Assessing the Impact of Game Day Schedule and Opponents on Travel Patterns and Route Choice using Big Data Analytics

The transportation system is crucial for transferring people and goods from point A to point B. However, its reliability can be decreased by unanticipated congestion resulting from planned special events. For example, sporting events collect large crowds of people at specific venues on game days and disrupt normal traffic patterns. The goal of this study was to understand issues related to road traffic management during major sporting events by using widely available INRIX data to compare travel patterns and behaviors on game days against those on normal days. A comprehensive analysis was conducted on the impact of all Nebraska Cornhuskers football games over five years on traffic congestion on five major routes in Nebraska. We attempted to identify hotspots, the unusually high-risk zones in a spatiotemporal space containing traffic congestion that occur on almost all game days. For hotspot detection, we utilized a method called Multi-EigenSpot, which is able to detect multiple hotspots in a spatiotemporal space. With this algorithm, we were able to detect traffic hotspot clusters on the five chosen routes in Nebraska. After detecting the hotspots, we identified the factors affecting the sizes of hotspots and other parameters. The start time of the game and the Cornhuskers’ opponent for a given game are two important factors affecting the number of people coming to Lincoln, Nebraska, on game days. Finally, the Dynamic Bayesian Networks (DBN) approach was applied to forecast the start times and locations of hotspot clusters in 2018 with a weighted mean absolute percentage error (WMAPE) of 13.8%

Spatial dependence of body mass index and exposure to night-time noise in the Geneva urban area

In this study, we calculated the night-noise mean (SonBase 2014, compatible with the EU Environmental Noise Directive) for the 5 classes obtained after computation of Local Indicators of Spatial Association (LISA; Anselin et al 1995) on the BMI of the participants in the Bus Santé study, a cohort managed by the Geneva University Hospitals (N=15’544; Guessous et al 2014). We expected the mean of dBs to be significantly higher in the group showing spatial dependence of high BMI values (high-high class). We ran an ANOVA and multiple T-tests to compare the dB means between LISA clusters. The approach was applied to the participants of the whole State Geneva cohort, and to a reduced set of individuals living in the urban environment of the municipality of Geneva only

The effects of upstream Natural Flood Management on urban surface drainage performance

The evaluation of rural Natural Flood Management (NFM) has traditionally focused on the ability of interventions to mitigate downstream fluvial flooding by attenuating catchment response. This research expands this focus – investigating whether these same interventions could also mitigate surface flood risk in downstream urban areas. By moderating water levels in receiving watercourses, upstream NFM could promote free discharge from urban drainage outfalls and thereby improve local surface drainage performance. A novel modelling methodology has been developed to characterise the response of three separate catchments – the Bin Brook in Cambridgeshire, the Asker in Dorset and a sub-catchment of the upper Calder in Yorkshire. The upstream, rural response is simulated by coupling Dynamic TOPMODEL (a semi-distributed hydrological model) and HEC-RAS (which solves the shallow flow equations). This offers a freely-available, spatially-informed approach for the evaluation of a range of upstream NFM interventions (located both within and beyond the riparian zone) at a catchment-scale. This modelled rural response then provides the input for a downstream, integrated urban drainage model (Infoworks ICM). This is then be used to examine how any consequent changes in outfall inundation by the urban watercourse alter local drainage performance. Each case study is examined separately before a comparative study of all three is undertaken to identify broader trends. These trends suggest that during more frequent events (e.g. 1 in 10 year), upstream NFM interventions create the greatest reductions for the time low-lying outfalls are submerged by local watercourses. As storm severity increases (heightening risk of drainage surcharge or failure) these reductions diminish. Despite this, the slight delay in rural response continues to allow more water to escape surface systems before outfall inundation occurs, increasing the effective capacity of networks and reducing surface flood volumes. While any improvements to outfall discharge would not, in themselves, justify NFM implementation, these interventions have the potential to contribute to a downstream water level management strategy in certain locations and therefore will be of interest to urban flood risk practitioners.Engineering and Physical Sciences Research Counci

Retrospective Geospatial Modeling of PM10 Exposures from Open Burning at Joint Base Balad, Iraq

