Part III: Cellular Automata
Discrete spatial models of land-use change with formal transition rules, calibration metrics, and high-performance implementations. From simple stochastic grids to operational urban growth simulators.
Part Overview
Discrete spatial models of land-use change with formal transition rules, calibration metrics, and high-performance implementations. The neighborhood influence function \(\Psi_{ij}\) drives stochastic transitions, calibrated via Figure of Merit (Jaccard index), with SLEUTH and FLUS as operational frameworks.
Key Topics
- • Neighborhood influence function \(\Psi_{ij}\)
- • Stochastic transition probabilities
- • SLEUTH model components
- • Figure of Merit (Jaccard index)
- • FLUS adaptive inertia
- • Fortran CA core
3 chapters | Grid-based urban simulation | From rules to operational models
Chapters
Chapter 1: Stochastic CA
Foundations of cellular automata for land-use modeling. Neighborhood influence functions, stochastic transition probabilities, and calibration with the Figure of Merit (Jaccard index).
Chapter 2: SLEUTH Model
The SLEUTH (Slope, Land-use, Exclusion, Urbanization, Transportation, Hillshade) model and its five growth coefficients. Brute-force calibration, self-modification rules, and scenario forecasting.
Chapter 3: FLUS Adaptive Inertia
The FLUS model combines neural-network suitability with adaptive inertia for multi-type land-use simulation. Roulette-wheel competition and demand-driven allocation across land categories.