Pitney Bowes MapInfo Vertical Mapper - Manual (Page 176)

When to Aggregate Data
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Vertical Mapper 3.7
Aggregating Data
Data aggregation is a mathematical process for reducing the number of points in a point file.
Different methods are available to process a point file, but the underlying goal is to spatially group
and statistically merge points that are in close proximity. This not only results in fewer points but also
creates a more uniform distribution of points and point values.
Vertical Mapper provides two options for data aggregation.
• Simple Point Aggregation quickly aggregates data when you do not need to keep track of the
spatial or mathematical properties of the aggregation process at each point;. For example,
knowing the average of the aggregated points is sufficient.
• Point Aggregation With Statistics tracks the statistical parameters associated with each
aggregated point (for example, standard deviation or coefficient of variation). This technique can
also produce a region file displaying the actual circular or square cell region used to gather and
aggregate points. Statistical information is attached as attributes to both the new point file and to
the region file.
When to Aggregate Data
The following reasons for aggregating data are the most common ones.
• There are multiple values at a given location.
• Data is erratic, and the average of the data area represents an appropriate estimate of a point.
• The sum of the data in a given area is required.
• A representative value at an “average” location is acceptable when the location of the data is not
accurate.
• The original data set has too many points to permit efficient processing. The number of points
can be substantially reduced without adversely affecting the accuracy of any operation.
• Values representing specific spacing or area criteria applied over the entire mapped area (most
applicable to the “square cell” method) are required.
Techniques for Data Aggregation
The following data aggregation techniques are available:
• Simple Point Aggregation
• Point Aggregation with Statistics, which comprises the Forward Stepping, Cluster Density, and
Square Cell aggregation techniques.
When you use these techniques, Vertical Mapper creates a new file containing the aggregated
points and leaves the original point file unaltered.