Land use or land-use changes can trigger or generate hazards and affect the potential consequences of these hazards. Deforestation can trigger land slides, for example, and land reclamation or levee construction can increase flood hazards downstream. New dwellings in or near forests can trigger wildfires, especially if home owners fail to prioritise fire safety measures. In addition, if land is used for industrial activities, new technological hazards, such as the risks resulting from the storage or production of hazardous materials, can be introduced into the environment. Moreover, land-use changes can increase damage potential. Residential developments in hazard-prone areas, such as areas prone to flooding or earthquakes, can negatively affect the number of properties and people exposed to hazards. Consequently, spatial planning activities that are concerned with influencing land use by locating physical structures and activities such as agriculture, recreation or industry within a territory (Couclelis, 2005; Tewdwr-Jones, 2001) can result in new or increased safety risks in a particular area.
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The Maritime Spatial Planning (MSP) Challenge simulation platform helps planners and stakeholders understand and manage the complexity of MSP. In the interactive simulation, different data layers covering an entire sea region can be viewed to make an assessment of the current status. Users can create scenarios for future uses of the marine space over a period of several decades. Changes in energy infrastructure, shipping, and the marine environment are then simulated, and the effects are visualized using indicators and heat maps. The platform is built with advanced game technology and uses aspects of role-play to create interactive sessions; it can thus be referred to as serious gaming. To calculate and visualize the effects of planning decisions on the marine ecology, we integrated the Ecopath with Ecosim (EwE) food web modeling approach into the platform. We demonstrate how EwE was connected to MSP, considering the range of constraints imposed by running scientific software in interactive serious gaming sessions while still providing cascading ecological feedback in response to planning actions. We explored the connection by adapting two published ecological models for use in MSP sessions. We conclude with lessons learned and identify future developments of the simulation platform.
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Research statementOur study analyses the factors that drive decision-making on distribution structures, including the layout of distribution channels and the locations of distribution centres. Distribution is a primary firm activity, which strongly influences logistics costs and logistics performance. Distribution is a challenging activity as customer demand is often volatile and unpredictable. Consumers continuously expect higher service related to distribution, e.g., same day delivery and more flexibility in delivery locations. Therefore, it is of strategic importance to shippers and Logistics Service Providers (LSPs) to decide which distribution channel layout to use and, accordingly, plan distribution centre location(s). Distribution structure selection concerns the number and locations of distribution centres, as part of the larger corporate planning process. The main questions we strive to answer in this paper are: (1) what are the main criteria that determine the spatial layout of distribution structures? and (2) how important are these criteria, relative to each other?Methodology The literature on distribution channel design mostly revolves around optimization methods; we are not aware of literature that takes a descriptive approach. We therefore develop a descriptive conceptual model that includes these factors, developed from the contextual literature around this decision. The second part of the study concerns the measurement of the relative importance of these factors. We implemented an elaborate survey and used the Best-Worst Method (BWM) to identify these weights. The survey considers different experts (e.g., logistics managers versus logistics professors) and population segments (e.g., in-house versus outsourced distribution).Data and resultsCurrently we are completing the survey dedicated to evaluating the above factors. We have received sufficient response to estimate a first model. These first estimations already provide useful results. Final estimations will be completed and reported in June 2017. At the I-NUF conference we will be able to present the results and analysis of all factors when comparing respondents and parameters.Preliminary conclusionsBased on literature review, eight main factors – divided into 33 sub factors – are included in our research: 1) Demand factors, 2) Service level factors, 3) Product Characteristics factors, 4) Logistics costs factors, 5) Proximity-related location factors, 6) Accessibility-related location factors, 7) Resources-related location factors and 8) Institutional factors. A number of hypotheses were built from the literature analysis relating, for example, to the relative importance of service- and cost- related factors within different industries. We will revisit these hypotheses and provide the quantitative results of the importance of the individual factors in our paper and at the conference.
In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
The capacity on the Northern ring road in Breda is approaching its limits. Due to planned spatial developments the ring road might even be under further pressure. Therefore the municipality of Breda is working on an action plan to deal with this task. This requires insight into the functioning of the Northern ring road, which has been achieved by combining the following data sources: • Meetweken Breda 1st edition (GPS)• Meetweken Breda 2nd edition (GPS)• OViN• License plate cameras (NRW)• Counting data (NRW)• Bluetooth data (NRW)• Weather data (KNMI)The results show that in comparison with other strongly urbanized cities, Breda is more oriented towards the car and less use is made of public transport and the bicycle. Particularly on short distances there is still potential to further increase bicycle usage. In depth results can be found in the presentation, including information about: peak hours, the number of trips per person per day, the percentage of multimodal trips and the effect of rain on route choice. By combining the insights from the different forms of data, additional insights and an overarching mobility picture emerge. In other words, the overall picture is more than the sum of the parts.
