Sierra Leone cities list with latitude and longitude in CSV,SQL,XML,JSON formats
Last update : 15 January 2025.
This is the best list of 14029 cities in the Sierra Leone available in 4 formats ( CSV, Json, SQL, XML ). We have cleaned up the Geoname database to leave only the towns, capitals and villages. All are all 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 Sierra Leone 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 |
---|---|---|---|---|---|---|---|---|---|---|---|
2403753 | Songo | Songo,Songo Town | SL | Northern Province | 8.36843 | -12.93282 | 0 | Africa/Freetown | populated place | ||
10038825 | Duore | Duore | SL | Northern Province | 8.69014 | -11.67671 | 0 | Africa/Freetown | populated place | ||
9880669 | Makamila | Makamila | SL | Northern Province | 9.01733 | -12.8252 | 0 | Africa/Freetown | populated place | ||
9871940 | Topogoama | Topogoama | SL | Southern Province | 7.92195 | -12.09741 | 0 | Africa/Freetown | populated place | ||
9870763 | Herikor | Herikor | SL | Northern Province | 9.78431 | -11.58834 | 0 | Africa/Freetown | populated place | ||
9872426 | Madina | Madina | SL | Southern Province | 7.8804 | -12.01096 | 0 | Africa/Freetown | populated place | ||
2407732 | Kimbima | Kimbima | SL | Southern Province | 8.18045 | -12.10074 | 0 | Africa/Freetown | populated place | ||
2403323 | Tomboma | Tomboma | SL | Eastern Province | 7.9219 | -10.85894 | 0 | Africa/Freetown | populated place | ||
2410005 | Boko | Boko | SL | Eastern Province | 8.35454 | -10.39513 | 0 | Africa/Freetown | populated place | ||
2409118 | Gbangba | Gbangba | SL | Southern Province | 7.45061 | -12.01596 | 0 | Africa/Freetown | populated place | ||
9878376 | Kaniya | Kaniya | SL | Southern Province | 7.69337 | -11.80998 | 0 | Africa/Freetown | populated place | ||
10131952 | Mamila | Mamila | SL | Northern Province | 8.58922 | -12.46827 | 0 | Africa/Freetown | populated place | ||
2409946 | Bonganema | Bonganema | SL | Southern Province | 8.12823 | -12.05594 | 0 | Africa/Freetown | populated place | ||
9879933 | Yaama | Yaama | SL | Eastern Province | 8.25185 | -10.52421 | 0 | Africa/Freetown | populated place | ||
2403291 | Tonkolele | Tonkolele | SL | Northern Province | 8.6485 | -11.68343 | 0 | Africa/Freetown | populated place | ||
9893159 | Giawamei | Giawamei | SL | Southern Province | 7.21522 | -11.45622 | 0 | Africa/Freetown | populated place | ||
2407066 | Lalehun | Lalehun | SL | Eastern Province | 7.68478 | -10.97232 | 0 | Africa/Freetown | populated place | ||
2408570 | Herako | Herako | SL | Northern Province | 9.17259 | -11.48507 | 0 | Africa/Freetown | populated place | ||
2405544 | Matuk | Matuk | SL | Northern Province | 8.70908 | -11.9132 | 0 | Africa/Freetown | populated place | ||
9908877 | Pboajebu | Pboajebu | SL | Southern Province | 8.13083 | -11.7281 | 0 | Africa/Freetown | populated place | ||
2404522 | Petifu | Petifu | SL | Southern Province | 8.11766 | -12.62003 | 0 | Africa/Freetown | populated place | ||
2409515 | Faiama | Faiama | SL | Southern Province | 7.60672 | -11.68091 | 0 | Africa/Freetown | populated place | ||
2410030 | Bobobu | Bobobu | SL | Southern Province | 8.04497 | -11.82594 | 0 | Africa/Freetown | populated place | ||
9878163 | Damaworo | Damaworo | SL | Southern Province | 7.3714 | -11.86435 | 0 | Africa/Freetown | populated place | ||
2405573 | Matoir | Matoir | SL | Northern Province | 8.47531 | -12.40923 | 0 | Africa/Freetown | populated place | ||
