Analysis of Traffic Collisions in Dublin Using GIS Based System

This study aims to analyse traffic collisions in the Greater Dublin Region between the period 2006-2012, using GIS to identify hotspots and examine the relationship between collisions and a range of contributory factors including vehicular speeds, traffic volume, road curvature, road category and distance from intersection that could enable prediction of traffic collisions. To this end, Road Safety Authority (RSA) collision data for Dublin Region geocoded as point events, road profiles, traffic flow characteristics on which these occur are spatially merged using ArcGIS and FME software to establish if a significant relationship exists between collision frequencies on road links and the specific link characteristics and traffic flow characteristics. The road network has been divided into uniform segments and the collision frequencies on each of these noted. Traffic collisions are rare and random events and often a major proportion of segments would have no instance of collisions, thus following a Negative Binomial distribution. The outputs from GIS exercise are tested through SPSS software using Negative Binomial distribution for modelling the relationship between different variables. This paper comes at a significant time where efforts are being made to improve the safety of roads within the European Union [1]. Every year, road collisions cause human fatalities together with huge financial loss which can be significantly reduced by improving road safety through the enforcement of traffic laws and road user compliance. By identifying the cause effect relationship and the spatial locations most prone to collisions, prioritized regulatory and safety interventions can be put in place to reduce the collisions on the roads

Analysis of Traffic Collisions in Dublin Using GIS Based System

This study aims to analyse traffic collisions in the Greater Dublin Region between the period 2006-2012, using GIS to identify hotspots and examine the relationship between collisions and a range of contributory factors including vehicular speeds, traffic volume, road curvature, road category and distance from intersection that could enable prediction of traffic collisions. To this end, Road Safety Authority (RSA) collision data for Dublin Region geocoded as point events, road profiles, traffic flow characteristics on which these occur are spatially merged using ArcGIS and FME software to establish if a significant relationship exists between collision frequencies on road links and the specific link characteristics and traffic flow characteristics. The road network has been divided into uniform segments and the collision frequencies on each of these noted. Traffic collisions are rare and random events and often a major proportion of segments would have no instance of collisions, thus following a Negative Binomial distribution. The outputs from GIS exercise are tested through SPSS software using Negative Binomial distribution for modelling the relationship between different variables. This paper comes at a significant time where efforts are being made to improve the safety of roads within the European Union [1]. Every year, road collisions cause human fatalities together with huge financial loss which can be significantly reduced by improving road safety through the enforcement of traffic laws and road user compliance. By identifying the cause effect relationship and the spatial locations most prone to collisions, prioritized regulatory and safety interventions can be put in place to reduce the collisions on the roads

A field GIS solution to Derelict Sites and Dangerous Structures Management

The subjective nature of the definitions and lack of guidance under the Derelict Sites Act 1990 and the Local Government Sanitary Services Act 1964 (Ireland) have led to inconsistent applications of the Acts and a reluctance to enforce. Dereliction has been a blight on the scenic beauty and attractiveness of town and countryside in Ireland, taking away from their appeal to inhabitants, investors and tourists. The Derelict Sites Act 1990 was introduced to empower local authorities in the remediation of problem sites. Part 8 of the Act requires that Local Authorities keep a register of derelict sites. The register is used to apply a levy on lands and to encourage owners to remediate sites. Part 10 of the Act requires that Local Authorities take reasonable measures to ensure that sites in their functional area does not become or continue to be Derelict. Dangerous structures pose a problem to local authorities and many sites initially start out as Derelict Sites become dangerous over time posing a risk to property and persons. Local Authorities are liable for the safety of public areas and steps must be taken to ensure that they are made safe promptly. A recent amalgamation of North and South Tipperary County Councils have highlighted problems with the reporting and recording of Derelict Sites and Dangerous Structures due to problems interpreting the definition of what is derelict and what is dangerous when sites are assessed by different professionals. The lack of uniform standards for site assessment can lead to problems with the management of sites, they are difficult to compare and rank for prioritising sites for future action and remediation. Comprehensive research into the area of dereliction and dangerous structures was undertaken and set of criteria produced to identify what is ‘Derelict’ and what is ‘Dangerous’ based on a critical combination of site indicators, group decisions and geographical data. It is possible to quantify dereliction and danger by using a web and smartphone application and Feature Manipulation Engine (FME) software. The generation of standardized sites scores from the data input using the smartphone app combined with weighted thematic maps in a GIS environment allow problem sites to be ranked in order of priority for remediation works. A GIS-based web application offers an effective solution to the above problem by removing the subjectivity from the definition of derelict sites and dangerous structure

OS-WALK-EU: An open-source tool to assess health-promoting residential walkability of European city structures

Introduction This paper introduces OS-WALK-EU, a new open-source walkability assessment tool developed specifically for urban neighbourhoods and using open-source spatial data. A free and open-source tool, OS-WALK-EU is accessible to the general public. It uses open data available worldwide and free online services to compute accessibility, while at the same time allowing users to integrate local datasets if available. Based on a review of existing measurement concepts, the paper adopts dimensions of walkability that were tested in European city environments and explains their conceptualization for software development. We invite the research community to collaboratively test, adopt and use the tool as part of the increasing need to monitor walkability as part of health-promoting urban development. Methods Tool development is based on spatial analysis methods to compute indicators for five dimensions of walkability: residential density, weighted proximities to amenities, pedestrian radius of activity, share of green and blue infrastructure, and slope. Sample uses in the cities of Dublin, Düsseldorf and Lisbon test the validity of input data and results, including scenarios for target groups like older people. Results Overall, application of the tool in Dublin, Düsseldorf and Lisbon shows conclusive results that conform to local knowledge. Shortcomings can be attributed to deficiencies in open source input data. Local administrative data, if available, is suitable to improve results. Conclusions OS-WALK-EU is the first software tool that allows free and open walkability assessments with pedestrian routing capacities for ‘proximity to facilities’ calculations. Large scale implementation for 33 German city regions in an online application shows the value of comparative assessments of walkable neighbourhoods between urban and suburban neighbourhoods. Such assessments are important to monitor progress in a mobility transition towards improved walkability and public health

Analysis of Traffic Collisions in Dublin Using GIS Based System

This study aims to analyse traffic collisions in the Greater Dublin Region between the period 2006-2012, using GIS to identify hotspots and examine the relationship between collisions and a range of contributory factors including vehicular speeds, traffic volume, road curvature, road category and distance from intersection that could enable prediction of traffic collisions. To this end, Road Safety Authority (RSA) collision data for Dublin Region geocoded as point events, road profiles, traffic flow characteristics on which these occur are spatially merged using ArcGIS and FME software to establish if a significant relationship exists between collision frequencies on road links and the specific link characteristics and traffic flow characteristics. The road network has been divided into uniform segments and the collision frequencies on each of these noted. Traffic collisions are rare and random events and often a major proportion of segments would have no instance of collisions, thus following a Negative Binomial distribution. The outputs from GIS exercise are tested through SPSS software using Negative Binomial distribution for modelling the relationship between different variables. This paper comes at a significant time where efforts are being made to improve the safety of roads within the European Union [1]. Every year, road collisions cause human fatalities together with huge financial loss which can be significantly reduced by improving road safety through the enforcement of traffic laws and road user compliance. By identifying the cause effect relationship and the spatial locations most prone to collisions, prioritized regulatory and safety interventions can be put in place to reduce the collisions on the roads