map_spatial_grid

Maps latitude/longitude trajectory data to Geohash grids for aggregation using Python's Geohash encoding.

Updated Jun 2, 2026

Search Tags:#trajectory #GPS #spatial analysis #Geohash #spatial aggregation

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill map-spatial-grid

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: map_spatial_grid
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/spatiotemporal_trajectory/map_spatial_grid
Command: npx skills add https://github.com/bettercallfan/deerflow --skill map-spatial-grid

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps in mapping and aggregating spatial trajectory data, enabling efficient spatial analysis by converting latitude/longitude coordinates into Geohash grids.

Core Features & Use Cases

Spatial Aggregation: Converts spatial data into Geohash grids for efficient analysis.
Geohash Encoding: Utilizes Pure-Python Geohash encoding to map coordinates.
Grid-Level Counting: Aggregates counts at the grid level for spatial analysis.
Use Case: When analyzing GPS trajectories of vehicles or individuals, this Skill can help in visualizing movement patterns and understanding spatial distribution.

Quick Start

Run the following command to map spatial trajectory records into Geohash grids:

cd /mnt/skills/custom/map_spatial_grid
python3 scripts/map_spatial_grid.py --input /path/to/cleaned_points.jsonl --output-dir /path/to/output --geohash-precision 6

Frequently Asked Questions about map_spatial_grid

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

FAQPage Schema

How do I aggregate GPS trajectory data into spatial grids for analysis?▼

Aggregating GPS trajectory data into spatial grids involves mapping latitude and longitude coordinates to Geohash encodings, enabling efficient grid-level counting for spatial analysis of movement patterns.

What is Geohash spatial aggregation used for in trajectory analysis?▼

Geohash spatial aggregation is used for mapping trajectory data into grid cells to analyze traffic patterns, visualize person movement, and aggregate spatial events efficiently.

How do I map latitude and longitude points to Geohash grids using Python?▼

You can map latitude and longitude points to Geohash grids by running a Python script that utilizes Pure-Python Geohash encoding to process cleaned trajectory records and output spatially aggregated grid counts.

What Geohash precision should I use for spatial aggregation of vehicle GPS data?▼

The appropriate Geohash precision for spatial aggregation of vehicle GPS data depends on your required grid size, and you can specify this via a command-line parameter to control the aggregation granularity.

Can I use this spatial aggregation approach without installing external dependencies?▼

Yes, you can use this spatial aggregation approach without external dependencies because the Skill utilizes Pure-Python Geohash encoding to map coordinates directly within the standard Python environment.

What is the best way to visualize spatial distribution from large trajectory datasets?▼

The best way to visualize spatial distribution from large trajectory datasets is to aggregate coordinates into Geohash grids, reducing complex movement patterns into manageable grid-level counts for analysis.