Environmental Engineering Reference
In-Depth Information
Roads (HCR) and 6,000 km of High-Speed Rail (HSR) lines. The assessment is
carried out on the basis of the comparison between the 'construction alternative'
(APEIT) and the 'do-nothing alternative' (A0). The accessibility calculations were
made using a network accessibility analysis GIS toolbox [14] . The general method-
ological stages explained in the previous section are given as theoretical back-
ground for the case study application which follows next.
Implementation of the Methodology
Stage 1: Definition of the study area
The study area basically comprises the Spanish mainland and its corresponding
cross-border regions in neighbouring countries, which include Portugal and the
three southern French NUTS-2 (Nomenclature of Territorial Units for Statistics,
defined by the Statistical Office of the European Communities, i.e. EUROSTAT)
regions.
Stage 2: Implementation of the transport and socio-economic system
In order to calculate accessibility values, a dense intermodal (road and rail) network
was modelled with the support of a GIS; the ArcGis software was used in this case.
Accessibility values are obtained for each node of the network, which coincide with
the nodes of the road network, which are nearly 12,000 km. The first task consisted
in modelling the road network of the do-nothing alternative (A0). A vectorial GIS was
used, in which the network is modelled as a graph with a set of nodes and arcs. For
each arc on the road network, the length, estimated speed according to the type of
road (120 km/h for highways, 110 for expressways, 90 for interregional roads, 80
for other roads and 50 for urban roads) and resulting travel time were also recorded.
For the rail mode, each arc is given a commercial speed according to both infra-
structure and quality of service characteristics. Rail network modelling tasks are
significantly more complex than those of the road mode, as it is necessary to
include track gauge (Iberian/UIC) data, the location of the stations and frequency
of service information in order to calculate travel times, as described in [9] , which
is not possible to detail in this paper for space reasons.
The population is the selected variable to measure each destination's attrac-
tiveness in the accessibility model. In Spain, the selected destination centres cor-
respond to the centroids of the approximately 8,000 municipalities of the Spanish
mainland.
Stage 3: Calculation of travel time savings
In this stage, the location accessibility values of each origin centroid i is computed,
using Eq. 1. Intermediate calculations include the measurement of each i-j travel
time, using minimum-path algorithms embedded in the GIS. The location indicator
is therefore used as a proxy for the evaluation of travel time savings, when its
results in the PEIT alternative are compared to those of the do-nothing alternative.
Hence, a single aggregated value of the location indicator for all Spain has been
computed and compared to that of the do-nothing alternative. For clarity reasons, the
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