Central African Republic 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 Central African Republic, 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 5685 geographic locations across Central African Republic.
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 Central African Republic is Bangui.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2382257 | Zaorosongou | CF | Mambéré-Kadéï | Gadzi | 5.04082 | 16.21282 | 0 | Africa/Bangui | populated place | ||
| 2383234 | Salo | CF | Sangha-Mbaéré | Nola | 3.18303 | 16.11936 | 0 | Africa/Bangui | populated place | ||
| 412491 | Colingi | CF | Ouaka | Bambari | 5.79433 | 20.64173 | 0 | Africa/Bangui | populated place | ||
| 236423 | Sayo | CF | Mbomou | Bangassou | 4.76403 | 22.8206 | 0 | Africa/Bangui | populated place | ||
| 2384648 | Mbo | Mbo,Pebo,Pébo | CF | Ouham | Kabo | 8.0983 | 18.7107 | 0 | Africa/Bangui | populated place | |
| 2388160 | Bongba | CF | Ouham | Bossangoa | 6.75148 | 16.90577 | 0 | Africa/Bangui | populated place | ||
| 2382830 | Togbo | CF | Ouham | Bouca | 6.49136 | 18.2399 | 0 | Africa/Bangui | populated place | ||
| 2389848 | Banguinda | CF | Nana-Mambéré | Abba | 5.19111 | 14.95322 | 0 | Africa/Bangui | populated place | ||
| 7525508 | Kéota | CF | Kémo | Ndjoukou | 5.15357 | 19.61974 | 0 | Africa/Bangui | populated place | ||
| 240755 | Bagra | CF | Ouaka | Ippy | 6.26667 | 21.2 | 0 | Africa/Bangui | populated place | ||
| 2389383 | Békajouté | CF | Ombella-M’Poko | Yaloke Sub-Prefecture | 5.50284 | 16.77956 | 0 | Africa/Bangui | populated place | ||
| 237590 | Mbima | CF | Ouaka | Kouango | 5.04995 | 20.04261 | 0 | Africa/Bangui | populated place | ||
| 2385263 | Lia Moya | Lia,Lia Moya | CF | Ouham-Pendé | Paoua | 6.90078 | 16.28573 | 0 | Africa/Bangui | populated place | |
| 2387629 | Bouzélé | CF | Ombella-M’Poko | Bimbo Sub-Prefecture | 4.41615 | 18.41394 | 0 | Africa/Bangui | populated place | ||
| 2387694 | Bounou | CF | Ouham | Markounda | 7.58701 | 16.93131 | 0 | Africa/Bangui | populated place | ||
| 2388412 | Bogue | CF | Ouham | Bossangoa | 6.55 | 17.48333 | 0 | Africa/Bangui | populated place | ||
| 2386326 | Goumissi | CF | Ouham | Markounda | 7.78333 | 17.3 | 0 | Africa/Bangui | populated place | ||
| 240005 | Bougoua | CF | Haut-Mbomou | Bambouti | 5.21667 | 26.76667 | 0 | Africa/Bangui | populated place | ||
| 2388655 | Bobili | Bobili | CF | Ouham | Bossangoa | 6.7588 | 16.85409 | 0 | Africa/Bangui | populated place | |
| 2586355 | Bobéré | CF | Ombella-M’Poko | Bimbo Sub-Prefecture | 4.00525 | 18.45771 | 0 | Africa/Bangui | populated place | ||
| 239258 | Garba | Garba | CF | Bamingui-Bangoran | Ndélé | 9.20253 | 20.49241 | 0 | Africa/Bangui | populated place | |
| 237636 | Mbari | CF | Mbomou | Rafai | 5.46667 | 24.16667 | 0 | Africa/Bangui | populated place | ||
| 2387041 | Dongali | CF | Mambéré-Kadéï | Gadzi | 5.18036 | 16.64807 | 0 | Africa/Bangui | populated place | ||
| 2388468 | Bogbolo | CF | Ouham | Bossangoa | 6.49331 | 17.03312 | 0 | Africa/Bangui | populated place | ||
