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Stefan Fina Patterns of Urban Sprawl Geographical Analysis
- DI is straight forward to calculate and the concept of a comparison between actual and artificially
dispersed urban entities is intuitive to understand and descriptive to communicate.
- DI is suitable to monitor land use change over time: The measure will react if new urban entities
are added to existing urban compound. DI will either go down when average distances between
actual entities decrease (this is mostly the case with infill development) or go up when the average
distances increase (typical for isolated greenfield developments).
- DI can give effect to weighted features, for instance with the number of people living in a building
or the number of households in an area. With such information energy consumption or number of
trips that originate from a building can be modeled more accurately.
These initial tests are certainly insufficient to prove the practicability of the new indicator. Its
acceptance will depend on the performance of the measure in future implementations. Some of the
challenges that are foreseeable at this point are:
- The values of DI depend to a large degree on the definition of developable and undevelopable land
for the artificial dispersion process of urban entities. Inclusion or exclusion of certain restrictions
can cause large variations. Expert knowledge is needed to make informed judgments and reach
consensus about the definition of restrictions.
- Feature weighting (number of people, households, etc.) for DI is a good way to include
information on the intensity of interactions in the study area and works well for residential urban
entities. Business and industry interactions are more difficult to include. Business data on the
number of employees or pedestrian volumes could help to reach good approximations.
- DI is currently a measure that combines simple point pattern analysis (nearest neighbor
algorithms) with a rather complicated algorithm for the distribution of urban entities as points
(extracted as centroids from polygons). DI could also work for the actual polygons (i.e. blocks,
census tracts, land use zones) if the distribution process could be refined so that features can be
equally distributed reflecting their actual size iv .
In summary, this indicator or variations thereof will hopefully be explored further and / or combined
with other measures to fill methodological gaps and possibly stimulate some further research.