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• This paper investigates the correlation between pedestrian crashes and sidewalk gaps within the Central Florida region. • The presence of sidewalk is one of the main factors that have significant impact on the expected number of pedestrian crashes along a roadway segment. • The number of crashes increases with the increase in the gap length where shorter segments less than 2 miles in length with no sidewalks had no crashes. • The likelihood of a pedestrian crash along roadways with no sidewalk is 1.67 times greater than the likelihood of a crash with the presence of a sidewalk. • The likelihood of a pedestrian crash per mile along roadways with no sidewalk is 3 times greater than the likelihood of a crash per mile with the presence of a sidewalk. In recent years, pedestrian safety has emerged to be of major concern to selected States in the US and at the national level. With the transition to the mobility of people, pedestrian safety has become more prevalent for governmental agencies to address and prioritize for strategic implementation. It was crucial to address the pedestrian-vehicular conflict within Florida as it was reported as having the highest four pedestrian incident locations in the country. Many pedestrian sidewalks in Florida are not continuous and there is a concern among planners and engineers in the Florida Department of Transportation (FDOT) that these gaps constitute discontinuity of flow and are potentially posing threats to pedestrian safety. This paper investigates the correlation between pedestrian safety and sidewalk gaps within the Central Florida region. A sidewalk gap is defined as a length of a roadway segment with missing or absent sidewalk between existing sidewalks (before and after) along the same segment. "Missing" sidewalks are locations where the sidewalk is not only absent, but there is a desire to have one constructed or it would be used if it were constructed. The missing sidewalk can be on one side of the road or both sides. A wide array of Geographic Information Systems (GIS) information associated with the sidewalk gaps and the safety data were secured by FDOT. The data included all the Roadway Characteristics Inventory (RCI) within the district. Crash data combined with other geometric design data, traffic data, and census data were used to develop a statistical model. The results showed that presence of sidewalk along roadway segments is one of the main factors that have significant impact on the expected number of pedestrian crashes at a specific location. Other factors included daily traffic volumes, roadway category, specifically along urban two-way divided and undivided arterials with four to six lanes as well as the population within half-mile radius surrounding the crash location. The model results revealed that the Incident Risk Ratio (IRR) of a pedestrian crash along roadways with no sidewalk is 1.67 times greater than the likelihood of a crash with the presence of a sidewalk at 95% Confidence Interval (C.I.). The analysis also concluded that the likelihood of a pedestrian crash per mile along roadways with no sidewalk is three times greater than the likelihood of a crash per mile with the presence of a sidewalk. [ABSTRACT FROM AUTHOR]

Abstract Over the years, as the roadway networks have been developing gradually to improve transportation accessibility to various facilities, the probability of traffic crash occurrences has also increased consequently. With an increasing transportation demand, the traffic safety needs to be improved in order to reduce the crash rates and the exposure of the population to crash-prone regions. This paper aims to conduct a spatiotemporal analysis to quantify the exposure of population to crash-prone locations focusing on different age groups, and to statistically analyze the decision-making process for possible improvement. For this purpose, first, the crash-prone locations for different population age groups and various time intervals of a day were identified by using a geographic information system (GIS) hotspot analysis. This was followed by an Origin-Destination (OD) analysis applied on a case study in Tampa Bay region (Florida, District 7) to calculate the roadway network-based travel times between census blocks centroids (origins) and crash hotspot locations (destinations) along the least-cost roadways. Later, the results were utilized in an exceedance probability analysis to simplify the decision-making process for improvement. The results showed that the time-based analysis provides more accurate and detailed information than the distance-based analysis. The Weighted Hotspot Exposure Measure parameter introduced for statistical analysis showed that the senior age group (over 65 years old) are more exposed to the risk of being injured in a crash compared to other age groups. Highlights • Time-based analyses created more accurate results than distance-based analyses. • The risk of crash injury varied substantially across different age groups. • Minors were the least exposed age group to the risk of crash injury. • There is a need to improve the safety of the Seniors in District 7, Florida. [ABSTRACT FROM AUTHOR]

Sinkhole is one of major geohazards in karst area where soluble carbonate bedrock is underlain by cover soils (e.g., sandy or clayey soils) and active groundwater circulation is present. Groundwater recharge easily erode the overburden soils away into cavities in the bedrock, and ultimately structural collapse in ground. The induced ground collapse/subsidence may pose a great threat to human safety, environment, and buildings and infrastructure. The goal of this study is to develop a method/tool to spatially assess the possibility of sinkhole occurrence. The paper presents two main taks: (1) development of a probabilistic spatial prediction model of sinkhole susceptibility and (2) a geographical information system (GIS)-based regional-scale sinkhole susceptibility map. The study area is the east central Florida (ECF) region that has been experiencing more abrupt and larger cover collapse sinkholes. The research methodology employs two statistical methods for the spatial prediction model, frequency ratio (FR) and logistic regression (LR), accounting for six criteria that are soil erosion, mechanical stability, distance, geology, human activity, and climate condition. The final section of factors includes head difference, soil permeability, thicknesses of aquifer systems (overburden, surficial/intermediate aquifer), distance to karst features, surficial geology, lithology, land use/land cover, and rainfall. Once the models were constructed, both models were validated and compared by using receiver operating characteristics (ROC) analysis. The results indicate that the LR model better delineates high susceptibility areas of sinkhole and hydrological factors (recharge and head difference) are more accurately reflected on the model of the LR. • Develop probabilistic spatial susceptibility model of carbonate karst sinkhole. • A regional-scale sinkhole susceptibility map for the east central Florida region. • Evaluate the performance of Frequency Ratio (FR) and Logistic Regression (LR) methods in the sinkhole susceptibility model. • Statistical analysis on the impact of sinkhole contributing factors. [ABSTRACT FROM AUTHOR]

• GIS-based analysis was conducted to assess the accessibility to mental health services in Florida. • Accessibility of vulnerable population such as seniors was studied. • Counties with the least accessibility are mainly clustered in Northwest Florida. • Counties with a poor access are mostly located in rural areas. The demand for mental health services has been growing stronger over the last couple of decades. This indicates the need to study and assess the access to these mental health services especially with a focus on the vulnerable populations having the greatest need. As such, this paper presents a Geographical Information Systems (GIS)-based analysis in order to study and evaluate the accessibility of mental health facilities using the information on the spatial distributions of population and facilities, and regional traffic characteristics. For this purpose, different age group segments are utilized including the total population as well as those aged between 18 and 21, 22 and 49, 50 and 64, and those aged over 65 and 85. Focusing on the State of Florida, spatially detailed accessibility metrics are calculated with regard to healthcare facilities using travel times between population block groups and these critical mental health facilities. These estimates are used to calculate the weighted county accessibility scores for each county. Findings clearly delineate those counties that lack access to mental facilities, especially those in Northwest Florida, a demographically diverse and substantially rural region. This type of analysis can help planners and policy makers develop better strategies in order to provide adequate mental health care options needed in targeted locations. [ABSTRACT FROM AUTHOR]