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Return to Insilico - Discrete Modeling Development




This short unit about the spreading of forest fires is intended to teach some of the basics of using a simple pre-made model/simulation. While there are many benefits to using this model, the ability to physically verify the results proves to be difficult. It turns out that the rudimentary simulation of a wild fire spreading through a forest of varying densities can be implemented in a wide range of tools including NetLogo, AgentSheets, Vensim, Excel, and possibly others. Thus, this single model can teach the basics of simulation techniques like agent modeling, cellular automata, and systems dynamics without requiring students to relearn or rediscover what results to expect and allows them to focus on the methods and the techniques.

Background Reading

For Teachers/TAs

WildFire Modeling (wikipedia)

Agent-based modeling and simulation of wildland fire suppression

For Students

Cellular Automata (wikipedia)

History of Cellular Automata

Reference Material

Lecture Notes

Lecture 1

Lecture 2

Some "why we care" to tie it back together at the end, like how we can use it for estimating and planning, would be nice.


This lab will consist of learning how to use NetLogo's wildfire model to see how minor changes in parameters can, under certain circumstances, producing wildly different results.

The student should first see the tediousness of the process of:

  1. Set the desired parameter to some value
  2. Run the model
  3. Record the proper results into a spreadsheet
  4. Increment the parameter and repeat steps (2-4)

The next step is to learn how to use NetLogo's parameter sweep ("Behavior Space") functionality to automate this process.

Ideally, when they run the manual parameter sweep they'll get results that tell them very little about how the density of the affects how much of it gets burnt. This will stress the importance of taking representative data sets to be able to accurately analyze the model.

Use this exercise to illustrate 3 points in a range (looks linear) compared to 8 points (the true sigmoid shape is revealed). Notion of a critical parameter.

A continuation of the lab would be to use one of the extended models (likely written by one of the TAs) and run parameter sweeps to understand how the different features can dramatically change the results.


Bill of Materials

As long as the students don't try to actually burn down a forest to validate these models, there is no cost for this lab.


Don't forget to mark the correct answers by bolding them.

CRS Questions

  1. A technique called "systematic dynamical conflagration"
  2. Going out back campus and ....
  3. Coding all the properties of wood into a program
  4. A technique called "cellular automata"

This one might be a bit facetious.  :P

  1. Automated Telecomune
  2. Tessellation Automata
  3. Biological Automated Simulation
  4. Systems Dynamics
  1. Stephen Wolfram
  2. John von Neumann
  3. Alan Turing
  4. Stanislaw Ulam

Quiz Questions

* A question.

Fire Metadata


This should be very early in the semester as it is a fairly simple and short topic. Given its simplicity, it should only be a single week.

Concepts and Techniques

This unit should teach the basics of using someone else's model, as well the importance of conducting multiple runs with different parameters in order to gain an accurate understanding of the effect of the model. Also VVA, if we're talking about how this model isn't a good indicator of real life. And don't forget cellular automata.

General Education Alignment

Analytical Reasoning Requirement

Abstract Reasoning

*** Analysis of this unit's support or not for this item.
Nice work!

Quantitative Reasoning

Scientific Inquiry Requirement

Scaffolded Learning

The NetLogo model(s) in question are easy to use and easy to witness the effect of changing parameters to obtain different results. As well there are fairly clear extensions for the student inclined towards taking those steps. It would be nice if we had a set of extension questions for students interested in going further. Possibly trying to get certain situations to occur (a larger percentage of the time) by changing different variables. Or just trying to get certain situations to occur.

Inquiry Based Learning

This unit should be able to pique the curiosity of the student, most likely in the form of the question: "Why is that that a single variable can have such a dramatic effect on the output of a system?" I think there's also a lot to be said that the entire lab is based on tweaking parameters and so seeing what happens with different experiments.

To Do

Personal tools
this semester