Predicting, determining, and linking theater-related source-specific exposures to health effects has proven difficult. The purpose of this research is to delineate retrospective exposure zones using spatially interpolated particulate air sampling point data from Joint Base Balad, create burn pit exposure isopleths from dispersion model outputs, and merge into a combined exposure model in GIS. Interpolated monitoring results and dispersion modeled results were combined to compare modeled exposures across base. Burn pit contribution to total PM10 was also modeled. The combined dispersion and interpolation map showed elevated concentrations within a 1 kilometer buffer of the burn pit. Buildings within this area were identified by geoprocessing. The east side of the base receives greater burn pit-specific PM10, compared to the west side. The west side showed high ambient PM10 from monitoring results, but it is unclear whether this was due to spatial or temporal effects. High temporal variability highlights the need for temporally representative sampling across the geographical area throughout the year. It was shown that source-specific individual exposure can be estimated with dispersion model isopleth maps and individual time-activity patterns. All modeling performed can all be refined with improved estimates of emission rates

Investigating summer thermal stratification in Lake Ontario

Summer thermal stratification in Lake Ontario is simulated using the 3D hydrodynamic model Environmental Fluid Dynamics Code (EFDC). Summer temperature differences establish strong vertical density gradients (thermocline) between the epilimnion and hypolimnion. Capturing the stratification and thermocline formation has been a challenge in modeling Great Lakes. Deviating from EFDC's original Mellor-Yamada (1982) vertical mixing scheme, we have implemented an unidimensional vertical model that uses different eddy diffusivity formulations above and below the thermocline (Vincon-Leite, 1991; Vincon-Leite et al., 2014). The model is forced with the hourly meteorological data from weather stations around the lake, flow data for Niagara and St. Lawrence rivers; and lake bathymetry is interpolated on a 2-km grid. The model has 20 vertical layers following sigma vertical coordinates. Sensitivity of the model to vertical layers' spacing is thoroughly investigated. The model has been calibrated for appropriate solar radiation coefficients and horizontal mixing coefficients. Overall the new implemented diffusivity algorithm shows some successes in capturing the thermal stratification with RMSE values between 2-3°C. Calibration of vertical mixing coefficients is under investigation to capture the improved thermal stratification

Rodent assemblages and rodent associated pathogens in a counter-urbanizing landscape

Human population declines in urban centers (also known as counter-urbanization) can result in increased levels of vacancy and infrastructure loss, though relatively little is known regarding the ecological outcomes of this type of landscape change. The abundance and diversity of pest and zoonotic pathogen hosts are predicted to increase in counter-urbanizing environments, giving rise to a novel human-animal interface. Furthermore, the human-animal interface is a key location for zoonotic pathogen emergence, thus, understanding how host communities shift in regard to counter-urbanization can lend insight into risk of zoonotic pathogens in these areas.In this dissertation, I investigate the abundance and diversity of rodent hosts across a counter-urbanizing environment in the city of New Orleans, Louisiana, USA to understand how features of the urban environment shape rodent assemblages and the risk of zoonotic pathogens. I demonstrate that rodent abundance and diversity increase in areas with higher levels of vacancy, and that increased rodent abundance and diversity also translate to increased risk from some zoonotic pathogens. However, this work also indicates that not all zoonotic pathogens show similar patterns across the landscape. In this work I provide practical insight into specific environmental and sociological risk factors associated with rodent abundance and zoonotic pathogens, while also leveraging the gradient of rodent abundance and diversity present in the counter-urbanizing environment of New Orleans to test predictions regarding relationships between host diversity, host abundance, pathogen prevalence, and diversity

2017 Scientific Consensus Statement: land use impacts on the Great Barrier Reef water quality and ecosystem condition. Chapter 4: management options and their effectiveness

This chapter seeks to answer the following questions: 1. What are the values of the Great Barrier Reef? 2. How effective are better agricultural practices in improving water quality? 3. How can we improve the uptake of better agricultural practices? 4. What water quality improvement can non-agricultural land uses contribute? 5. How can Great Barrier Reef water quality improvement programs be improved? Each section summarises the currently available peer reviewed literature and comments on implications for management and research gaps. This chapter has a wider scope than previous Scientific Consensus Statements, including, for the first time, the social and governance dimensions of management and the management of non-agricultural land uses. These new sections are constrained by a lack of Great Barrier Reef–specific data and information. The relevance of information from other locations must be carefully considered. In comparison, the agricultural practice change and economics sections provide an update on material compiled as part of the 2013 Scientific Consensus Statement. This report has been confined to peer reviewed literature, which is generally published in books and journals or major reports. There is additional evidence in grey literature, such as project and program reports, that has not been included here. Each section of this chapter has been compiled by a writing team and then revised following a series of review processes

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity