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Surallah
City in South Cotabato, Philippines
Overview
Surallah is a lively municipality in South Cotabato, set in the scenic SOCCSKSARGEN region. It's famed for its agricultural prosperity, friendly locals, and proximity to natural attractions like the Allah River. The town gives visitors a glimpse into authentic rural life in Mindanao.
Geographic Context
Jurisdiction
Philippines
Province
South Cotabato
Population
91,412
Time Zone
Asia/Manila
Coordinates
6.33°, 124.56°
Key Metrics
Safety Score · estimate
52
Female Safety
48
LGBTQ+ Safety
38
Traffic Safety
55
Food Safety
50
Monthly Cost · estimate
$464
Local Cost
$230
Local Income
$250
Cashless
25
English
35
Temperature
22.7°C
Summer Avg
22.6°C
Winter Avg
22.4°C
Record High
34.4°C
Record Low
14.4°C
Humidity
88%
Precipitation
2053 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
AAV
Distance
21 km
Explore
Neighborhoods
EstimatedNeighborhood highlights with vibe, safety, and cost profiles.
View featured neighborhoodsData sources
Source-backed data
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: 60/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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