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Vaglia
City in Tuscany, Italy
Overview
Vaglia is a tranquil Tuscan town on the northern slopes of Florence, renowned for its lush landscapes, historic villas, and authentic village atmosphere. It's an ideal base for exploring rural Tuscany while staying close to Florence's cultural riches.
Geographic Context
Jurisdiction
Italy
Region
Tuscany
Population
5,164
Time Zone
Europe/Rome
Coordinates
43.91°, 11.28°
Key Metrics
Safety Score · estimate
87
Female Safety
80
LGBTQ+ Safety
65
Traffic Safety
80
Food Safety
95
Monthly Cost · estimate
$2,025
Local Cost
$1,410
Local Income
$1,700
Cashless
60
English
40
Temperature
11.8°C
Summer Avg
21.6°C
Winter Avg
2.8°C
Record High
38.9°C
Record Low
-12.2°C
Humidity
78%
Precipitation
735 mm
Internet Speed
51 Mbps
Upload
10 Mbps
Latency
19 ms
City Vibrancy
2
Coworking
0
Cafes
2
Nightlife
0
Parks
0
Transport
5
Walk Score
5
Footways
9.0
Airport
FLR
Distance
13 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 2025-12-07.
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: 72/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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