Geographic Information Systems Network Analysis Research Articles

Assessment of Disparity in Accessing Railway Stations in Thailand: an Application Geographic Information System Network Analysis

Ensuring that people from all regions in a country can easily access railway stations is a crucial objective in the development of transportation and mobility systems and is essential for the convenient travel within the country. Furthermore, accurately assessing accessibility in disadvantaged areas is pivotal in designing and implementing development policies for equitable and sustainable transportation systems. Although various methods and tools are available for measuring accessibility, interpreting local-level data remains challenging. This study was conducted in Thailand, a country with severe accessibility disparities but undergoing considerable development. Therefore, the objective of this study was to evaluate accessibility disparities to analyze accessibility capabilities and inequality of railway stations. The objective of the study was to aid the development of inequality and railway services to cover all areas. The geographic information system methodology with network analysis tools was used to visualize and analyze spatial accessibility data and identify regional disparities. The results of this study indicate inequality in accessing railway services, which revealed that densely populated areas have superior access to railway stations compared with districts with a lower population density. Additionally, over 41% of the study area’s population resides more than half an hour away from access to a railway station. This study highlights regional inequality in accessing railway station services. Furthermore, strategies to alleviate this inequality are presented, and the findings will aid government agencies and railway planners in designing critical strategies or formulating policies for improving accessibility to rail transportation systems and reducing inequality in accessing railway services.

Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices

Due to rapid urbanization and population growth, identification and management of illegal dump sites has been a global challenge. In this study, satellite imagery and geographic information system were used to map potential illegal dump sites (PIDS). An original analytical approach was developed to identify PIDS using a set of remote sensing indices and vector files. The Network Analysis tool was used to prioritize PIDS considering driving distance between PIDS and neighboring populated points. A total of five variables (Landfills, LST, HCHO, Highways, and EVI) were considered. A study area in Saskatchewan, Canada, was selected, and the identified PIDS account for about 37.3% of the total area. Road network intensity and accessibility appear important to the occurrence of PIDS. Overall road densities in identified PIDS ranged from 0.098 to 0.251 km/km2. All five variables have observable effects on the occurrence of PIDS; however, LST and highways are recommended for future studies due to their higher membership grade and spatial sensitivity. The combination of multiple remote sensing indices and network analysis on PIDS prioritization is advantageous. The proposed PIDS mapping and prioritization method can be easily employed elsewhere.

Geographic access to lung cancer screening among eligible adults living in rural and urban environments in the United States.

Although recommended lung cancer screening with low-dose computed tomography scanning (LDCT) reduces mortality among high-risk adults, annual screening rates remain low. This study complements a previous nationwide assessment of access to lung cancer screening within 40 miles by evaluating differences in accessibility across rural and urban settings for the population aged 50 to 80years and a subset eligible population based on the 2021 US Preventive Services Task Force LDCT lung screening recommendations. Distances from population centers to screening facilities (American College of Radiology Lung Cancer Screening Registry) were calculated, and the number of individuals who had access within graduating distances, including 10, 20, 40, 50, and 100 miles, were estimated. Census tract results were aggregated to counties, and both geographies were classified with rural-urban schemas. Approximately 5% of the eligible population did not have access to lung cancer screening facilities within 40 miles; however, different patterns of accessibility were observed at different distances, between regions, and across rural-urban environments. Across all distances and geographies, there was a larger percentage of the population in rural geographies with no access. Although the rural population represented approximately 8% of the eligible population, the larger percentage of the rural population with no access was noteworthy and translated into a larger number of individuals with no access at longer distance thresholds (≥40 miles). Disparities in access should be examined as both percentages of the population and numbers of individuals with no access in order to tailor interventions to communities and increase access. Geospatial analysis at the census tract level is recommended to help to identify optimal focus areas and reach the most people. As annual lung cancer screening rates remain low, this study examines access to lung cancer screening nationwide and across rural and urban settings. A geographic information system network analysis of census tract-level populations is used to estimate access at different distances, including 10, 20, 40, 50, and 100 miles, and the results are aggregated to counties. Approximately 5% of the eligible population does not have access to screening facilities within 40 miles; however, different patterns of accessibility are observed at different distances, between regions, and across rural-urban environments. Across all distances and geographies, there is a larger percentage of the population in rural geographies with no access.

