Namibia Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 24 March 2026.
Here you’ll find a curated sample of 100 key cities from Namibia, 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 2137 geographic locations across Namibia.
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 Namibia is Windhoek.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3354265 | Onankali | Onankali | NA | Oshikoto | -18.16667 | 16.35 | 0 | Africa/Windhoek | populated place | ||
| 3354442 | Omitivine | NA | Omaheke | -23.33333 | 19.35 | 0 | Africa/Windhoek | populated place | |||
| 3354130 | Oniipa | Oniipa | NA | Oshikoto | -17.91667 | 16.03333 | 0 | Africa/Windhoek | populated place | ||
| 3354297 | Onamudime | NA | Ohangwena | -17.56667 | 16.95 | 0 | Africa/Windhoek | populated place | |||
| 12538234 | Glencoe Post Two | Glencoe Post 2,Glencoe Post Two,GlencoePost2,GlencoePostTwo | NA | Hardap | -24.98081 | 18.10956 | 0 | Africa/Windhoek | populated place | ||
| 3353868 | Otjimukona | NA | Khomas | -22.68333 | 17.63333 | 0 | Africa/Windhoek | populated place | |||
| 3356295 | Katope-Komugoro | NA | Kavango West | -17.75 | 18.21667 | 0 | Africa/Windhoek | populated place | |||
| 3353345 | Saigcakate | Saigcakate,Saigeakate | NA | Kavango West | -17.86667 | 19.48333 | 0 | Africa/Windhoek | populated place | ||
| 3353980 | Oshilulu | NA | Omusati | -18.01667 | 15.06667 | 0 | Africa/Windhoek | populated place | |||
| 876800 | Simajumbulas | Simajumbulas,Simayumbula | NA | Zambezi | -17.73333 | 23.95 | 0 | Africa/Windhoek | populated place | ||
| 877051 | Matongos | Matongo,Matongos | NA | Zambezi | -17.73333 | 23.88333 | 0 | Africa/Windhoek | populated place | ||
| 3358079 | Dakwa | NA | Kavango West | -17.71667 | 18.16667 | 0 | Africa/Windhoek | populated place | |||
| 3355653 | Lyakahani | NA | Oshikoto | -17.85 | 16.1 | 0 | Africa/Windhoek | populated place | |||
| 3354140 | Onhunda | NA | Ohangwena | -17.63333 | 16.81667 | 0 | Africa/Windhoek | populated place | |||
| 3357608 | Esheshete | NA | Oshikoto | -18.1 | 16.1 | 0 | Africa/Windhoek | populated place | |||
| 877335 | Bwabwata | NA | Zambezi | -17.8 | 22.56667 | 0 | Africa/Windhoek | populated place | |||
| 3354626 | Okovihona | NA | Kunene | -17.66667 | 13.08333 | 0 | Africa/Windhoek | populated place | |||
| 3355074 | Nossobville | NA | Omaheke | -22.45 | 18.98333 | 0 | Africa/Windhoek | populated place | |||
| 3354997 | Oahava | NA | Omaheke | -23.55 | 19.33333 | 0 | Africa/Windhoek | populated place | |||
| 877227 | Kaliangile | NA | Zambezi | -17.75 | 23.85 | 0 | Africa/Windhoek | populated place | |||
| 3354077 | Opuwo | OPW,Ohopoho,Ohopuho,Opuwa | NA | Kunene | -18.06068 | 13.83998 | 5101 | Africa/Windhoek | seat of a first-order administrative division | ||
| 3355569 | Mavanze | NA | Kavango East | -17.98333 | 19.75 | 0 | Africa/Windhoek | populated place | |||
| 3354858 | Okakwiyu | NA | Oshikoto | -18.18333 | 16.26667 | 0 | Africa/Windhoek | populated place | |||
| 3353790 | Otjomukona | NA | Omaheke | -23.16667 | 19.46667 | 0 | Africa/Windhoek | populated place | |||
| 3352452 | Uukwanatshikale | NA | Omusati | -17.58333 | 15.58333 | 0 | Africa/Windhoek | populated place | |||
| 12519872 | Goedgevonden | NA | Karas | -27.63821 | 18.63388 | 0 | Africa/Windhoek | populated place | |||
| 12536434 | Poortjie | NA | Karas | -26.19931 | 18.0168 | 0 | Africa/Windhoek | populated place | |||
| 877007 | Mushovoyi | Mushovoyi,Musovoye | NA | Kavango East | -17.91667 | 20.08333 | 0 | Africa/Windhoek | populated place | ||
| 876945 | Nhoma | NA | Kavango East | -18.91667 | 20.93333 | 0 | Africa/Windhoek | populated place | |||
| 12521960 | Middelplaas | NA | Karas | -28.39395 | 18.60691 | 0 | Africa/Windhoek | populated place | |||
| 3352075 | Wolfbeen | NA | Karas | -27.2 | 16.85 | 0 | Africa/Windhoek | populated place | |||
