# movement-trajectory

> Claude/Codex skill by [@muend](https://omgskills.com/library/muend/index.md) · 35 stars · Updated 2026-10-17

Movement and trajectory analytics from GPS/GNSS tracks: cleaning, stop/trip detection, road-network map matching, speed/direction, flow aggregation, and origin-destination construction. Use for fleets, human mobility, animal tracking, AIS, or sports tracks. Trigger on GPS points, GPX, trajectories, stop detection, map matching, or timestamped positions per moving object. Also invoke for privacy, aggregation, de-identification, or release of individual trajectories. Use network-accessibility-analysis for hypothetical routes, isochrones, or static OD costs without observed tracks.

Tags: agent-skills, ai, ai-agents, claude-code, codex, geoai, geospatial, gis, github-copilot, google-earth-engine, lidar, machine-learning, postgis, remote-sensing, spatial-analysis, spatial-data-science

## Install

```sh
git clone https://github.com/muend/geoai-skills /tmp/geoai-skills && ln -s /tmp/geoai-skills/skills/movement-trajectory ~/.claude/skills/movement-trajectory
```

## From README

Movement & Trajectory Analytics Purpose: turn noisy timestamped points into defensible movement facts. The recurring failure modes: speed computed through GPS noise (teleporting points → 400 km/h pedestrians), stops invented by signal drift, and privacy-blind delivery of individual-level traces. Data model first A trajectory = ordered fixes per object: (objectid, timestamp, x, y, \[accuracy, ...\]). Before analysis, report per object: fix count, time span, median sampling interval, and interval distribution — sampling rate drives every method choice (1 s vehicle traces and 1 fix/hour animal tags are different problems wearing the same schema).

## Links

- HTML page: https://omgskills.com/library/muend/geoai-skills/skills/movement-trajectory/
- GitHub: https://github.com/muend/geoai-skills
- Author: [@muend](https://omgskills.com/library/muend/index.md)

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