Guinea Bissau cities list with latitude and longitude in Excel, CSV, XML, SQL, JSON formats
Last update : 20 January 2026.
Below is a list of 100 prominent cities in Guinea Bissau. Each row includes a city's latitude, longitude, region and other variables of interest. This is a subset of all 3878 places in Guinea Bissau that you'll find in our World Cities Database. You're free to use the data below for personal or commercial applications. The data below can be downloaded in Excel (.xlsx), .csv, .json, .xml and .sql formats. Notable Cities: The capital of Guinea Bissau is Bissau.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2372005 | Jafo | GW | 12.6 | -14.96667 | 0 | Africa/Bissau | populated place | ||||
| 2375041 | Barraca Begoá | GW | Cacheu | 12.44833 | -16.13222 | 0 | Africa/Bissau | populated place | |||
| 2370439 | Quenhaque | GW | Oio | 12.19806 | -15.42278 | 0 | Africa/Bissau | populated place | |||
| 2372906 | Demba Cali | Demba Cali,Demba Calije | GW | 12.26667 | -14.5 | 0 | Africa/Bissau | populated place | |||
| 8335083 | Prabis | GW | Biombo | 11.80401 | -15.74036 | 0 | Africa/Bissau | populated place | |||
| 2369288 | Sinchã Sutu | Sincha Sulo,Sincha Sutu,Sinchã Sulo,Sinchã Sutu | GW | 12.21667 | -14.76667 | 0 | Africa/Bissau | populated place | |||
| 2371434 | Marim | GW | 11.85 | -15.66667 | 0 | Africa/Bissau | populated place | ||||
| 2371942 | Jatadaca | GW | 11.68333 | -14.28333 | 0 | Africa/Bissau | populated place | ||||
| 2375161 | Bananto | GW | Oio | 12.46111 | -15.0625 | 0 | Africa/Bissau | populated place | |||
| 2374704 | Bôeme | Babeme,Boeme,Bãbeme,Bôeme | GW | Cacheu | 12.22167 | -15.76444 | 0 | Africa/Bissau | populated place | ||
| 2372881 | Demba Tacoba | Demba Tacaba,Demba Tacabá,Demba Tacoba,Dembaco Toba,Dembacó Tobá | GW | 11.96667 | -14.73333 | 0 | Africa/Bissau | populated place | |||
| 2371458 | Mantefa | GW | Oio | 12.10556 | -15.32 | 0 | Africa/Bissau | populated place | |||
| 2374185 | Calaque | GW | Cacheu | 12.20917 | -15.82222 | 0 | Africa/Bissau | populated place | |||
| 2374736 | Bloi | GW | 12.1 | -15.81667 | 0 | Africa/Bissau | populated place | ||||
| 2373948 | Canchungozinho | GW | 11.41667 | -15.31667 | 0 | Africa/Bissau | populated place | ||||
| 2375265 | Badâ | GW | Cacheu | 12.18389 | -15.80778 | 0 | Africa/Bissau | populated place | |||
| 2371191 | Nhambalã | Nhambala,Nhambalan,Nhambalã | GW | Cacheu | 12.39028 | -16.29083 | 0 | Africa/Bissau | populated place | ||
| 2369522 | Sinchã Gaè | GW | 12.33333 | -13.66667 | 0 | Africa/Bissau | populated place | ||||
| 2375172 | Bambaià | Bambaia,Bambaià | GW | 11.95 | -14.6 | 0 | Africa/Bissau | populated place | |||
| 2370079 | Sanjalo | GW | 12.5 | -15.3 | 0 | Africa/Bissau | populated place | ||||
| 2374335 | Cáchajà | GW | 12.51667 | -13.83333 | 0 | Africa/Bissau | populated place | ||||
| 2370632 | Ponta J. Fona | GW | 12.08333 | -15.7 | 0 | Africa/Bissau | populated place | ||||
| 2372185 | Ida Fula | GW | 12.36667 | -14.38333 | 0 | Africa/Bissau | populated place | ||||
| 2369806 | Saro | Charo,Saro | GW | 11.28333 | -15.86667 | 0 | Africa/Bissau | populated place | |||
| 2375501 | Áfià | GW | 12.18333 | -14.65 | 0 | Africa/Bissau | populated place | ||||
