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Motosu-shi
City in Gifu, Japan
Overview
Motosu-shi, set in Gifu Prefecture, is a quiet, nature-rich city characterized by rivers, forests, and relaxed rural living. Offering access to beautiful waterfalls, outdoor recreation, and authentic Japanese countryside experiences, Motosu is perfect for travelers seeking tranquility away from city crowds.
Geographic Context
Jurisdiction
Japan
Prefecture
Gifu
Population
—
Time Zone
Asia/Tokyo
Coordinates
35.66°, 136.62°
Key Metrics
Safety Score · estimate
92
Female Safety
90
LGBTQ+ Safety
75
Traffic Safety
88
Food Safety
98
Monthly Cost · estimate
$1,195
Local Cost
$755
Local Income
$1,800
Cashless
60
English
30
Temperature
12.8°C
Summer Avg
23.4°C
Winter Avg
1.8°C
Record High
34.8°C
Record Low
-10.2°C
Humidity
83%
Precipitation
1803 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
QGU
Distance
37 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: 65/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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