Cameroon Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 23 March 2026.
Here you’ll find a curated sample of 100 key cities from Cameroon, each with essential data points such as latitude, longitude, administrative region, and other relevant attributes.
This preview is extracted from our full dataset, which includes a total of 13441 geographic locations across Cameroon.
Whether you’re working on mapping, analytics, or app development, the data is available for both personal and commercial use.
All entries can be downloaded in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML.
Capital Highlight: The official capital city of Cameroon is Yaoundé.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 6858018 | Koano | CM | South-West | 5.7721 | 9.7976 | 0 | Africa/Douala | populated place | |||
| 6730840 | DaĂŻba | CM | Far North | 10.29532 | 14.99201 | 0 | Africa/Douala | populated place | |||
| 6732110 | Guiziguel | CM | Far North | 10.75053 | 14.41961 | 0 | Africa/Douala | populated place | |||
| 2222653 | Patakou | Patakou,Pataku,PatakĂş | CM | 6.13333 | 11.26667 | 0 | Africa/Douala | populated place | |||
| 2594921 | Mbanga | CM | Littoral | 4.0066 | 9.8002 | 0 | Africa/Douala | populated place | |||
| 2223792 | Nkongabok I | Nkongabok,Nkongabok I | CM | Centre | 3.7 | 11.26667 | 0 | Africa/Douala | populated place | ||
| 2235558 | Anguie | Angie,Anguie | CM | North-West | 5.80063 | 9.80881 | 0 | Africa/Douala | populated place | ||
| 9074323 | Oudsnat | CM | Far North | 10.82029 | 13.8771 | 0 | Africa/Douala | populated place | |||
| 6858167 | Meangwe | CM | South-West | 5.0409 | 9.1409 | 0 | Africa/Douala | populated place | |||
| 2595163 | Ehom | CM | South-West | 4.748 | 9.6071 | 0 | Africa/Douala | populated place | |||
| 2220756 | Zaorbia | CM | 7.65 | 13.8 | 0 | Africa/Douala | populated place | ||||
| 2233745 | Bola | CM | North | 9.77582 | 13.69746 | 0 | Africa/Douala | populated place | |||
| 2230365 | Kéléo | Kele,Keleo,Kélé,Kéléo | CM | Far North | 10.73708 | 14.96647 | 0 | Africa/Douala | populated place | ||
| 6730403 | Tchaba Tchaba | CM | Far North | 10.92419 | 14.23885 | 0 | Africa/Douala | populated place | |||
| 2235144 | Baina | CM | Adamaoua | 6.4 | 14.28333 | 0 | Africa/Douala | populated place | |||
| 2222854 | Ouro Haman Hadama | Ouro Hamahadama,Ouro Haman Hadama | CM | North | 9.1077 | 14.1253 | 0 | Africa/Douala | populated place | ||
| 2231455 | Gadjia | CM | Far North | 10.34035 | 14.6969 | 0 | Africa/Douala | populated place | |||
| 2229785 | Koutoubingono | CM | Centre | 4.3 | 12.6 | 0 | Africa/Douala | populated place | |||
| 2595251 | Timbo | CM | Littoral | 3.46306 | 9.74917 | 0 | Africa/Douala | populated place | |||
| 6915335 | Tikoro | CM | South-West | 4.7027 | 8.7004 | 0 | Africa/Douala | populated place | |||
| 9085769 | Mantcha | CM | West | 5.58727 | 10.28887 | 0 | Africa/Douala | populated place | |||
| 2233168 | Demba | CM | North | 8.6 | 12.55 | 0 | Africa/Douala | populated place | |||
| 2225331 | Déga | Dega,Déga,Ndega,Ndéga | CM | Far North | 12.44776 | 14.20096 | 0 | Africa/Douala | populated place | ||
| 2234276 | Bibé | CM | Centre | 3.71667 | 11.4 | 0 | Africa/Douala | populated place | |||
| 2234636 | Bazer | CM | Adamaoua | 6.8 | 13.91667 | 0 | Africa/Douala | populated place | |||
| 2235215 | Badjoki | CM | Littoral | 4.7 | 9.93333 | 0 | Africa/Douala | populated place | |||
| 2232104 | Ekondong | CM | Centre | 4.81667 | 12.2 | 0 | Africa/Douala | populated place | |||
| 2233552 | Bougay | Bougay,Bougaye | CM | Far North | 10.25645 | 15.11022 | 0 | Africa/Douala | populated place | ||
| 2223320 | Nyos-Acha | CM | North-West | 6.45 | 10.26667 | 0 | Africa/Douala | populated place | |||
| 2229313 | Lobétal | Lobetal,Lobethal,Lobétal | CM | Littoral | 3.64472 | 9.78694 | 0 | Africa/Douala | populated place | ||
