An application of fuzzy logic reasoning for GIS temporal modeling of dynamic processes
β Scribed by Suzana Dragicevic; Danielle J. Marceau
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 717 KB
- Volume
- 113
- Category
- Article
- ISSN
- 0165-0114
No coin nor oath required. For personal study only.
β¦ Synopsis
The analysis and modeling of dynamic processes require the consideration of both spatial and temporal attributes of data and their integration into a GIS database. However, current GIS raster databases have severe limitations related to the temporal component of data. Data are generally stored through a series of snapshot layers associated to particular instants in time. If the interval between two consecutive snapshots is too long the essential information about the change may remain undetected. In this study, spatio-temporal interpolation based on fuzzy logic theory was applied in order to model the missing information about change that happened between consecutive snapshots. Three di erent scenarios of rural-to-urban landuse transformation were conceived to simulate di erent dynamics of change using module FUZZY TEMP integrated in the GRASS4.1 environment. The obtained results were validated through a comparison of the urban boundaries obtained from aerial photographs and those which were generated using the proposed methodology. The results conΓΏrm the potential of the approach to produce realistic simulations of the dynamics of the urbanization process.
π SIMILAR VOLUMES
By analyzing bifurcations from the marginal gain settings of a nonlinear reactor under PIcontrol, several oharacteristios of the closed-loop reactor dynamics are revealed via the center manifold projection and normal form techniques of dynamic singularity theory. Of particular practical interests ar
An approach for fuzzy modeling and decision is presented based upon fuzzy logic inference. Modeling and decision making for process control in a real-world activated sludge process were studied. The modeling work for the process is based upon some historical on-line measurable and off-line sampling