author(s):  
Alexander R. Koch ◽  
Cari L. Johnson ◽  
Lisa Stright
Keyword(s):  
Large Scale ◽  
Small Scale ◽  
Point Pattern ◽  
Point Patterns ◽  
Spatial Point ◽  
Channel Belt ◽  
John Henry Member ◽  
Scale Point ◽  
Belt Width ◽  
Digital Outcrop

ABSTRACT Spatial point-pattern analyses (PPAs) are used to quantify clustering, randomness, and uniformity of the distribution of channel belts in fluvial strata. Point patterns may reflect end-member fluvial architecture, e.g., uniform compensational stacking and avulsion-generated clustering, which may change laterally, especially at greater scales. To investigate spatial and temporal changes in fluvial systems, we performed PPA and architectural analyses on extensive outcrops of the Cretaceous John Henry Member of the Straight Cliffs Formation in southern Utah, USA. Digital outcrop models (DOMs) produced using unmanned aircraft system-based stereophotogrammetry form the basis of detailed interpretations of a 250-m-thick fluvial succession over a total outcrop length of 4.5 km. The outcrops are oriented roughly perpendicular to fluvial transport direction. This transverse cross-sectional exposure of the fluvial system allows a study of the system's variation along depositional strike. We developed a workflow that examines spatial point patterns using the quadrat method, and architectural metrics such as net sand to gross rock volume (NTG), amalgamation index, and channel-belt width and thickness within moving windows. Quadrat cell sizes that are ∼ 50% of the average channel-belt width-to-thickness ratio (16:1 aspect ratio) provide an optimized scale to investigate laterally elongate distributions of fluvial-channel-belt centroids. Large-scale quadrat point patterns were recognized using an array of four quadrat cells, each with 237× greater area than the median channel belt. Large-scale point patterns and NTG correlate negatively, which is a result of using centroid-based PPA on a dataset with disparately sized channel belts. Small-scale quadrat point patterns were recognized using an array of 16 quadrat cells, each with 21× greater area than the median channel belt. Small-scale point patterns and NTG correlate positively, and match previously observed stratigraphic trends in the fluvial John Henry Member, suggesting that these are regional trends. There are deviations from these trends in architectural statistics over small distances (hundreds of meters) which are interpreted to reflect autogenic avulsion processes. Small-scale autogenic processes result in architecture that is difficult to correlate between 1D datasets, for example when characterizing a reservoir using well logs. We show that 1D NTG provides the most accurate prediction for surrounding 2D architecture.

scholarly journals Efficiency loss and support for income redistribution: Evidence from a laboratory experiment

2021 ◽  
pp. 104346312110155
Author(s):  
Markus Tepe ◽  
Fabian Paetzel ◽  
Jan Lorenz ◽  
Maximilian Lutz
Keyword(s):  
Laboratory Experiment ◽  
Group Communication ◽  
Negative Relationship ◽  
Income Redistribution ◽  
Point Pattern ◽  
Minor Role ◽  
Treatment Variable ◽  
Efficiency Loss ◽  
Tax Rate ◽  
Negative Effect

Income redistribution with an efficiency loss is expected to have a twofold negative effect on support for redistribution, as it lowers egoistic support for redistribution and activates efficiency preferences. This study tests whether such a negative relationship exists, increases with the size of efficiency loss and interacts with group communication and the income position. We present a laboratory experiment in which subjects receive a randomly allocated income and must coordinate on a majority tax rate using a deliberative communication tool. The rate of money lost as a part of the redistribution process is manipulated as a treatment variable (0%, 5%, 20%, or 60%). Experimental evidence shows that efficiency loss exerts a robust negative effect on support for redistribution. The effect shows a tipping point pattern, is stronger at the lower end of the income distribution and is not fully explained by egoistic preferences. Inefficiency matters mostly for the chosen tax rate after group communication. At an efficiency loss of 60%, however, group communication does not affect support for redistribution, which implies that inefficiencies tend to play a minor role in the context of redistribution as long as they are within a moderate range. JEL Classification: C91, C92, D63, D72

A point pattern model of the spread of foot-and-mouth disease

2002 ◽  
Vol 56 (1) ◽  
pp. 33-49 ◽  
Author(s):  
G Gerbier ◽  
J.N Bacro ◽  
R Pouillot ◽  
B Durand ◽  
F Moutou ◽  
...  
Keyword(s):  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Point Pattern ◽  
Foot And Mouth

scholarly journals Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mariem Ben-Said
Keyword(s):  
Spatial Patterns ◽  
Pattern Analysis ◽  
Biotic Interactions ◽  
Plant Ecology ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Summary Statistics ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis

Abstract Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

Combinatorial and Experimental Methods for Approximate Point Pattern Matching

Algorithmica ◽  
2003 ◽  
Vol 38 (1) ◽  
pp. 59-90 ◽  
Author(s):  
Martin Gavrilov ◽  
Piotr Indyk ◽  
Rajeev Motwani ◽  
Suresh Venkatasubramanian
Keyword(s):  
Pattern Matching ◽  
Experimental Methods ◽  
Point Pattern ◽  
Point Pattern Matching

scholarly journals Occurrence of tuberculosis cases in Crato, Ceará, from 2002 to 2011: a spatial analisys of specific standards

2015 ◽  
Vol 18 (2) ◽  
pp. 313-325 ◽  
Author(s):  
Mayrla Lima Pinto ◽  
Talina Carla da Silva ◽  
Lidiane Cristina Félix Gomes ◽  
Maria Rita Bertolozzi ◽  
Lourdes Milagros Mendoza Villavicencio ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Urban Area ◽  
Temporal Trend ◽  
Kernel Method ◽  
Quantitative Approach ◽  
Point Pattern ◽  
Hybrid Design ◽  
Population Densities ◽  
Population Groups

OBJECTIVE: to analyze the spatial distribution of tuberculosis in Crato, Ceará, Brazil, from 2002 to 2011, aiming to check for a point pattern. METHODS: This is an ecological, temporal trend and hybrid design study, with a quantitative approach. A total of 261 cases of tuberculosis were geo-referenced and 20 (7.1%) were considered as losses due to the lack of address. The profile of patients in 10 years of study was in accordance with the following pattern: men aged between 20 and 59 years, with low schooling, affected by the pulmonary form of tuberculosis and who were cured from the disease. RESULTS: The analysis of the spatial distribution of tuberculosis points out that in the period of study, new cases of the disease were not distributed on a regular basis, indicating a clustered spatial pattern, confirmed by the L-function. The map with the density of new cases estimated by the Kernel method showed that the "hot" areas are more concentrated in the vicinity of the central urban area. CONCLUSION: The study allowed pointing out areas of higher and lower concentration of tuberculosis, identifying the spatial pattern, but it also recognized that the disease has not reached all of the population groups with the same intensity. Those who were most vulnerable were the ones who lived in regions with higher population densities, precarious living conditions, and with intense flow of people.

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