2404498 | Petifu | Petifu | SL | Northern Province | 8.68682 | -13.09859 | 0 | Africa/Freetown | populated place | ||
2403899 | Senyekhuri | Senyekhuri | SL | Northern Province | 9.63747 | -12.29047 | 0 | Africa/Freetown | populated place | ||
9870902 | Kumbakada | Kumbakada | SL | Northern Province | 9.72379 | -11.59768 | 0 | Africa/Freetown | populated place | ||
2405490 | Mayanki | Mayanki | SL | Northern Province | 9.03826 | -12.41287 | 0 | Africa/Freetown | populated place | ||
2407245 | Kumando | Kumando,Kumandu | SL | Eastern Province | 8.72337 | -10.66459 | 0 | Africa/Freetown | populated place | ||
9878181 | Benduma | Benduma | SL | Southern Province | 7.3239 | -11.79345 | 0 | Africa/Freetown | populated place | ||
10046477 | Yigbeda | Yigbeda | SL | Eastern Province | 8.53559 | -11.24797 | 0 | Africa/Freetown | populated place | ||
9988677 | Rolal | Rolal | SL | Northern Province | 8.66688 | -12.57845 | 0 | Africa/Freetown | populated place | ||
9989343 | Robbom | Robbom | SL | Northern Province | 8.66451 | -12.51035 | 0 | Africa/Freetown | populated place | ||
10131964 | Madik | Madik | SL | Northern Province | 8.62235 | -12.46138 | 0 | Africa/Freetown | populated place | ||
2405663 | Masuri | Masuri | SL | Northern Province | 9.15844 | -12.34971 | 0 | Africa/Freetown | populated place | ||
2405782 | Masegea | Masegea | SL | Northern Province | 9.46776 | -12.3094 | 0 | Africa/Freetown | populated place | ||
9875332 | Katima | Katima | SL | Northern Province | 8.47729 | -12.02 | 0 | Africa/Freetown | populated place | ||
10133458 | Masembi | Masembi | SL | Northern Province | 9.11561 | -12.20877 | 0 | Africa/Freetown | populated place | ||
10131115 | Mamaria | Mamaria | SL | Northern Province | 9.3222 | -12.27546 | 0 | Africa/Freetown | populated place | ||
9893257 | Pujehun | Pujehun | SL | Southern Province | 7.08942 | -11.38322 | 0 | Africa/Freetown | populated place | ||
9875429 | Fabaina | Fabaina | SL | Eastern Province | 7.82068 | -11.02535 | 0 | Africa/Freetown | populated place | ||
2407286 | Kpuwuta | Kpuwuta,Pawula | SL | Southern Province | 7.7 | -11.95 | 0 | Africa/Freetown | populated place | ||
2405274 | Mogbwemo | Mogbembo,Mogbwemo | SL | Southern Province | 7.76237 | -12.30864 | 2900 | Africa/Freetown | populated place | ||
2407582 | Komende-Luyama | Komende-Luyama | SL | Eastern Province | 8.06259 | -10.99644 | 0 | Africa/Freetown | populated place | ||
2403158 | Waidu | Waidu | SL | Eastern Province | 8.76359 | -10.87648 | 0 | Africa/Freetown | populated place | ||
9873352 | Lopet | Lopet | SL | Northern Province | 8.46897 | -12.47719 | 0 | Africa/Freetown | populated place | ||
9985910 | Rokon | Rokon | SL | Northern Province | 8.79681 | -12.76055 | 0 | Africa/Freetown | populated place | ||
9893161 | Gengema | Gengema | SL | Southern Province | 7.22963 | -11.41033 | 0 | Africa/Freetown | populated place | ||
9920224 | Madina-Golala | Madina-Golala | SL | Eastern Province | 8.14899 | -10.78514 | 0 | Africa/Freetown | populated place | ||
2408027 | Kangama | Kangama | SL | Southern Province | 7.84128 | -12.83927 | 0 | Africa/Freetown | populated place | ||
2403630 | Takpoima | Takpoima | SL | Eastern Province | 8.30023 | -10.66885 | 0 | Africa/Freetown | populated place | ||
2593587 | Bomdei | Bomdei | SL | Southern Province | 7.88416 | -12.53991 | 0 | Africa/Freetown | populated place | ||