| 2369668 | Sinchã Bobo | GW | 12.33333 | -13.86667 | 0 | Africa/Bissau | populated place | ||||
| 2369802 | Satecuta | GW | 11.75 | -15.31667 | 0 | Africa/Bissau | populated place | ||||
| 2369654 | Sinchã Bolama | GW | 12.41667 | -13.66667 | 0 | Africa/Bissau | populated place | ||||
| 2375472 | Aldeia de Cuor | Aldeia de Cuor,Aldeia do Cuhor | GW | 12.1 | -14.85 | 0 | Africa/Bissau | populated place | |||
| 2375387 | Ancamona | Ancamona,Ancamone | GW | 11.15 | -16.1 | 0 | Africa/Bissau | populated place | |||
| 2374353 | Cabufara | Cabofara,Cabofará,Cabufara | GW | 11.96667 | -14.66667 | 0 | Africa/Bissau | populated place | |||
| 2369172 | Suar | Suar,Suare | GW | 12.4 | -15.58333 | 0 | Africa/Bissau | populated place | |||
| 2368790 | Umaro Baldé | GW | 12.41667 | -13.9 | 0 | Africa/Bissau | populated place | ||||
| 2372356 | Garcia | Curdia,Curdiá,Garcia | GW | 12.43333 | -14.9 | 0 | Africa/Bissau | populated place | |||
| 2372348 | Gã Soares | GW | 12.15 | -14.8 | 0 | Africa/Bissau | populated place | ||||
| 2371128 | Nhime | GW | Oio | 12.16056 | -15.16583 | 0 | Africa/Bissau | populated place | |||
| 2369671 | Sinchã Birom | GW | 12.46667 | -14.85 | 0 | Africa/Bissau | populated place | ||||
| 2371138 | Nhaulem | GW | 12.15 | -14.06667 | 0 | Africa/Bissau | populated place | ||||
| 2372188 | Iastem | Cabaz Balanta,Iastem | GW | 11.01667 | -15.01667 | 0 | Africa/Bissau | populated place | |||
| 2374177 | Calege | Calaje,Calege | GW | 11.51667 | -15.58333 | 0 | Africa/Bissau | populated place | |||
| 2372111 | Incomené Manjaco | GW | 11.45 | -15.2 | 0 | Africa/Bissau | populated place | ||||
| 2374194 | Cajila | GW | 11.88333 | -15.6 | 0 | Africa/Bissau | populated place | ||||
| 2372092 | Inhangabute | Inhangabute,Inhangabutes | GW | 12.11667 | -16.3 | 0 | Africa/Bissau | populated place | |||
| 2369441 | Sinchã Madiu | GW | 11.68333 | -14.78333 | 0 | Africa/Bissau | populated place | ||||
| 2370389 | Queuel Lei | GW | 11.48333 | -15.06667 | 0 | Africa/Bissau | populated place | ||||
| 2370010 | Sarauol | GW | 12.11667 | -15.11667 | 0 | Africa/Bissau | populated place | ||||
| 2370206 | Samandim | Samadim,Samandim | GW | Oio | 12.64 | -15.12694 | 0 | Africa/Bissau | populated place | ||
| 2370577 | Ponta Rocha | GW | 11.93333 | -15.65 | 0 | Africa/Bissau | populated place | ||||
| 2369370 | Sinchã Queba | GW | 12 | -14.63333 | 0 | Africa/Bissau | populated place | ||||
| 2369180 | Sori Uoreá | Sori Uorea,Sori Uoreá,Sorioria,Sorioriá | GW | 11.26667 | -14.88333 | 0 | Africa/Bissau | populated place | |||
| 2374962 | Benájar | GW | 12.21667 | -15.66667 | 0 | Africa/Bissau | populated place | ||||
| 2372231 | Gundagà Segundo | GW | 12.63333 | -14.18333 | 0 | Africa/Bissau | populated place | ||||
| 2372617 | Fenimã | Fenima,Fenimã,Finima,Finimã | GW | 11.73333 | -15.38333 | 0 | Africa/Bissau | populated place | |||
| 7902189 | Caravela | GW | Bolama | 11.56667 | -16.26667 | 0 | Africa/Bissau | populated place | |||
| 2369376 | Sinchã Perim | GW | 12.65 | -14.21667 | 0 | Africa/Bissau | populated place | ||||
| 2374257 | Cafià | Cafia,Cafià,Cufia,Cufía | GW | 12.18333 | -14.85 | 0 | Africa/Bissau | populated place | |||
| 2369822 | Sare Tambá | GW | 12.4 | -14.58333 | 0 | Africa/Bissau | populated place | ||||
