# DBSCAN clustering with Haversine metric
**URL:** https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685
**Category:** Geo
**Tags:** clustering
**Created:** [October 24, 2024, 8:57am UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685 "2024-10-24T08:57:49Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@miguelborrero](https://discourse.julialang.org/u/miguelborrero)
#### Post date: [October 24, 2024, 8:57am UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685/1 "2024-10-24T08:57:50Z")
Hi there,
I have an array of points (latitude, longitude) in radians and I am trying to use the package `Clustering.jl` to cluster my points. In the documentation it seems like a metric can be given, the default being: `Euclidean()` however I need to use the Haversine metric and I dont seem to find the way of using such metric. Any ideas?
Thanks a lot!
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### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [October 24, 2024, 9:50am UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685/2 "2024-10-24T09:50:33Z")
Perhaps you can try the clustering API in GeoStats.jl. I believe we have all Clustering.jl models over there too. The latlon will be taken care of for you internally. But it is been a while since the last time we tested DBSCAN
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### Author:  [@evetion](https://discourse.julialang.org/u/evetion)
#### Post date: [October 24, 2024, 11:02am UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685/3 "2024-10-24T11:02:09Z")
Looking at the documentation it seems that only DBScan takes a metric keyword argument:
[DBSCAN ยท Clustering.jl](https://juliastats.org/Clustering.jl/stable/dbscan.html#Clustering.dbscan).
You should be able to pass `Haversine()` to it instead of `Euclidean()`.
Some other (not all) methods (e.g. hierarchical, k-mediods), take a distance matrix, instead of a data matrix, so you could compute all `pairwise` distances yourself with `Haversine()` first.
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### Author:  [@miguelborrero](https://discourse.julialang.org/u/miguelborrero)
#### Post date: [October 24, 2024, 11:10am UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685/4 "2024-10-24T11:10:58Z")
I tried and passing `Haversine()` did not work (or other transformations of the same command). Yep, I could do the pairwise distance but as the documentation says, that method results in efficiency losses so I was wondering whether it could be avoided. After all, passing some haversine version of `Euclidean()` seems like it should be there.
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### Author:  [@joa-quim](https://discourse.julialang.org/u/joa-quim)
#### Post date: [October 24, 2024, 12:53pm UTC](https://discourse.julialang.org/t/dbscan-clustering-with-haversine-metric/121685/5 "2024-10-24T12:53:46Z")
Alternative: project the geogs into a Cartesian system and use euclidean distances. And at the end convert back to geogs.