GIS-based volunteer cotton habitat prediction and plant-level detection with UAV remote sensing

Volunteer cotton plants germinate and grow at unwanted locations like transport routes and can serve as hosts for a harmful cotton pests called cotton boll weevils. The main objective of this study was to develop a geographic information system (GIS) framework to efficiently locate volunteer cotton plants in the cotton production regions in southern Texas, thus reducing time and economic cost for their removal. A GIS network analysis tool was applied to estimate the most likely routes for cotton transportation, and a GIS model was created to identify and visualize potential areas of volunteer cotton growth. The GIS model indicated that, of the 31 counties in southern Texas that may have habitat for volunteer cotton, Hidalgo, Cameron, Nueces, and San Patricio are the counties at the greatest risk. Moreover, a method based on unmanned aerial vehicle (UAV) remote sensing was proposed to detect the precise locations of volunteer cotton plants in potential areas for their subsequent removal. In this study, a UAV was used to scan limited samples of potential volunteer cotton growth areas identified with the GIS model. The results indicated that UAV remote sensing coupled with the proposed image analysis methods could accurately identify the precise locations of volunteer cotton and could potentially assist in the elimination of volunteer cotton along transport routes.

Driving Coverage of Charging Stations for Battery Electric Trucks Located at Truck Stop Facilities

Battery-powered electric trucks could soon be deployed on a large scale along long-haul routes on the U.S. trunk highway system. These vehicles have numerous advantages, including zero emissions, fuel savings, and lower maintenance costs, that make them attractive for motor carrier companies. However, the deployment of this technology depends on the development of a convenient network of fast-charging stations that can provide sufficient driving coverage along the Interstate highway system. The majority of existing fast-charging stations in rural areas currently are not adequate for the movement of large trucks. A potential solution is to install fast-charging stations at the vast network of rural truck stops. Truck stops are specifically designed for the movement of trucks and are already located on the routes with the highest truck demand. The main objective of this study was to develop a methodology for identifying the driving coverage provided if fast-charging stations were located at truck stop facilities along the U.S. Interstate highway system. The contiguous U.S.A. was taken as the study area. The study approach was based on a geographic information system network analysis with a specific focus on the service area. It was found that truck stop facilities could potentially provide 99.5% driving coverage for electric trucks on the Interstate highway system. This makes them opportune locations for future fast-charging stations. These findings may assist transportation planners and operators in defining strategies required for planning the deployment of long-haul electric trucks on the U.S. highway system.

Integrating GIS Accessibility and Location-Allocation Models with Multicriteria Decision Analysis for Evaluating Quality of Life in Buraidah City, KSA

The present study was aimed at evaluating the quality of life in the districts of Buraidah city in the Kingdom of Saudi Arabia as part of the Kingdom’s Vision 2030, based on provided services in terms of distance and time parameters. This was achieved by integrating Geographic Information System (GIS)-based network analysis and multicriteria decision analysis (MCDA) techniques. The service area analysis technique of the GIS Network Analysis tools was applied to the available services in the districts of Buraidah city. Twelve services were investigated with regard to their coverage within 5, 10, and 15 minutes of travel time: universities, high schools, middle schools, elementary schools, hospitals, health centers, ambulance facilities, government services, religious services, security services, sports services, and recreational services. GIS-based multicriteria decision analysis (GIS-MCDA) was implemented in the study to obtain a spatial suitability map of the standard of living quality in the various districts in Buraidah city. The analytic hierarchy process (AHP) technique was used to determine the criteria weights. The location-allocation model was used in the study as well for suggestions of new service locations to improve the spatial distribution of services and enhance the quality of life in the districts. The results of the final suitability map to determine districts with the best standard of living according to the provided services show that the living standards in the city are very good, with very high and high levels in around 51 districts, representing 72.9% (449,235 people), and about 19 districts with moderate, low, and very low levels, representing 27.1% (56,765 people). Narrowing the quality of life gap and improving spatial planning requires correcting the current deficiency in services, which is estimated in this study to be 16 services: one high school, one elementary school, one middle school, two universities, one sports service, two security services, two courts, two hospitals, one health center, one park, and two ambulance facilities.

