Visualizing accessibility with choropleth maps

2021 ◽  
Author(s):  
David Li ◽  
Hanan Samet ◽  
Amitabh Varshney
Keyword(s):  
Choropleth Maps

scholarly journals Examining the Neighborhood Attributes of Recently Housed Partner Violence Survivors in Rapid Rehousing

2021 ◽  
Vol 18 (8) ◽  
pp. 4177
Author(s):  
Charvonne N. Holliday ◽  
Kristin Bevilacqua ◽  
Karen Trister Grace ◽  
Langan Denhard ◽  
Arshdeep Kaur ◽  
...  
Keyword(s):  
Partner Violence ◽  
Housing Affordability ◽  
Structural Racism ◽  
Census Tracts ◽  
Social Familiarity ◽  
Choropleth Maps ◽  
Economic Tradeoffs ◽  
Safety And Stability ◽  
Depth Interviews ◽  
Neighborhood Level

Survivors’ considerations for re-housing following intimate partner violence (IPV) are understudied despite likely neighborhood-level influences on women’s safety. We assess housing priorities and predictors of re-housing location among recent IPV survivors (n = 54) in Rapid Re-housing (RRH) in the Baltimore-Washington Metropolitan Area. Choropleth maps depict residential location relative to census tract characteristics (neighborhood deprivation index (NDI) and residential segregation) derived from American Community Survey data (2013–2017). Linear regression measured associations between women’s individual, economic, and social factors and NDI and segregation. In-depth interviews (n = 16) contextualize quantitative findings. Overall, survivors re-housed in significantly more deprived and racially segregated census tracts within their respective regions. In adjusted models, trouble securing housing (B = 0.74, 95% CI: 0.13, 1.34), comfortability with proximity to loved ones (B = 0.75, 95% CI: 0.02, 1.48), and being unsure (vs unlikely) about IPV risk (B = −0.76, 95% CI: −1.39, −0.14) were significantly associated with NDI. Economic dependence on an abusive partner (B = −0.31, 95% CI: −0.56, −0.06) predicted re-housing in segregated census tracts; occasional stress about housing affordability (B = 0.39, 95% CI: 0.04, 0.75) predicted re-housing in less segregated census tracts. Qualitative results contextualize economic (affordability), safety, and social (familiarity) re-housing considerations and process impacts (inspection delays). Structural racism, including discriminatory housing practices, intersect with gender, exacerbating challenges among survivors of severe IPV. This mixed-methods study further highlights the significant economic tradeoffs for safety and stability, where the prioritization of safety may exacerbate economic devastation for IPV survivors. Findings will inform programmatic policies for RRH practices among survivors.

scholarly journals Empirical Insights from a Study on Outlier Preserving Value Generalization in Animated Choropleth Maps

2021 ◽  
Vol 10 (4) ◽  
pp. 208
Author(s):  
Christoph Traun ◽  
Manuela Larissa Schreyer ◽  
Gudrun Wallentin
Keyword(s):  
Time Series ◽  
Empirical Research ◽  
Global Trends ◽  
First Order ◽  
Choropleth Maps ◽  
Temporal Generalization ◽  
Perceptual Limits ◽  
Local Outlier

Time series animation of choropleth maps easily exceeds our perceptual limits. In this empirical research, we investigate the effect of local outlier preserving value generalization of animated choropleth maps on the ability to detect general trends and local deviations thereof. Comparing generalization in space, in time, and in a combination of both dimensions, value smoothing based on a first order spatial neighborhood facilitated the detection of local outliers best, followed by the spatiotemporal and temporal generalization variants. We did not find any evidence that value generalization helps in detecting global trends.

Collection, Analysis, and Reporting of Kentucky Traffic Incident Management Performance

2021 ◽  
pp. 036119812110010
Author(s):  
Xu Zhang ◽  
Reginald R. Souleyrette ◽  
Eric Green ◽  
Teng Wang ◽  
Mei Chen ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Management Strategies ◽  
Incident Management ◽  
Vehicle Crashes ◽  
Clearance Time ◽  
Emergency Responders ◽  
Traffic Incident ◽  
Choropleth Maps ◽  
Traffic Incident Management ◽  
Secondary Crashes

Traffic incidents remain all too common. They negatively affect the safety of the traveling public and emergency responders and cause significant traffic delays. Congestion associated with incidents can instigate secondary crashes, exacerbating safety risks and economic costs. Traffic incident management (TIM) provides an effective approach for managing highway incidents and reducing their occurrence and impacts. The paper discusses the establishment and methods of calculation for five TIM performance measures that are used by the Kentucky Transportation Cabinet (KYTC) to improve incident response. The measures are: roadway clearance time, incident clearance time, secondary crashes, first responder vehicle crashes, and commercial motor vehicle crashes. Ongoing tracking and analysis of these metrics aid the KYTC in its efforts to comprehensively evaluate its TIM program and make continuous improvements. As part of this effort, a fully interactive TIM dashboard was developed using the Microsoft Power BI platform. Dashboard users can apply various spatial and temporal filters to identify trends at the state, district, county, and agency level. The dashboard also supports dynamic visualizations such as time-series plots and choropleth maps. With the TIM dashboard in place, KYTC personnel, as well as staff at other transportation agencies, can identify the strengths and weaknesses of their incident management strategies and revise practices accordingly.

