Kenya cities list with latitude and longitude in Excel, CSV, SQL, XML, JSON formats
Last update : 16 February 2026.
This is the best list of 6552 cities in the Kenya available in 5 formats ( Excel, CSV, JSON, SQL, XML ). You will find only data associated with the cities of a country (capital, towns and villages). There is no information concerning the environment, such as the location of a river or a mountain, for example. All cities are associated with regions and sub-regions (where available).
Each file contains the following data: Geoname_ID, City, Alternate_Name, Country_Code, Region, Sub_region, Latitude, Longitude, Elevation, Population, Timezone, Fcode_Name. See the FAQ below for a detailed explanation.
Here is an example of the data from the Kenya file that you are going to retrieve. The data is displayed here in the form of a table:
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 188724 | Loiya | Loiya,Loya | KE | Turkana | 2.51267 | 34.97869 | 0 | Africa/Nairobi | populated place | ||
| 11964289 | Apoko | KE | Kisumu | -0.38449 | 34.88847 | 0 | Africa/Nairobi | populated place | |||
| 181748 | Otamba | KE | Kisii | -0.72472 | 34.7639 | 0 | Africa/Nairobi | populated place | |||
| 11981765 | Wamwathi | KE | Kitui | -0.79303 | 38.18959 | 0 | Africa/Nairobi | populated place | |||
| 11829899 | El Bonwala | KE | Nakuru | -0.09715 | 36.02592 | 0 | Africa/Nairobi | populated place | |||
| 194245 | Kanzalu | KE | Machakos | -1.24278 | 37.36863 | 0 | Africa/Nairobi | populated place | |||
| 178134 | Wetima One | KE | Nyeri | -0.55 | 36.98333 | 0 | Africa/Nairobi | populated place | |||
| 192058 | Kilili | KE | Makueni | -1.91772 | 37.5999 | 0 | Africa/Nairobi | populated place | |||
| 187125 | Mbagathi | Mbagathi | KE | Nairobi Area | -1.38171 | 36.7669 | 0 | Africa/Nairobi | populated place | ||
| 11964627 | Kama | KE | Nakuru | -0.35363 | 35.97517 | 0 | Africa/Nairobi | populated place | |||
| 185084 | Mwananyamala | Mwananyamala,Mwanayamala | KE | Kwale | -4.4192 | 39.25993 | 0 | Africa/Nairobi | populated place | ||
| 7889855 | Gomesa | KE | Tana River | -2.34635 | 40.21607 | 0 | Africa/Nairobi | populated place | |||
| 11886099 | Boma | KE | Kajiado | -2.81844 | 37.53686 | 0 | Africa/Nairobi | populated place | |||
| 197347 | Gikui | Gakui,Gikui | KE | Kiambu | -0.93333 | 36.91667 | 0 | Africa/Nairobi | populated place | ||
| 11280828 | Ekerenyo | KE | Nyamira | -0.52955 | 34.98983 | 0 | Africa/Nairobi | populated place | |||
| 180138 | Sinonin | KE | Baringo | 0.06531 | 35.70247 | 0 | Africa/Nairobi | populated place | |||
| 191477 | Kiriari | KE | Embu | -0.39715 | 37.4774 | 0 | Africa/Nairobi | populated place | |||
| 198111 | Esumeyia | KE | Kakamega | 0.31862 | 34.68157 | 0 | Africa/Nairobi | populated place | |||
| 11871463 | Kamungei | KE | Baringo | 0.48143 | 35.85965 | 0 | Africa/Nairobi | populated place | |||
| 192295 | Kiganjo | Kiganjo | KE | Nyeri | -0.39626 | 37.00006 | 0 | Africa/Nairobi | populated place | ||
| 178982 | Tulwet | KE | Kericho | -0.4884 | 35.12968 | 0 | Africa/Nairobi | populated place | |||
| 186908 | Mechimeru | KE | Bungoma | 0.50232 | 34.64953 | 0 | Africa/Nairobi | populated place | |||
| 11829932 | Long’s Drift | KE | Nakuru | -0.45775 | 36.08335 | 0 | Africa/Nairobi | populated place | |||
| 184168 | Ndengelwa | KE | Bungoma | 0.59044 | 34.60049 | 0 | Africa/Nairobi | populated place | |||
| 181681 | Pangani | KE | Lamu | -2.36044 | 40.55931 | 0 | Africa/Nairobi | populated place | |||
| 11871594 | Tapsagoi | KE | Uasin Gishu | 0.60438 | 35.02512 | 0 | Africa/Nairobi | populated place | |||
