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Trento
City in Caraga, Philippines
Overview
Trento is a rapidly growing municipality in the Agusan del Sur province, located within Caraga region of the Philippines. Surrounded by lush forests and agricultural land, it's known for its laid-back culture and proximity to natural attractions.
Geographic Context
Jurisdiction
Philippines
Region
Caraga
Population
51,179
Time Zone
Asia/Manila
Coordinates
8.05°, 126.06°
Key Metrics
Safety Score · estimate
52
Female Safety
47
LGBTQ+ Safety
34
Traffic Safety
38
Food Safety
50
Monthly Cost · estimate
$592
Local Cost
$270
Local Income
$230
Cashless
22
English
63
Temperature
26.3°C
Summer Avg
26.8°C
Winter Avg
25.6°C
Record High
36.1°C
Record Low
19.6°C
Humidity
84%
Precipitation
3324 mm
Internet Speed
46 Mbps
Upload
38 Mbps
Latency
23 ms
City Vibrancy
1
Coworking
0
Cafes
0
Nightlife
0
Parks
1
Transport
0
Walk Score
0
Footways
—
Airport
BPH
Distance
33 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: 48/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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