Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling
Abstract
:1. Introduction
2. Contemporary LCLUC Models
Modeling Approaches | Description |
---|---|
1. Machine Learning and Statistical Models | Generally automatized, software programs recognize and reproduce the patterns of change. Based on rigorous statistical methods, use observations of changes in order to establish space and time relations between change and drivers. |
2. Cellular | Integrates maps of land cover and land use suitability, taking into account the neighborhood effect and information on the amount of change. |
3. Spatially-Disaggregated Economic Models | Assess the econometric models in a structural and reduced manner to identify the causal relations having an influence on the spatial equilibrium of land systems. |
4. Sector-Based Economic Models | Use models of partial or general structural equilibrium in order to represent the offer and demand of land by economic sectors within the regions based on general economic and commercial activity. |
5. Agent-Based Models | Simulate the heterogeneous decisions and actions of actors of change that interact on the land surface, which lead to LCLUC. |
6. Hybrid Approach | Includes applications combining different approaches in a single model or modeling frame. |
2.1. Inputs
2.2. Training or Calibration of the Model
2.3. Simulation
2.4. Model Assessment
3. Historical LCLUC Models
3.1. Objectives
3.2. Inputs
3.3. Training and Simulation
3.4. Validation
4. Discussion
5. Conclusions
- (1)
- We identified three large groups of historical models of LCLUC: pattern-based models, agent-based models and hybrid models.
- (2)
- The historical LCLUC models could benefit from the vast experience accumulated by contemporary modeling of LCLUC; however, the inputs required for historical modeling are drastically different and have limitations. Because of the scarceness and characteristics of the inputs used, historical models cannot be totally based on data (data driven), but must rather be largely based either on expert knowledge or on hybrid approaches.
- (3)
- Most models of past LCLUC aim at reconstructing the landscape for a given date rather than at making simulations between dates. This means that historical models are not dynamic through time. Recently, historical simulation has been oriented towards more realistic models of the processes of LCLUC, which allows for better understanding problems, such as environmental deterioration. It is likely that some historical models of LCLUC will adopt that same trend.
- (4)
- Depending on the objective of modeling and inputs, an appropriate modeling approach should be chosen. Agent-based models are preferred when modeling decision-making; pattern-based models are suggested when models aim at reconstructing past landscapes or simulating LCLUC changes.
- (5)
- The quantity and quality of inputs directly determines the performance of the model and limits the possibilities for its evaluation. Awareness must be kept about the fact that modeling is an exercise of the simplification of reality and that results must be interpreted cautiously. However, model assessment, which is a common practice in contemporary models, should be adopted in past modeling and adapted to the modeling objectives.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Chang-Martínez, L.A.; Mas, J.-F.; Valle, N.T.; Torres, P.S.U.; Folan, W.J. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling. ISPRS Int. J. Geo-Inf. 2015, 4, 1791-1812. https://doi.org/10.3390/ijgi4041791
Chang-Martínez LA, Mas J-F, Valle NT, Torres PSU, Folan WJ. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling. ISPRS International Journal of Geo-Information. 2015; 4(4):1791-1812. https://doi.org/10.3390/ijgi4041791
Chicago/Turabian StyleChang-Martínez, Laura Alfonsina, Jean-François Mas, Nuria Torrescano Valle, Pedro Sergio Urquijo Torres, and William J. Folan. 2015. "Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling" ISPRS International Journal of Geo-Information 4, no. 4: 1791-1812. https://doi.org/10.3390/ijgi4041791