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Interaction data and regional data - Accessibility indices and peripherality indicators

Accessibility indices

Accessibility is the main product of a transport system. It determines the locational advantage of a region relative to all regions. Accessibility indicators can be defined to reflect both within-region infrastructure and infrastructure outside the region of interest which affect this region. Accessibility indicators range from simple infrastructure measure towards complex indicators taking account of connectivity and opportunities.

"Accessibility indicators describe the location of an area with respect to opportunitiesm activities or assets existing in other areas and in the area itself, where ‘area’ may be a region, a city or a corridor [or any other spatial entity of interest]" (Wegener et al., 2002).

The basic mathematical form to describe accessibility is as follows:


where g(Wj) is the activity function and f(cij) is the impedance (or distance) function. Different types of accessibility indicators can then be constructed by specifying different forms of the functions g(Wj) and f(cij), as the following table shows (Schürmann et al., 1997):

Type of accessibility Activity function Impedance function
1 Travel cost Wj | 1 if Wj > Wmin Cij
Accumulated travel cost to a set of activities 0 if Wj < Wmin
2 Daily accessibility Wj 1 if cij < cmax
Accumulated activities in a given travel time 0 if cij > cmax
3 Potential

Exp(-ßcij)
Accumulated activities weighed by a function of travel cost


It is possible to calculate all three types of accessibility, depending on the data needs and purpose of the analysis. The parameter α and ß will also be defined in accordance with the analysis requirements.

In general, accessibility indicators can be calculated for all NUTS levels, i.e. from NUTS-0 level (country level) to NUTS-5 level (municipality level), with applications on NUTS-2 level and NUTS-3 level being the most common ones. Most applications use accessibility to population or accessibility to GDP indicators (i.e. population and GDP being the activity function), but it is also possible to calculate accessibilities to other sets of activities than these (e.g. accessibility to airports, accessibility to universities, accessibility to hospitals), if desired.


Peripherality indicators

Fundamentally, peripherality indicators can be interpreted as an inverse function of accessibility, i.e. the higher the accessibility is, the less peripheral a region is located and vice versa. This, moreover, means that in any case the regional accessibility will be calculated using one of the three types as outlined above, and will afterwards be standardised in a way to construct peripherality indicators.

Two ways of standardising accessibilities to p construct peripherality indicators are commonly used:

1. Standardisation to the interval between 0 and 100, with 0 representing the most central region and 100 the most peripheral region
2. Standardisation at the average of all regions, where high values indicate central and small values peripheral regions.

So as for the accessibility indices, the peripherality indicators can also be constructed for all NUTS levels, with NUTS-2 level and NUTS-3 level being the widely used ones. Usual, peripherality with respect to population or GDP is calculated, but also any other activity function can be applied.


For further information on the calculation of accessibility indices and the application of peripherality indicators please refer to this online paper, or contact us to receive further information on the generation of accessibility indices and peripherality indicators. The following overview provides more insight into the dimension of these indicators and so into the specific settings that can be set for their calculation.


 More on this topic
Related documents:Dimensions of accessibility indicators and peripherality indices



RRG GIS Database contents:

General information
Transport networks
Region boundaries, admninistrative boundaries
Geography
Interaction data and regional data

Introduction
Neighbourhood matrices
Airline distances, network distances or Manhattan distances
Travel time and travel cost matrices
Isochrones
Accessibility indices and peripherality indicators
Climatic conditions
Quality of life
Topographic data

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