| 9074893 | Sikia | CM | Far North | 10.55929 | 13.95512 | 0 | Africa/Douala | populated place | |||
| 2226846 | Méyos | CM | South | 3.25 | 12.16667 | 0 | Africa/Douala | populated place | |||
| 2236042 | Aboudangala Chia | Abou Dangala,Aboudangala Chia | CM | Far North | 12.66787 | 14.53492 | 0 | Africa/Douala | populated place | ||
| 2228121 | Mbaka | CM | Centre | 3.91667 | 12.23333 | 0 | Africa/Douala | populated place | |||
| 9074985 | Mewak | CM | West | 5.51412 | 10.2085 | 0 | Africa/Douala | populated place | |||
| 2224102 | Nkoambé | CM | South | 2.6 | 11.03333 | 0 | Africa/Douala | populated place | |||
| 6760182 | Dihi | CM | Far North | 10.24762 | 13.51464 | 0 | Africa/Douala | populated place | |||
| 2594801 | Koto II | CM | South-West | 4.3216 | 9.0654 | 0 | Africa/Douala | populated place | |||
| 2222095 | Sep I | CM | Centre | 3.28333 | 11.63333 | 0 | Africa/Douala | populated place | |||
| 8605698 | Chienke | CM | West | 5.25714 | 10.40049 | 0 | Africa/Douala | populated place | |||
| 2226474 | Mremié | Miribie,Miribié,Mremie,Mremié | CM | Far North | 12.56827 | 14.68118 | 0 | Africa/Douala | populated place | ||
| 2224805 | Ngat | CM | Centre | 3.85 | 11.98333 | 0 | Africa/Douala | populated place | |||
| 2233346 | Chouam | CM | East | 3.33333 | 12.81667 | 0 | Africa/Douala | populated place | |||
| 8669506 | Ouro Babouba | CM | North | 9.7966 | 13.96486 | 0 | Africa/Douala | populated place | |||
| 2594828 | Mokoko | CM | South-West | 4.5429 | 9.0443 | 0 | Africa/Douala | populated place | |||
| 2232515 | Douma | CM | South | 3.5 | 12.31667 | 0 | Africa/Douala | populated place | |||
| 2231637 | Fignolé | CM | North | 8.5696 | 13.05225 | 0 | Africa/Douala | populated place | |||
| 2228244 | Mayaakwé | Mayaakwe,Mayaakwé,Mayakoue,Mayakoué,Mayakwe,Mayakwé | CM | West | 5.11588 | 10.87422 | 0 | Africa/Douala | populated place | ||
| 9074602 | Mbougouane | CM | Far North | 10.55535 | 13.6956 | 0 | Africa/Douala | populated place | |||
| 2227924 | Mbébé | CM | South | 3.38333 | 10.11667 | 0 | Africa/Douala | populated place | |||
| 6730412 | Ngoulmoun | CM | Far North | 10.91912 | 14.98437 | 0 | Africa/Douala | populated place | |||
| 7110241 | Maloup | Maloup | CM | West | 5.52938 | 10.84126 | 0 | Africa/Douala | populated place | ||
| 2230908 | Grand Viri | CM | Far North | 10.05 | 15.18333 | 0 | Africa/Douala | populated place | |||
| 2229601 | Larbak | Larba,Larbak | CM | North | 10.03697 | 13.91182 | 0 | Africa/Douala | populated place | ||
| 2228019 | Mbang | Mbang | CM | East | 4.58333 | 13.33333 | 1237 | Africa/Douala | populated place | ||
| 6857986 | Mobang | CM | North-West | 5.8126 | 9.7779 | 0 | Africa/Douala | populated place | |||
| 2234867 | Ngang | Bangang,Ngang | CM | West | 5.56747 | 10.17435 | 0 | Africa/Douala | populated place | ||
| 6729808 | Portsamay | CM | Far North | 10.60141 | 14.12119 | 0 | Africa/Douala | populated place | |||
| 2235874 | Akamé | CM | South | 2.33333 | 11.83333 | 0 | Africa/Douala | populated place | |||
| 2227033 | Méré | CM | 7.65 | 12.95 | 0 | Africa/Douala | populated place | ||||
| 9096812 | Tankwo | CM | North-West | 5.82641 | 10.43983 | 0 | Africa/Douala | populated place | |||
| 6870384 | Vibara | CM | North | 7.5925 | 15.5004 | 0 | Africa/Douala | populated place | |||
| 2232192 | Éfoulan II | CM | South | 3.26667 | 12.13333 | 0 | Africa/Douala | populated place | |||
| 6730128 | Brouwi | CM | Far North | 10.12864 | 14.08861 | 0 | Africa/Douala | populated place | |||
| 2225106 | Ndokomouen | CM | Littoral | 4.43333 | 10.15 | 0 | Africa/Douala | populated place | |||
| 2229487 | Léta | Leta,Letz,Léta | CM | East | 4.25 | 14 | 0 | Africa/Douala | populated place | ||
| 9101218 | Maakouop | CM | West | 5.55368 | 10.64542 | 0 | Africa/Douala | populated place | |||
| 2220772 | Zamana | CM | Adamaoua | 7.63333 | 13.68333 | 0 | Africa/Douala | populated place | |||
