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The term “spatial modelling” refers to a particular form of disaggregation, in which an area is divided into a number (often a large number) of similar units: typically grid squares or polygons. The model may be linked to a GIS for data input and display. The transition from non-spatial to spatial modelling is often considered to be pretty significant, and there are a number of modelling packages that advertise their spatial modelling capabilities: indeed, many are labelled as landscape or landuse modelling tools.
Simile is rather odd in that it can do spatial modelling — in fact, it can do it rather well — while having no explicit spatial modelling constructs! All you need to use are the standard Simile model-design elements. It is only the use of maps for displaying model results (and potentially inputting information into the model) that reveal that it is a spatial model - and all the Simile input/output tools (helpers) are quite independent of the basic simulation engine.
In Simile, a spatial unit is just like any other unit. You define a single instance in a submodel, and then specify that you have many instances. The only difference now is that each instance will have two attributes specifying its x and y coordinates. These enable any display tool to locate each unit in the appropriate part of the display (map). They may also be used in spatial reasoning within the model: e.g. for working out the distance between two spatial units to calculate seed dispersal or shading.
The model itself does not “know” if a spatial unit is a square, a polygon, a hexagon or whatever (in fact, it does not even know that it contains spatial units). It is up to the modeller to model each type in a way which is consistent with what is intended. Thus, if the units are grid squares, then they should all have the same value for an “area” attribute, and the rule for defining which units are neighbours of which other units can be defined in terms of the column and row attributes. If they are polygons, then both the area of each unit and its neighbours will (typically) be defined in a data file. And in either case, the user of the model would need to choose a display tool that is appropriate to the type of unit being modelled.
As of version 6.1, we did introduce pre-defined array types for rectangular and hexagonal grids. Such grids are a very common methodology in ecological modelling, and it makes more sense to allow a modeller to select a pre-defined type and thus get access to functions providing each grid square instance with values from particular neighbouring grid squares, than have to figure out how to create a neighbour relationship to provide access to these values. We would hope that this feature encourages modellers to experiment, and perhaps lead on to use of the full power of the association submodel methodology.