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Land Use Modelling is the process of modelling the transformation of land use and land cover in time. The GeoDMS was initially developed to support land use modelling. The Land Use Scanner (Dutch: Ruimtescanner) is currently a prime example of land-use modelling and is extensively used in Dutch spatial planning. There is also a land-use scanner version for Germany which is being used by the Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR). Furthermore, a European land-use model is the LUISA model developed by the Joint Research Centre of the European Commission and Object Vision.
Related concepts: land use change dynamics, dynamic Land use/cover simulation, Land Use and Transport Interaction (LUTI).
Looking into the future has fascinated mankind for ages. With the advent of sufficiently powerful personal computers, we no longer need a crystal ball to foresee what our country will look like in, say, 30 years from now. All that is needed now to simulate future spatial developments is a set of spatial data, modelling software and some thoughts on which spatial developments you expect to happen in the coming decades. The latter is, of course, the tricky part. By looking at current developments, we may identify trends that are likely to continue for the coming 5 to 10 years. Yet, looking much further is risky at best, as many uncertainties prevail. Will population growth come to a halt? Will economic development be slow? Will society prefer ecological sustainability or economic prosperity? How will the government try to steer spatial developments? Will they succeed?
A popular approach to dealing with uncertainties relating to future spatial developments is the use of scenarios. By describing several opposing views on the future, we can simulate a broad range of spatial developments, thus offering a full overview of possible land-use alterations. Each individual outlook on the future will not necessarily contain the most likely prospects, but together, the simulations may provide the bandwidth of possible land-use changes. The individual scenarios should, in fact, not strive to be as probable as possible but should stir the imagination and broaden the view of the future. Important elements are plausible unexpectedness and informational vividness (Xiang and Clarke, 2003).
Land use allocation is the process of assigning land resources for various usage purposes. In land use modelling, claims at the regional/national level are usually allocated to grid cells based on suitability scores. Different allocation methods are in use:
- The allocation is discrete when each unit of land is allocated to only one out of a limited set of land use types.
- The allocation is continuous when each unit of land can have any non-negative amount of land use for each type up to a fixed total.
If the intensity of land use is spatially variant and/or different land use types don't exclude each other (multi-functional land use and/or land functions are (partially) abandoned), one needs quantitative allocation.
Both allocations require suitability for each allocation alternative (thus, for each land use type, there is a map that assigns suitability to each land unit.
Furthermore, one can define restrictions per land use type on the total amount of allocated land.
When facing many land use types, allocation can also be nested if a type hierarchy makes sense. Sub-typing can also be done as a post-processing step. If the occurrence is also constrained per sub-type, one needs another round of allocation within the space allocated to the primary type. Subtyping can more often be done as unconstrained classification.
Driving factors at the grid cell level influence possible transitions between different land use types. Accessibility is, in many models, an important driving factor.