GIS for planning a sustainable and inclusive community: multi-criteria suitability analysis for siting low-income housing in a sustainable community and suitable neighborhood in Buffalo Metropolitan Area, New York

This study utilized Geographic Information System (GIS) as a tool for sustainable community planning which incorporateslow-income communities into current sustainable neighborhoods. GIS suitability analysis aimed at finding suitable and sustainable neighborhoods for locating subsidized housing projects for low-income families through the Low-Income Housing Tax Credit (LIHTC) program in the Buffalo Metropolitan Area (BMA), New York. LIHTC projects allocate 30% of their rental units for low-income families. They must be located in sustainable neighborhoods to ensure economically and socially sustainable livesfor low-income inhabitants. Data was collected from various New York State government agencies and used as input for several raster-based criteria maps using GIS network analysis, raster cost-distance analysis, Kernel density analysis, raster-based local statistics, and surface analysis.The criteria of sustainable neighborhoodsusing GIS multi-criteria analysis (MCA) were grouped into five factors, namely public amenities, economic viability, population growth, property conditions, and environmental factors. A final suitability map was created by multiplying the derived raster maps with their respective weight resulting from the Analytical Hierarchical Process (AHP). The study found several locations in suburban areas of the BMA that meet the criteria and canbe usedby the Buffalo Metropolitan Housing Authority (BMHA) to site the LIHTC housing.

Relationship between accessibility and resources to treat acute ischemic stroke. Hokkaido, Japan: Analysis of inequality and coverage using geographic information systems

ObjectivesThis study aimed to clarify the relationship between the institution and resident with respect to accessibility to acute ischemic stroke (AIS) treatment in Hokkaido and to propose new methodology monitoring for accessibility to healthcare resources. MethodsThis study involves the use of geographic information system (GIS) network analysis. We established hospital/clinic with one of the following conditions as resources for AIS treatment: (1) medical facility practicing AIS treatment, (2) having computed tomography (CT) equipment, (3) having angiography equipment, and (4) having AIS specialists (neurosurgeons). We evaluated the coverage of population resources using transport time between ambulance departure and arrival at the healthcare facility. Furthermore, we compared the population coverage rate using available resources and calculated a Gini coefficient to analyze its relation with inequality. Empirical analysis was performed, and public database for data collection was utilized. We calculated the rate of population coverage with a transport time within 10 min as an indicator of accessibility to medical resources by GIS. ResultsThe Gini coefficients of practicable facilities, CT, angiography, and neurosurgeons are 0.35, 0.16, 0.18, and 0.30, respectively. The inequality of accessibility differs depending on the resources, and Gini coefficients indicate that hospital/clinic and neurosurgeons were considered to have higher allocation inequalities than CT and angiography. ConclusionsCombining Gini coefficient and GIS network analysis in accessibility can be useful in quantifying and monitoring variation by region. We propose this combination as a new method for helping the government to make evidence-based healthcare planning.

