The Impact of Data Aggregation on Potential Accessibility Values - Geoinformatics for Intelligent Transportation - page 223

observed in peripheral parts of the study area [ 34 ]. The so-called was also

observed in accessibility analyses (e.g. [ 35 , 36 ], among others). In order to account for
this problem, potential analysis was carried out based on the study area extended to the
whole country, even though the remote destinations have limited impact on potential
indicator values. Thus, all municipalities in Poland are included when calculating the
potential accessibility indicator, however results are only presented and analysed for
those which are located within the Mazovia region (314 units).
The municipal population data for 2012 were collected from the Local Data
Bank. Apart from analysis at the very detailed administrative level (LAU-2, the
lowest administrative division in Poland), the model has also been developed at the
higher resolution of 1 km 2 grid cells. Therefore, the population data in 1

' edge effect '

1km
grid cells were prepared on the basis of the GEOSTAT 2006 population grid
dataset. In order to ensure the comparability of results the GEOSTAT data were
updated using 2012 population data at municipality level derived from the Local
Data Bank for the estimates. Finally, due to the extremely time-consuming calcu-
lations expected, population data is only disaggregated in the case of LAU-2 units
located within the Mazovia region. In consequence, municipalities located outside
the Mazovia region remain unaffected.
The original, very detailed road network dataset is used in the analysis which
corresponds to the road infrastructure in Poland on 1st January 2013. The database
consists of approx. 70 thousand edges, divided into different road categories
(motorways, express roads, dual-carriageway roads, main (national), secondary
(regional) and tertiary (local) roads). Travel times are calculated based on the
maximum speeds for a private car derived from the Polish Highway Code and then,
adjusted downwards, taking account of impediments to driving, i.e. built-up areas,
topography and population density (for details consult: [ 37 ]). The node representing
a municipality is located in the centre of its main locality. The nodes representing
1-km grids are the centroids of grid cells. The latter are connected to the existing
road network using a straight line to the nearest road section. Travel times between
municipalities or between grid cells are received based on the shortest travel time
algorithm between network nodes that represent the pair of units analysed (grid
cells or municipalities).
Taking the assumed aims of the study as the point of departure, three different
potential accessibility models were prepared based on the same theoretical back-
ground. Nevertheless, due to the different spatial resolution of the data involved and
differences in the aggregation procedure, some slight differences can be noticed. In
detail, the potential accessibility models developed and used in the research pre-
sented can be characterised as follows:

×

1. Municipal model (M1). In the first model, every municipality is represented by

one node, located in the central part of an administrative unit (e.g. main
crossroads), with the mass of the unit attributed to one node. Therefore, the
value of the potential accessibility indicator for municipality i (A i ) is calculated
by using the travel times between node i and any other administrative node