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Gangolli

City in Karnataka, India

Overview

Gangolli is a charming coastal town in Karnataka renowned for its busy fishing industry, beautiful beaches, and laid-back rural vibe. With a small, friendly population and easy access to rivers and the Arabian Sea, Gangolli offers visitors an authentic slice of Malnad culture and natural beauty.

Geographic Context

Jurisdiction
India
State
Karnataka
Population
15,200
Time Zone
Asia/Kolkata
Coordinates
13.65°, 74.67°

Key Metrics

Safety Score · estimate
65
Female Safety
45
LGBTQ+ Safety
35
Traffic Safety
50
Food Safety
55
Monthly Cost · estimate
$326
Local Cost
$168
Local Income
$110
Cashless
35
English
30
Temperature
27.9°C
Summer Avg
27.4°C
Winter Avg
27.6°C
Record High
32.7°C
Record Low
22.7°C
Humidity
76%
Precipitation
3824 mm
Internet Speed
28 Mbps
Upload
39 Mbps
Latency
20 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0

Neighborhoods

Estimated

Neighborhood highlights with vibe, safety, and cost profiles.

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Data sources

Source-backed data

World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
Ookla Open Data - Internet speed aggregates for 2024Q3 from 4 tests. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. 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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