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Schönthal

City in Bavaria, Germany

Overview

Schönthal is a picturesque village in Bavaria renowned for its serene landscapes, historic monastery, and close-knit community. With under 2,000 residents, it offers travelers a glimpse into authentic rural German life and beautiful countryside vistas.

Geographic Context

Jurisdiction
Germany
Land
Bavaria
Population
1,971
Time Zone
Europe/Berlin
Coordinates
49.35°, 12.60°

Key Metrics

Safety Score · estimate
93
Female Safety
85
LGBTQ+ Safety
60
Traffic Safety
90
Food Safety
98
Monthly Cost · estimate
$1,512
Local Cost
$970
Local Income
$2,300
Cashless
55
English
58
Temperature
8.2°C
Summer Avg
18.2°C
Winter Avg
-1.7°C
Record High
37.2°C
Record Low
-24.3°C
Humidity
81%
Precipitation
743 mm
City Vibrancy
1
Coworking
0
Cafes
0
Nightlife
1
Parks
0
Transport
1
Walk Score
1
Footways
1.0
Airport
—
Distance
—

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 2026-03-22.
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: 65/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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