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Ponot
City in Zamboanga Sibugay, Philippines
Overview
Ponot is a compact, riverside town in Zamboanga Sibugay, Philippines, offering a genuine provincial atmosphere and warm local community. The town is known for its marketplaces, scenic river landscapes, and easygoing lifestyle. While it remains largely undiscovered by tourists, Ponot provides an authentic Mindanao experience.
Geographic Context
Jurisdiction
Philippines
Province
Zamboanga Sibugay
Population
—
Time Zone
Asia/Manila
Coordinates
8.45°, 123.02°
Key Metrics
Safety Score · estimate
55
Female Safety
45
LGBTQ+ Safety
40
Traffic Safety
60
Food Safety
50
Monthly Cost · estimate
$433
Local Cost
$215
Local Income
$180
Cashless
30
English
58
Temperature
26.7°C
Summer Avg
26.8°C
Winter Avg
26.1°C
Record High
34.2°C
Record Low
21.7°C
Humidity
84%
Precipitation
2243 mm
Internet Speed
12 Mbps
Upload
13 Mbps
Latency
239 ms
City Vibrancy
1
Coworking
0
Cafes
0
Nightlife
0
Parks
1
Transport
2
Walk Score
2
Footways
3.0
Airport
DPL
Distance
39 km
Explore
Data sources
Source-backed data
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-09.
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: 62/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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