Point Data Analysis

There are 3 types of point data analysis which befalls under:

1. Spatial density
2. Spatial Centography
3. Spatial Pattern

Simple Density

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Sampling Density

Centography which means by spatially equivalent for conventional descriptive statistics.

• Measures of Central Tendency

1. Mean centre
2. Weighted mean centre

• Measure of dispersion

1. Standard distance

Determine or conclude whether or not the pattern is random, clustered or dispersed:

• Quadrat analysis

Besides determining density, the quadrat analysis is useful for finding outpoint pattern. For determining point pattern via quadrat analysis, a Variance to Mean Ratio (VMR) is put in place.

1. VMR close to zero, pattern is dispersed 
2. VMR around 1, pattern is random
3. VMR above 1, pattern is clustered

• Nearest Neighbour Index

To overcome the weakness of quadrat analysis, a Nearest Neighbour Index (NNI) is used where the basis  of distnces between points are implemented.

NNI compares the mean of the distance observed between each point and its nearest neighbour with the expected mean distance that would occur if the distribution were random.

1. For a random pattern, NNI = 1
2. For a dispersed pattern, NNI = 2.149
3. For a clustered pattern, NNI = 0