---
title: nexyron.temporal_geo_dbscan
url: https://nexyron.tech/docs/cypher/procedures/temporal-and-streaming/nexyron-temporal-geo-dbscan
description: Cluster one temporal property history of geographic points using DBSCAN.
---

# nexyron.temporal_geo_dbscan

## Generic Description

Cluster one temporal property history of geographic points using DBSCAN.

Simple example:

```cypher
CALL nexyron.temporal_geo_dbscan(42, 'position', 0, 10000, 75.0, 3)
YIELD ts, lat, lon, cluster_id, is_noise
RETURN ts, lat, lon, cluster_id, is_noise
```

Temporal and streaming procedures inspect registered temporal history, rollups, time ranges, and global event timelines.

## Consumer-Level Explanation

Use this procedure when one node has a temporal location history and you want to group those historical samples into dense geographic clusters.

Inputs:

-   `node_id`
-   `property`
-   `from`
-   `to`
-   `eps_m`
-   `min_pts`

The property history can currently hold either:

-   native point values
-   object payloads like `{lat, lon}` or `{latitude, longitude}`

## Conceptual Explanation

This procedure does not introduce a new geo-track storage model.

It uses the current temporal-property model:

1.  read hidden temporal history for one node property
2.  normalize each value into a WGS84 point
3.  run in-memory DBSCAN over the filtered time range
4.  return cluster labels for each historical sample

That keeps geo clustering on top of the current architecture instead of adding a second temporal geo subsystem.

## More Detailed Explanation

In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with `YIELD` and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.

## Advanced Example

```cypher
MATCH (r:Runner {name: 'Mia'})
CALL nexyron.temporal_geo_dbscan(id(r), 'position', 1710000000000, 1710086400000, 60.0, 4)
YIELD ts, value, lat, lon, cluster_id, is_noise
RETURN ts, lat, lon, cluster_id, is_noise, value
ORDER BY ts
```

## Real Use Cases

-   find repeated stop zones or dwell areas in one runner, courier, or vehicle history
-   separate dense local movement from isolated outlier samples
-   pre-label historical temporal positions before session alignment or downstream feature work
-   compose the procedure output with `YIELD`, `WITH`, and `RETURN` rather than hiding follow-up logic outside Cypher

## Real Limitations And Tradeoffs

-   This first implementation is per-subject and bounded-window oriented.
-   It uses direct point-to-point distance checks, not a geospatial index.
-   It currently clusters WGS84 points only; cartesian temporal points are not part of this procedure.
-   procedure calls are explicit contracts; missing state, unsupported parameters, or absent artifacts should fail rather than silently falling back