EXERCISE 6:
CREATING YOUR OWN DYNA-CLUE APPLICATION:
A STEPWISE PROCEDURE
Step 1: Is Dyna-CLUE the adequate tool for my research questions?
The exercises, paper and descriptions of the CLUE models should have given you a
good idea of what you can use the model for. Basically, the CLUE modelling framework
is developed to spatially allocate land use changes for visualising the impacts of different
scenarios on land use patterns. In case your research has different objectives, e.g.,
determining the aggregate quantity of land use change as result of economic policies, it
is better to choose another model.
Step 2: Do you have sufficient information with respect to changes in demand for
land use areas at the aggregate level?
The Dyna-CLUE model requires projections of the change in area for the different land
cover types at the level of the study region as a whole. These may be derived from trend
extrapolation (so trends are needed), from rough scenario assumptions (e.g., a 10%
increase of agricultural area over the next 20 years) or from advanced models such as
global global economic models or integrated assessment models (as in
www.eururalis.nl). For a specific application it may also be possible to combine methods
for the different land cover types, as long as is made sure that the results are leading to
a consistent change in land areas, i.e., equalling the total area available within the study
region. These data should be prepared before the Dyna-CLUE modelling is started.
Step 3: Build a conceptual model for your study area
The conceptual model should address a number of questions relevant to the design of
the model:
Q1: What is the extent of the study area that you want to address?
Q2: What are the land use types that you are interested in (only include land use types
for which you think information is available)?
Q3: List for each of the land use types a number of location factors which you think may
affect allocation decisions?
Q4: Determine for each of the land use types how you will determine the change in area
at the level of the study region (see step 2)
Q5: Are there any specific, fixed conversion trajectories that need to be taken into
account?
Q6: Are there specific spatial polices to be considered?
The answers to these questions can be filled in the diagram (figure 1) for a schematized
model setup
Step 4: Prepare data
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-Choose the resolution of your spatial data based on the resolution of your land use data
and location factor data. It makes no sense to choose a resolution for which the location
factors do not show any variation between cells. Furthermore, a high spatial resolution
will result in high calculation times. Calculation times are reasonable at resolutions below
1200x1200 cells.
-Convert all spatial data to a similar projection. Equal area projections are preferred
-Reclassify thematic data to a classification to be used in the modelling, e.g., the land
use types or the classes to be used as location factors. Please note that the first class
should always have class number 0.
-Convert all data to a grid with the same extent and resolution (pls note that the upper
left corner of each grid should be located at exactly the same location)
-Prepare a ‘mask’ that contains value 1 inside the study area and ‘nodata’ outside.
-Fill gabs within all data layers, either by adding auxiliary data or by interpolation
methods (e.g., ‘assign proximity’ / ‘eucallocate’).
-Multiply all layers with the mask
-Export all data to ASCII grid data files. It is easiest to directly use the naming
conventions of CLUE: cov_all.0 for the initial land cover and sc1gr[number coding].fil for