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92cf271 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 | """Fetch road network classification data from OpenStreetMap Overpass API.
Usage:
python scripts/data/fetch_road_network.py [--cities mumbai,chennai] [--all]
Fetches road classification data (motorway/trunk/primary/secondary/tertiary/residential)
and maps each to Indian road authority ownership.
"""
from __future__ import annotations
import argparse
import csv
import json
import sys
import time
from pathlib import Path
try:
import httpx
except ImportError:
print("ERROR: httpx required. Run: pip install httpx")
sys.exit(1)
PROJECT_ROOT = Path(__file__).resolve().parents[2]
OUTPUT_DIR = PROJECT_ROOT / 'data' / 'civic_intel' / 'road_network'
BBOXES_FILE = PROJECT_ROOT / 'data' / 'civic_intel' / 'city_bboxes.json'
OVERPASS_URL = 'https://overpass-api.de/api/interpreter'
# Indian road authority mapping
AUTHORITY_MAP = {
'motorway': {'authority': 'NHAI', 'category': 'Expressway', 'maintenance': 'Central'},
'motorway_link': {'authority': 'NHAI', 'category': 'Expressway Ramp', 'maintenance': 'Central'},
'trunk': {'authority': 'NHAI', 'category': 'National Highway', 'maintenance': 'Central'},
'trunk_link': {'authority': 'NHAI', 'category': 'NH Ramp', 'maintenance': 'Central'},
'primary': {'authority': 'State PWD', 'category': 'State Highway', 'maintenance': 'State'},
'primary_link': {'authority': 'State PWD', 'category': 'SH Ramp', 'maintenance': 'State'},
'secondary': {'authority': 'State PWD', 'category': 'Major District Road', 'maintenance': 'State'},
'secondary_link': {'authority': 'State PWD', 'category': 'MDR Link', 'maintenance': 'State'},
'tertiary': {'authority': 'Municipal Corporation', 'category': 'Other District Road', 'maintenance': 'Municipal'},
'tertiary_link': {'authority': 'Municipal Corporation', 'category': 'ODR Link', 'maintenance': 'Municipal'},
'residential': {'authority': 'Municipal Corporation', 'category': 'Residential Street', 'maintenance': 'Municipal'},
'unclassified': {'authority': 'Municipal/Panchayat', 'category': 'Village Road', 'maintenance': 'Local'},
'living_street': {'authority': 'Municipal Corporation', 'category': 'Residential', 'maintenance': 'Municipal'},
'service': {'authority': 'Private/Municipal', 'category': 'Service Road', 'maintenance': 'Private'},
}
ROAD_TYPES = ['motorway', 'trunk', 'primary', 'secondary', 'tertiary', 'residential']
def build_road_query(bbox: list[float]) -> str:
"""Build Overpass query for road network."""
s, w, n, e = bbox
type_filter = '|'.join(ROAD_TYPES)
return f"""[out:json][timeout:120];
(
way["highway"~"^({type_filter})(_link)?$"]({s},{w},{n},{e});
);
out tags center;"""
def fetch_roads(city: str, bbox: list[float]) -> list[dict]:
"""Fetch road data for a city."""
query = build_road_query(bbox)
try:
with httpx.Client(follow_redirects=True) as c:
r = c.get(
OVERPASS_URL,
params={'data': query},
headers={'User-Agent': 'SafeVixAI-CivicIntel/1.0'},
timeout=120,
)
r.raise_for_status()
data = r.json()
elements = data.get('elements', [])
roads = []
for el in elements:
tags = el.get('tags', {})
highway = tags.get('highway', '')
center = el.get('center', {})
auth_info = AUTHORITY_MAP.get(highway, {
'authority': 'Unknown',
'category': highway,
'maintenance': 'Unknown',
})
roads.append({
'osm_id': el.get('id', 0),
'name': tags.get('name', tags.get('ref', '')),
'name_local': tags.get('name:hi', tags.get('name:ta', tags.get('name:te', ''))),
'highway_type': highway,
'road_category': auth_info['category'],
'authority': auth_info['authority'],
'maintenance_level': auth_info['maintenance'],
'ref': tags.get('ref', ''),
'lanes': tags.get('lanes', ''),
'surface': tags.get('surface', ''),
'maxspeed': tags.get('maxspeed', ''),
'oneway': tags.get('oneway', ''),
'lit': tags.get('lit', ''),
'center_lat': center.get('lat', ''),
'center_lon': center.get('lon', ''),
'city': city,
})
return roads
except Exception as e:
print(f" ERR {city}: {e}")
return []
def main():
parser = argparse.ArgumentParser(description='Fetch road network classification')
parser.add_argument('--cities', help='Comma-separated city names')
parser.add_argument('--all', action='store_true', help='Process all cities')
args = parser.parse_args()
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
# Load bboxes
if not BBOXES_FILE.exists():
print(f"ERROR: {BBOXES_FILE} not found")
sys.exit(1)
with open(BBOXES_FILE, 'r', encoding='utf-8') as f:
raw_bboxes = json.load(f)
metro_data = raw_bboxes.get('metros', raw_bboxes)
all_bboxes = {}
for city_name, city_info in metro_data.items():
if isinstance(city_info, dict) and 'bbox' in city_info:
all_bboxes[city_name] = city_info['bbox']
elif isinstance(city_info, list):
all_bboxes[city_name] = city_info
if args.cities:
cities = [c.strip() for c in args.cities.split(',')]
elif args.all:
cities = sorted(all_bboxes.keys())
else:
cities = sorted(all_bboxes.keys())[:5] # Default: top 5
print()
print('=' * 56)
print(' SafeVixAI Road Network Classifier')
print('=' * 56)
print(f' Cities: {len(cities)}')
print(f' Output: {OUTPUT_DIR}')
print()
summary = {}
csv_fields = [
'osm_id', 'name', 'name_local', 'highway_type', 'road_category',
'authority', 'maintenance_level', 'ref', 'lanes', 'surface',
'maxspeed', 'oneway', 'lit', 'center_lat', 'center_lon', 'city'
]
for i, city in enumerate(cities):
if city not in all_bboxes:
print(f" SKIP {city}: no bbox")
continue
print(f"[{i+1}/{len(cities)}] Fetching {city}...")
roads = fetch_roads(city, all_bboxes[city])
if roads:
outfile = OUTPUT_DIR / f'{city}_roads.csv'
with open(outfile, 'w', newline='', encoding='utf-8') as f:
writer = csv.DictWriter(f, fieldnames=csv_fields)
writer.writeheader()
writer.writerows(roads)
# Count by type
by_type = {}
for r in roads:
t = r['highway_type']
by_type[t] = by_type.get(t, 0) + 1
summary[city] = {
'total': len(roads),
'by_type': by_type,
}
top_types = sorted(by_type.items(), key=lambda x: x[1], reverse=True)[:3]
top_str = ', '.join(f'{t}={c}' for t, c in top_types)
print(f" OK {city}: {len(roads):,} roads [{top_str}]")
else:
print(f" EMPTY {city}")
time.sleep(2) # Be respectful to Overpass
# Save summary
summary_file = OUTPUT_DIR / 'road_network_summary.json'
summary_file.write_text(json.dumps(summary, indent=2), encoding='utf-8')
total = sum(v['total'] for v in summary.values())
print()
print(f' Total: {len(summary)} cities, {total:,} road segments')
print(f' Output: {OUTPUT_DIR}')
print()
if __name__ == '__main__':
main()
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