Distance and Density of Roads Data

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Using ArcView a value was assigned to each cell corresponding to the distance from the nearest road. A fine grid was also constructed across the study region and the values in the cells were coded with a value 1 if they contained road and 0 otherwize. This fine grid was then aggregated to a 1DM resolution grid where the values in each cell was assigned as the sum of values in the smaller grid. This gave a proxy for road density. The view above shows a classification of distance and density values also created using ArcView.
Source=Bartholomew data


  • The bartholomew source data generalises road curvature, this generalisation is relatively unimportant given the scale at which we require the model to work at, (it is somewhat coped with by the aggregation). A more concerning generalisation relates to urban areas, not all roads in urban areas are included in the Bartholomew data. It could be hoped that this generalisation is coped with by the inclusion of other data layers in the input, but this may be a bit presumptive. If the average level of urban road generalisation was evaluated the density layer could be altered by multiplying by a function of this average in urban areas.

  • Generally: The denser the road network is the denser the population is; and the further the distance to a road the less dense the population is.

  • Many more road related data layers could be created and used in future models, such as, distance from junctions. The road layers can also be split into several layers each providing distance and density information for different classes of road.


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    Pages constructed by Andy Turner

    Last Modified
    20th December 1997