Burundi 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 Burundi, 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 1219 geographic locations across Burundi.
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 Burundi is Gitega.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 430258 | Gihororo | BI | Ngozi | Marangara | -2.6896 | 29.9554 | 0 | Africa/Bujumbura | populated place | ||
| 432389 | Bugabira | BI | Kirundo | Commune of Kirundo | -2.5314 | 30.0706 | 0 | Africa/Bujumbura | populated place | ||
| 426826 | Nyarumuri | BI | Cankuzo | Commune of Cankuzo | -3.28964 | 30.45814 | 0 | Africa/Bujumbura | populated place | ||
| 431575 | Butihinda | Butihinda | BI | Muyinga | Butihinda | -2.7163 | 30.3197 | 0 | Africa/Bujumbura | populated place | |
| 8306766 | Monge | BI | Ruyigi | Ruyigi | -3.36277 | 30.34931 | 0 | Africa/Bujumbura | populated place | ||
| 423258 | Mudende | BI | Rumonge | Buyengero | -3.8917 | 29.5166 | 0 | Africa/Bujumbura | populated place | ||
| 432497 | Kanyinya | BI | Kirundo | Commune of Kirundo | -2.6116 | 30.0743 | 0 | Africa/Bujumbura | populated place | ||
| 428132 | Gashanga | BI | Karuzi | Bugenyuzi | -3.03993 | 30.14003 | 0 | Africa/Bujumbura | populated place | ||
| 428261 | Bwasare | BI | Karuzi | Buhiga | -3.14401 | 30.19465 | 0 | Africa/Bujumbura | populated place | ||
| 428327 | Kaganda | BI | Karuzi | Gihogazi | -3.20105 | 30.02517 | 0 | Africa/Bujumbura | populated place | ||
| 430413 | Nyamurenza | BI | Ngozi | Nyamurenza | -2.8232 | 29.8645 | 0 | Africa/Bujumbura | populated place | ||
| 428114 | Mugende | BI | Karuzi | Gitaramuka | -3.02906 | 30.09676 | 0 | Africa/Bujumbura | populated place | ||
| 429709 | Kirumura | BI | Cibitoke | Bukinanyana | -2.87302 | 29.38963 | 0 | Africa/Bujumbura | populated place | ||
| 428091 | Kidahwe | BI | Karuzi | Bugenyuzi | -3.01432 | 30.00771 | 0 | Africa/Bujumbura | populated place | ||
| 422146 | Gitabi | BI | Rutana | Gitanga | -4.0625 | 29.9456 | 0 | Africa/Bujumbura | populated place | ||
| 423814 | Mutumba | BI | Mwaro | Rusaka | -3.5199 | 29.6918 | 0 | Africa/Bujumbura | populated place | ||
| 423154 | Ngoma | BI | Rumonge | Buyengero | -3.8256 | 29.5324 | 0 | Africa/Bujumbura | populated place | ||
| 424119 | Murango | BI | Bururi | Commune of Matana | -3.7433 | 29.6663 | 0 | Africa/Bujumbura | populated place | ||
| 428229 | Ntarika | BI | Karuzi | Bugenyuzi | -3.1142 | 30.0855 | 0 | Africa/Bujumbura | populated place | ||
| 428144 | Rubavu | BI | Karuzi | Buhiga | -3.0505 | 30.2202 | 0 | Africa/Bujumbura | populated place | ||
| 423885 | Gitara | BI | Mwaro | Gisozi | -3.5628 | 29.6455 | 0 | Africa/Bujumbura | populated place | ||
| 427761 | Kabweru | BI | Muyinga | Buhinyuza | -3.01421 | 30.32521 | 0 | Africa/Bujumbura | populated place | ||
| 9173226 | Rusenyi | BI | Kirundo | Busoni | -2.44694 | 30.25306 | 0 | Africa/Bujumbura | populated place | ||
| 422317 | Muhama | BI | Makamba | Kayogoro | -4.1911 | 29.9627 | 0 | Africa/Bujumbura | populated place | ||
