Scenario 2 Scenario-based land use modeling by using CLUE-S model
41 There are also several limitations related to the method and findings of this
research, including justification in parameter settings and land use conversion elasticity that only based on local knowledge and interview with local community.
In the previous sub-chapter, it can be seen that in order to determine the temporal dynamic of the simulation by using reversibility of land use changes, three different
decision rules are used. To produce equal conversion behavior, the coefficient of elasticity is set in dimensionless range 0-1 to determine level of reversibility. The
elasticity of grassland area is 0.4, estate is 0.6, and forest is 0.4. Since there is no exact method in determining the elasticity level, empirical assessment of land use
behavior and multi-temporal observation then will be a major contribution in the improvement of the model.
Another issue is related to the reliability of driving factors involved in this model. The implicit assumption in such an approach is that the driving factors are
stable during the modeling time period and influence the dynamic of land use in the area. This assumption ignores the possibility of driving factors to change and their
effects to the land use change. For example the development of local road and additional facilities that may respond to changes in land use. The CLUE-S
framework is capable in involving dynamic driving factors as additional variables to assess future land use pattern, therefore, if data about new dynamic driving
factors are available, it could therefore be useful to improve the utility of scenarios.