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Sample Data: Castilla-La Mancha Forest Fires

Source Notebook

Locations of forest fires in the Castilla-La Mancha region of Spain between 1998 and 2007, annotated with cause (accident / intentional / lightning / other), area (in hectares), and date marks

Details

Locations of forest fires in the Castilla-La Mancha region of Spain between 1998 and 2007, in a polygonal observation region bounded by the region Rectangle[{4.13112, 18.565}, {391.38, 385.189}] kilometers, annotated with cause (accident / intentional / lightning / other), area (in hectares), and date marks.

Examples

Basic Examples (1) 

In[1]:=
ResourceData[\!\(\*
TagBox["\"\<Sample Data: Castilla-La Mancha Forest Fires\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Castilla-La Mancha Forest Fires-Input",
AutoDelete->True]\), "Data"]
Out[1]=

Summary of the spatial point data:

In[2]:=
ResourceData[\!\(\*
TagBox["\"\<Sample Data: Castilla-La Mancha Forest Fires\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Castilla-La Mancha Forest Fires-Input",
AutoDelete->True]\), "Data"]["Summary"]
Out[2]=

Visualizations (1) 

Plot the spatial point data:

In[3]:=
ListPlot[ResourceData[\!\(\*
TagBox["\"\<Sample Data: Castilla-La Mancha Forest Fires\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Castilla-La Mancha Forest Fires-Input",
AutoDelete->True]\), "Data"], AspectRatio -> 1]
Out[3]=

Analysis (3) 

Compute probability of finding a point within given radius of an existing point - NearestNeighborG is the CDF of the nearest neighbor distribution:

In[4]:=
nnG = NearestNeighborG[ResourceData[\!\(\*
TagBox["\"\<Sample Data: Castilla-La Mancha Forest Fires\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Castilla-La Mancha Forest Fires-Input",
AutoDelete->True]\), "Data"]]
Out[4]=
In[5]:=
maxR = nnG["MaxRadius"]
Out[5]=
In[6]:=
DiscretePlot[nnG[r], {r, maxR/100, maxR, maxR/100}, AxesLabel -> {"radius", "probability"}]
Out[6]=

Mean distance between a typical point and its nearest neighbor (for positive support distribution can be approximated via a Riemann sum of 1-CDF):

In[7]:=
step = maxR/100;
partition = Table[{k, k + step}, {k, 0, maxR, step}];
values = nnG[Mean /@ partition];
In[8]:=
Total[(1 - values)*step]
Out[8]=

Test for complete spacial randomness:

In[9]:=
SpatialRandomnessTest[ResourceData[\!\(\*
TagBox["\"\<Sample Data: Castilla-La Mancha Forest Fires\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Castilla-La Mancha Forest Fires-Input",
AutoDelete->True]\), "Data"], {"PValue", "TestConclusion"}]
Out[9]=

Gosia Konwerska, "Sample Data: Castilla-La Mancha Forest Fires" from the Wolfram Data Repository (2021)  

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