Massa Fiscaglia
City in Emilia-Romagna, Italy
Overview
Massa Fiscaglia is a tranquil town in Emilia-Romagna, Italy, known for its rural atmosphere, historic architecture, and warm community feel. It offers an authentic taste of Italian small town life away from busy tourist crowds.
Geographic Context
Jurisdiction
Italy
Region
Emilia-Romagna
Population
—
Time Zone
Europe/Rome
Coordinates
44.81°, 12.01°
Key Metrics
Safety Score · estimate
82
Female Safety
75
LGBTQ+ Safety
65
Traffic Safety
78
Food Safety
94
Monthly Cost · estimate
$1,439
Local Cost
$832
Local Income
$1,420
Cashless
60
English
30
Temperature
14.9°C
Summer Avg
25.3°C
Winter Avg
4.9°C
Record High
41.4°C
Record Low
-5.9°C
Humidity
73%
Precipitation
733 mm
Internet Speed
128 Mbps
Upload
86 Mbps
Latency
46 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
8
Walk Score
8
Footways
16.0
Airport
—
Distance
—
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: 63/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.