In today's article, I will cover a question I got from Devon and Cornwall Police a few weeks back.
The general idea was to show movement between some points that had been collected. These points could be locations from mobile phone locations, sightings, or collected in another way. This isn't that important.
They could look like the example in the image below. In the browser, you can see an ObservationID, an ID for each observation, and a time stamp. In the browser, I have extracted the time from the time stamp to show the time of day only.
Already this gives you some idea of the movement following the time shown.
They would however like to connect the points in the order of the observations to see better how the movement took place.
You can do this with the Create Polylines from Table option on the Spatial tab.
And back in the Coordinate Extractor dialog, these columns have been selected and all I have to do is to ensure the right projection has been selected before I click on the OK button.
With the coordinate columns added and updated, I now only need to create a new table to hold the polyline created. I base my new table on my Observation table.
Now I am ready to create a polyline from my points. I will only get one polyline created as my observations all refer to the same person, car, or whatever it is I am observing. If I had multiple IDs in the ObservationID column, I would end up with a polyline for each.
When I click on the Create Polylines from Table menu item, the Create Polylines from Table dialog is shown.
I start by selecting the table with my observations, then I specify the columns holding the X and Y coordinates, the Key column identifying the individual polylines to create, and the Node Number column identifying the individual nodes on the polyline.
Finally, I select the Target Table to save the polylines and the column to insert the Key value into, too.
I can also select a specific line style for my polylines.
The resulting polyline now clearly shows the movement between the observations.
You could also use the Time Series feature to show the points as time goes by. This could be another way to ilælustrate movement.
Happy #MapInfoMonday
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Peter Horsbøll Møller
Principal Presales Consultant | Distinguished Engineer
Precisely | Trust in Data
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