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Sanmu-shi
City in Chiba, Japan
Overview
Sanmu-shi blends rural landscapes with beaches and a relaxed local lifestyle on the Pacific coast of Chiba. The city offers a peaceful escape from Tokyo, with easy rail access and scenic countryside. Visitors enjoy its friendly atmosphere, seaside parks, and traditional festivals.
Geographic Context
Jurisdiction
Japan
Prefecture
Chiba
Population
—
Time Zone
Asia/Tokyo
Coordinates
35.62°, 140.42°
Key Metrics
Safety Score · estimate
87
Female Safety
88
LGBTQ+ Safety
74
Traffic Safety
85
Food Safety
98
Monthly Cost · estimate
$1,155
Local Cost
$735
Local Income
$1,800
Cashless
66
English
48
Temperature
17.1°C
Summer Avg
24.0°C
Winter Avg
9.4°C
Record High
33.7°C
Record Low
0.7°C
Humidity
78%
Precipitation
1659 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
NRT
Distance
17 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 2026-03-22.
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: 63/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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