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Politischer Bezirk Schwaz

City in Tyrol, Austria

Overview

Politischer Bezirk Schwaz is a scenic region in Tyrol, Austria, with beautiful Alpine landscapes, welcoming towns, and access to lakes and ski resorts. The area blends historic charm with plenty of outdoor activities, making it ideal for families, cultural explorers, and adventure seekers alike.

Geographic Context

Jurisdiction
Austria
State
Tyrol
Population
81,841
Time Zone
Europe/Vienna
Coordinates
47.27°, 11.77°

Key Metrics

Safety Score · estimate
90
Female Safety
87
LGBTQ+ Safety
78
Traffic Safety
85
Food Safety
97
Monthly Cost · estimate
$2,583
Local Cost
$1,532
Local Income
$2,300
Cashless
78
English
72
Temperature
5.7°C
Summer Avg
14.9°C
Winter Avg
-3.7°C
Record High
31.9°C
Record Low
-28.9°C
Humidity
84%
Precipitation
1333 mm
City Vibrancy
3
Coworking
0
Cafes
3
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
INN
Distance
32 km

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 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-05.

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: 80/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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