Plan the pattern.
Explore the consequences.
HexPlan is a community-planning simulation. You set a direction for growth, preservation, and investment; the model lets local conditions, neighboring places, and uncertainty turn that direction into a range of plausible 25-year futures.
HexPlan does not claim to forecast one inevitable future. It makes assumptions visible, then helps you see how those assumptions can compound across a community. The useful question is not “what will happen?” but “what patterns become likely if we choose this direction?”
Choose one planning direction
Or set each policy position
Raises or lowers the baseline chance that a place advances.
Rewards locations already connected to the central urban core.
Adds friction to changing lower-intensity contexts.
Three ingredients, one yearly transition.
The model tests each hex every year. A location can stay as it is or advance one context step. It does not leap across the map, and its future depends on the surrounding system.
What is around it?
Nearby higher-intensity places, access to the core, and local suitability create a bounded transition potential for each hex.
How much change is allowed?
Development has inertia. Policy can pace or resist change by context, especially in rural and town areas.
What happens this run?
The transition is sampled, so small differences can accumulate. Repeat runs reveal a range of plausible planning outcomes.
A logistic function keeps the local transition potential bounded between 0 and 1 while allowing the scenario weights to express different planning hypotheses.
P* = σ(β₀ + βₙNₕ + βₐAₕ + βₛSₕ)That local potential is then tempered by time since the last change and a context-specific policy gate. The result is sampled once for every hex, every year.
P(advance) = P* × (1 − e−t/τ) × FcontextFor the uncertainty map: 100 runs produce a final-state distribution for each hex. Normalized Shannon entropy shows where those plausible futures disagree most.
H = −Σ p(state) log₂ p(state) / log₂(5)The outcome is a conversation starter.
Use HexPlan to surface trade-offs early: where to concentrate investment, which contexts to protect, and where uncertainty deserves more investigation before a long-range commitment.
Compare strategies, not just maps
Run the same community under a few policy directions. The differences reveal which assumptions truly shape the pattern.
Read the edges carefully
Areas that vary most across runs are not errors. They are places where future context is sensitive to the choices and conditions in the scenario.
Bring infrastructure into the picture
Context change alters the demand, exposure, and operating conditions that transportation, water, energy, and public systems must serve.
Keep uncertainty in view
The simulation is designed for exploratory planning. It supports better questions under deep uncertainty; it does not erase the need for local evidence and judgment.
The model illustrated here is a simplified, approachable interpretation of the HexPlan spatial Markov framework: hexagonal context units, neighborhood influence, accessibility, suitability, persistence, policy friction, and stochastic scenario simulation.
See where a community's future could go.
Use HexPlan to try a planning direction, see the spatial pattern it encourages, and have a more concrete conversation about the choices in front of a community.