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Santa Clara do Sul
City in Rio Grande do Sul, Brazil
Overview
Santa Clara do Sul is a small, tranquil city in Brazil's Rio Grande do Sul state, embraced by rolling hills and rural landscapes. Known for its strong German heritage, community spirit, and tidy streets, the city offers a laid-back atmosphere ideal for a peaceful retreat.
Geographic Context
Jurisdiction
Brazil
State
Rio Grande do Sul
Population
7,079
Time Zone
America/Sao_Paulo
Coordinates
-29.46°, -52.14°
Key Metrics
Safety Score · estimate
75
Female Safety
67
LGBTQ+ Safety
45
Traffic Safety
65
Food Safety
80
Monthly Cost · estimate
$593
Local Cost
$450
Local Income
$420
Cashless
35
English
18
Temperature
19.0°C
Summer Avg
23.8°C
Winter Avg
13.9°C
Record High
40.6°C
Record Low
-2.5°C
Humidity
82%
Precipitation
1577 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
CSU
Distance
36 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 2025-12-07.
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: 52/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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