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transbigdata-taxi

Clean taxi GPS status anomalies and extract trip origins and destinations.

4|2|Updated Feb 4, 2026
Search Tags:#trajectory#preprocessing#geospatial#gps#transbigdata#taxi#od
One-click install
npx skills add https://github.com/ni1o1/claude-skill-transbigdata --skill transbigdata-taxi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: transbigdata-taxi
Source: https://github.com/ni1o1/claude-skill-transbigdata/tree/main/skills/transbigdata-taxi
Command: npx skills add https://github.com/ni1o1/claude-skill-transbigdata --skill transbigdata-taxi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cleans noisy taxi GPS records and extracts passenger trip origins and destinations to enable rapid OD analysis and trajectory separation for urban transport studies.

Core Features & Use Cases

  • Status cleaning: Remove instantaneous and spurious passenger status changes to improve trip detection quality.
  • OD extraction and aggregation: Derive pickup/dropoff times and locations and aggregate results into grids or administrative areas for heatmaps and flow analysis.
  • Trajectory separation: Split datasets into passenger-carrying and idle (cruising) trajectories for operational analysis and visualization.
  • Use case: Clean a city's taxi GPS feed, extract OD pairs, aggregate to 500m grids, and produce geospatial outputs for mapping and further modeling.

Quick Start

Analyze my taxi_gps.csv to clean status anomalies, extract OD pairs, separate passenger and idle trajectories, and save the OD results as taxi_od.csv.

Frequently Asked Questions about transbigdata-taxi

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract OD pairs from taxi GPS data?▼

Extract OD pairs from taxi GPS data by processing timestamped records with vehicle identifiers, longitude, latitude, and passenger status fields to derive pickup and dropoff times and locations.

What is the best way to clean noisy taxi GPS trajectory records?▼

Clean noisy taxi GPS trajectory records by removing instantaneous and spurious passenger status changes, which improves trip detection quality for accurate transport analysis.

Can I separate passenger-carrying and idle cruising trajectories from vehicle GPS datasets?▼

Separate passenger-carrying and idle cruising trajectories from vehicle GPS datasets by splitting records based on passenger status fields to support operational analysis and visualization.

Does taxi OD extraction support grid aggregation for flow analysis?▼

Taxi OD extraction supports grid aggregation and administrative area aggregation to produce heatmaps, flow analysis, and exportable tabular and geospatial outputs.

What GPS data fields are required for taxi trip segmentation and OD extraction?▼

Taxi trip segmentation and OD extraction require timestamped GPS records containing vehicle identifiers, longitude and latitude coordinates, and passenger status fields.

Why does taxi GPS trip detection produce spurious origin and destination points?▼

Taxi GPS trip detection produces spurious origin and destination points due to instantaneous passenger status anomalies, which require status cleaning to improve extraction quality.

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