| 2231714 | Fakélé I | CM | Centre | 3.48333 | 11.6 | 0 | Africa/Douala | populated place | |||
| 2221915 | Songndong | Leb Nkengue,Leb Nkengué,Songndong | CM | Littoral | 3.88333 | 10.28333 | 0 | Africa/Douala | populated place | ||
| 2234334 | Betenge | CM | South-West | 4.834 | 9.2312 | 0 | Africa/Douala | populated place | |||
| 9096851 | Shingo | CM | North-West | 5.81453 | 10.35205 | 0 | Africa/Douala | populated place | |||
| 2233066 | Dikonop | Dikongob,Dikonop | CM | Centre | 3.96667 | 10.75 | 0 | Africa/Douala | populated place | ||
| 2235361 | Awa | CM | Centre | 4 | 12.58333 | 0 | Africa/Douala | populated place | |||
| 2235380 | Avébé | CM | South | 2.98333 | 11.76667 | 0 | Africa/Douala | populated place | |||
| 2233213 | Davagan | CM | Far North | 11.11347 | 15.02697 | 0 | Africa/Douala | populated place | |||
| 8696654 | Manbarla | CM | Adamaoua | 6.39223 | 12.57797 | 0 | Africa/Douala | populated place | |||
| 2228547 | Mangamba | CM | Littoral | 4.7641 | 9.8759 | 0 | Africa/Douala | populated place | |||
| 2233320 | Daboulao | CM | Far North | 11.29576 | 15.03072 | 0 | Africa/Douala | populated place | |||
| 2225820 | Mouvoulwa | Mouvouloua,Mouvoulwa | CM | Far North | 10.43159 | 13.88332 | 0 | Africa/Douala | populated place | ||
| 9074971 | Zemeto | CM | West | 5.51627 | 10.1636 | 0 | Africa/Douala | populated place | |||
| 8696641 | Djaoro Kombo | CM | Adamaoua | 6.24598 | 12.90996 | 0 | Africa/Douala | populated place | |||
| 2231797 | Etouha | CM | Littoral | 3.66667 | 10.3 | 0 | Africa/Douala | populated place | |||
| 2223075 | Osokoé | CM | Centre | 3.66667 | 11.35 | 0 | Africa/Douala | populated place | |||
| 8607487 | Njila’ | CM | West | 5.41955 | 10.32692 | 0 | Africa/Douala | populated place | |||
| 2223443 | Ntouesong V | CM | Centre | 3.96667 | 11.61667 | 0 | Africa/Douala | populated place | |||
| 2231888 | Esangmvout | Esangmvout,Essongwout | CM | South | 2.81667 | 12.26667 | 0 | Africa/Douala | populated place | ||
| 9096856 | Bali-Gashu | Bali-Gashu | CM | North-West | 5.81461 | 10.38893 | 0 | Africa/Douala | populated place | ||
| 2224022 | Nkolébang | CM | South | 3.36667 | 12.05 | 0 | Africa/Douala | populated place | |||
| 2225475 | Nana | CM | North | 7.2 | 15 | 0 | Africa/Douala | populated place | |||
| 6858173 | Kuma | CM | South-West | 5.084 | 9.0787 | 0 | Africa/Douala | populated place | |||
| 2235943 | Afan | CM | South | 2.38333 | 10 | 0 | Africa/Douala | populated place | |||
| 2221179 | Walango | Garangatchi,Wafango,Walango | CM | North | 10.01707 | 13.25415 | 0 | Africa/Douala | populated place | ||
| 6870325 | NgaĂŻ | CM | North | 7.6103 | 15.0606 | 0 | Africa/Douala | populated place | |||
| 2234943 | Muambong I | Bamoungo,Muambong,Muambong I | CM | South-West | 4.9457 | 9.7225 | 0 | Africa/Douala | populated place | ||
| 2227889 | Mbella | CM | Adamaoua | 6.71667 | 13.03333 | 0 | Africa/Douala | populated place | |||
| 9112596 | Mfon Payèt | CM | West | 5.86607 | 10.89723 | 0 | Africa/Douala | populated place | |||
| 2234749 | Barkari | Barkari,Barkari I | CM | Far North | 12.50936 | 14.33063 | 0 | Africa/Douala | populated place | ||
| 8710847 | Yabal | CM | Far North | 11.1516 | 13.9413 | 0 | Africa/Douala | populated place | |||
| 2226087 | Mondoni | CM | South-West | 4.1883 | 9.4719 | 0 | Africa/Douala | populated place |
Cameroon: A Geographic Canvas of Diversity and Precision
From the Gulf to the Highlands: A Geographer’s Fascination
Cameroon is a country that defies simple classification. It stretches from the humid coastal plains of the Gulf of Guinea to the savannas of the north, weaving together ecosystems, languages, and cultures into a singular national identity. For any geographer, it is a dream—an intricate interplay of topography, climate zones, and administrative frameworks.