| 193975 | Kaptagat | KE | Elegeyo-Marakwet | 0.42979 | 35.4808 | 0 | Africa/Nairobi | populated place | |||
| 188704 | Luanda Magwar | Luanda Magwar,Lwanda | KE | Migori | -0.87234 | 34.19542 | 0 | Africa/Nairobi | populated place | ||
| 189574 | Lemek | Lemek | KE | Narok | -1.1016 | 35.38869 | 0 | Africa/Nairobi | populated place | ||
| 197555 | Gatundu | KE | Nyeri | -0.52423 | 37.14012 | 0 | Africa/Nairobi | populated place | |||
| 179718 | Surungai | KE | Nandi | 0.47462 | 34.97453 | 0 | Africa/Nairobi | populated place | |||
| 183939 | Nduu | KE | Makueni | -1.77311 | 37.37385 | 0 | Africa/Nairobi | populated place | |||
| 201200 | Aitong | KE | Narok | -1.19317 | 35.24963 | 0 | Africa/Nairobi | populated place | |||
| 184996 | Mwazi | Mwazi | KE | Lamu | -1.89778 | 41.22558 | 0 | Africa/Nairobi | populated place | ||
| 11981803 | Katumbi | KE | Kitui | -0.30097 | 38.33009 | 0 | Africa/Nairobi | populated place | |||
| 195483 | Kagwongo | Kagwongo | KE | Kiambu | -0.98333 | 36.73333 | 0 | Africa/Nairobi | populated place | ||
| 11428650 | Koitasilibwet | KE | Bomet | -0.84714 | 35.33855 | 0 | Africa/Nairobi | populated place | |||
| 197221 | Githunguri | KE | Kiambu | -1.04722 | 36.90206 | 0 | Africa/Nairobi | populated place | |||
| 11964318 | Kiangose | KE | Nyamira | -0.64672 | 34.81471 | 0 | Africa/Nairobi | populated place | |||
| 7889764 | Mikameni | KE | Tana River | -2.0651 | 40.16176 | 0 | Africa/Nairobi | populated place | |||
| 187677 | Marera | KE | Migori | -0.73156 | 34.61458 | 0 | Africa/Nairobi | populated place | |||
| 182693 | Nyika | KE | Kwale | -3.88278 | 39.21544 | 0 | Africa/Nairobi | populated place | |||
| 181260 | Riachina | KE | Embu | -0.79182 | 37.82698 | 0 | Africa/Nairobi | populated place | |||
| 194325 | Kanusin | KE | Bomet | -0.7709 | 35.21356 | 0 | Africa/Nairobi | populated place | |||
| 200820 | Asinge | KE | Busia | 0.54718 | 34.18619 | 0 | Africa/Nairobi | populated place | |||
| 191823 | Kinari | KE | Kiambu | -0.90419 | 36.63557 | 0 | Africa/Nairobi | populated place | |||
| 188353 | Magombo | KE | Nyamira | -0.68475 | 34.91838 | 0 | Africa/Nairobi | populated place | |||
| 197996 | Furaha | Furaha,Furaka | KE | Tana River | -2.48175 | 40.21023 | 0 | Africa/Nairobi | populated place | ||
| 190179 | Kutus | Gutu,Kutu,Kutus,Mucakuthi | KE | Kirinyaga | -0.57534 | 37.3269 | 0 | Africa/Nairobi | populated place | ||
| 11817415 | Todo | KE | Baringo | 1.1926 | 35.71005 | 0 | Africa/Nairobi | populated place | |||
| 183894 | Netima | KE | Bungoma | 0.65114 | 34.47904 | 0 | Africa/Nairobi | populated place | |||
| 195610 | Kadem | Kadem,Nyandema | KE | Migori | -1.00504 | 34.24674 | 0 | Africa/Nairobi | populated place | ||
| 178470 | Waguthu | KE | Kiambu | -1.1891 | 36.79329 | 0 | Africa/Nairobi | populated place | |||
| 192907 | Keria | KE | Tharaka - Nithi | -0.21272 | 37.65617 | 0 | Africa/Nairobi | populated place | |||
| 11871897 | Tebeson | KE | Nandi | 0.32733 | 35.15016 | 0 | Africa/Nairobi | populated place | |||
| 182945 | Nyamache | KE | Kisii | -0.85508 | 34.82852 | 0 | Africa/Nairobi | populated place | |||
| 184081 | Ndiuini | Ndioni,Ndiuini | KE | Kiambu | -1.09239 | 36.59375 | 0 | Africa/Nairobi | populated place | ||
| 12188504 | Cheploch | KE | Baringo | 0.39915 | 36.07631 | 0 | Africa/Nairobi | populated place | |||
| 200956 | Ankish | Ankish | KE | Lamu | -1.95189 | 40.85304 | 0 | Africa/Nairobi | populated place | ||
| 178756 | Umande | KE | Laikipia | 0.09647 | 37.15087 | 0 | Africa/Nairobi | populated place | |||
| 184143 | Ndhiwa | Ndhiwa | KE | Homa Bay | -0.73148 | 34.36785 | 0 | Africa/Nairobi | populated place | ||
