the heat map visualization type in Kibana does not really show what we would expect. It should bring out areas of high incidence.
Consider:
Judging from this image we would expect the densest cluster of data to be at the Ohio-Indiana border.
However, the peakiest data is in the Philadelphia area.
This is because we are creating a heatmap based on aggregation data (at the geohash-cell), but not on the raw incident data. This causes us to overweigh the clump of geohashes in Indiana, but ignore the peaky incidence in Philadelphia.
Ironically, the 'Shaded Geohash Grid' map best approximates a "heat map", albeit a coarsely grained one.
There is no "quick" fix for this. Heat maps should be generated from raw incidence-data. Generating these from a derivative causes unintuitive results.
the heat map visualization type in Kibana does not really show what we would expect. It should bring out areas of high incidence.
Consider:
Judging from this image we would expect the densest cluster of data to be at the Ohio-Indiana border.
However, the peakiest data is in the Philadelphia area.
This is because we are creating a heatmap based on aggregation data (at the geohash-cell), but not on the raw incident data. This causes us to overweigh the clump of geohashes in Indiana, but ignore the peaky incidence in Philadelphia.
Ironically, the 'Shaded Geohash Grid' map best approximates a "heat map", albeit a coarsely grained one.
There is no "quick" fix for this. Heat maps should be generated from raw incidence-data. Generating these from a derivative causes unintuitive results.