Housing units located near transportation facilities tend to have a higher market value than those that are at a greater distance to transport facilities but have similar characteristics. Provision of public infrastructure has a great impact on urban areas, especially on urban development patterns, spatial distribution of urban land use and real estate values. Mass transit systems are one of the most important public infrastructures in cities. Mass transit operations have a significant effect on property values, since they increase accessibility in urban areas. Railway projects are long-lasting investments and by their nature are extremely expensive when compared to other land transportation modes. It is not always possible or reasonable for many countries to fund these high-price projects only with their national budget generated by taxes collected from all citizens. Literature suggests that property values tend to rise in parallel to land values after any kind of public infrastructure investment. Nowadays transportation, especially railway system investments, is regarded as the most important public infrastructure in urban areas impacting land values maximally. Railway investments are becoming widespread in Turkey, especially in Istanbul as Istanbul is the most important and most populated city in country. As due to their high operation costs urban public transport systems, especially railway systems, rarely make a profit, private investors are not willing to get involved in these projects. Furthermore, it is not possible to finance all rail system investments from public funds. This article aims to prove the impact of railway systems on housing values and investigate the possibility of internalizing this increased value for financing railway investments. The main objective of this article is to calculate the impact of distance to a railway station on the value of properties by using the hedonic price model on an existing railway corridor and applying this anticipated impact on a proposed railway corridor. Finally, the calculated value is used as a prelimi- nary basis as a funding model for railway projects in developing countries like Turkey.

In many transit systems, operators use skip–stop strategies to reduce travel time of particular train services by not stopping (skipping) at less densely populated stations. This decision of omitting some stops reduces the travel time for the users within the vehicle and increases the speed of operation, favouring the provision of new transit services where are more necessary. In this work, the best A/b stop–skip patterns for a set of transit services along a railway corridor are determined by means a three-phase methodology that includes the formulation of a nonlinear integer programming inspired in the multiple knapsack problem and the application of a heuristic algorithm based on mathematical properties (matheuristic).

The research takes into consideration diverse perspectives and parameters for assessing accessibility in urban spaces within the Frankfurt Rhein-Main Area, with the initiation of pilot study in Darmstadt, being one of the major cities forming the urban agglomeration. Diverse tools including public transport accessibility level and Space Syntax which contribute to the factor of accessibility are studied and utilized in different urban spaces and further correlated. The study takes into consideration the city centre, the main transit station and a residential area, as three urban spaces within Darmstadt, to understand how the selected performance measures quantify leading to qualitative learning and inferences. The study aims to further evolve in future stages, in order to understand the diversity through the accessibility performance measures through different cities, based on commuter flows, within the urban agglomeration. Assessing accessible mobility in continuum within the urban agglomeration, through interdisciplinary means of research methodology, would assist in the vision (as per German legislation) of obtaining an accessible and integrated multimodal transport system by 2022.

This research aims at investigating the direct and indirect influence of network structures on urban transportation performance with a macroscopic perspective. Transport systems are complex – the functional properties of a transportation network can affect mobility patterns which in turn changes the network performance. Understanding the topology of transportation networks is important in order to upgrade transport network design and to improve transportation performance. This paper attempts to determine important network indicators such connectivity, centrality and clustering measures for different network types (road, rail and bike) from 86 urban areas and 32 countries, based on compa- rable, directly observable open-source data such as OpenStreetMap (OSM) and the TomTom congestion database. Relations between indicators are identified through correlation measures. In addition, regression models are calibrated which quantify the relations between infrastructure accessibility (IA) and network indicators and average traffic delay times. The indicator average road connectivity over average road circuity (RCRC), which is proposed in this study, has not been cited before in literature. The main results suggest that the determination of distance-based connectivity of networks is an important proxy to understand road transportation performance. Consequently, two main results were obtained: (1) an increase in average short-distance connectivity of road networks (average closeness centrality and RCRC) eases road congestion, presumably because the network distributes road traffic more homogenously while decreasing low-permeability choke points, (2) an increase of the average short-distance connectivity of networks of alternative modes such as rail or bike (average weighted rail clustering coefficient and average cycle closeness centrality) does alleviate road congestion. In particular, for cities with over 0.4 km per km$^2$ cycleway density, an increase in cycleway closeness centrality decreases road congestion and it does so almost as efficiently as an increase in road infrastructure accessibility. Presumably, well-connected, alternative networks with short and direct routes convince car users to shift to the alternative mode, which decreases road traffic volumes.

