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Awa-shi
City in Tokushima, Japan
Overview
Awa-shi is a small city set in Tokushima Prefecture, Japan, known for its traditional neighborhoods, peaceful rural atmosphere, and easy access to nature. Visitors can explore historic shrines, busy local markets, and scenic mountain trails all within the city limits.
Geographic Context
Jurisdiction
Japan
Prefecture
Tokushima
Population
—
Time Zone
Asia/Tokyo
Coordinates
34.10°, 134.25°
Key Metrics
Safety Score · estimate
91
Female Safety
87
LGBTQ+ Safety
66
Traffic Safety
83
Food Safety
95
Monthly Cost · estimate
$1,210
Local Cost
$785
Local Income
$1,700
Cashless
42
English
38
Temperature
14.1°C
Summer Avg
24.0°C
Winter Avg
3.9°C
Record High
36.9°C
Record Low
-6.4°C
Humidity
82%
Precipitation
1815 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
TAK
Distance
25 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 2025-12-09.
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: 75/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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