Volunteer Hotspot Finder

Find data gaps in eBird coverage and propose survey missions to volunteers.

Status

🔨 In Progress — Foundation phase

Problem

Birdwatchers typically visit popular, already well-surveyed locations. This creates massive "blind spots" — areas with low observation coverage despite high biodiversity potential.

Solution

Grid-based analysis that identifies geographic cells with low eBird coverage, ranks them by priority, and outputs actionable survey recommendations.

Installation

pip install birdlife-hotspot-finder

Usage

from birdlife_hotspot_finder import HotspotFinder

finder = HotspotFinder.from_env()  # Reads EBIRD_API_KEY
gaps = await finder.find_gaps(region="RS", limit=10)

Output Formats

• JSON (API response envelope)
• CSV (spreadsheet import)
• GeoJSON (maps — Leaflet, QGIS)

API Response Convention

Follows BirdLife API Response Convention:

{
  "data": [
    {
      "locationID": "...",
      "name": "Grid cell 44.8N 20.4E",
      "decimalLatitude": 44.8,
      "decimalLongitude": 20.4,
      "extensions": {
        "coverage.checklistCount": "0",
        "coverage.gapType": "spatial",
        "coverage.priorityScore": "0.85"
      }
    }
  ],
  "meta": {
    "resultType": "coverage-gaps",
    "gridSizeKm": "10"
  }
}

Community

License

MIT — see LICENSE