In follow-up to our tutorial on Creating Dynamic Marathon Route Visualizations with MapPlus: A No-Code GIS Solution, we compiled a comprehensive dataset of Chinese marathons through automated data processing. This article documents the methodology and technical implementation.


Marathon distribution heatmap in QGIS

Data Sources

Official platform:
China Marathon Website: https://www.runchina.org.cn/

Workflow

Step 1: Race Calendar Scraping

Extracted all race events from the official calendar:

Output: events.json

Step 2: Geocoding Locations

Implemented reverse geocoding for spatial analysis:

  • Used Tianditu Geocoding API
  • Required developer registration: http://lbs.tianditu.gov.cn/home.html

  • API Endpoint:

    http://api.tianditu.gov.cn/geocoder?ds={"keyWord":"Address"}&tk=YOUR_API_KEY
  • Daily quota: 7,000 requests (free tier)
  • Added latitude/longitude to events.json

Step 3: JSON to CSV Conversion

Employed Node.js json2csv package for tabular output

Implementation Code

Complete Node.js solution:

Execution Guide

  1. Install dependencies:

    yarn install  # or npm install

  2. Run sequential processing:

    node index.js              # Scrape initial data
node generateGeoCode.js    # Geocode locations (edit API key)
node json2csv.js            # Generate final CSV

System Requirements

  • Node.js v18+
  • Tianditu developer account
  • Basic command-line proficiency

Technical support available via comments section.

Geospatial Insight: The dataset reveals marathon distribution patterns across China, with higher concentration in eastern regions and seasonal clustering in spring/autumn months.