| 3357806 | Eengolo | NA | Omusati | -17.6 | 15.08333 | 0 | Africa/Windhoek | populated place | |||
| 3354163 | Ongolongela | NA | Ohangwena | -17.61667 | 17.18333 | 0 | Africa/Windhoek | populated place | |||
| 3358723 | Aminuis | Aminuis | NA | Omaheke | -23.63333 | 19.36667 | 0 | Africa/Windhoek | populated place | ||
| 12519856 | Goedgevonden | NA | Karas | -27.73019 | 18.68569 | 0 | Africa/Windhoek | populated place | |||
| 876741 | Utokota | NA | Kavango East | -17.9 | 20.01667 | 0 | Africa/Windhoek | populated place | |||
| 3354019 | Oshali | NA | Ohangwena | -17.5 | 17.03333 | 0 | Africa/Windhoek | populated place | |||
| 3354113 | Ontuli | NA | Oshikoto | -17.75 | 17.21667 | 0 | Africa/Windhoek | populated place | |||
| 3354429 | Ompunda | NA | Oshana | -18.03333 | 15.88333 | 0 | Africa/Windhoek | populated place | |||
| 3354279 | Onandomba | NA | Oshikoto | -18.11667 | 16.28333 | 0 | Africa/Windhoek | populated place | |||
| 3353934 | Otavi | Otavi,Otawi | NA | Otjozondjupa | -19.65 | 17.33333 | 4562 | Africa/Windhoek | populated place | ||
| 3356172 | Klein Aub | Klein Aub | NA | Hardap | -23.78333 | 16.63333 | 0 | Africa/Windhoek | populated place | ||
| 876841 | Sharughanda | NA | Kavango East | -18.01667 | 20.78333 | 0 | Africa/Windhoek | populated place | |||
| 12238015 | Motsomi | NA | Omaheke | -23.50236 | 19.89357 | 0 | Africa/Windhoek | populated place | |||
| 877158 | Khance | NA | Zambezi | -18.2 | 21.78333 | 0 | Africa/Windhoek | populated place | |||
| 877148 | Kushalula | NA | Zambezi | -18 | 23.31667 | 0 | Africa/Windhoek | populated place | |||
| 3355402 | Musu | NA | Kavango West | -17.6 | 18.6 | 0 | Africa/Windhoek | populated place | |||
| 3358735 | Amasbank | Amasbank,Klein Amasbank | NA | Erongo | -21.11667 | 15.06667 | 0 | Africa/Windhoek | populated place | ||
| 3354416 | Omukondo | Omukonda,Omukondo | NA | Omusati | -17.96667 | 15.08333 | 0 | Africa/Windhoek | populated place | ||
| 3354768 | Okaserawe | NA | Erongo | -20.55 | 15.45 | 0 | Africa/Windhoek | populated place | |||
| 3353506 | Rietoog | Rietoog | NA | Hardap | -23.96667 | 16.55 | 0 | Africa/Windhoek | populated place | ||
| 3358711 | Amuteya | NA | Oshikoto | -18.08333 | 16.43333 | 0 | Africa/Windhoek | populated place | |||
| 3358651 | Arbeidsloon | NA | Otjozondjupa | -18.95 | 18.9 | 0 | Africa/Windhoek | populated place | |||
| 3353883 | Otjikorondo | NA | Omaheke | -20.98333 | 18.91667 | 0 | Africa/Windhoek | populated place | |||
| 3352760 | Tantus | NA | Khomas | -23.16667 | 16.23333 | 0 | Africa/Windhoek | populated place | |||
| 3353110 | Simanya | Shimanje,Shimanya,Simanya | NA | Kavango West | -17.55 | 18.56667 | 0 | Africa/Windhoek | populated place | ||
| 3353378 | Rus En Vrede | Rus En Vrede,Rus-en-Vrede,RusEnVrede | NA | Karas | -28.65215 | 18.75924 | 0 | Africa/Windhoek | populated place | ||
| 3356146 | Klein Hakiesdoorn | NA | Karas | -28.7634 | 18.148 | 0 | Africa/Windhoek | populated place | |||
| 3354322 | Onalusheshete | NA | Oshikoto | -18.31667 | 16.33333 | 0 | Africa/Windhoek | populated place | |||
| 3357669 | Enongo | NA | Omusati | -18 | 15.23333 | 0 | Africa/Windhoek | populated place | |||
| 3352672 | Tondoro | Tondoro | NA | Kavango West | -17.75 | 18.78333 | 0 | Africa/Windhoek | populated place | ||
| 12536417 | Blinkoog | NA | Karas | -26.13937 | 18.30475 | 0 | Africa/Windhoek | populated place | |||
| 3355787 | Last Hope | NA | Oshikoto | -18.78333 | 18 | 0 | Africa/Windhoek | populated place | |||
| 3354834 | Okambaramba | NA | Kunene | -18.25 | 13.33333 | 0 | Africa/Windhoek | populated place | |||
| 3357743 | Ekuli | NA | Kavango West | -17.81667 | 18.71667 | 0 | Africa/Windhoek | populated place | |||
| 12520949 | Tunis | NA | Karas | -28.11834 | 17.99996 | 0 | Africa/Windhoek | populated place | |||
| 876822 | Sibinda | Sibinda | NA | Zambezi | -17.78333 | 23.81667 | 0 | Africa/Windhoek | populated place | ||