| 428258 | Kigarama | BI | Karuzi | Gihogazi | -3.1404 | 30.0044 | 0 | Africa/Bujumbura | populated place | ||
| 421706 | Nyarubanga | BI | Makamba | Kibago | -4.2654 | 29.9695 | 0 | Africa/Bujumbura | populated place | ||
| 431135 | Katoke | BI | Muyinga | Giteranyi | -2.4336 | 30.4895 | 0 | Africa/Bujumbura | populated place | ||
| 424503 | Muyuga | BI | Gitega | Ryansoro | -3.7028 | 29.8348 | 0 | Africa/Bujumbura | populated place | ||
| 428141 | Mutumba | BI | Karuzi | Gitaramuka | -3.0462 | 30.0897 | 0 | Africa/Bujumbura | populated place | ||
| 422771 | Vyuma | BI | Rutana | Musongati | -3.8101 | 30.0251 | 0 | Africa/Bujumbura | populated place | ||
| 423602 | Kabezi | BI | Bujumbura Rural | Kabezi | -3.5375 | 29.3502 | 0 | Africa/Bujumbura | populated place | ||
| 423030 | Kayogoro | BI | Makamba | Kayogoro | -4.12889 | 29.94222 | 0 | Africa/Bujumbura | populated place | ||
| 429893 | Mugina | BI | Cibitoke | Commune of Mugina | -2.756 | 29.1101 | 0 | Africa/Bujumbura | populated place | ||
| 424099 | Gasibe | BI | Bururi | Commune of Matana | -3.723 | 29.7361 | 0 | Africa/Bujumbura | populated place | ||
| 425972 | Bitare | BI | Gitega | Bugendana | -3.2657 | 29.9031 | 0 | Africa/Bujumbura | populated place | ||
| 428352 | Kibande | BI | Karuzi | Mutumba | -3.2158 | 30.2244 | 0 | Africa/Bujumbura | populated place | ||
| 425595 | Munanira | BI | Muramvya | Rutegama | -3.2957 | 29.7432 | 0 | Africa/Bujumbura | populated place | ||
| 11205199 | Ntwago | BI | Kirundo | Ntega | -2.54103 | 30.02628 | 0 | Africa/Bujumbura | populated place | ||
| 431256 | Ruhehe | BI | Kirundo | Bugabira | -2.4349 | 30.0419 | 0 | Africa/Bujumbura | populated place | ||
| 422178 | Rusenyi | BI | Makamba | Commune of Makamba | -4.0958 | 29.8085 | 0 | Africa/Bujumbura | populated place | ||
| 428128 | Mayenzi | BI | Karuzi | Buhiga | -3.03491 | 30.24492 | 0 | Africa/Bujumbura | populated place | ||
| 427891 | Muryamvubu | BI | Muyinga | Mwakiro | -3.0992 | 30.2814 | 0 | Africa/Bujumbura | populated place | ||
| 430745 | Rwira | BI | Kayanza | Kabarore | -2.8218 | 29.5853 | 0 | Africa/Bujumbura | populated place | ||
| 428357 | Rwigitsibati | BI | Karuzi | Shombo | -3.2195 | 30.0716 | 0 | Africa/Bujumbura | populated place | ||
| 423397 | Kirogorya | BI | Bururi | Bururi | -3.9973 | 29.7317 | 0 | Africa/Bujumbura | populated place | ||
| 428362 | Rwera | BI | Karuzi | Nyabikere | -3.22101 | 30.19247 | 0 | Africa/Bujumbura | populated place | ||
| 429589 | Cunywe | BI | Gitega | Bugendana | -3.2392 | 29.8938 | 0 | Africa/Bujumbura | populated place | ||
| 428192 | Bugenyuzi | BI | Karuzi | Bugenyuzi | -3.08875 | 30.06183 | 0 | Africa/Bujumbura | populated place | ||
| 12324432 | Murango | BI | Rumonge | Commune of Rumonge | -3.86513 | 29.37691 | 0 | Africa/Bujumbura | populated place | ||
| 428117 | Muririmbo | BI | Karuzi | Bugenyuzi | -3.0282 | 30.0416 | 0 | Africa/Bujumbura | populated place | ||
| 430479 | Buye | BI | Ngozi | Mwumba | -2.865 | 29.819 | 0 | Africa/Bujumbura | populated place | ||
