Mean Centre
A spatial statistic representing the average location of a set of points, useful for identifying central tendencies in spatial distributions (inferred from standard GIS usage).
What is the purpose of a Mean Centre?
The average location of a collection of geographic locations is represented by the Mean Centre, a spatial statistic in GIS. It is computed by taking the average of each feature's x (longitude) and y (latitude) coordinates within a dataset.
In GIS, a spatial statistic called the Mean Centre is used to determine the average geographic location of a collection of points. It is computed by taking the average of each feature's x (longitude) and y (latitude) coordinates within a dataset.
Purpose:
Determine Central Tendency: This indicates the "balance point" or geographic centre of a geographical distribution.
Track Movement: Helpful for examining changes over time, including disease outbreaks or the population's shifting centre.
Data Summarisation: Assists in compiling and contrasting spatial distributions between areas or eras.
Example:
The mean centre provides a single point that represents the central location of all stores combined when you map out the locations of every retail establishment in a city.
Related Keywords
A spatial statistical technique for determining the centre of a collection of geographic locations is mean centre computation. The geographic centre of distribution is represented by a single point that is obtained by averaging the x- and y-coordinates of every feature in a dataset. This facilitates the comparison of distributions, the analysis of geographical patterns, and the detection of position changes over time.
The geographic centre, or "average location," of a collection of points can be found using the Mean Centre spatial statistic in GIS. A single central point that reflects the whole distribution is obtained by averaging the x and y coordinates of every feature. This tool can be used to analyse geographic data clustering or dispersion, compare location changes over time, and comprehend spatial patterns.
A GIS technique called "spatial mean centre analysis" determines the average position of spatial features, displaying the distribution's centre point for pattern analysis.
A spatial analysis method for locating the centre of a collection of geographic points in a geographic information system is the Mean Centre Point Method. It creates a single point that serves as the "geometric centre" of the distribution by averaging the x- and y-coordinates of every feature in a dataset. This approach is helpful for comparing distributions, finding spatial patterns, and examining how the central tendency of geographic data has changed over time.