I have a point file extracted from an AIS network. 1 year is about 900 million points. Each point has a timestamp.
I want to make a heatmap for a longer period of time, but I want the heatmap to take the timestamp into account. I only want the heatmap to show me hotspots if the points are within a certain distance within a limited timeframe.
I'll try to explain my needs further with a hypothetical example: Imagine a school with a centre hallway and 2 classrooms on either side of the hallway (4 classrooms in total).
At 1500 the bell rings, all the children jump out of their seat, run to the door into the central hallway, and run to the main door that leads to the playground.
At 1500 the bell rings, and one by one, the children get up from their seat, walk to the door into central hallway, 1st classroom 1, then 2, then 3, then 4. Forming a nice neat line to the main door.
At 1500 the bell rings, the two classrooms on the left side of the centre hallway behave as in Situation 1, and on the right side of the central hallway behave as in Situation 2.
In a normal heatmap, that doesn't take a timefactor into account, you will see similar results on all three situations.
What I am trying to accomplish is show congestion. I think that: If I am able to get the timestamp of every datapoint into the mix the heatmap will reveal in:
- Situation 1: Hotspots in front of all the doors that lead to the central hallway and a hotspot in front of the main door to the playground.
- Situation 2: No hotspots.
- Situation 3: Hotspots in front of the doors on the left side of the central hallway and a smaller hotpot in front of the main door (because the chaotic behavior of the left classrooms, influences the behavior of the right classrooms)
Is there a workflow, methodology or algorithm available that can build a heatmap with a timefactor?