| 877173 | Katungu | Katonga,Katungu | NA | Zambezi | -17.71667 | 24.01667 | 0 | Africa/Windhoek | populated place | ||
| 3352442 | Uuntyaye | NA | Oshikoto | -18.23333 | 16.31667 | 0 | Africa/Windhoek | populated place | |||
| 3355136 | Nkutu | NA | Kavango East | -18.01667 | 19.51667 | 0 | Africa/Windhoek | populated place | |||
| 3354186 | Onepandaulo | NA | Ohangwena | -17.65 | 15.68333 | 0 | Africa/Windhoek | populated place | |||
| 3357715 | Elim | NA | Khomas | -23.86667 | 15.83333 | 0 | Africa/Windhoek | populated place | |||
| 3354518 | Omawewozonyanda | Omauozonjanda,Omawewozonyanda | NA | Omaheke | -21.6 | 19.41667 | 0 | Africa/Windhoek | populated place | ||
| 3356974 | Haigamkab | Haigamchab,Haigamkab | NA | Erongo | -22.7 | 14.9 | 0 | Africa/Windhoek | populated place | ||
| 3358301 | Bokiesbank Ost | Bokiesbank,Bokiesbank Oos,Bokiesbank Ost,Pockiesbank-Ost | NA | Karas | -28.33333 | 19.33333 | 0 | Africa/Windhoek | populated place | ||
| 3354500 | Ombawe | NA | Kunene | -17.78333 | 12.66667 | 0 | Africa/Windhoek | populated place | |||
| 3355282 | Naris | NA | Hardap | -23.7 | 17.13333 | 0 | Africa/Windhoek | populated place | |||
| 3354961 | Ohaikedi | NA | Ohangwena | -17.4 | 16.36667 | 0 | Africa/Windhoek | populated place | |||
| 3356395 | Kankudi | NA | Kavango West | -17.73333 | 18.48333 | 0 | Africa/Windhoek | populated place | |||
| 876843 | Shankara | NA | Kavango East | -17.95 | 20.5 | 0 | Africa/Windhoek | populated place | |||
| 877063 | Mashika | NA | Kavango East | -17.88333 | 20.2 | 0 | Africa/Windhoek | populated place | |||
| 3357777 | Ehomba | NA | Kunene | -17.48333 | 13.81667 | 0 | Africa/Windhoek | populated place | |||
| 3354552 | Omambuumbuu | NA | Omusati | -17.43333 | 15.18333 | 0 | Africa/Windhoek | populated place | |||
| 3354285 | Onandi | NA | Oshikoto | -18.11667 | 16.31667 | 0 | Africa/Windhoek | populated place | |||
| 877024 | Mukuvi | NA | Kavango East | -17.96667 | 20.98333 | 0 | Africa/Windhoek | populated place | |||
| 3352055 | Wortel | NA | Karas | -27.98141 | 18.64269 | 0 | Africa/Windhoek | populated place | |||
| 3353698 | Oyovu | NA | Oshikoto | -18.16667 | 16.16667 | 0 | Africa/Windhoek | populated place | |||
| 3353694 | Ozombari | NA | Kunene | -18.93333 | 13.5 | 0 | Africa/Windhoek | populated place | |||
| 3355211 | Ncarise | NA | Kavango West | -17.85 | 18.31667 | 0 | Africa/Windhoek | populated place | |||
| 877178 | Katima Mulilo | Katima Molilo,Katima Mulilas,Katima Mulilo,Katima-Mulilo,MPA,ka di ma mu li luo,katimamullillo,katyma mwlylw,Катима Мулило,Катима-Мулило,Катіма-Муліло,קאטימה מולילו,کاتیما مولیلو,カティマ・ムリロ,卡蒂马穆利洛,카티마물릴로 | NA | Zambezi | -17.50467 | 24.27574 | 25027 | Africa/Windhoek | seat of a first-order administrative division | ||
| 12538030 | Sout Put Post | Sout Put Post,SoutPutPost | NA | Hardap | -25.0143 | 17.81136 | 0 | Africa/Windhoek | populated place | ||
| 3356136 | Klein Klipneus | NA | Erongo | -23.4 | 14.91667 | 0 | Africa/Windhoek | populated place | |||
| 11282119 | Asab | NA | Hardap | -25.46563 | 17.95316 | 0 | Africa/Windhoek | populated place | |||
| 3354585 | Oluteyi | NA | Omusati | -17.81667 | 15.16667 | 0 | Africa/Windhoek | populated place | |||
| 877028 | Mukassa | Mukasa,Mukassa | NA | Zambezi | -17.78333 | 24.45 | 0 | Africa/Windhoek | populated place | ||
| 3357996 | Die Park | NA | Otjozondjupa | -18.86667 | 18.35 | 0 | Africa/Windhoek | populated place | |||
| 876879 | Samulandela | NA | Zambezi | -18.13333 | 23.95 | 0 | Africa/Windhoek | populated place | |||
| 3354790 | Okaonde | NA | Oshikoto | -18.11667 | 16.15 | 0 | Africa/Windhoek | populated place | |||
| 3351980 | Zone | NA | Kavango West | -17.55 | 18.31667 | 0 | Africa/Windhoek | populated place | |||
| 3356258 | Keibeb | NA | Otjozondjupa | -18.93333 | 18.33333 | 0 | Africa/Windhoek | populated place |
