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Scharn
City in Limburg, Netherlands
Overview
Scharn is a quaint neighborhood on the edge of Maastricht in Limburg, Netherlands, blending local Dutch character with a peaceful rural ambiance. Its proximity to central Maastricht makes it ideal for visitors seeking a quieter base with easy access to city amenities. Scharn offers a welcoming environment, green spaces, and a taste of genuine local life.
Geographic Context
Jurisdiction
Netherlands
Province
Limburg
Population
—
Time Zone
Europe/Amsterdam
Coordinates
50.85°, 5.73°
Key Metrics
Safety Score · estimate
92
Female Safety
90
LGBTQ+ Safety
85
Traffic Safety
87
Food Safety
97
Monthly Cost · estimate
$2,080
Local Cost
$1,370
Local Income
$2,700
Cashless
91
English
80
Temperature
10.4°C
Summer Avg
18.3°C
Winter Avg
2.6°C
Record High
40.3°C
Record Low
-16.5°C
Humidity
81%
Precipitation
770 mm
Internet Speed
134 Mbps
Upload
27 Mbps
Latency
17 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
100
Walk Score
100
Footways
230.0
Airport
MST
Distance
7 km
Explore
Data sources
Source-backed data
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-09.
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 2026-03-21.
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: 74/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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