In order to get better grip on the different scale levels and to subsequently enable a discussion about their interlinkages, an overview of facts and figures on different scale levels in relation to the specific urban node has been developed, the so called ‘fingerprint’. The fingerprint works as a guiding methodology during the workshop and it enables distinguishing different types of urban nodes, due to the use of comparable data and standard categories. Also it will enable comparison between various urban nodes analysed by the VitalNodes project in the future (e.g. between the tier 1 urban nodes). Within the so-called fingerprint, data will be collected about the functional area of the urban node as well as the use of the networks related to freight and logistics.
The fingerprint contains information on the urban node, the corridors, the current and forecasted function on the corridor, traffic flows, modal shift – including forecast and challenges for the urban node. The information is categorised on successively three different scale levels: TEN-T corridor level, the urban regional/functional urban area/Daily Urban System level and local/city level. Ideally facts and figures on the functional level are present, in case the urban node already has a clear definition of its functional region. Developments, characteristics and governance structures are included as well.
Urban nodes have very diverse geographical and infrastructural characteristics such as their size and location, their position on one or more TEN-T corridors, urban and regional and socio-economic developments, and the state of the art of their local and regional multimodal infrastructure networks. Based on the urban node’s fingerprint, consisting of facts and figures relating to the urban node’s freight and logistic situation on national, regional and local level, main challenges are addressed. The fingerprint is a tool to support discussions between stakeholders during the workshops and to improve the understanding of the specific location and circumstances of the urban node, including challenges. Besides that, a categorisation of urban nodes can be made via a comparison of the different fingerprints. Each urban node fingerprint is based on European Commission definitions and data (EuroStat) to facilitate comparison. Based on these facts and figures the fingerprint is drafted and maps are developed.
The fingerprint comprises the following other tools:
Facts and figures
Containing an analysis of infra networks (regarding road, rail, navigation and aviation), traffic figures and trends for the various modalities – with a focus on freight/logistic relationships (source-destination), interrelationships of this with passengers traffic (also in relation to public transport and active modes), spatial lay-out of the area and trends, institutional framework. All of this at the three scales of corridor level, functional urban area, local/city/level in order to enable analysis and discussion about the interrelationships between the scales (zooming in and out)
Regarding infrastructure network, mobility, spatial lay-out, bottlenecks and development as well as institutional framework and development. This provides insights in the specific circumstances of an urban node and show the issues that need to be dealt with. A main focus is on freight and logistics, taking into account all other aspects analysed and mentioned (facts and figures).
Drivers and barriers
Containing information as a result from interviews with key stakeholders and the workshop, giving insight to locally important aspects in relation to solution direction(s), possibilities and impossibilities. Including the needs regarding the various dimensions as well as the interrelations between these dimensions (see figure 1).
Indicating type of practise, description of the potential solutions, link with the urban node’s challenge(s), impacts and contact person(s) as being good practices as result of previous experiences and outcomes of the urban node workshops.
The full preliminary toolbox can be downloaded here.