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Lama dei Peligni
City in Abruzzo, Italy
Overview
Lama dei Peligni is a quaint mountain village in Abruzzo, Italy, set at the foot of the Majella National Park. It is renowned for its stunning natural landscapes, prehistoric sites, and friendly local culture.
Geographic Context
Jurisdiction
Italy
Region
Abruzzo
Population
1,057
Time Zone
Europe/Rome
Coordinates
42.04°, 14.19°
Key Metrics
Safety Score · estimate
90
Female Safety
85
LGBTQ+ Safety
55
Traffic Safety
85
Food Safety
95
Monthly Cost · estimate
$1,528
Local Cost
$850
Local Income
$1,200
Cashless
30
English
25
Temperature
13.7°C
Summer Avg
23.4°C
Winter Avg
5.0°C
Record High
41.0°C
Record Low
-8.8°C
Humidity
72%
Precipitation
713 mm
Internet Speed
37 Mbps
Upload
11 Mbps
Latency
15 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
1
Walk Score
1
Footways
1.0
Airport
PSR
Distance
43 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: 65/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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