scholarly journals Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale

2018 ◽  
Vol 58 ◽  
pp. 22-32 ◽  
Author(s):  
Matthew Quick ◽  
Guangquan Li ◽  
Ian Brunton-Smith
Keyword(s):  
Spatial Analysis ◽  
Spatial Patterns ◽  
Small Area ◽  
Multivariate Spatial Analysis ◽  
Crime Types

scholarly journals Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking

2020 ◽  
Vol 135 (4) ◽  
pp. 472-482
Author(s):  
Elisabeth Dowling Root ◽  
Emelie D. Bailey ◽  
Tyler Gorham ◽  
Christopher Browning ◽  
Chi Song ◽  
...  
Keyword(s):  
Public Health ◽  
Preterm Birth ◽  
Spatial Analysis ◽  
Infant Mortality ◽  
Spatial Patterns ◽  
Urban Areas ◽  
Vital Statistics ◽  
Infant Mortality Rate ◽  
Spatial Inequalities ◽  
Geographic Clustering

Objectives Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis. Methods We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space–time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time. Results The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared. Conclusions Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

scholarly journals Spaces of Islamophobia and spaces of inequality in Greater Paris

2020 ◽  
pp. 239965442094152
Author(s):  
Kawtar Najib
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Spatial Patterns ◽  
Quantitative Data ◽  
Statistical Data ◽  
Great Majority ◽  
Demographic Variables ◽  
Public Institutions ◽  
Terrorist Attacks ◽  
Population Census

This paper draws upon quantitative data collected from one of the principal associations fighting Islamophobia in France along with the population census, and provides a step forward in understanding the operation and distribution of Islamophobia. It presents a geography of Islamophobia in Paris based on statistical data, and aims to observe whether or not this geography corresponds or contrasts with geographies of inequality (such as those associated with gentrification, deprivation and marginalisation), by analysing the various spatial patterns stemming from the maps. This socio-spatial analysis of anti-Muslim discrimination is important in Paris because since the terrorist attacks in 2015, anti-Muslim sentiment has increased sharply. The mapping of Islamophobia and its association with the spatial distribution of different socioeconomic and demographic variables synthetized in a typological map display significant forms, relations and diversities within Paris. This cartographic analysis demonstrates that the geography of Islamophobia does not necessarily refer to spaces where ‘Muslims’ and the victims of Islamophobia live in great majority, and rather refers to more privileged and central areas such as Paris intra-muros. Victims mostly experience anti-Muslim incidents outside their everyday spaces away from their homes, such as public institutions and workplaces. Indeed, the findings raise the significance of the exact place where incidents occur as well as societal attitudes to these ‘hierarchical’ places where the perpetrator probably feels more comfortable in behaving in an antisocial and sometimes violent way.

scholarly journals A multivariate spatial analysis of vowel formants in American English

2013 ◽  
Vol 1 (1) ◽  
pp. 31-51 ◽  
Author(s):  
Jack Grieve ◽  
Dirk Speelman ◽  
Dirk Geeraerts
Keyword(s):  
United States ◽  
Spatial Analysis ◽  
American English ◽  
Western United States ◽  
The West ◽  
Acoustic Data ◽  
Vowel Formant ◽  
Multivariate Spatial Analysis ◽  
Vowel Formants ◽  
Vowel Shift

This paper presents the results of a multivariate spatial analysis of thirty-eight vowel formant variables measured in 236 cities from across the contiguous United States, based on the acoustic data from the Atlas of North American English. The results of the analysis both confirm and challenge the results of the Atlas. Most notably, while the analysis identifies similar patterns as the Atlas in the West and the Southeast, the analysis finds that the Midwest and the Northeast are distinct dialect regions that are considerably stronger than the traditional Midland dialect region identified in the Atlas. The analysis also finds evidence that a vowel shift is actively shaping the language of the Western United States.