Equity Analysis of Proactively- vs. Reactively-Identified Traffic Safety Issues

Traffic safety issues often impede bicyclist and pedestrian trips, preventing potential users from realizing the benefits of active transport. Traditional active transportation safety analyses, however, take a reactive approach to traffic safety, only accounting for people currently walking or bicycling by analyzing crashes, injuries, and fatalities. This begs the question: which populations are most affected by traffic safety issues neglected by traditional crash analyses? To answer this, we developed a tool to proactively measure perceived traffic safety issues. We focused on child pedestrian and bicycle trips to and from schools in Denver, Colorado by measuring the number of children that would encounter roads perceived as unsafe. We converted these perceptions into barriers in a geographic information system network analysis to estimate trip suppression and used that as a proactive indicator of traffic safety. We finally examined—reactively and proactively—the socio-demographics of those affected via linear regression models and bivariate choropleth mapping. Results of both analyses suggest that negative impacts are borne disproportionately by low-income, low-education, Hispanic, and black neighborhoods. Proactive analyses results identified perceived safety issues in north and northeast Denver neighborhoods neglected by reactive analyses results. Findings suggest the inequitable distribution of traffic safety issues identified in past crash-based literature is graver than conventional reactive analysis would lead one to believe. By incorporating the proactive tool into traditional traffic safety analyses, we hope to better define the places and people that could most benefit from traffic safety improvements, thereby more effectively facilitating the benefits of walking and biking.

Logistics of air medical transport: When and where does helicopter transport reduce prehospital time for trauma?

Trauma is a time sensitive disease. Helicopter emergency medical services (HEMS) have shown benefit over ground emergency medical services (GEMS), which may be related to reduced prehospital time. The distance at which this time benefit emerges depends on many factors that can vary across regions. Our objective was to determine the threshold distance at which HEMS has shorter prehospital time than GEMS under different conditions. Patients in the Pennsylvania trauma registry 2000 to 2013 were included. Distance between zip centroid and trauma center was calculated using straight-line distance for HEMS and driving distance from geographic information systems network analysis for GEMS. Contrast margins from linear regression identified the threshold distance at which HEMS had a significantly lower prehospital time than GEMS, indicated by nonoverlapping 95% confidence intervals. The effect of peak traffic times and adverse weather on the threshold distance was evaluated. Geographic effects across EMS regions were also evaluated. A total of 144,741 patients were included with 19% transported by HEMS. Overall, HEMS became faster than GEMS at 7.7 miles from the trauma center (p = 0.043). Helicopter emergency medical services became faster at 6.5 miles during peak traffic (p = 0.025) compared with 7.9 miles during off-peak traffic (p = 0.048). Adverse weather increased the distance at which HEMS was faster to 17.1 miles (p = 0.046) from 7.3 miles in clear weather (p = 0.036). Significant variation occurred across EMS regions, with threshold distances ranging from 5.4 to 35.3 miles. There was an inverse but non-significant relationship between urban population and threshold distance across EMS regions (ρ, -0.351, p = 0.28). This is the first study to demonstrate that traffic, weather, and geographic region significantly impact the threshold distance at which HEMS are faster than GEMS. Helicopter emergency medical services was faster at shorter distances during peak traffic while adverse weather increased this distance. The threshold distance varied widely across geographic region. These factors must be considered to guide appropriate HEMS triage protocols. Therapeutic, level IV.

A practical approach to constructing hierarchical networks for urban hazard mitigation planning using GIS: The case of Futian, Shenzhen

Urban disasters can cause extensive losses of life and property, but these losses can be reduced by systemic and spatial planning for urban hazard mitigation (UHM). The emergency facilities are composed of emergency shelters (ESs), evacuation routs (ERs), and emergency shelter zones (ESZs) and these components play an important role in UHM. Constructing a hierarchical network is an effective approach to layout the emergency facilities. This paper proposes a conceptual framework to construct a hierarchical UHM network based on Central Place Theory and suggests a practical approach using geographic information systems (GIS). In the proposed method, the configuration of ESs considers the population distribution, security, fairness, and accessibility using GIS to meet the survival needs of refugees, provide required materials and coordinate rescue and relief efforts. The minimal cost path linking an ES to the higher level ES is calculated to be the ER for material transport and transferring refugees via GIS network analysis function. The ESZs of the ESs at each level can be partitioned using a bottom-up algorithm based on the relationships among hierarchical ERs, which can support policy and strategy development for emergency administrative management. This paper provides a practical approach to constructing a hierarchical UHM network for earthquakes that can reduce disaster losses and enhance the efficiency of rescue and relief efforts to decrease urban vulnerability.