2405689 | Masumana | Masumana | SL | Northern Province | 8.47574 | -11.98922 | 0 | Africa/Freetown | populated place | ||
9876180 | Bandajuma | Bandajuma | SL | Southern Province | 7.61147 | -12.15327 | 0 | Africa/Freetown | populated place | ||
2405469 | Mayemberi Tendokom | Mayemberi Tendokom | SL | Southern Province | 8.39665 | -11.76035 | 0 | Africa/Freetown | populated place | ||
2406492 | Makagbo | Makagbo | SL | Northern Province | 8.40171 | -12.39402 | 0 | Africa/Freetown | populated place | ||
2404320 | Rokel | Rokel,Rokell | SL | Western Area | 8.38189 | -13.10511 | 0 | Africa/Freetown | populated place | ||
9986419 | Tumbo | Tumbo | SL | Northern Province | 8.78607 | -12.71961 | 0 | Africa/Freetown | populated place | ||
2405686 | Masumarandugu | Masumarandugu | SL | Northern Province | 9.17263 | -11.70105 | 0 | Africa/Freetown | populated place | ||
10133249 | Mayamane | Mayamane | SL | Northern Province | 8.99564 | -12.09797 | 0 | Africa/Freetown | populated place | ||
2403614 | Taluke | SL | Eastern Province | 8.36667 | -11.3 | 0 | Africa/Freetown | populated place | |||
10133371 | Gbanka | Gbanka | SL | Northern Province | 9.18296 | -12.16005 | 0 | Africa/Freetown | populated place | ||
2409927 | Bonjema | Bonjema | SL | Southern Province | 7.98436 | -12.64805 | 0 | Africa/Freetown | populated place | ||
2407075 | Laia | Laia | SL | Northern Province | 9.57131 | -12.15805 | 0 | Africa/Freetown | populated place | ||
2410250 | Baw-o-bu | Baw-o-bu | SL | Western Area | 8.33024 | -12.99024 | 0 | Africa/Freetown | populated place | ||
2408417 | Jibima | Jibima | SL | Southern Province | 7.28197 | -11.3922 | 0 | Africa/Freetown | populated place | ||
2404517 | Petifu | Petifu | SL | Northern Province | 8.39616 | -12.03329 | 0 | Africa/Freetown | populated place | ||
2407813 | Kegbema | Kegbema | SL | Northern Province | 9.01077 | -11.698 | 0 | Africa/Freetown | populated place | ||
2403647 | Tagbwema | SL | Eastern Province | 8.23333 | -10.63333 | 0 | Africa/Freetown | populated place | |||
2408938 | Gbonkomipere | Gbonkomipere,Gbonkompere | SL | Northern Province | 8.96603 | -12.95261 | 0 | Africa/Freetown | populated place | ||
10133488 | Momaia | Momaia | SL | Northern Province | 9.15512 | -12.1193 | 0 | Africa/Freetown | populated place | ||
9877122 | Ponati | Ponati | SL | Southern Province | 7.27857 | -12.15234 | 0 | Africa/Freetown | populated place | ||
2403690 | Sundodu | Sundodu | SL | Northern Province | 9.06801 | -10.82742 | 0 | Africa/Freetown | populated place | ||
9988644 | Magbala | Magbala | SL | Northern Province | 8.62654 | -12.64722 | 0 | Africa/Freetown | populated place | ||
9892976 | Kanella | Kanella | SL | Southern Province | 7.36365 | -11.42314 | 0 | Africa/Freetown | populated place | ||
10131749 | Mafuri | Mafuri | SL | Northern Province | 8.94316 | -12.41598 | 0 | Africa/Freetown | populated place | ||
9875192 | Kpai | Kpai | SL | Eastern Province | 7.85389 | -11.25019 | 0 | Africa/Freetown | populated place | ||
9879874 | Bamba | Bamba | SL | Eastern Province | 8.28355 | -10.72689 | 0 | Africa/Freetown | populated place | ||
9904538 | Jawonga | Jawonga | SL | Southern Province | 8.2465 | -11.74599 | 0 | Africa/Freetown | populated place | ||
10133341 | Mafoyoka | Mafoyoka | SL | Northern Province | 8.80497 | -12.0806 | 0 | Africa/Freetown | populated place | ||