| 2369159 | Sucutoto | GW | 12.5 | -15.18333 | 0 | Africa/Bissau | populated place | ||||
| 2372783 | Elacunda | GW | 12.63333 | -14.03333 | 0 | Africa/Bissau | populated place | ||||
| 2371860 | Jumbembem | Fula,Jumbembem | GW | 12.58333 | -15.08333 | 0 | Africa/Bissau | populated place | |||
| 2370873 | Paunca | GW | 12.56667 | -14.28333 | 0 | Africa/Bissau | populated place | ||||
| 2373321 | Códè | GW | 12.43333 | -13.96667 | 0 | Africa/Bissau | populated place | ||||
| 2371214 | Nhago | GW | 11.96667 | -16.06667 | 0 | Africa/Bissau | populated place | ||||
| 2372593 | Flaque Injã | GW | 11.3 | -15.11667 | 0 | Africa/Bissau | populated place | ||||
| 2372446 | Gambia | GW | Oio | 12.05611 | -15.41667 | 0 | Africa/Bissau | populated place | |||
| 2369078 | Taláià | GW | 11.23333 | -14.9 | 0 | Africa/Bissau | populated place | ||||
| 2371130 | Nhenque | GW | 12.08333 | -15.4 | 0 | Africa/Bissau | populated place | ||||
| 2368854 | Uaranto | Uaranto,Uranto | GW | 12.56667 | -14.86667 | 0 | Africa/Bissau | populated place | |||
| 2369765 | Serração Morais | GW | 12.43333 | -15.41667 | 0 | Africa/Bissau | populated place | ||||
| 2373451 | Chancum Sate | GW | 11.8 | -14.08333 | 0 | Africa/Bissau | populated place | ||||
| 2369694 | Sinchã Bácar | GW | 12.53333 | -14.76667 | 0 | Africa/Bissau | populated place | ||||
| 2373202 | Cossicunto | Cossicunta,Cossicunto | GW | Oio | 12.29806 | -15.53694 | 0 | Africa/Bissau | populated place | ||
| 2373934 | Canconté | GW | 11.73333 | -14.85 | 0 | Africa/Bissau | populated place | ||||
| 2371587 | Mali Bula | GW | 11.93333 | -14.58333 | 0 | Africa/Bissau | populated place | ||||
| 2371289 | Naga | GW | 11.81667 | -15.68333 | 0 | Africa/Bissau | populated place | ||||
| 2374721 | Boa Esperança | GW | 11.41667 | -15.13333 | 0 | Africa/Bissau | populated place | ||||
| 2373176 | Cuchame | Ambanhe,Ambonhe,Cuchame | GW | 11.5 | -16.21667 | 0 | Africa/Bissau | populated place | |||
| 2369984 | Sare Bori | Sare Bor,Sare Bori | GW | Oio | 12.63306 | -15.10167 | 0 | Africa/Bissau | populated place | ||
| 2372085 | Injassane Beafada | GW | 11.75 | -14.98333 | 0 | Africa/Bissau | populated place | ||||
| 2369182 | Sorguidê | GW | 11.68333 | -14.63333 | 0 | Africa/Bissau | populated place | ||||
| 2372378 | Ganquélè | GW | 11.88333 | -15.1 | 0 | Africa/Bissau | populated place | ||||
| 2369836 | Sare Samba Baldè | Sare Famora,Sare Famorã,Sare Samba Balde,Sare Samba Baldè | GW | 12.61667 | -15.1 | 0 | Africa/Bissau | populated place | |||
| 2374137 | Cã Mamudo | Ca Mamudo,Cam Mamude,Cã Mamudo | GW | 12.36667 | -14.41667 | 0 | Africa/Bissau | populated place | |||
| 2370244 | Salabà | GW | 12.26667 | -14.6 | 0 | Africa/Bissau | populated place | ||||
| 2374219 | Cã Iero Sane | GW | 12.25 | -14.58333 | 0 | Africa/Bissau | populated place | ||||
| 2369453 | Sinchã Lenquetó | GW | 12.4 | -13.76667 | 0 | Africa/Bissau | populated place | ||||
| 2373670 | Capó | Capo,Capó,Cepo,Cepó | GW | Cacheu | 12.22278 | -16.14833 | 0 | Africa/Bissau | populated place | ||
| 2368678 | Velíngarà Samba | GW | 12.58333 | -13.88333 | 0 | Africa/Bissau | populated place | ||||
| 2374638 | Botê | GW | 12.21667 | -16.21667 | 0 | Africa/Bissau | populated place | ||||
| 2374970 | Belibar | GW | 12.15 | -15.76667 | 0 | Africa/Bissau | populated place | ||||