Enrolling in the Closest School or Not? Implications of School Choice Decisions for Active Transport to School

Absence of requirements to attend a local school combined with social factors driving school choice make distance to school less important in school choice decisions. However, school choice decisions have implications not only for education but also for public health, transport and environmental sustainability. This study examined correlates of adolescents’ enrolment in the closest school in the absence of school zoning policies and its implications for active transport to school. Adolescents (n=797; age: 15.2±1.4 years; 51.4% boys) from six non-integrated public secondary schools without school zoning in Dunedin, New Zealand, completed an online survey including items on school choice. Distance to school was calculated using Geographic Information Systems network analysis. Data were analysed using descriptive statistics, independent samples t-tests, Chi-square tests and mixed effects binary logistic regression analysis. Half of adolescents (51.3%) enrolled in the closest school (range across schools: 28.3% to 81.6%). These adolescents had three times higher rates of walking to school (52.3% vs. 14.4%), five times higher rates active transport to school (46.5% vs. 8.8%) and >40% lower rates of using only motorized transport to school (40.3% vs. 68.8%) compared to those who did not enrol in the closest school (all p<0.05). Among adolescents who enrolled in the closest school, a greater proportion reported choosing their school because of its proximity to home (enrolled versus did not enrol in the closest school: 67.5% vs. 14.2%) and existing social connections at school (siblings attended/enrolled: 35.6% vs. 26.5%; parents/family members attended in the past: 28.4% vs. 19.6%; friends enrolled: 55.5% vs. 51.5%) compared to their counterparts (all p<0.05). In a multivariate analysis, positive correlates of enrolment in the closest school were attending a co-educational school [4.55 (2.82-7.32)] and choosing school because of its proximity to home [2.29 (1.97-2.66)] whereas negative correlates were distance to school [OR (95%CI): 0.87 (0.83-0.91)] and negative comments from students from the closest school [0.68 (0.47-0.98]. In the absence of school zoning, shorter distance to school, choosing school because of its proximity to home, co-educational school status, and absence of negative peer feedback were associated with adolescents’ enrolment in the closest secondary school. Policies that incentivise enrolment in the closest school could increase the rates of active transport and may contribute to addressing physical inactivity among adolescents, traffic congestion and sustainability concerns. Other consequences of such policies including implications for house pricing and reinforcing class/wealth structures also need to be considered.

Enrolling in the Closest School or Not? Implications of school choice decisions for active transport to school

Abstract Background Absence of requirements to attend a local school combined with social factors driving school choice make distance to school less important in school choice decisions. This study examined correlates of adolescents’ enrolment in the closest school in the absence of school zoning policies. Methods Adolescents (n=797; age: 15.2±1.4 years; 51.4% boys) from six non-integrated (regular) public secondary schools without school zoning in Dunedin, New Zealand, completed an online survey about school choice. Distance to school was calculated using Geographic Information Systems network analysis. Data were analysed using t-tests, Chi-square tests and mixed effects binary logistic regressions. Results Overall, 51.3% of adolescents enrolled in the closest school (range across schools: 28.3% to 81.6%). These adolescents had five times higher rates of active transport (46.5% vs. 8.8%) and lower rates of motorised transport to school (40.3% vs. 68.8%) compared to their counterparts (all p Conclusions In the absence of school zoning, shorter distance to school, importance of school's proximity to home, co-educational school status, and absence of negative peer feedback were associated with adolescents’ enrolment in the closest secondary school. School choice decisions have implications not only for education but also for public health, transport and environmental sustainability. A multi-sector approach and extensive collaboration between educational policy makers, urban designers, health promoters, and community groups is required to reduce the tensions between parental and students’ school choice expectations of getting the best education possible and the goal of increasing rates of active transport to school.

