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Lachamp-Ribennes
City in Lozère, France
Overview
Lachamp-Ribennes is a picturesque rural commune in the Lozère department of southern France, characterized by its rolling fields, traditional stone houses, and small population. Visitors can expect peace and authentic French village life amid unspoiled countryside.
Geographic Context
Jurisdiction
France
Metropolitan Department
Lozère
Population
375
Time Zone
Europe/Paris
Coordinates
44.63°, 3.22°
Key Metrics
Safety Score · estimate
90
Female Safety
82
LGBTQ+ Safety
65
Traffic Safety
88
Food Safety
95
Monthly Cost · estimate
$1,502
Local Cost
$910
Local Income
$1,600
Cashless
45
English
30
Temperature
8.7°C
Summer Avg
17.2°C
Winter Avg
0.8°C
Record High
37.0°C
Record Low
-16.9°C
Humidity
80%
Precipitation
867 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
MEN
Distance
28 km
Explore
Data sources
Source-backed data
World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-08.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-06.
Estimates and unverified origins
Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-23.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 58/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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