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Ina-shi
City in Nagano, Japan
Overview
Ina-shi is a tranquil city set in the heart of Nagano Prefecture, surrounded by the picturesque scenery of the Ina Valley and the Southern Alps. With its blend of rural landscapes, historical sites, and outdoor activities, it is an ideal destination for nature lovers and those seeking authentic Japanese countryside charm.
Geographic Context
Jurisdiction
Japan
Prefecture
Nagano
Population
—
Time Zone
Asia/Tokyo
Coordinates
35.79°, 138.07°
Key Metrics
Safety Score · estimate
90
Female Safety
85
LGBTQ+ Safety
60
Traffic Safety
80
Food Safety
98
Monthly Cost · estimate
$1,075
Local Cost
$697
Local Income
$2,100
Cashless
65
English
40
Temperature
8.2°C
Summer Avg
19.3°C
Winter Avg
-3.6°C
Record High
32.5°C
Record Low
-19.1°C
Humidity
82%
Precipitation
1329 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
7
Walk Score
7
Footways
13.0
Airport
MMJ
Distance
44 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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