Sample Data: Fertile Crescent Sites

Source Notebook

Archeological sites in the Fertile Crescent region annotated with names

Details

Locations of some archeological sites in the region called Fertile Crescent, annotated with names.

Examples

Basic Examples (1) 

In[1]:=
ResourceData[\!\(\*
TagBox["\"\<Sample Data: Fertile Crescent Sites\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Fertile Crescent Sites-Input",
AutoDelete->True]\), "Data"]
Out[1]=

Summary of the spatial point data:

In[2]:=
ResourceData[\!\(\*
TagBox["\"\<Sample Data: Fertile Crescent Sites\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Fertile Crescent Sites-Input",
AutoDelete->True]\), "Data"]["Summary"]
Out[2]=

Visualizations (1) 

Plot the spatial point data:

In[3]:=
GeoListPlot[ResourceData[\!\(\*
TagBox["\"\<Sample Data: Fertile Crescent Sites\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Fertile Crescent Sites-Input",
AutoDelete->True]\), "Data"]]
Out[3]=

Analysis (4) 

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[\!\(\*
TagBox["\"\<Sample Data: Fertile Crescent Sites\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Fertile Crescent Sites-Input",
AutoDelete->True]\), "Data"]]
Out[4]=
In[5]:=
maxR = nnG["MaxRadius"]
Out[5]=
In[6]:=
res = Table[nnG[r], {r, range = Range[maxR/100, maxR, maxR/100]}];
ListPlot[Transpose[{range, res}], AxesLabel -> {"radius", "probability"}]
Out[7]=

NearestNeighborG as the CDF of nearest neighbor distribution can be used to compute the mean distance between a typical point and its nearest neighbor - the mean of a positive support distribution can be approximated via a Riemann sum of 1- CDF. To use Riemann approximation create the partition of the support interval from 0 to maxR into 100 parts and compute the value of the NearestNeighborG at the middle of each subinterval:

In[8]:=
step = maxR/100;
middles = Subdivide[step/2, maxR - step/2, 99];
values = nnG[middles];

Now compute the Riemann sum to find the mean distance between a typical point and its nearest neighbor:

In[9]:=
Total[(1 - values)*step]
Out[9]=

Test for complete spacial randomness:

In[10]:=
SpatialRandomnessTest[ResourceData[\!\(\*
TagBox["\"\<Sample Data: Fertile Crescent Sites\>\"",
#& ,
BoxID -> "ResourceTag-Sample Data: Fertile Crescent Sites-Input",
AutoDelete->True]\), "Data"], {"PValue", "TestConclusion"}]
Out[10]=

Gosia Konwerska, "Sample Data: Fertile Crescent Sites" from the Wolfram Data Repository (2022)  

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