| 6857458 | Béré | CF | Ouham | Markounda | 7.36691 | 16.82631 | 0 | Africa/Bangui | populated place | ||
| 2382920 | Tchabanda | CF | Ouaka | Grimari | 6.02444 | 19.95509 | 0 | Africa/Bangui | populated place | ||
| 2388469 | Bogbo | CF | Ouham | Nana-Bakassa | 6.81639 | 17.46778 | 0 | Africa/Bangui | populated place | ||
| 2388467 | Bogboro | CF | Lobaye | Mbaiki | 4.46602 | 17.76605 | 0 | Africa/Bangui | populated place | ||
| 7524153 | Mala | CF | Ouham | Batangafo | 7.46767 | 18.20621 | 0 | Africa/Bangui | populated place | ||
| 239857 | Congo | CF | Basse-Kotto | 9143474 | 5.13499 | 21.24975 | 0 | Africa/Bangui | populated place | ||
| 2388508 | Bogan | CF | Mambéré-Kadéï | Gadzi | 5.07108 | 16.23735 | 0 | Africa/Bangui | populated place | ||
| 2385806 | Kéwiné | CF | Ouham | Nana-Bakassa | 7.0075 | 17.28686 | 0 | Africa/Bangui | populated place | ||
| 239552 | Djema | Diema,Djema,Djemah,Jema | CF | Haut-Mbomou | Djéma | 6.04628 | 25.32607 | 0 | Africa/Bangui | populated place | |
| 7524439 | Ngou Sara | CF | Haute-Kotto | Bria | 7.0528 | 21.87768 | 0 | Africa/Bangui | populated place | ||
| 412252 | Mbata | CF | Ouaka | Bambari | 5.74742 | 20.62522 | 0 | Africa/Bangui | populated place | ||
| 239437 | Dourdour | CF | Vakaga | Birao | 10.19482 | 22.90471 | 0 | Africa/Bangui | populated place | ||
| 2387285 | Déré | CF | Nana-Grébizi | Kaga-Bandoro | 6.84416 | 19.2178 | 0 | Africa/Bangui | populated place | ||
| 235775 | Zouniaka | CF | Ouaka | Grimari | 5.43341 | 20.09098 | 0 | Africa/Bangui | populated place | ||
| 2388015 | Boséra | Bosera,Bossera,Bosséra,Boséra | CF | Ouham | Nana-Bakassa | 7.01525 | 17.51026 | 0 | Africa/Bangui | populated place | |
| 2387702 | Boungba | CF | Ouham | Bossangoa | 6.8192 | 17.21316 | 0 | Africa/Bangui | populated place | ||
| 2387290 | Dépa | CF | Sangha-Mbaéré | Bambio | 4.12628 | 16.80173 | 0 | Africa/Bangui | populated place | ||
| 236748 | Owou | Owou,Owou II | CF | Haute-Kotto | Yalinga | 6.40932 | 22.98376 | 0 | Africa/Bangui | populated place | |
| 2383050 | Songo | CF | Ouham-Pendé | Bozoum Sub-Prefecture | 6.42505 | 16.02432 | 0 | Africa/Bangui | populated place | ||
| 237786 | Maliko | CF | Mbomou | Bakouma | 5.04166 | 22.47732 | 0 | Africa/Bangui | populated place | ||
| 2387373 | Dao II | CF | Ouham | Bouca | 6.68333 | 18.25 | 0 | Africa/Bangui | populated place | ||
| 2382479 | Yandiba | CF | Mambéré-Kadéï | Dédé-Mokouba | 3.91358 | 15.42983 | 0 | Africa/Bangui | populated place | ||
| 2390358 | Baga | CF | Kémo | Dékoa | 6.18333 | 19.41667 | 0 | Africa/Bangui | populated place | ||
| 2382139 | Zofo | CF | Nana-Mambéré | Bouar Sub-Prefecture | 5.98208 | 15.57901 | 0 | Africa/Bangui | populated place | ||
| 236667 | Pata | Adabourou,Pata | CF | Bamingui-Bangoran | Ndélé | 8.05517 | 21.39734 | 0 | Africa/Bangui | populated place | |
| 2387868 | Boudoua | Bidoua,Boudoua,Budua | CF | Mambéré-Kadéï | Carnot | 4.47047 | 16.35464 | 0 | Africa/Bangui | populated place | |
| 237586 | Mbinda | CF | Ouaka | Kouango | 5.1482 | 20.34161 | 0 | Africa/Bangui | populated place | ||
