![](bg5.png)
concepts was used (Hansen 1993). This
methodology was taken from Laplace´s rule formula
and adapted for the BoLD model using ArcGIS to
calculate distances between land-uses and their
relation to land-use cells in a defined searching
radius.
(1)
Where,
A= Land-use A
B= Land-use B
D
AB
= Distance between A and B
R= Searching radius
n= Number of cells in A
X
AB
= Attractiveness Index of A to B
d. Accessibility is the level of transport service
provided in a specific area. For LUCC models,
accessibility refers to the preference of most land-
uses to locate closer to transport services. A highly
accessible location is more likely to be developed.
Mathematically, accessibility in a LUCC model
based on cellular automata can be expressed as
(RIKS 2007):
(2)
Where:
is the accessibility of cell, c, in
relation to a certain type of node or
transport link, y, (for example, a main road
or train station) for a specific land-use, s
is the accessibility distance decay
factor (ADDF) which varies depending on
the type of infrastructure, y, and it is
individual for each land-use, s
is the distance to the specific cell
being analyzed to the infrastructure, y, and
at a specific time, t
Result from this equation can only have a value
between 0 and 1 for each cell. As the scenarios being
modeled determine distance to the nearest transport
infrastructure, assigning ADDF for each type of
infrastructure considered and for each land-use is a
key task for the modeler.
Although the determination of ADDF is
commonly based on empirical experiences (Furtado
2009), the significance of these factors required us to
explore advanced technical approaches to determine
ADDF. A methodology based on GIS was used to
determine ADDF. We have called this methodology
OSDD (Overtime Spatial Decay Determination).
OSDD is based on three principles. The first is
that ADDF factors are usable for modeling future
scenarios.
The second assumption is that ADDF for each
type of infrastructure and for each land-use is
proportional to each other. In other words, if two
ADDF for two different infrastructures are equal
they have the same contribution to the overall
attractiveness of cells in the model. Consequently,
and considering that OSDD creates ADDF with
values between 0 and 1, specific transport
infrastructure, y, for particular land-uses, s, has a
low proportional accessibility, OSDD would assign
a value of 0.
The third principle considers that the average
distance between cells within 2 km of a particular
land-use and the infrastructure is a good indicator of
the ADDF. In consequence, the larger the average
distance, the smaller the decay factor would be.
The results of applying OSDD are ADDF values
between 0 and 1. Additionally, and considering that
transport infrastructure could be modeled as lines or
points in a GIS system, double normalization is
conducted.
Using processed datasets for 2005 and 2014 in
the BoLD model, OSDD was applied and the results
were compared.
3 RESULTS
After implementing BoLD using the parameters
described in the previous section, including de
ODDC for accessibility analysis, results were
obtained for all scenarios. Maps results of the
baseline year (2014) and the simulated result for
2040 for each scenario are presented in figure 2.
General patterns of development are maintained
in all scenarios. This is probably due to the fact that
Bogota is a mature city in where trends have been in
place for many years. However, there are differences
in specific zones between scenarios (highlighted
with red circles). For the first scenario, increased
commercial development along the proposed road
with additional industrial in their surrounding areas
can be noticed. Also, industrial areas in the far West
appear among farming zones. These two are
expected results as additional road capacity is
particularly attractive to commercial and residential.
Modelling Transport-based Land-use Scenarios in Bogota
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