2409484 | Falabadi | Falabadi,Falabodi | SL | Northern Province | 9.77693 | -12.03721 | 0 | Africa/Freetown | populated place | ||
2406417 | Makema | Makema | SL | Northern Province | 8.73248 | -11.50989 | 0 | Africa/Freetown | populated place | ||
2408782 | Gloucester | Gloucester | SL | Western Area | 8.45089 | -13.21457 | 0 | Africa/Freetown | populated place | ||
2408858 | Giebu | Giebu | SL | Southern Province | 8.32548 | -11.65419 | 0 | Africa/Freetown | populated place | ||
10033114 | Matoro | Matoro | SL | Northern Province | 9.21007 | -11.92562 | 0 | Africa/Freetown | populated place | ||
2403190 | Vaama | Vaama | SL | Eastern Province | 8.33165 | -10.85623 | 0 | Africa/Freetown | populated place | ||
2403384 | Tobanda | Tobanda | SL | Southern Province | 7.1989 | -11.76008 | 0 | Africa/Freetown | populated place | ||
2406777 | Mabuya | Mabuya | SL | Northern Province | 8.53534 | -12.9107 | 0 | Africa/Freetown | populated place | ||
9871237 | Gbekema | Gbekema | SL | Southern Province | 7.19088 | -11.62552 | 0 | Africa/Freetown | populated place | ||
2406370 | Makobolo | Makobolo | SL | Northern Province | 8.49501 | -11.93382 | 0 | Africa/Freetown | populated place | ||
9893214 | Gewojahun | Gewojahun | SL | Southern Province | 7.23847 | -11.32265 | 0 | Africa/Freetown | populated place | ||
9986610 | Makambali | Makambali | SL | Northern Province | 8.53338 | -12.75056 | 0 | Africa/Freetown | populated place | ||
9893270 | Maboina | Maboina | SL | Southern Province | 8.19956 | -12.60263 | 0 | Africa/Freetown | populated place | ||
2407448 | Konta | Konta,Ronta | SL | Northern Province | 8.74702 | -12.0483 | 0 | Africa/Freetown | populated place | ||
2409749 | Bwendu | Bwedu,Bwendu | SL | Eastern Province | 8.46324 | -10.64365 | 0 | Africa/Freetown | populated place | ||
2410656 | Gbahama | Bahama,Gbahama | SL | Southern Province | 8.0224 | -11.6479 | 0 | Africa/Freetown | populated place | ||
2408173 | Kalu | Kalu | SL | Eastern Province | 7.87454 | -10.93399 | 0 | Africa/Freetown | populated place | ||
10133511 | Makundigi | Makundigi | SL | Northern Province | 9.15951 | -12.0725 | 0 | Africa/Freetown | populated place | ||
9989359 | Robis | Robis | SL | Northern Province | 8.56859 | -12.7345 | 0 | Africa/Freetown | populated place |
Sierra Leone: A Geographical Exploration of West Africa’s Hidden Gem
Sierra Leone, located on the west coast of Africa, is a country marked by both stunning natural beauty and a complex history. From its tropical forests and serene beaches to the vast hinterlands, Sierra Leone offers a geographical landscape that is as diverse as it is captivating. As a geographer, understanding this country involves not just looking at its physical features but also at how human activity has interacted with its environment over time. In particular, acquiring detailed geographical data on Sierra Leone’s cities, regions, and departments is essential for a comprehensive understanding of the country’s growth, development, and regional dynamics.
The Geography of Sierra Leone: A Land of Diversity
Sierra Leone’s geographical diversity is one of its defining features. The country stretches from the Atlantic Ocean in the west to the interior regions, which are marked by savannahs, wetlands, and forested mountains. In the western part of the country lies the Freetown Peninsula, home to the nation’s capital, Freetown, which is a port city of great historical and economic importance.
