Erpfendorf
City in Tyrol, Austria
Overview
Erpfendorf is a charming village in the Tyrolean Alps, renowned for its peaceful ambiance, stunning mountain scenery, and proximity to outdoor activities like hiking, skiing, and golf. With its mix of traditional Austrian culture and modern wellness resorts, it offers a relaxing escape year-round.
Geographic Context
Jurisdiction
Austria
State
Tyrol
Population
—
Time Zone
Europe/Vienna
Coordinates
47.58°, 12.47°
Key Metrics
Safety Score · estimate
90
Female Safety
85
LGBTQ+ Safety
70
Traffic Safety
90
Food Safety
97
Monthly Cost · estimate
$1,860
Local Cost
$1,250
Local Income
$2,400
Cashless
80
English
67
Temperature
5.1°C
Summer Avg
14.2°C
Winter Avg
-4.3°C
Record High
31.4°C
Record Low
-29.0°C
Humidity
85%
Precipitation
1454 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
1
Walk Score
1
Footways
1.0
Airport
SZG
Distance
46 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: 70/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.