| 236606 | Piko | CF | Mbomou | Bangassou | 4.95 | 23.65 | 0 | Africa/Bangui | populated place | ||
| 2386552 | Godoroforo | CF | Ombella-M’Poko | Boali Sub-Prefecture | 4.51813 | 17.84283 | 0 | Africa/Bangui | populated place | ||
| 2385298 | Lébé II | CF | Lobaye | Mbaiki | 3.78223 | 17.53087 | 0 | Africa/Bangui | populated place | ||
| 237227 | Ngoto | CF | Basse-Kotto | Kembe | 4.43333 | 21.91667 | 0 | Africa/Bangui | populated place | ||
| 7524070 | Bouyali | CF | Ombella-M’Poko | Bossembele Sub-Prefecture | 5.2649 | 17.8311 | 0 | Africa/Bangui | populated place | ||
| 239163 | Gondo | Gondo | CF | Bamingui-Bangoran | Ndélé | 8.47463 | 20.68185 | 0 | Africa/Bangui | populated place | |
| 238452 | Kaousa | CF | Mbomou | Bakouma | 5.77927 | 22.48233 | 0 | Africa/Bangui | populated place | ||
| 7525370 | Nguéréfara-Rèngao | CF | Ouaka | Grimari | 5.76267 | 19.7387 | 0 | Africa/Bangui | populated place | ||
| 2382530 | Yaka | CF | Lobaye | Mbaiki | 4.12886 | 18.24332 | 0 | Africa/Bangui | populated place | ||
| 239510 | Dokoua | CF | Ouaka | Kouango | 4.66869 | 20.47286 | 0 | Africa/Bangui | populated place | ||
| 2383416 | Poko | CF | Nana-Grébizi | Kaga-Bandoro | 6.84069 | 19.16277 | 0 | Africa/Bangui | populated place | ||
| 240693 | Bakoua | CF | Mbomou | Bangassou | 5.33333 | 23.23333 | 0 | Africa/Bangui | populated place | ||
| 6870034 | Babri | CF | Ouham-Pendé | Ngaoundaye | 7.13252 | 15.26733 | 0 | Africa/Bangui | populated place | ||
| 238956 | Gouleniero | CF | Basse-Kotto | Kembe | 4.36667 | 21.46667 | 0 | Africa/Bangui | populated place | ||
| 7524125 | Nonbandja | CF | Ouham | Kabo | 7.97046 | 18.69363 | 0 | Africa/Bangui | populated place | ||
| 2390658 | Ambili | CF | Ouham | Bouca | 6.46667 | 18.3 | 0 | Africa/Bangui | populated place | ||
| 2384248 | Nagati | CF | Sangha-Mbaéré | Nola | 3.75406 | 16.22411 | 0 | Africa/Bangui | populated place | ||
| 240044 | Botcho | CF | Ouaka | Kouango | 5.02455 | 20.41062 | 0 | Africa/Bangui | populated place | ||
| 239221 | Ginidagini | CF | Haut-Mbomou | Zémio | 5.35 | 25.35 | 0 | Africa/Bangui | populated place | ||
| 2387962 | Botouba | CF | Ombella-M’Poko | Bogangolo | 5.45198 | 18.34127 | 0 | Africa/Bangui | populated place | ||
| 2387669 | Bourou II | CF | Ouham-Pendé | Paoua | 6.8773 | 16.5216 | 0 | Africa/Bangui | populated place | ||
| 236616 | Pibi | CF | Mbomou | Bakouma | 5.87208 | 22.21514 | 0 | Africa/Bangui | populated place | ||
| 237976 | Lengo | CF | Mbomou | Bakouma | 5.67422 | 22.87578 | 0 | Africa/Bangui | populated place | ||
| 2388470 | Bogbo | CF | Ombella-M’Poko | Damara | 4.96737 | 18.71144 | 0 | Africa/Bangui | populated place | ||
| 2387894 | Bouboui | CF | Ombella-M’Poko | Bimbo Sub-Prefecture | 4.61201 | 18.32555 | 0 | Africa/Bangui | populated place | ||
| 236507 | Rehou | Rehou,Reou,Réou | CF | Ouaka | Bambari | 5.56665 | 21.63218 | 0 | Africa/Bangui | populated place | |
| 2386146 | Hokso II | CF | Ouham-Pendé | Paoua | 6.73326 | 16.65028 | 0 | Africa/Bangui | populated place | ||
| 2384769 | Mbaka | Baya-Kala,M’Bacca,Mbaka,M’Bacca | CF | Mambéré-Kadéï | Carnot | 4.8777 | 15.97641 | 0 | Africa/Bangui | populated place | |