The terrain of Sierra Leone is varied, with coastal plains in the west, hilly regions in the center, and mountainous areas in the east. This diversity in landscape supports a wide range of ecosystems, from lush rainforests that house endemic species to the dry savannahs of the northern regions. The country is also rich in water resources, with numerous rivers, including the Rokel and the Moa, which provide crucial lifelines to both the environment and the people who depend on them.
Administrative Divisions and Regions
Sierra Leone is divided into five regions, further subdivided into districts and then towns or villages. These divisions are crucial for understanding the country’s political and social structure, as well as for analyzing regional patterns in population distribution, economic activity, and infrastructure development.
The regions are: the Western Area (which includes the capital city of Freetown), Northern Province, Southern Province, Eastern Province, and the Western Rural Area. The Western Area, with its focus on Freetown, is the country’s political, economic, and cultural hub. It represents the country’s most developed area in terms of infrastructure and services. Meanwhile, the other provinces are more rural, with agricultural activity playing a major role in their economies.
For geographers, these regions offer rich opportunities for study, as the topography and infrastructure of each area impact human settlement patterns and development strategies. Whether it’s mapping the effects of urbanization in Freetown or exploring the agricultural trends in the rural districts, the geographical data of each region is invaluable for understanding how the country functions and grows.
Why Geographical Data is Essential for Sierra Leone
For a more profound understanding of Sierra Leone’s spatial dynamics, obtaining detailed geographical data is essential. This includes information about the cities, districts, regions, and, crucially, the exact latitude and longitude of each location. Such data not only helps define the boundaries of regions and towns but also plays a significant role in understanding the economic, environmental, and social interactions that occur within these spaces.
Precise geographical coordinates provide insight into the relative positioning of cities, helping geographers analyze trade routes, migration patterns, and the accessibility of various regions. For example, data on cities like Freetown, Bo, and Kenema can help identify regional differences in development, demographic changes, and even potential for growth in infrastructure and industry. Understanding where these cities are located in relation to each other also aids in optimizing transportation networks and regional planning.
The Benefits of Accessing Geographic Data for Sierra Leone
Having access to detailed geographical data of Sierra Leone, including the latitude and longitude of each city, region, and district, offers a multitude of advantages for researchers, urban planners, and policymakers. For example, precise geographic data allows for more effective urban planning in growing cities like Freetown, where population pressures and environmental concerns often require careful management.
Furthermore, geographical data is invaluable when it comes to disaster preparedness. Sierra Leone’s coastal regions, for instance, are vulnerable to sea-level rise and storms, and accurate data on elevation, proximity to water, and population density can aid in disaster risk management. Similarly, data on rural areas can help improve resource distribution, especially in regions where agriculture and natural resource management are vital to the local economy.
Access to such data also supports environmental research, particularly when studying deforestation, land use changes, and the impacts of climate change. By knowing the exact coordinates of important ecosystems, such as the Gola Rainforest National Park, researchers can better understand how these environments are changing and develop strategies to protect them.
Unlocking the Potential of Sierra Leone’s Geographic Data
The potential for deeper research and more effective decision-making lies in the accessibility of comprehensive geographical data for Sierra Leone. By obtaining detailed coordinates and information about cities, regions, and districts, it is possible to conduct more nuanced analyses of the country’s geography, economy, and social structure.
For example, researchers can track patterns in urbanization, assess regional disparities in development, and predict future trends based on current data. In turn, this data helps policymakers make informed decisions about resource allocation, infrastructure development, and environmental protection. Moreover, access to geographic data enhances the capacity of international organizations to provide aid and support for development projects in the country.
Conclusion: The Value of Geographical Insight
In conclusion, Sierra Leone’s geographical makeup is as varied and complex as the country’s history. Its diverse landscapes, administrative divisions, and socio-economic dynamics offer a rich field for geographic research and analysis. To unlock the full potential of Sierra Leone’s geographical data, it is essential to obtain detailed information on its cities, regions, and districts, including the precise coordinates of each. This data is vital for understanding the country’s development, environmental challenges, and future growth.
For anyone looking to gain a deeper understanding of Sierra Leone, the key lies in the accessibility of accurate geographic data. By obtaining and analyzing this data, researchers and policymakers can make informed decisions that will contribute to the sustainable development of the country and its people.
FaQ about Sierra Leone
- 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.