| 2373102 | Cumule | GW | 11.36667 | -15.38333 | 0 | Africa/Bissau | populated place | ||||
| 2373160 | Cufar Nalu | GW | 11.3 | -15.18333 | 0 | Africa/Bissau | populated place | ||||
| 2372953 | Dára | GW | 12.26667 | -14.11667 | 0 | Africa/Bissau | populated place | ||||
| 2373795 | Canjomba | GW | 12.43333 | -14.43333 | 0 | Africa/Bissau | populated place | ||||
| 2593133 | Jol | GW | Cacheu | 12.19889 | -15.78306 | 0 | Africa/Bissau | populated place | |||
| 2374347 | Cacandi | GW | 12.45 | -14.1 | 0 | Africa/Bissau | populated place | ||||
| 2374166 | Caliute | GW | 11.98333 | -15.98333 | 0 | Africa/Bissau | populated place | ||||
| 2371922 | Jétuntum | GW | Cacheu | 12.32306 | -15.79194 | 0 | Africa/Bissau | populated place | |||
| 2374359 | Caboxanque | Cabochanque,Caboxanque | GW | 11.28333 | -15.11667 | 0 | Africa/Bissau | populated place | |||
| 2374133 | Camanca | GW | 12.41667 | -14.31667 | 0 | Africa/Bissau | populated place |
**Exploring Guinea-Bissau: A Geographer's Perspective**
Nestled along the western coast of Africa, Guinea-Bissau is a country of vibrant culture, diverse landscapes, and rich biodiversity. As a geographer delving into the geographical intricacies of this West African nation, obtaining data on its cities, regions, and geographical coordinates offers a deeper understanding of its unique characteristics and challenges.
Discovering Guinea-Bissau's Urban Centers**
Guinea-Bissau's urban centers serve as vital nodes of economic activity, cultural exchange, and political administration. From the capital city of Bissau, with its bustling markets and colonial-era architecture, to the coastal town of Bafatá, with its vibrant street life and historic landmarks, Guinea-Bissau's cities offer insights into the country's urban dynamics and demographic trends. Obtaining data on Guinea-Bissau's cities involves mapping their geographical coordinates, analyzing their population density, and understanding their role in the country's socio-economic development.
Mapping Guinea-Bissau's Regions and Departments**
Beyond its urban centers, Guinea-Bissau is divided into regions and departments, each with its own unique landscapes, ethnic communities, and cultural traditions. From the lush forests of the Gabú region to the mangrove-lined estuaries of the Cacheu River, Guinea-Bissau's regions showcase the country's ecological diversity and natural resources. Obtaining data on Guinea-Bissau's regions and departments entails delineating their administrative boundaries, studying their environmental characteristics, and analyzing their socio-economic indicators.
Tracing Latitude and Longitude Across Guinea-Bissau**
The geographical coordinates of Guinea-Bissau serve as essential reference points for navigating its varied terrain, from the savannah grasslands of the interior to the coastal mangrove swamps and estuaries. Situated within the West African tropics, Guinea-Bissau experiences a humid tropical climate characterized by distinct wet and dry seasons. Obtaining accurate latitude and longitude data for Guinea-Bissau's cities and landmarks is crucial for understanding their spatial distribution, environmental context, and vulnerability to climate change.
