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Sacavém

City in Guarda, Portugal

Overview

Sacavém is a charming riverside town set northeast of Lisbon, combining industrial heritage with local traditions. Its welcoming neighborhoods, affordable living, and creative street art make it popular among families and young professionals.

Geographic Context

Jurisdiction
Portugal
District
Guarda
Population
17,718
Time Zone
Europe/Lisbon
Coordinates
38.79°, -9.11°

Key Metrics

Safety Score · estimate
77
Female Safety
78
LGBTQ+ Safety
75
Traffic Safety
80
Food Safety
94
Monthly Cost · estimate
$1,646
Local Cost
$1,004
Local Income
$950
Cashless
68
English
65
Temperature
16.0°C
Summer Avg
19.9°C
Winter Avg
11.8°C
Record High
36.3°C
Record Low
0.0°C
Humidity
80%
Precipitation
574 mm
Internet Speed
363 Mbps
Upload
135 Mbps
Latency
6 ms
City Vibrancy
85
Coworking
0
Cafes
55
Nightlife
1
Parks
29
Transport
0
Walk Score
0
Footways
—
Airport
LIS
Distance
3 km

Data sources

Source-backed data

Ookla Open Data - Internet speed aggregates for 2024Q3 from 83 tests. 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 2026-03-22.
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: 75/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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