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scripts/overlay/cities-geojson-generate.py
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45
scripts/overlay/cities-geojson-generate.py
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#!/usr/bin/env python3
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"""
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convert_cities.py
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BoopLabs Pupmap Europe/Nordics Cities GeoJSON
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Version: 2025-10-03
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"""
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import geopandas as gpd
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# ---------- User paths ----------
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cities_shp = "ne_10m_populated_places.shp"
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output_dir = "/mnt/storage/docker-data/pupmap/www/data/"
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# ---------- Europe + Nordics ISO3 ----------
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europe_nordics = [
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'ALB','AND','AUT','BEL','BIH','BGR','HRV','CYP','CZE','DNK','EST','FIN','FRA','DEU',
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'GRC','HUN','ISL','IRL','ITA','LVA','LTU','LUX','MLT','MDA','MCO','MNE','NLD','NOR',
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'POL','PRT','ROU','RUS','SMR','SRB','SVK','SVN','ESP','SWE','CHE','UKR','GBR','VAT'
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]
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# ---------- Load cities shapefile ----------
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print("Processing cities...")
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cities = gpd.read_file(cities_shp)
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# Filter Europe/Nordics
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if 'ADM0_A3' in cities.columns:
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cities_filtered = cities[cities['ADM0_A3'].isin(europe_nordics)].copy()
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else:
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cities_filtered = cities.copy() # fallback: include all
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# Rename columns to match map expectations
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cities_filtered = cities_filtered.rename(columns={
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'NAME': 'name',
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'ADM0NAME': 'country',
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'POP_MAX': 'population'
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})
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# Keep only required columns
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cities_filtered = cities_filtered[['name','country','population','geometry']]
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# Save to GeoJSON
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cities_geojson_path = output_dir + "world_cities_europe.geojson"
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cities_filtered.to_file(cities_geojson_path, driver='GeoJSON')
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print(f"Saved {cities_geojson_path} ({len(cities_filtered)} features)")
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