| 11817376 | Garogua | KE | Elegeyo-Marakwet | 1.19578 | 35.6208 | 0 | Africa/Nairobi | populated place | |||
| 198411 | Emulundu | Emulundu,Moluondo | KE | Kakamega | 0.24522 | 34.59746 | 0 | Africa/Nairobi | populated place | ||
| 197366 | Gikaru | Gikaru | KE | Kiambu | -1.2 | 36.7 | 0 | Africa/Nairobi | populated place | ||
| 194656 | Kamudi | Kamudi | KE | Tana River | -0.65 | 39.8 | 0 | Africa/Nairobi | populated place | ||
| 189994 | Kwoyo | KE | Migori | -0.7641 | 34.55434 | 0 | Africa/Nairobi | populated place | |||
| 11867983 | Manzeni | KE | Kitui | -1.50043 | 38.04899 | 0 | Africa/Nairobi | populated place | |||
| 11981751 | Musanani | KE | Kitui | -0.17112 | 38.2004 | 0 | Africa/Nairobi | populated place | |||
| 10400164 | Kapsokwony | KE | Bungoma | 0.85222 | 34.70194 | 0 | Africa/Nairobi | populated place | |||
| 180066 | Sisokhe | KE | Kakamega | 0.43762 | 34.59794 | 0 | Africa/Nairobi | populated place | |||
| 11964199 | Morhengo | KE | Kisii | -0.83817 | 34.63088 | 0 | Africa/Nairobi | populated place | |||
| 11844349 | Katitini | KE | Makueni | -1.66305 | 37.41813 | 0 | Africa/Nairobi | populated place | |||
| 198145 | Eshitari | KE | Kakamega | 0.25011 | 34.59829 | 0 | Africa/Nairobi | populated place | |||
| 180371 | Shiraha | KE | Kakamega | 0.1906 | 34.56222 | 0 | Africa/Nairobi | populated place | |||
| 11784555 | Gogo | KE | Migori | -0.77427 | 34.1864 | 0 | Africa/Nairobi | populated place | |||
| 197888 | Gakoe | Gakee,Gakoe | KE | Kiambu | -0.89108 | 36.81095 | 0 | Africa/Nairobi | populated place | ||
| 198029 | Fort Ternan | Fort Ternan | KE | Kericho | -0.20468 | 35.34313 | 0 | Africa/Nairobi | populated place | ||
| 185623 | Munyange Two | KE | Nyeri | -0.5 | 36.86667 | 0 | Africa/Nairobi | populated place | |||
| 185670 | Mungala | KE | Machakos | -1.48333 | 37.26667 | 0 | Africa/Nairobi | populated place | |||
| 200049 | Bura | Bura | KE | Tana River | -1.09431 | 39.94185 | 0 | Africa/Nairobi | populated place | ||
| 186799 | Meto | Meto,Metu | KE | Kajiado | -2.40945 | 36.5563 | 0 | Africa/Nairobi | populated place | ||
| 200613 | Bara Hoyo | Bara Hoyo | KE | Kilifi | -3.92521 | 39.76574 | 0 | Africa/Nairobi | populated place | ||
| 195538 | Kagioini | Kagioini | KE | Nyeri | -0.48333 | 36.9 | 0 | Africa/Nairobi | populated place | ||
| 11257885 | Dandora Phase 4 | KE | Nairobi Area | -1.24275 | 36.90001 | 0 | Africa/Nairobi | populated place | |||
| 179248 | Thur Gem | KE | Kisumu | -0.29062 | 35.00399 | 0 | Africa/Nairobi | populated place | |||
| 190661 | Kom | KE | Samburu | 1.08262 | 38.02396 | 0 | Africa/Nairobi | populated place | |||
| 185375 | Muthetheni | KE | Machakos | -1.49848 | 37.51726 | 0 | Africa/Nairobi | populated place | |||
| 11829975 | Kipipiri Settlement | KE | Nyandarua | -0.43434 | 36.43573 | 0 | Africa/Nairobi | populated place | |||
| 193612 | Karuru One | KE | Murang’A | -0.73333 | 37.05 | 0 | Africa/Nairobi | populated place | |||
| 186470 | Mkaumoto | KE | Kilifi | -3.24038 | 40.05715 | 0 | Africa/Nairobi | populated place | |||
| 191728 | Kiogoro | KE | Kisii | -0.72561 | 34.78226 | 0 | Africa/Nairobi | populated place | |||
| 188332 | Magunga | KE | Kisumu | -0.27952 | 34.98277 | 0 | Africa/Nairobi | populated place | |||
| 11835329 | Gakuyu | KE | Nyeri | -0.53622 | 37.13778 | 0 | Africa/Nairobi | populated place | |||
| 186934 | Mbuzia | KE | Kitui | -1.28333 | 38.11667 | 0 | Africa/Nairobi | populated place | |||
| 199748 | Cheboin | KE | Kericho | -0.53709 | 35.12794 | 0 | Africa/Nairobi | populated place | |||