| 422128 | Jenda | BI | Makamba | Commune of Makamba | -4.0437 | 29.8086 | 0 | Africa/Bujumbura | populated place | ||
| 428298 | Kigina | BI | Karuzi | Gihogazi | -3.1753 | 30.0036 | 0 | Africa/Bujumbura | populated place | ||
| 428083 | Murwirambo | BI | Karuzi | Gitaramuka | -3.009 | 30.09286 | 0 | Africa/Bujumbura | populated place | ||
| 428772 | Kiziba | BI | Kayanza | Commune of Matongo | -3.03251 | 29.60992 | 0 | Africa/Bujumbura | populated place | ||
| 427766 | Shori | BI | Muyinga | Buhinyuza | -3.01429 | 30.38225 | 0 | Africa/Bujumbura | populated place | ||
| 426868 | Ruhanura | BI | Ruyigi | Butezi | -3.32153 | 30.30559 | 0 | Africa/Bujumbura | populated place | ||
| 423836 | Nyakararo | BI | Mwaro | Gisozi | -3.5297 | 29.6054 | 0 | Africa/Bujumbura | populated place | ||
| 428163 | Burenza | BI | Karuzi | Buhiga | -3.0609 | 30.2356 | 0 | Africa/Bujumbura | populated place | ||
| 422559 | Kanyuzwa | BI | Bururi | Rutovu | -3.819 | 29.8262 | 0 | Africa/Bujumbura | populated place | ||
| 8300748 | Nyamihanda | BI | Rutana | Musongati | -3.7387 | 30.1254 | 0 | Africa/Bujumbura | populated place | ||
| 428152 | Nyagoba | BI | Karuzi | Bugenyuzi | -3.05455 | 30.10721 | 0 | Africa/Bujumbura | populated place | ||
| 428007 | Mikuku | BI | Cankuzo | Commune of Cankuzo | -3.19704 | 30.49639 | 0 | Africa/Bujumbura | populated place | ||
| 423819 | Rukina | BI | Bujumbura Rural | Mukike | -3.52679 | 29.51233 | 0 | Africa/Bujumbura | populated place | ||
| 428228 | Rwimbogo | BI | Karuzi | Bugenyuzi | -3.11382 | 30.10398 | 0 | Africa/Bujumbura | populated place | ||
| 8306760 | Murago | BI | Ruyigi | Gisuru | -3.4255 | 30.3934 | 0 | Africa/Bujumbura | populated place | ||
| 427917 | Gakombe | BI | Muyinga | Mwakiro | -3.1187 | 30.2784 | 0 | Africa/Bujumbura | populated place | ||
| 426854 | Rusasa | BI | Ruyigi | Bweru | -3.30695 | 30.43986 | 0 | Africa/Bujumbura | populated place | ||
| 427609 | Nyakatsi | BI | Cankuzo | Commune of Cankuzo | -3.1556 | 30.63 | 0 | Africa/Bujumbura | populated place | ||
| 428305 | Nyarudehe | BI | Karuzi | Mutumba | -3.1813 | 30.1828 | 0 | Africa/Bujumbura | populated place | ||
| 427848 | Mukoni | BI | Karuzi | Buhiga | -3.0694 | 30.254 | 0 | Africa/Bujumbura | populated place | ||
| 432608 | Bukuba | BI | Kirundo | Vumbi | -2.6832 | 30.0797 | 0 | Africa/Bujumbura | populated place | ||
| 429914 | Kagogo | BI | Cibitoke | Commune of Mugina | -2.7753 | 29.1113 | 0 | Africa/Bujumbura | populated place | ||
| 423225 | Mbariza | BI | Bururi | Songa | -3.8705 | 29.5907 | 0 | Africa/Bujumbura | populated place | ||
| 425886 | Nyamurenge | BI | Mwaro | Kayokwe | -3.4637 | 29.7169 | 0 | Africa/Bujumbura | populated place | ||
| 428172 | Bihemba | BI | Karuzi | Bugenyuzi | -3.07172 | 30.04762 | 0 | Africa/Bujumbura | populated place | ||
| 426995 | Nyarutiti | BI | Ruyigi | Ruyigi | -3.4008 | 30.3793 | 0 | Africa/Bujumbura | populated place | ||
| 426913 | Gasyangiri | BI | Ruyigi | Bweru | -3.34465 | 30.41917 | 0 | Africa/Bujumbura | populated place | ||