But to understand Cameroon properly, one must go far beyond maps. The real power lies in structured urban and administrative data—city by city, region by region, department by department. I’ve spent years building a geographic dataset that makes Cameroon legible to planners, researchers, and professionals. The architecture of this data opens the door to deep insights, and now, with a recent enhancement, users can access it in Excel (xlsx) format—arguably the most intuitive and flexible tool for geographic data exploration.
Urban Systems Anchored in Administrative Logic
Each city in Cameroon has a story, but just as importantly, each belongs to a framework of administrative hierarchy. The nation is divided into ten regions, and within those lie numerous departments and subdivisions. Understanding how cities are embedded within these structures is key to everything from economic modeling to social policy design.
With this dataset, you can identify not just where cities are located, but how they function within their regions and departments. This is invaluable for any field that requires an awareness of administrative boundaries—from education planning to infrastructure rollout.
Latitude, Longitude, and Spatial Accuracy
At the core of any serious geographic analysis lies precise geolocation. Every city in this Cameroon database is pinned to its exact latitude and longitude, enabling users to carry out spatial analysis, generate custom maps, or power location-based services.
Whether you're plotting transportation corridors, identifying risk zones for climate impact, or simply visualizing market reach, the power of coordinates—hidden but present—cannot be overstated. And in this case, every data point is ready to integrate seamlessly into your system.
The Excel Advantage
Let’s be honest: while formats like SQL and JSON are vital for technical workflows, Excel remains the unmatched champion of accessibility. With the new Excel (xlsx) support, this dataset becomes exponentially more powerful for users across all disciplines.
Public sector workers, NGO staff, analysts, and consultants can now filter, sort, and segment Cameroonian city data with ease—no coding required. Want to focus on cities within the North-West region? Filter the column. Need to extract department-level population centers? A few clicks. Excel empowers the many who rely on clarity, not complexity.
This is especially relevant in Cameroon's multilingual administrative environment, where local nuances often demand quick adaptability and customization—something Excel delivers effortlessly.
Formats That Fit Every Use Case
In addition to Excel, the Cameroon dataset is available in a suite of powerful formats designed to accommodate a wide range of technical needs:
* **CSV**, lightweight and universal
* **SQL**, for integration into geographic and urban information systems
* **JSON**, ideal for web development and app integration
* **XML**, for interoperability with legacy systems and regulatory platforms
Whether you're building a civic data portal, feeding an AI model, or planning a humanitarian response, this flexibility ensures the data meets you where you are.
Data That Serves the Future
Cameroon is at the crossroads of tradition and transformation. Urban expansion is reshaping the landscape, while decentralized governance structures are creating new dynamics across departments and regions. In this shifting context, access to clear, well-structured geographic data is not optional—it’s essential.
From logistics providers optimizing last-mile delivery routes to environmental scientists tracking land-use changes, structured city-level data is the backbone of evidence-based action. And with this dataset, Cameroon’s geographic complexity becomes navigable, measurable, and ultimately—understandable.
Conclusion
Cameroon’s rich mosaic of cities, regions, and departments deserves more than a dot on the map. It demands a structured, precise approach—rooted in passion for geographic detail and delivered through tools that work for real users. With support for Excel and other critical formats, my dataset offers a gateway to understanding and working with Cameroon like never before. For those who believe data can drive development, this is where the journey begins.
