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Bench Maji Zone
City in Southwest Ethiopia Peoples, Ethiopia
Overview
Bench Maji Zone is a culturally rich and biodiverse region in Southwest Ethiopia, recognized for its forests, coffee plantations, and friendly communities. The area is less traveled, offering authentic experiences in nature, culture, and food.
Geographic Context
Jurisdiction
Ethiopia
Region
Southwest Ethiopia Peoples
Population
—
Time Zone
Africa/Addis_Ababa
Coordinates
6.46°, 35.31°
Key Metrics
Safety Score · estimate
40
Female Safety
35
LGBTQ+ Safety
15
Traffic Safety
35
Food Safety
30
Monthly Cost · estimate
$416
Local Cost
$208
Local Income
$50
Cashless
10
English
10
Temperature
26.9°C
Summer Avg
25.4°C
Winter Avg
28.5°C
Record High
42.6°C
Record Low
16.8°C
Humidity
60%
Precipitation
935 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
TUJ
Distance
32 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 2025-12-09.
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 2026-03-21.
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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