scholarly journals Geo-Spatial Analysis of Population Density and Annual Income to Identify Large-Scale Socio-Demographic Disparities

2021 ◽  
Vol 10 (7) ◽  
pp. 432
Author(s):  
Nicolai Moos ◽  
Carsten Juergens ◽  
Andreas P. Redecker
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Methodological Approach ◽  
Spatial Relationship ◽  
Postal Code ◽  
Annual Income ◽  
Choropleth Maps ◽  
Clustering Approach ◽  
Relationship Of ◽  
Insight Into

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons.

scholarly journals Methodology for mapping the average transaction prices of residential premises using GIS

2016 ◽  
Vol 48 (4) ◽  
pp. 161-171 ◽  
Author(s):  
Martyna Sosnowska ◽  
Izabela Karsznia
Keyword(s):  
Real Estate ◽  
Open Data ◽  
Transaction Prices ◽  
Residential Properties ◽  
Choropleth Maps ◽  
Presentation Methods ◽  
Real Estate Prices ◽  
Gis Software ◽  
The Impact ◽  
Selection Of

Abstract Geographic information systems (GIS) and their tools support the process of real estate trading. Of key importance is the ability to visualise information about real estate in the form of maps of average real estate transaction prices. The following study presents a methodology for mapping average real estate transaction prices using GIS. The map development process comprised three main stages. In the first stage, the input data was processed and statistically analysed. Official data came from the Register of Real Estate Prices and Values, and open data from the National Register of Boundaries. The second stage involved the visualization of the data in the form of maps of average apartment prices using the cartographic methods of choropleth maps and diagrams. The commercial tool ArcMap 10.3 and the free Quantum GIS software were used in the design of the maps of average real estate transaction prices, to check the options for using these types of programs. As a result, eight maps were designed presenting the average transaction prices for residential properties in the Warsaw district of Ursynów in 2015. The final stage was the analysis of the designed maps. The influence of the selection of the reference units on the visualization content, and the impact of combining cartographic presentation methods on the complexity of the presentation of real estate information, were also analysed.

scholarly journals Patterns of Urban Violent Injury: A Spatio-Temporal Analysis

2021 ◽  
Author(s):  
Michael D. Cusimano ◽  
Sean P. Marshall ◽  
Claus Rinner ◽  
Depeng Jiang ◽  
Mary L. Chipman
Keyword(s):  
Social Deprivation ◽  
Temporal Analysis ◽  
Early Morning ◽  
Population Based ◽  
Homeless Shelters ◽  
Urban Centre ◽  
Violent Injury ◽  
Systems Software ◽  
Choropleth Maps ◽  
Spatio Temporal

Objectives: Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre. Methodology/Principal Findings: Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18-64) in Toronto, Canada, during 2002-2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a "nightlife" district. The locational pattern of patient residences remained unchanged during those times. Conclusions/Significance: Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. however, later at night, the injury location of highest density shifts to a "nightlife" district, whereas the residence locations of those most at risk of injury do not change.

scholarly journals The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts

2021 ◽  
Vol 8 ◽  
Author(s):  
Erin N. Biggs ◽  
Patrick M. Maloney ◽  
Ariane L. Rung ◽  
Edward S. Peters ◽  
William T. Robinson
Keyword(s):  
Population Density ◽  
Social Vulnerability ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Census Tracts ◽  
Control And Prevention ◽  
Choropleth Maps ◽  
The Relationship

Objective: To examine the association between the Centers for Disease Control and Prevention (CDC)'s Social Vulnerability Index (SVI) and COVID-19 incidence among Louisiana census tracts.Methods: An ecological study comparing the CDC SVI and census tract-level COVID-19 case counts was conducted. Choropleth maps were used to identify census tracts with high levels of both social vulnerability and COVID-19 incidence. Negative binomial regression with random intercepts was used to compare the relationship between overall CDC SVI percentile and its four sub-themes and COVID-19 incidence, adjusting for population density.Results: In a crude stratified analysis, all four CDC SVI sub-themes were significantly associated with COVID-19 incidence. Census tracts with higher levels of social vulnerability were associated with higher COVID-19 incidence after adjusting for population density (adjusted RR: 1.52, 95% CI: 1.41-1.65).Conclusions: The results of this study indicate that increased social vulnerability is linked with COVID-19 incidence. Additional resources should be allocated to areas of increased social disadvantage to reduce the incidence of COVID-19 in vulnerable populations.

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