| 422261 | Nyetongwe | BI | Makamba | Commune of Makamba | -4.1482 | 29.7827 | 0 | Africa/Bujumbura | populated place | ||
| 428058 | Kidogo | BI | Ruyigi | Bweru | -3.2367 | 30.4033 | 0 | Africa/Bujumbura | populated place | ||
| 432119 | Gakere | BI | Ngozi | Kiremba | -2.85417 | 30.04306 | 0 | Africa/Bujumbura | populated place | ||
| 425104 | Ruhongoro | BI | Ruyigi | Kinyinya | -3.6366 | 30.3799 | 0 | Africa/Bujumbura | populated place | ||
| 428243 | Gasaka | BI | Karuzi | Bugenyuzi | -3.13104 | 30.05432 | 0 | Africa/Bujumbura | populated place | ||
| 430754 | Kididiri | BI | Ngozi | Busiga | -2.8274 | 29.7329 | 0 | Africa/Bujumbura | populated place | ||
| 430339 | Birambi | BI | Ngozi | Nyamurenza | -2.78717 | 29.90024 | 0 | Africa/Bujumbura | populated place | ||
| 428289 | Gatare | BI | Karuzi | Bugenyuzi | -3.16546 | 30.04955 | 0 | Africa/Bujumbura | populated place | ||
| 431018 | Gahombo | BI | Kayanza | Gahombo | -2.9653 | 29.7332 | 0 | Africa/Bujumbura | populated place | ||
| 423767 | Gipfizi | BI | Rumonge | Commune of Rumonge | -3.7282 | 29.3508 | 0 | Africa/Bujumbura | populated place | ||
| 426895 | Bigombo | BI | Ruyigi | Bweru | -3.3354 | 30.473 | 0 | Africa/Bujumbura | populated place | ||
| 428784 | Gasenyi | BI | Kayanza | Commune of Matongo | -3.04112 | 29.63361 | 0 | Africa/Bujumbura | populated place | ||
| 423682 | Rugombero | BI | Rumonge | Muhuta | -3.6186 | 29.4306 | 0 | Africa/Bujumbura | populated place | ||
| 422819 | Nyamiyaga | BI | Rutana | Mpinga-Kayove | -3.8345 | 30.1322 | 0 | Africa/Bujumbura | populated place | ||
| 427871 | Rutarabana | BI | Muyinga | Mwakiro | -3.08117 | 30.30462 | 0 | Africa/Bujumbura | populated place | ||
| 429602 | Bitare | Bitare,Bugendana | BI | Gitega | Bugendana | -3.2313 | 29.9158 | 0 | Africa/Bujumbura | populated place | |
| 432572 | Rugomero | BI | Kirundo | Gitobe | -2.6612 | 30.192 | 0 | Africa/Bujumbura | populated place | ||
| 425909 | Rwibaga | BI | Bujumbura Rural | Mugongomanga | -3.47441 | 29.54593 | 0 | Africa/Bujumbura | populated place | ||
| 430732 | Rutega | BI | Kayanza | Kabarore | -2.8126 | 29.6489 | 0 | Africa/Bujumbura | populated place | ||
| 426498 | Rusamaza | BI | Karuzi | Shombo | -3.3218 | 30.0267 | 0 | Africa/Bujumbura | populated place | ||
| 428078 | Gasenyi | BI | Karuzi | Bugenyuzi | -3.00599 | 30.01133 | 0 | Africa/Bujumbura | populated place | ||
| 430067 | Murambagize | BI | Cibitoke | Commune of Buganda | -2.9411 | 29.1973 | 0 | Africa/Bujumbura | populated place |
Burundi: A Geographer’s Fascination with a Nation of Contrasts
Exploring the Heart of the African Great Lakes
Few countries stir the imagination of a geographer quite like Burundi. Tucked into the heart of the African Great Lakes region, it’s a nation where topography, culture, and human settlement form a tight and mesmerizing interlace. Despite its modest size, Burundi boasts a remarkably complex geography—rising hills, fertile valleys, and densely populated cities that seem to sprout from every ridge and shore.