The Chinese government is heavily investing in trade-related infrastructure with its one Belt one road initiative (OBOR), A proposal to build a new silk road or network of trade routes. This infrastructure-driven innovation will have a large economic, spatial and environmental impact on China; it is also likely to transform entire regions throughout asia, africa and Europe. in pursuing it, the Chinese government seeks to meaningfully combine a strong national interest in infrastructural and economic development with an equally strong national interest in environmental sustainability. This chapter explores how it might meet both goals. How do the initiative’s many projects intersect with local interests and needs in China? Will these investments carry out the proclaimed desire of the Chinese government for environmentally sustainable development? This chapter examines these questions by looking at how various governmental players are translating these investments and proposals into spatial plans. It focuses on port city regions, using the Dalian region in northeast China, one of the OBOR initiative hubs, as an example. Port regions are key spatial components in the OBOR initiative: as infrastructural hubs and as centres for trade and innovation, as sites of national oil storage or as hubs for the development of new maritime technology. as places where the industrial production and long-distance infrastructure of OBOR encounters densely populated areas, they are also particularly at risk from climate change, including rising sea levels. Thus, the OBOR initiative’s goals of economic improvement and environmental sustainability may well collide.

Despite the great attention that the field of maritime surveillance has gained nowadays, special effort is required to remove the barriers of collecting and integrating heterogeneous data into a common picture to be shared among all relevant parties and achieving a reasonable level of interoperability for improved efficiency of maritime surveillance systems. Traditional solutions offered mainly rely on the usage of either custom data models or the automatic identification system (AIS) types of messages which, although widely accepted, has significant restrictions regarding the types of data that can transmit (e.g. support of additional information and metadata). Based on the more modern, XML-based, inter-VTS exchange format service (IVEF) introduced by the IALA, we present the design and implementation of a uniform communication gateway (UCG) and an advanced user interface (AUI) for maritime surveillance systems, implementing the IVEF service model and protocol. The UCG consists of a set of interconnected processes implementing data listeners for acquiring raw vessel traffic data, translators from AIS or custom data models (based on reusable libraries) to the IVEF data model, a merging process for integrating the data streams and a IVEF-compliant and SSL/TLS-secured server serving the data to any IVEF-compatible client. For monitoring UCG data traffic, a web-based interface presenting statistics for the reception and sending rates is offered. Moreover, maritime environment data stemming from the EU Copernicus service are map illustrated. The AUI is a front-end system specifically designed to provide multiple categories of users (e.g. radar designers, operational users, result stream subscribers) with the functionalities required to operate and exploit the results of diverse sources of data reception (including AIS traffic and proprietary radars). Its basic component is a map-centric GUI displaying nautical charts, radar cells, vessels tracks and alerts and providing end-users analysis tools. Both implementations have been tested and validated in real operational environment.

With the increasing size of container ships, accurate methods to model manoeuvring and mooring conditions are indispensable. especially in confined waters, where the ship speed is low or even zero, wind forces add a significant contribution to the force balance. the calculation of wind forces is typically done using wind coefficients based on wind tunnel tests. in these computations, a reference wind pressure must be used which is often based on the wind speed at 10 m height. When the wind blows over a rough surface however, the wind profiles become non-uniform, resulting in much higher wind speeds near the top of the ship, for the same wind speed at 10 m height. in case of differences between the wind profile used in the wind tunnel and the one expected in the reality, an appropriate reference pressure should be used. a method proposed by blendermann to calculate such reference pressure is applied in this paper to a wind force calculation for an ultra large container ship. it is shown that, depending on the roughness of the surface, the reference pressure can be a factor 2 to 3 higher than the one corresponding to 10 m height. this means that wind forces are potentially highly underestimated. the results of the method are compared with CFD simulations with a uniform and non-uniform inlet profile. the comparison shows a good agreement between blendermann’s method and computational fluid dynamics (CFD) results for the surge force and roll moment. on the other hand, blendermann’s method seems to overestimate the sway force, but more simulations are needed before a firm conclusion can be drawn.