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Mine Shi

City in Yamaguchi, Japan

Overview

Mine Shi is a tranquil city in Yamaguchi Prefecture, celebrated for its stunning limestone caves, rolling plateaus, and traditional rural charm. With a calm atmosphere and scenic landscapes, it's a haven for nature lovers and those seeking authentic Japanese countryside experiences.

Geographic Context

Jurisdiction
Japan
Prefecture
Yamaguchi
Population
—
Time Zone
Asia/Tokyo
Coordinates
34.21°, 131.25°

Key Metrics

Safety Score · estimate
88
Female Safety
85
LGBTQ+ Safety
66
Traffic Safety
80
Food Safety
96
Monthly Cost · estimate
$1,099
Local Cost
$638
Local Income
$1,700
Cashless
60
English
34
Temperature
15.7°C
Summer Avg
25.0°C
Winter Avg
6.3°C
Record High
36.6°C
Record Low
-4.8°C
Humidity
79%
Precipitation
1820 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
UBJ
Distance
31 km

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 2025-12-09.
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: 63/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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