| 240418 | Barasi | CF | Mbomou | Bangassou | 4.94174 | 23.65011 | 0 | Africa/Bangui | populated place | ||
| 236648 | Payo | CF | Ouaka | Ippy | 6.28333 | 21.26667 | 0 | Africa/Bangui | populated place | ||
| 2382939 | Tanganésa | CF | Kémo | Sibut | 5.86667 | 19.15 | 0 | Africa/Bangui | populated place | ||
| 2389373 | Békaoussi | CF | Ombella-M’Poko | Yaloke Sub-Prefecture | 5.56087 | 16.70746 | 0 | Africa/Bangui | populated place | ||
| 239826 | Dacpa Mindou | CF | Bamingui-Bangoran | Bamingui | 8.15945 | 20.40737 | 0 | Africa/Bangui | populated place | ||
| 240631 | Balouba Yakandjia | Balouba Yakandjia | CF | Bamingui-Bangoran | Bamingui | 7.48333 | 20.18333 | 0 | Africa/Bangui | populated place | |
| 2385967 | Kambakota | Kamba,Kambakota | CF | Ouham | Batangafo | 7.15734 | 17.86769 | 0 | Africa/Bangui | populated place | |
| 2383116 | Moyenne-Sido | Moyenne-Sido,Sido | CF | Ouham | Kabo | 8.22525 | 18.71545 | 0 | Africa/Bangui | populated place | |
| 2389046 | Betoko | Betoko,Bokoto | CF | Nana-Mambéré | Baboua Sub-Prefecture | 5.91667 | 14.53333 | 0 | Africa/Bangui | populated place | |
| 2383030 | Soso | Soso,Sosso | CF | Mambéré-Kadéï | Sosso-Nakombo | 3.91941 | 15.50515 | 0 | Africa/Bangui | populated place | |
| 237700 | Massini | Masini,Massini | CF | Mbomou | Bakouma | 5.17781 | 22.83532 | 0 | Africa/Bangui | populated place | |
| 2387571 | Bozaka | CF | Ombella-M’Poko | Yaloke Sub-Prefecture | 5.109 | 17.12715 | 0 | Africa/Bangui | populated place | ||
| 2385416 | Kountao | CF | Ouham-Pendé | Bocaranga | 7.06296 | 15.67524 | 0 | Africa/Bangui | populated place | ||
| 7525381 | Badga | CF | Kémo | Sibut | 5.76355 | 19.44117 | 0 | Africa/Bangui | populated place | ||
| 238942 | Goulonga | CF | Ouaka | Ippy | 6.11667 | 21.3 | 0 | Africa/Bangui | populated place | ||
| 7524179 | Bodéya | CF | Ouham | Batangafo | 7.23553 | 18.3143 | 0 | Africa/Bangui | populated place | ||
| 236835 | Ouara | CF | Mbomou | Bakouma | 5.53333 | 23.31667 | 0 | Africa/Bangui | populated place | ||
| 2388834 | Bingakola | CF | Ouham | Bouca | 6.14039 | 18.37831 | 0 | Africa/Bangui | populated place | ||
| 238273 | Kolinga | CF | Ouaka | Bambari | 5.81431 | 21.36272 | 0 | Africa/Bangui | populated place | ||
| 2387876 | Boudingué | CF | Ombella-M’Poko | Bogangolo | 5.75 | 17.91667 | 0 | Africa/Bangui | populated place | ||
| 2593681 | Dimbanga | CF | Lobaye | Mbaiki | 4.32187 | 18.1811 | 0 | Africa/Bangui | populated place |
The Central African Republic: Mapping the Hidden Geometry of a Landlocked Heart
Geographical Complexity Beyond the Headlines
Often overlooked in global discourse, the Central African Republic (CAR) is not a blank space on the map—it’s a living, breathing mosaic of landscapes, cultures, and urban settlements that deserve far more analytical attention. As a geographer, I find in CAR a country that challenges conventional classifications. Its vast plateaus, savannah belts, and riverine boundaries are layered not only with environmental meaning but also with geopolitical weight.
