Tambre
City in Veneto, Italy
Overview
Tambre is a picturesque village in the Belluno province of Veneto, offering lush alpine scenery, traditional architecture, and a welcoming small-town ambiance. Known for its outdoor activities and rural charm, Tambre is a great base for exploring the Italian Dolomites.
Geographic Context
Jurisdiction
Italy
Region
Veneto
Population
1,297
Time Zone
Europe/Rome
Coordinates
46.13°, 12.42°
Key Metrics
Safety Score · estimate
92
Female Safety
90
LGBTQ+ Safety
70
Traffic Safety
85
Food Safety
95
Monthly Cost · estimate
$1,447
Local Cost
$938
Local Income
$1,150
Cashless
55
English
40
Temperature
12.1°C
Summer Avg
22.1°C
Winter Avg
2.3°C
Record High
37.5°C
Record Low
-12.0°C
Humidity
73%
Precipitation
1062 mm
Internet Speed
561 Mbps
Upload
283 Mbps
Latency
10 ms
City Vibrancy
5
Coworking
0
Cafes
0
Nightlife
5
Parks
0
Transport
13
Walk Score
13
Footways
25.0
Airport
BLX
Distance
14 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 2025-12-08.
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: 58/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.