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Land Use
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National Scale land use Change Modeling - Issues and Applications
Discussion and Conclusion
The global and regional studies of landuse changes identify the so-called PAT variables (population, affluence and technology) as having the strongest statistical correlations with the environmental change, often implying that the specific variables in questions are the underlying driving forces of change (Veldamp and Fresco, 1996b). Such results may reflect the problems of aggregation of the data for the analysis. It may also result from the subjective considerations that may creep into the study or due to the complexity involved in scaling the spatial and temporal aspects.
At present, ther is only IMAGE2 model (Alcamo et al., 1994), a global model integrating agricultural systems, food supply and other environmental issues. It has a compreshensive model for land cover estimations that is linked to the demands of the agricultural sector (Zuidema et al., 1994). The simulations consider human driving forces as population, GNP and technological developments based on scenarios for 13 world regions. But these do not consider the adaptations that may take place and hence its feedback. Most of the models are successful within their limited domains of validity and scale. No inter-scale dynamics are considered in most of these models, and as long as this is not done, it is difficult to get realistic simulations.
Recently, a new model CLUE (Veldmamp and Fresco, 1990a) was developed as a dynamic model to simulate conversion of land and its effects. It brings about change in land cover, at the sub-national level based on the interaction between the biophysical driver and human drivers. The model is based on rules derived from qualitative information, and includes feedback loops of effect to land condition assessment. In a test application of the model for simulation simultaneous local, regional and national land use/cover changes in Costa Rica, readily available data at the national scale was used. The authors observe that even though there are no methodological constraints to scale down and/or up and to link up with other models, there exists data limitations that prevent such an exercise.
Form the above discussion, we can conclude that the issues of dataset resolution, classification and its quality will matter a lot in the formaulation of the models. If a model is developed based on the known physical and qualitative information, then it needs to be further tuned to the area of application, and may need to be readjusted depending on the data used. So, the development of a robust framework of the land use model is necessary to accommodate the experiences of modeling in one country to its surrounding nations.
References
- Alcamo J., et. Al., 1994. Modeling the global society-biosphere-climate system. 1. Model description and testing. Water Air Soil Pollution., 76: 1-35.
- Global Daily summary., 1994. Temperature and Precipitation 1977-1991. National Geophysical Data Center, USA.
- GLOBE project., 1997. Global Land One-km base Elevation. National Geophysical Data Center, USA.
- Parry, M.. L., and Rosenzweig, C., 1994. Potential Impacts of climate change on world food supply, IIASA.
- Robinson, J., et. Al, 1994 Land -Use and Land-Cover projections, Report of WG C in "Changes in Land-Use and Land-Cover, A Global Prespective" (ed. Meyer and Turner). Cambridge Univ. Press.
- Veldkamp, A. and Fresco, L.O., 1996a. CLUE: a conceptual model to study the conversion of land use and its effects. Ecological Modelling., 85:253-270.
- Veldkamp, A. and Fresco, L.O., 1996b. CLUE-CR : an integrated multi-scale mode to simulate land use change scenarious in Costa Rica. Ecological Modelling., 91:231-248.
- Zuidema, G., et al., 1994. Simulating changes in global land cover as affected by economic and climatic factors. Water Air Soil Pollution., 76: 163-198.
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