| 200304 | Bondo | Bondo | KE | Siaya | 0.23522 | 34.28086 | 8683 | Africa/Nairobi | populated place | ||
| 200078 | Bumini | KE | Kakamega | 0.33166 | 34.5906 | 0 | Africa/Nairobi | populated place | |||
| 189722 | Langata Sein | KE | Narok | -1.02394 | 34.73205 | 0 | Africa/Nairobi | populated place | |||
| 186301 | Mombasa | MBA,Mambasa,Mombaaso,Mombaca,Mombasa,Mombaso,Mombassa,Mombaça,Mombása,Mompasa,Mvita,meng ba sa,mmbasa,momabaka,mombasa,monbasa,mwmbasa,mwmbsh,Μομπάσα,Мамбаса,Момбаса,מומבסה,ممباسا,مومباسا,मोम्बासा,মোমবাকা,მომბასა,モンバサ,蒙巴萨,몸바사 | KE | Mombasa | -4.05466 | 39.66359 | 1208333 | Africa/Nairobi | seat of a first-order administrative division | ||
| 199405 | Chiamanda | Chiamanda,Chiananda | KE | Embu | -0.41834 | 37.63685 | 0 | Africa/Nairobi | populated place |
Discovering Kenya: A Geographical Overview
Kenya, located in East Africa, is a country with a rich tapestry of diverse landscapes, vibrant cultures, and a growing economy. From the snow-capped peaks of Mount Kenya to the vast savannahs of the Maasai Mara, the country’s geography has not only shaped its history but also influenced its development. As one of the most prominent nations in Africa, Kenya offers a wealth of opportunities for geographical exploration. For those interested in understanding the spatial dynamics of Kenya, access to precise data about its cities, regions, and departments—including the exact latitude and longitude of each city—is essential. This article will explore the diverse geography of Kenya and highlight the importance of obtaining geographic data to further understand the country’s urban and regional organization.
A Country of Contrasts: Kenya's Physical Geography
Kenya is a land of contrasts, where you can experience vast deserts, fertile highlands, lush forests, and miles of coastline, all within a relatively short distance. The country spans approximately 580,367 square kilometers and is situated on the eastern edge of Africa, with the Indian Ocean to the southeast. Kenya’s landscape is divided into several key regions, each with its own unique characteristics.
The central region of Kenya is dominated by Mount Kenya, the second-highest peak in Africa. This region is fertile, with rich volcanic soils supporting the country's agricultural industry, including coffee, tea, and floriculture. Further to the north, the arid and semi-arid lands of the Rift Valley extend through the center of the country, creating dramatic landscapes that include lakes, volcanic mountains, and unique geological formations. In the south, Kenya borders Tanzania, home to the world-renowned Serengeti and the Ngorongoro Crater.
Kenya’s diverse landscapes have a direct impact on its settlements, infrastructure, and resource distribution. The variability of climate and terrain from region to region shapes the population density and economic activity in different areas. For a deeper understanding of how geography influences Kenya’s urban growth and regional characteristics, access to precise data about the cities, regions, and their departments is invaluable.
Urbanization and Cities in Kenya
Kenya's cities and towns are distributed across its diverse landscape, with each city playing a significant role in the country’s economy and culture. Nairobi, the capital and largest city, is situated in the central region, close to the Nairobi National Park. As one of the major economic hubs of East Africa, Nairobi is known for its vibrant economy, diverse industries, and as a gateway to the continent. It is a city of contrasts, where modern skyscrapers sit alongside traditional markets and slums.
