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lesnar February 2016
### Regd. map grid structure in GPS data mining

I have been exploring the GPS data mining literature esp. for problems like anomalous trajectory detection, time travel prediction, etc and one very common method I see is dividing the data or map into grids. Can any one please explain the logic of this? Are the coordinates euclidean in this case? Is grid decomposition really necessary? I would be grateful if someone can also give/ quote some links or materials I should explore. I am new to this field, so please pardon me if the question is very obvious.

Thanks & Regards, Lesnar

No they are not euclidean. But they don't have to be. The grids are not rectangles anymore, but can be treated as such for some operations.

If you create a lat/long grid, then each cell by means of meters is not rectangular. However it defines a zone where you add a counter, which has a clear inside/outside definition. And you can use cartesian operations (Rectangle.inside())

So the lat / lon span is constant for each cell, but not the longitudinal meters span, which shrinks by cos(latitude).

If one needs a grid with equal grid cells sizes by means of meters, then one has to transform the geo coordinates before.

Asked in February 2016

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