The simulation in R is presented here:

# Forest matrix trees encoding:

# 3 – green, 2 – burning, 1 – burnt, 0 – no tree

simulate

**<-****function****(**forest.density**=**0.6, size**=**251**)****{** forest

**<-**matrix**(**3*****rbinom**(**size**^**2, 1, forest.density**)**, nrow

**=**size**)** forest

**[**1,**]****<-**2**while**

**(**sum

**(**forest

**==**2

**)**

**>**0

**)**

**{**

list.red

**<-**which**(**forest**==**2**)**# find spots touching burning trees

ignite.x

**<-**1**+**floor**((**list.red**-**1**)****/**size**)** ignite.x

**<-**rep**(**ignite.x, each**=**4**)****+** rep

**(**c**(**1,**-**1, 0,0**)**, length**(**ignite.x**))** ignite.y

**<-**1**+****((**list.red**-**1**)**%% size**)** ignite.y

**<-**rep**(**ignite.y, each**=**4**)****+** rep

**(**c**(**0, 0, 1,**-**1**)**, length**(**ignite.y**))** include

**<-****(**ignite.x**>**0**)****&****(**ignite.x**<=**size**)****&****(**ignite.y

**>**0

**)**

**&**

**(**ignite.y

**<=**size

**)**

ignite.n

**<-****(**ignite.x**[**include**]****-**1**)*******size**+** ignite.y

**[**include**]**# ignite green trees

is.green

**<-****(**forest**[**ignite.n**]****==**3**)** forest

**[**ignite.n**[**is.green**]]****<-**2# trees burn for one period

forest

**[**list.red**]****<-**1**}**

return

**(**1**-**sum**(**forest**[-**1,**]****==**3**)****/**sum**(**forest**[-**1,**]****>**0**))****}**

The only thing left was to check that the results produced by NetLogo and R implementations are identical. I have simulated both models 1000 times for forest density equal to 60%. Here is the plot comparing percent burned density estimates and Kolmogorov-Smirnov test p-value.

It can be concluded that for the parametrization I have selected models produce similar results.

## No comments:

## Post a Comment