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Canhas
City in Madeira, Portugal
Overview
Canhas is a scenic parish in southern Madeira, Portugal, known for its rural landscapes, terraced hills, and traditional Madeiran village charm. With easy access to hiking trails and breathtaking coastal views, it's a peaceful destination for nature enthusiasts and those seeking local authenticity.
Geographic Context
Jurisdiction
Portugal
Autonomous Region
Madeira
Population
3,769
Time Zone
Europe/Lisbon
Coordinates
32.69°, -17.10°
Key Metrics
Safety Score · estimate
82
Female Safety
80
LGBTQ+ Safety
75
Traffic Safety
80
Food Safety
90
Monthly Cost · estimate
$1,473
Local Cost
$882
Local Income
$1,050
Cashless
40
English
50
Temperature
19.1°C
Summer Avg
21.5°C
Winter Avg
16.8°C
Record High
29.4°C
Record Low
11.7°C
Humidity
77%
Precipitation
363 mm
Internet Speed
244 Mbps
Upload
117 Mbps
Latency
4 ms
City Vibrancy
26
Coworking
0
Cafes
12
Nightlife
11
Parks
3
Transport
15
Walk Score
15
Footways
30.0
Airport
FNC
Distance
30 km
Explore
Data sources
Source-backed data
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-07.
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: 64/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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