Montevideo Urban Trees

Interactive map to explore the 234,464 trees lining the sidewalks of Montevideo, Uruguay.

🌳 View the map

Trees Species Next.js Mapbox

• 🗺️ Interactive map with all trees colored by species
• 🌲 Info panel with tree details (species, height, condition, location)
• 📷 Species photos from Wikipedia with carousel
• 🔍 Filter by species with search and dynamic count
• 🏘️ Filter by zone (18 CCZ municipal zones)
• 📍 Address search using Mapbox Geocoding
• 📊 Statistics modal with top species chart
• 🔗 Share tree via URL deep linking
• 📍 Geolocation to center the map on your location
• 📝 Report missing tree to contribute to the map
• 🌙 Dark/Light mode with dynamic map basemap
• 🌐 Internationalization (Spanish/English)
• 🌸 Species details - blooming calendar, height ranges, flower colors, growth rates
• 🌿 Native/introduced badges with species origin info
• 📶 Offline support with service worker caching
• 📱 Responsive - works on mobile and desktop

arbolesmvd/
├── .github/workflows/ # CI/CD (tests + build)
├── data/ # Raw and processed data
│ ├── raw/ # Census CSVs, WFS GeoJSON
│ └── processed/ # Unified dataset with coordinates
├── scripts/ # Python processing scripts
│ ├── merge_datasets.py
│ ├── geocode_final.py
│ ├── clean_common_names.py # Species name normalization
│ └── generate_geojson.py # Web data generation
└── web/ # Next.js application
 ├── src/
 │ ├── app/ # Pages (App Router)
 │ └── components/ # Map, TreePanel, Filters, StatsModal, etc.
 └── public/ # Tree data (PMTiles + gzipped JSON)

cd web
npm install
echo "NEXT_PUBLIC_MAPBOX_TOKEN=your_token" > .env.local
npm run dev

Open http://localhost:3000

cd web
npm test # Watch mode
npm run test:run # Single run (CI)
npm run test:coverage # Coverage report

The raw census data was cleaned and normalized:

• 100% species coverage - all 234,464 trees have common names assigned
• 359 unique species - duplicates and variants unified
• 566 scientific name corrections - fixed typos (Bahuinia→Bauhinia, etc.)
• 2,553 data entry fixes - corrected mismatched species names
• Vector tiles - PMTiles format (17MB, all points at all zoom levels)
• Gzip compression - trees-data.json.gz (4.1MB vs 54MB)

Run the data pipeline:

python scripts/clean_common_names.py # Clean species names
python scripts/generate_geojson.py # Generate web files
tippecanoe -o web/public/trees.pmtiles --force --layer=trees \
 --minimum-zoom=10 --maximum-zoom=16 \
 --no-feature-limit --no-tile-size-limit -r1 web/public/trees.json
gzip -k -9 web/public/trees-data.json # Compress data

• Tree Census 2008 - Montevideo City Government
• GeoWeb Montevideo - Geographic layers

Based on Gieß den Kiez, a Berlin project that maps urban trees.

Created by Mathi Fonseca

Data comes from the 2008 municipal census. Some locations may have changed.