But understanding Burundi isn’t just a question of elevation or rainfall patterns. It's about mapping the human thread—its cities, towns, and communities—and seeing how they breathe life into the land.
Why City-Level Data is Crucial
In my work, I’ve come to understand that macro-level mapping doesn’t do justice to countries like Burundi. With over a hundred urban settlements, each with their own administrative context, we need to zoom in with precision. That means having access to detailed information: the name of every city, the region it belongs to, the department it operates under, and most importantly, its geographical coordinates.
This kind of granular dataset allows researchers and planners to break through the fog of generality. A road development plan in the Bururi region or a health initiative in Ngozi needs more than a map—it needs structured, actionable data.
Putting Cities on the Map with Latitude and Longitude
Geographic coordinates are not just numerical placeholders. In a country like Burundi—marked by its rugged terrain and limited infrastructure—knowing the exact location of each settlement is essential. Elevation alone varies so dramatically that two cities just 50 kilometers apart may experience entirely different climates and agricultural realities.
That’s why my dataset includes detailed latitude and longitude data for each city. This lets you overlay urban centers onto climate maps, logistic corridors, or economic zones with a high level of confidence—opening up new layers of insight for anyone from hydrologists to telecom engineers.
Why Excel Has Become the Geographer’s Best Friend
One of the most significant enhancements I’ve recently made is adding full Excel (.xlsx) compatibility to the Burundi cities dataset. Why? Because Excel isn't just a spreadsheet tool—it's a geographer’s sandbox. With just a few filters, anyone can extract cities by department, sort them by region, or create instant charts to analyze urban distribution patterns.
Excel’s flexibility allows local governments, NGOs, and academics to interact with the data dynamically, without the need for heavy GIS software. From pivot tables to visual graphs, it’s now easier than ever to turn raw data into real-world insights.
Also Available in Other Key Formats
While Excel is now the centerpiece of our offering, the dataset is also available in formats tailored for integration into diverse systems:
* **CSV** for fast and lightweight processing
* **SQL** for embedding into relational databases
* **JSON** for seamless API deployment and web applications
* **XML** for robust enterprise-level interoperability
This ensures that whether you're using data in a research lab or a regional planning office, there’s a format that fits your workflow.
From Data to Development
The real value of this data lies in how it empowers progress. NGOs can map underserved urban zones for educational outreach. Researchers can correlate city growth with environmental degradation. Even tourism developers can use it to understand travel flows and investment hotspots.
The cities of Burundi are more than dots on a map—they’re anchors of commerce, culture, and change. And through structured data, we can make their stories legible.
Conclusion
Burundi’s geography is intricate, vibrant, and often misunderstood. But with the right tools—especially now with the addition of Excel—you can step beyond surface impressions and begin to work with a living, breathing geographic reality. This dataset opens the door not just to analysis, but to impact. It’s not about collecting names—it’s about making Burundi visible in every sense of the word.