Adolescents' perceptions of cycling versus walking to school: Understanding the New Zealand context

Cycling to school is less common than walking in many developed countries. This cross-sectional study compared correlates and perceptions of walking versus cycling to school in Dunedin adolescents living ≤4 km from school. Adolescents (n=764; 44.6% males; 15.2±1.4 years) from 12 secondary schools completed an online survey about perceptions of walking and cycling to school. Distance to school was calculated using Geographic Information Systems network analysis. Overall, 50.8% of adolescents walked and 2.1% cycled to school, 44.1% liked cycling for recreation and 58.8% were capable/able/confident to cycle to school. Adolescents expressed more positive experiential (walking: 45.9%; cycling: 34.9%) and instrumental beliefs (walking: 74.2%; cycling: 59.2%) towards walking versus cycling to school (p<0.001). Compared to walking, adolescents reported that cycling to school was perceived as less safe by themselves (cycling vs walking; 61.3% vs 89.8%) and their parents (71.4% vs 88.6%) and was less encouraged by their parents (23.0% vs 67.0%), peers (18.8% vs 48.4%) and schools (19.5% vs 30.8%) (all p<0.001). The route to school had fewer cycle paths compared to footpaths (37.2% vs 91.0%; p<0.001). Cycle friendly uniforms (41.4%), safer bicycle storage at school (40.1%), slower traffic (36.4%), bus bicycle racks (26.2%) and bicycle ownership (32.7%) would encourage cycling to school. Compared to walking, cycling to school among Dunedin adolescents was less common, perceived as less safe and had less social and infrastructure support. Future interventions should focus on creating supportive physical and social environments, and improving road safety for cyclists in New Zealand.

A novel methodology to characterize interfacility transfer strategies in a trauma transfer network

More than half of severely injured patients are initially transported from the scene of injury to nontrauma centers (NTCs), with many requiring subsequent transfer to trauma center (TC) care. Definitive care in the setting of severe injury is time sensitive. However, transferring severely injured patients from an NTC is a complex process often fraught with delays. Selection of the receiving TC and the mode of interfacility transport both strongly influence total transfer time and are highly amenable to quality improvement initiatives. We analyzed transfer strategies, defined as the pairing of a destination and mode of transport (land vs. rotary wing vs. fixed wing), for severely injured adult patients. Existing transfer strategies at each NTC were derived from trauma registry data. Geographic Information Systems network analysis was used to identify the strategy that minimized transfer times the most as well as alternate strategies (+15 or +30 minutes) for each NTC. Transfer network efficiency was characterized based on optimality and stability. We identified 7,702 severely injured adult patients transferred from 146 NTCs to 9 TCs. Nontrauma centers transferred severely injured patients to a median of 3 (interquartile range, 1-4) different TCs and utilized a median of 4 (interquartile range, 2-6) different transfer strategies. After allowing for the use of alternate transfer strategies, 73.1% of severely injured patients were transported using optimal/alternate strategies, and only 40.4% of NTCs transferred more than 90% of patients using an optimal/alternate transfer strategy. Three quarters (75.5%) of transfers occurred between NTCs and their most common receiving TC. More than a quarter of patients with severe traumatic injuries undergoing interfacility transport to a TC in Ontario are consistently transported using a nonoptimal combination of destination and mode of transport. Our novel analytic approach can be easily adapted to different system configurations and provides actionable data that can be provided to NTCs and other stakeholders. Therapeutic study, level IV.