Namibia: Mapping the Vast Expanse of a Desert Nation
A Geography Defined by Space and Sparsity
Namibia is a land where geography stretches beyond the horizon. Vast deserts like the Namib and Kalahari define its landscape, punctuated by scattered towns and cities that are as much oases of culture and commerce as they are markers on an immense map. For geographers, Namibia presents a study in contrasts: immense spaces, low population densities, and diverse ecosystems. To truly engage with this unique terrain requires precise and structured geographic data.
Despite Namibia’s importance as a regional hub, detailed, accurate data on its urban settlements and administrative divisions has remained fragmented. To address this, I have developed a comprehensive dataset that catalogs all cities and towns, linked to their corresponding regions and constituencies, complete with accurate geospatial coordinates.
Administrative Divisions: Regions and Constituencies
Namibia is divided into 14 regions, further broken down into constituencies. These divisions are critical for governance, resource management, and development planning. Each city or town is nested within this administrative framework, shaping everything from electoral boundaries to service delivery zones.
My dataset reflects this hierarchy with precision. Every locality is assigned its correct region and constituency, ensuring that users can analyze spatial data in a way that mirrors Namibia’s political and administrative reality.
Geographic Coordinates: Precision Across the Desert
In a country characterized by open spaces and remote settlements, location accuracy is non-negotiable. Every city and town in the dataset is tagged with verified latitude and longitude, enabling integration into Geographic Information Systems (GIS), logistics models, and environmental planning tools.
Such spatial precision supports diverse applications—from optimizing rural healthcare delivery to managing natural resource zones—and helps bridge the gap between remote locations and effective decision-making.
Excel: The Key to Unlocking Usable Data
While the dataset is also offered in CSV, SQL, JSON, and XML formats, the inclusion of Excel (.xlsx) stands out as a practical choice. Excel’s user-friendly interface allows a wide range of professionals—urban planners, researchers, government officials—to interact with the data without needing specialized skills.
This format facilitates quick filtering, sorting, and data exploration. Whether you want to analyze urban growth in Khomas region or compare constituencies in Kunene, Excel provides an intuitive and efficient way to handle complex data.
Dataset Contents
* Complete list of Namibia’s cities and towns
* Classification by region and constituency
* Verified latitude and longitude for each entry
* Available in Excel (.xlsx), CSV, SQL, JSON, and XML formats
Why Namibia Requires Detailed Geographic Data
Namibia is on a development trajectory that demands granular, reliable data. From expanding infrastructure to conserving fragile ecosystems, every project depends on understanding where people live and how administrative boundaries affect governance.
This dataset answers that call, providing the clarity and structure essential for informed policy-making, research, and implementation.
Mapping Namibia’s Expansive Identity
Namibia’s true geography lies in its balance of vast open spaces and concentrated human settlements. Towns like Windhoek, Swakopmund, and Oshakati are centers of life amid the arid wilderness. Each settlement holds a unique spatial and cultural role.
Through this dataset, enhanced by the accessibility of the Excel format, Namibia’s geography becomes a tool for insight and action—ready to support the country’s future growth while honoring the vastness that defines it.
