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Kinokawa Shi
City in Wakayama, Japan
Overview
Kinokawa Shi is a picturesque city in Wakayama Prefecture known for its lush orchards, tranquil atmosphere, and rich history centered around Kokawa-dera Temple. Its neighborhoods blend rural charm with cultural highlights, making it perfect for visitors seeking off-the-beaten-path Japan.
Geographic Context
Jurisdiction
Japan
Prefecture
Wakayama
Population
—
Time Zone
Asia/Tokyo
Coordinates
34.25°, 135.39°
Key Metrics
Safety Score · estimate
92
Female Safety
88
LGBTQ+ Safety
65
Traffic Safety
84
Food Safety
96
Monthly Cost · estimate
$988
Local Cost
$665
Local Income
$1,600
Cashless
50
English
35
Temperature
14.0°C
Summer Avg
24.0°C
Winter Avg
3.8°C
Record High
34.1°C
Record Low
-5.5°C
Humidity
83%
Precipitation
1752 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
KIX
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: 72/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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