It is in these layers that city-level data becomes essential—not just to understand where people live, but how they are organized, governed, and connected. My recent work focuses precisely on that: delivering a complete and accurate database of CAR’s cities, tied to their respective regions and departments.
From Bangui to the Periphery: A Decentralized Urban Puzzle
The capital, Bangui, often dominates the narrative. But the country’s spatial organization is far from centralized. From Bossangoa in the west to Obo near the Sudanese border, the towns of CAR form an essential puzzle of regional identities, trade dynamics, and socio-political networks. Each one belongs to a specific prefecture, a local administrative level that plays a crucial role in development policies, resource distribution, and local governance.
By mapping cities within their prefectures and sub-prefectures, we move past abstraction. We make the country legible. And more importantly, we make it actionable for planners, researchers, NGOs, and developers alike.
Precision in Position: The Role of Geographic Coordinates
Understanding the exact location of a city isn’t just for cartographers. In CAR, where logistics challenges are immense and accessibility is often seasonal, knowing the coordinates of each town is the difference between effective humanitarian aid and misallocation of resources. My database includes precise latitude and longitude points for every city in the country—offering the geospatial intelligence needed to power transportation models, election logistics, and environmental assessments.
Why Excel Matters: Accessibility Without Compromise
In the past, such data might have only existed in obscure formats or in disconnected silos. Today, I’m proud to say that this dataset is available in five structured formats, with a strong emphasis on the most universally useful: Excel (.xlsx).
Why Excel? Because it democratizes access. Urban planners in Bangui, humanitarian logisticians in Nairobi, or academic researchers in Paris can all interact with the data immediately—no technical setup required. You can filter by region, group by department, or visualize settlement density in seconds. Excel combines precision with usability in a way no other format does.
Multi-Format for Multi-Function
Of course, the needs of geographers and developers differ. That’s why the dataset is also available in:
* CSV: clean, lightweight, and ready for scripting
* SQL: ideal for structured database systems and query design
* JSON: perfect for front-end development and web integration
* XML: compatible with a wide range of legacy systems
But Excel remains the flagship—because it brings this knowledge directly into the hands of non-specialists without sacrificing structure or integrity.
Why City-Level Data in CAR Is Not Optional
In a nation where physical infrastructure remains limited and institutional presence often fragile, cities are more than urban units—they are lifelines. Understanding the full spectrum of CAR’s urban geography enables better humanitarian deployment, more targeted infrastructure planning, and deeper academic inquiry into spatial inequality and urban resilience.
The complexity of CAR demands a granular lens. That lens is built on data—rich, structured, and accessible.
Conclusion
The Central African Republic may span thousands of kilometers of forest and grassland, but it’s the web of its cities that defines its spatial logic. By gathering and structuring the urban data of CAR—including region, department, and exact coordinates—we do more than just catalog settlements. We illuminate a country too often left in statistical darkness. With new access via Excel and other formats, this dataset opens a door to better planning, smarter research, and meaningful progress in a region where every kilometer counts.
