# Sample Data: Redwood Saplings

Locations of redwood saplings (young slender trees), annotated with binary indicator

## Details

Locations of redwood saplings (young slender trees) in the observation region Rectangle[{0, 0}, {1, 1}], annotated with binary categorical indicator (0 or 1).

## Examples

### Basic Examples (1)

 In[1]:=
 Out[1]=

Retrieve the default content:

 In[2]:=
 Out[2]=

### Visualizations (3)

Plot the spatial point data:

 In[3]:=
 Out[3]=

Visualize the data points with annotations:

 In[4]:=
 Out[4]=

Visualize the smooth point density of the data:

 In[5]:=
 Out[5]=
 In[6]:=
 Out[6]=

### 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[7]:=
 Out[7]=
 In[8]:=
 Out[8]=
 In[9]:=
 Out[9]=

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[10]:=

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

 In[11]:=
 Out[11]=

Test for complete spatial randomness:

 In[12]:=
 Out[12]=

Gosia Konwerska, "Sample Data: Redwood Saplings" from the Wolfram Data Repository (2022)