Baltimore's Mass-Transit Modification: Exploring the Relationship Between Commute Time and Local Population Density

ABSTRACTThe concentric zone model is one of the earliest models to explain how a city will grow based on its urban social structures. This model assumes an isotopic landscape, thus city expansion can grow in every direction, with some emphasis on extending social structures and the expense of commute times. This study seeks to understand if the presence of mass-transit routes in the city of Baltimore has modified the rounded shape of the concentric zone model and population distribution, as urban expansion has continued. To accomplish this, we explored a relationship between population density and travel-time-to-center (TTC). The expenditure in time a commuter must face to reach the urban center was calculated based on the availability of automobile transit routes using a geographic information system network analysis. We calculated a correlation coefficient between the variables so that the relationship could be explored. Results suggest a moderate negative relationship between TTC and population density in Baltimore, supporting the argument that mass-transit routes are one of the key players in the modification of the urban population distribution. This new variable can be incorporated into future studies to understand how the addition of mass-transit routes will cause a reaction in population distribution of an urban zone.

Rural-urban difference in female breast cancer diagnosis in Missouri

The stage at cancer diagnosis has a tremendous impact on type of treatment, recovery and survival. In most cases the earlier the cancer is detected and treated the higher the survival rate for the patient. The purpose of this study was to examine the impact of spatial access to healthcare services on late detection of female breast cancer diagnosis in Missouri, taking into account access and distance to the nearest mammography center and/or hospital. This was a cross-sectional retrospective study of female breast cancer diagnosis in different geographic regions of Missouri. The sample was restricted to Missouri women diagnosed with breast cancer, whose cases had been reported to the Missouri Cancer Registry and Research Center between 2003 and 2008. A geographic information system network analysis was used to calculate distance traveled by road from the centroid of each county to the nearest healthcare facility. A total of 28 536 cases of female breast cancers were reported to the Missouri Cancer Registry and Research Center between 2003 and 2008. Of these 25 743 (90.2%) were Caucasian (white) while 2793 (9.8%) were African-American (black). Analysis showed that the proportion of African-Americans with late-stage detection exceeded that of whites in almost all rural and urban locations. From 2003 to 2005 more than 50% of all late-stage diagnoses of African-American women occurred in metropolitan (metro) medium (55.6%) and completely rural counties (66.7%). Other locations recorded a smaller number of late-stage detection among African-American women: metro small (42.3%), urban large (47.4%) and urban small (44.9%) counties. Most of the late-stage diagnoses of white women were reported in urban small (32.2%) and rural (32.3%) counties. Between 2006 and 2008, again, the proportion of late-stage diagnoses among black women was the highest. Access to hospitals is fairly distributed among all counties. Women from disadvantaged non-metro areas have the same level of access to hospitals as those in metro areas within a travel time of 15 to 30 minutes. However, although there are almost 180 mammography screening centers across the state, access to these services is not evenly distributed. A network analysis of the closest facility of the type showed that women living in 19 non-metro rural counties have to travel more than 45 minutes one way by car for mammography services. Thirteen of the 19 counties are classified as completely rural. Women with breast cancer living in areas with limited access to healthcare services are more likely to have been diagnosed with late-stage breast cancer.

Emergency Management: Building an O-D Ranking Model Using GIS Network Analysis

Enormous natural disasters due to climate change are frequently observed all around the world. Unexpected catastrophes become a huge threat for community residents. Activating an evacuation order in a large-scale incident such as a wildfire depends on how information can be acquired in real time. Geographic Information Systems (GIS) provide highly analyzed map products to decision makers. Under real wildfire circumstances, GIS map products are very effective materials that include collected and analyzed information and results visualized to enable interpretation of the situation in real time. The challenge of this study is the construction of an optimal route selection method using a GIS network for issuing evacuation-order decisions. The most effective evacuation routes were defined by networking analysis using 2007 San Diego wildfire datasets. The shortest evacuation routes were calculated between affected points and shelters and chosen automatically by an O-D (Origin - Destination) ranking model. Considerable roads and land features and other environmental factors when the closest facilities and routes are selected, selection criteria and approach methods can be suggested for future events. Using this model, accessible routes can be chosen any time and any place, even during an ongoing evacuation. Decision makers should therefore provide proper evacuation orders to rescue crews using this O-D ranking model.