Mombasa, located on the coast, is Kenya’s second-largest city and its primary port. As an important trade and tourism center, Mombasa is also a melting pot of cultures, with Swahili, Arab, and European influences shaping its architecture and lifestyle. The city is known for its beautiful beaches, historic sites, and the bustling Old Town.
Other significant cities in Kenya include Kisumu, located on the shores of Lake Victoria in the west, which serves as a major economic and cultural center for the western region; Nakuru, in the heart of the Rift Valley, known for its wildlife reserves and agricultural activity; and Eldoret, a key agricultural hub in the highlands of western Kenya. Each of these cities and towns plays a crucial role in the country’s development and has its own unique geographical and cultural identity.
Understanding the distribution of these cities and their regions is crucial for studying Kenya’s urbanization patterns, economic development, and regional governance. Accessing detailed data on each city's exact latitude and longitude, as well as its regional and departmental affiliations, allows for a more nuanced exploration of how geography shapes Kenya’s growth.
The Importance of Geographic Data for Kenya
For geographers, urban planners, researchers, and anyone interested in understanding Kenya’s spatial organization, access to detailed geographic data is essential. This includes not only basic geographical information such as the latitude and longitude of cities, but also data on the administrative divisions of Kenya. The country is divided into 47 counties, each with its own local government, and this division has significant implications for governance, infrastructure development, and regional planning.
Having access to the exact geographic coordinates of each city, along with its regional boundaries, enables researchers to understand the distribution of resources, the movement of populations, and the dynamics of urban growth across the country. For example, knowing the exact location of Nairobi and its surrounding urban sprawl allows for more effective planning of transportation infrastructure and housing. Similarly, understanding the locations of cities in arid and semi-arid regions of the country can inform decisions regarding resource allocation, water management, and agricultural strategies.
Enhancing Research with a Comprehensive Geographic Database
Access to a comprehensive database containing detailed geographic data on Kenya’s cities, regions, and departments provides a valuable resource for researchers, planners, and policy makers. This data is instrumental in understanding the relationships between Kenya’s physical geography and its urban centers. By examining the spatial distribution of cities and regions, one can gain insight into how geography influences social, economic, and environmental patterns within the country.
For example, in Kenya’s northern regions, which are largely arid, cities such as Garissa and Isiolo face unique challenges related to water scarcity and climate change. By accessing data that includes latitude and longitude, researchers can pinpoint vulnerable regions and develop targeted interventions. In contrast, the agricultural regions of central Kenya benefit from fertile soil and consistent rainfall, making them ideal for crops like tea and coffee. Understanding the geography of these areas can lead to more sustainable agricultural practices and resource management.
For anyone studying Kenya’s geography in-depth, having access to such data can make the difference between a general understanding and a truly insightful analysis. Whether the focus is on environmental studies, urban planning, or economic development, precise geographic data offers the tools necessary for detailed research and informed decision-making.
Conclusion
Kenya’s diverse and dynamic geography, ranging from lush highlands to arid deserts, from bustling cities to tranquil lakesides, offers a unique opportunity for geographical exploration. The country’s cities and regions are shaped by their natural landscapes, and understanding their geographical distribution is key to studying Kenya’s development. Access to detailed geographic data, including the latitude and longitude of cities, as well as information about their regions and departments, is essential for anyone looking to gain a deeper understanding of Kenya’s spatial dynamics. This data provides valuable insights for researchers, urban planners, and policymakers, enabling more informed decisions that support the country’s continued growth and sustainability.
FaQ about Kenya
- Geoname_ID: This is a unique identifier for each place or geographical name in the Geoname database.
- City: The name of the place, which can be a town, village or any other form of human settlement.
- Alternate_Name: Other names or appellations that the place may have. These alternative names may be in different languages, dialects or even local names.
- Country_Code: This is the ISO 3166-1 alpha-2 code for the country in which the place is located. For example, "US" for the United States, "FR" for France.
- Region: This represents the first-order administrative division in which the location is situated. For example, this could be a state, province or territory.
- Sub_region: This is a second-order administrative division, such as a county or district, within the region.
- Latitude: The geographical latitude of the location, usually in decimal degrees.
- Longitude: The geographical longitude of the location, also usually in decimal degrees.
- Elevation: The elevation or altitude of the location in relation to sea level, usually measured in metres.
- Population: The estimated number of inhabitants or population of the location.
- Timezone: The time zone in which the location is located, in accordance with global time zone standards.
- Fcode_Name: This is a code that categorises the type of location. For example, "PPL" could mean a populated place, while "PPLC" could be the capital of a political entity.