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Ampflwang

City in Upper Austria, Austria

Overview

Ampflwang is a picturesque village located in Upper Austria, celebrated for its rolling hills, equestrian culture, and proximity to the Hausruck forest. Known as a gateway for outdoor activities, it offers a relaxing rural escape with authentic Austrian hospitality.

Geographic Context

Jurisdiction
Austria
State
Upper Austria
Population
—
Time Zone
Europe/Vienna
Coordinates
48.08°, 13.57°

Key Metrics

Safety Score · estimate
90
Female Safety
85
LGBTQ+ Safety
70
Traffic Safety
80
Food Safety
95
Monthly Cost · estimate
$1,685
Local Cost
$994
Local Income
$2,200
Cashless
75
English
65
Temperature
8.2°C
Summer Avg
17.7°C
Winter Avg
-1.4°C
Record High
35.8°C
Record Low
-21.6°C
Humidity
83%
Precipitation
1257 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
5
Walk Score
5
Footways
10.0
Airport
LNZ
Distance
49 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 2025-12-09.
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: 65/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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