Using GIS to analyze the role of barriers and facilitators to walking in children's travel to school

Extensive research in response to the decline of walkability in the past 30 years has identified a multitude of factors that affect children's ability to work or bicycle to school. Among others, urban form – the layout and configurations of urban blocks and street networks - can constraint or facilitate pedestrian travel to a destination such as a school. Although contemporary research uses approximate measures of walkability such as straight-line distance between origin and destination, or even measures of distances along roadway networks, the presence of physical barriers and facilitators to walking calls for a more accurate method for assessing walkability as a function of distance dictated by constraints of urban form. Modern technologies like Geographic Information Systems (GIS) offer capabilities to enable calculation of such measures. This article presents a GIS methodology that analyzes children travel to school as a function of distance along the network and the role of barriers and facilitators that impact the path and the accessibility to school. The study is conducted in 32 randomly selected elementary schools in four Florida counties. Three pedestrian sheds of 1/2 mile (10 minutes walk) are generated around each school based respectively on (a) straight-line distance, (b) roadway network distance and (c) pedestrian network distance adjusted for barriers such as major roads, and lack of sidewalks and facilitators such as pedestrian paths, crossing guards and rear entrances to school. The pedestrian sheds are compared based on two measures: (1) pedestrian route directness (PRD) – an index that measures urban form permeability and connectivity and (2) the student count in each shed – a measure that indicates how effectively the pedestrian shed captures potential students along these networks. Results show that the pedestrian shed decreases in size upon considering network distance over straight-line distance, and readjusts upon consideration of barriers and facilitators. PRD values decrease as the pedestrian shed is adjusted which indicates shorter, more direct paths to schools are available. Findings suggest that inclusion of barriers and facilitators when measuring distance along the network offers a more realistic version of the true distance a child could potentially walk to school. The study found that barriers and facilitators play critical roles in how the urban landscape can be traversed and, in turn, greatly affect walkability and accessibility to school. Barriers can reduce walkability and accessibility to school whereas facilitators can increase the permeability and connectivity of pedestrian networks. In addition to improving walkability measurement methods by enhancing the GIS network analysis to include barriers and facilitators, this research has broader implications for the study of walkability as it relates to urban form. The findings can be used by local governments to develop better policies to promote close coordination of school siting with residential development and transportation. These findings can also inform the urban design of the layout and configuration of street networks, urban blocks and placement of buildings to support safe pedestrian circulation with good permeability connectivity and accessibility throughout the neighborhood. Especially, findings from this study emphasize the importance of designing for connected pedestrian paths that minimize barriers and maximize facilitators.

Measuring the food environment using geographical information systems: a methodological review

Through a literature review, we investigated the geographic information systems (GIS) methods used to define the food environment and the types of spatial measurements they generate. Review study. Searches were conducted in health science databases, including Medline/Pubmed, PsycINFO, Francis and GeoBase. We included studies using GIS-based measures of the food environment published up to 1 June 2008. Twenty-nine papers were included. Two different spatial approaches were identified. The density approach quantifies the availability of food outlets using the buffer method, kernel density estimation or spatial clustering. The proximity approach assesses the distance to food outlets by measuring distances or travel times. GIS network analysis tools enable the modelling of travel time between referent addresses (home) and food outlets for a given transportation network and mode, and the assumption of travel routing behaviours. Numerous studies combined both approaches to compare food outlet spatial accessibility between different types of neighbourhoods or to investigate relationships between characteristics of the food environment and individual food behaviour. GIS methods provide new approaches for assessing the food environment by modelling spatial accessibility to food outlets. On the basis of the available literature, it appears that only some GIS methods have been used, while other GIS methods combining availability and proximity, such as spatial interaction models, have not yet been applied to this field. Future research would also benefit from a combination of GIS methods with survey approaches to describe both spatial and social food outlet accessibility as important determinants of individual food behaviours.