Geocoding Tweets Approach Based on Conceptual Representations in the Context of the Knowledge Society

2016 ◽  
Vol 12 (1) ◽  
pp. 44-61 ◽  
Author(s):  
Imelda Escamilla ◽  
Miguel Torres-Ruiz ◽  
Marco Moreno-Ibarra ◽  
Rolando Quintero ◽  
Giovanni Guzmán ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Mexico City ◽  
Spatial Patterns ◽  
Knowledge Society ◽  
Spatial Relationships ◽  
Visualization Method ◽  
Urban Context ◽  
Conceptual Representations ◽  
The Core ◽  
Application Ontology

In this paper, an approach to geocode tweets published in Spanish is proposed. The tweets are related to traffic events within an urban context of the Mexico City. They are generated by a particular phenomenon for knowing the behavior of the involved geographic entities. In order to disambiguate and verify the consistency of information, an application ontology was defined. Thus, the core goal is to identify location as well as spatial relationships between entities presented in the events, using semantic and spatial analysis of the collected dataset. In consequence, a visualization method for presenting the results was also proposed. The paper describes the methodology for enabling the discovery of spatial patterns within traffic tweets and provides useful information to make timely decisions and contribute in the context of Knowledge Society.

scholarly journals Motif: an open-source R tool for pattern-based spatial analysis

2020 ◽  
Author(s):  
Jakub Nowosad
Keyword(s):  
Spatial Analysis ◽  
Land Cover ◽  
Open Source ◽  
Spatial Patterns ◽  
Forest Cover ◽  
R Package ◽  
Growth Monitoring ◽  
Forest Cover Change ◽  
Land Cover Data ◽  
Wide Range

*Context* Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns. *Objectives* We developed an R package **motif** as a set of open-source tools for pattern-based spatial analysis. *Methods* This package provides most of the functionality of existing software (except spatial segmentation), but also extends the existing ideas through support for multi-layer raster datasets. It accepts larger-than-RAM datasets and works across all of the major operating systems. *Results* In this study, we describe the software design of the tool, its capabilities, and present four case studies. They include calculation of spatial signatures based on land cover data for regular and irregular areas, search for regions with similar patterns of geomorphons, detection of changes in land cover patterns, and clustering of areas with similar spatial patterns of land cover and landforms. *Conclusions* The methods implemented in **motif** should be useful in a wide range of applications, including land management, sustainable development, environmental protection, forest cover change and urban growth monitoring, and agriculture expansion studies. The **motif** package homepage is https://nowosad.github.io/motif.

scholarly journals Temporal-spatial Analysis of Contributors’ Mapping Behavior for Building Data in OpenStreetMap

2019 ◽  
Vol 2 ◽  
pp. 1-10
Author(s):  
Jin Xu ◽  
Qi Zhou
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Spatial Patterns ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Developing Regions ◽  
Temporal And Spatial Patterns ◽  
Temporal And Spatial ◽  
One Year ◽  
Beijing China

<p><strong>Abstract.</strong> Volunteered Geographic Information (VGI) crowdsourced from volunteering posts, is closely related to contributors’ mapping behavior. As the most noticeable VGI source, OpenStreetMap (OSM) is one of the most studied objectives in VGI and data contributors. In this paper, temporal-spatial analysis is applied in seeking the temporal and spatial patterns of the number of buildings and contributors in Beijing, China. Temporal changes of the number of updated buildings, and the population of total, new and quitted contributors, were interpreted, as well as the spatial distribution of updated buildings, participated contributors, and frequency of updates. The result suggests that the number of updated buildings, participated contributors, new and quitted contributors are growing. Buildings are mostly updated by a small number of contributors, the majority of which did not participated in mapping in the previous year. Most contributors update buildings for one year without succeeding till the next. Contributors are interested in updating a large amount of buildings frequently around landmarks, commercial districts, universities, and transit hubs. They update buildings at an expanding range and an increasing density, but their attentions do not necessarily bring large quantity of building updates. In general, OSM buildings in developing regions with less complete database are updated under similar patterns as developed regions where data are much more complete.</p>

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