Point Pattern Analysis and Its Use in Descriptive Statistics (Frequency and Density, Central Tendencies, Standard Distance Deviation) (Especially for GATE-Geospatial 2022)

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Point Pattern Analysis

Point pattern analysis has become an extremely important application in recent years, particularly in crime analysis, in epidemiology and in facility location planning and management.

The most common techniques for analyzing spatial distributions are applied to point patterns. Point objects can be individual trees, houses, animals, street lights and even cities, depending on the scale. Point objects can be represented in linear or area form as well.

It deals with the examination and evaluation of spatial patterns and the processes of point features.

Image Shows Point Patterns is the Density of the Point Distr …

Descriptive Statistics Based on Point Pattern Analysis

Some other basic questions we can use the simple descriptive statistics that we would use for a numerical dataset: Count, Mean, Median and Standard Deviation. Applying these, we can describe how dense a pattern is, where the center of a set of points is, and how dispersed these points are.

Diagram Shows How Dense a Patterns

Frequency and Density

The simplest measure of point patterns is the density of the point distribution. This is done by dividing the number of points by the total area in which the point exists. Population density, tree density, etc. are used to provide a measure of the compactness of points. With that information, we can compare the densities to those of comparable points.

Frequency is the most basic way of evaluating a spatial pattern and simply counting the number of points in your area. To get density, you divide this total by unit of area or time in whatever units you deem are most appropriate: Hospital per square mile, violent crimes per month, etc.

Central Tendencies

Many of the standard descriptive statistics can be applied or slightly modified to describe spatial data. Mean center is simply the mean of the X and the mean of the Y coordinates for your set of points, giving you the middle of your point pattern. Median Center is a slightly different way to calculate middle.

This Figure Shows Descriptive Spatial Statistics

Standard Distance Deviation

It is the standard deviation of the distance of each point from the mean center. Standard Deviational Ellipse is a modified version of standard distance that captures the shape of this distribution by showing any directional bias in the pattern.

This Figure Shows Standard Distance Deviation

Other Statistical Operations

These are some of the many spatial statistics that can be treated as analogous to numerical data sets. Just as one can examine the median, or the distribution of a numerical data set, one can perform the same operations on spatial statistics.

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