Embracing Guinea-Bissau's Geographic Diversity**
In conclusion, Guinea-Bissau's geographical landscape is a mosaic of diverse ecosystems, cultural traditions, and socio-economic challenges. As geographers, let us continue to explore and document the wonders of this West African nation. By obtaining data on its cities, regions, and geographical coordinates, we can contribute to a deeper understanding of Guinea-Bissau's cultural heritage, environmental sustainability, and socio-economic development.

Download data files for Guinea Bissau's cities in Excel (.xlsx), CSV, SQL, XML and JSON formats
Exploring Guinea-Bissau’s Geography: Unlocking the Power of City Data
Guinea-Bissau, a small country located on the west coast of Africa, may not always make headlines, but its geographical and administrative structure offers valuable insights for researchers, urban planners, and policy makers alike. For geographers, understanding the relationship between the country's cities, regions, and departments is key to mapping its development trajectory and potential. One of the most powerful tools to explore and analyze Guinea-Bissau’s spatial dynamics lies in the accurate and detailed data about its cities, regions, and departments.
Obtaining data about Guinea-Bissau’s cities—including their regions and departments—is essential for anyone looking to conduct meaningful geographical studies in this diverse country. Additionally, precise latitude and longitude coordinates provide the foundation for mapping, analyzing urban development, and planning infrastructure projects. Having access to these data in flexible formats such as CSV, SQL, JSON, and XML enhances their usability, making it easier for users to integrate them into various systems for analysis and decision-making.
Understanding Guinea-Bissau’s Administrative and Geographical Structure
Guinea-Bissau is divided into several regions and departments, each with its own unique geographical, cultural, and economic characteristics. The capital, Bissau, is the largest and most significant urban area in the country, serving as the political, economic, and cultural heart of Guinea-Bissau. However, the country’s landscape also features a rich diversity of smaller cities and towns that contribute to the country’s economy, particularly through agriculture, fisheries, and natural resources.
For geographers studying Guinea-Bissau, understanding the relationships between these cities, regions, and departments is crucial. These administrative divisions reflect the spatial and socio-economic organization of the country, influencing everything from resource distribution to governance. Accessing detailed data about the locations of cities, their corresponding regions, and departments allows researchers to gain insights into the population distribution, urban growth, and economic activities within each region.
For example, regions like Bafatá, Cacheu, and Gabu have distinct characteristics that reflect their geography, with different levels of development and infrastructure. Data on these regions, including specific information on the cities within them, enables a more comprehensive understanding of Guinea-Bissau’s urban and rural landscape.
The Importance of Latitude and Longitude in Mapping Guinea-Bissau
Latitude and longitude coordinates are fundamental to any geographic study, especially in a country like Guinea-Bissau where precise mapping and spatial analysis are critical. Accurate geographic data, such as the coordinates for cities, regions, and departments, provides a clear understanding of their physical location relative to one another. This data serves as the foundation for creating detailed maps, conducting spatial analysis, and developing geographic information systems (GIS) that support urban planning, resource management, and disaster preparedness.
For instance, knowing the exact latitude and longitude of Bissau allows for an accurate representation of its location on a map. This information is essential for connecting Bissau to other cities and regions in the country, making it easier to understand transportation networks, trade routes, and regional interconnectivity. Similarly, the coordinates of other cities in Guinea-Bissau allow for the study of rural-urban dynamics and the distribution of infrastructure across the country.
By acquiring latitude and longitude data for each city in Guinea-Bissau, geographers and planners can better understand how the country’s cities are positioned geographically, helping them identify areas of growth, infrastructure needs, and development opportunities.
Flexible Data Formats for Geographic Analysis
The accessibility and usability of geographic data are just as important as its accuracy. To effectively use geographic data for analysis, it must be available in flexible formats that can be easily integrated into various applications and systems. For users working with Guinea-Bissau’s city data, having the information available in formats such as CSV, SQL, JSON, and XML is crucial for making the data adaptable to different tools and platforms.
- **CSV (Comma-Separated Values)** is one of the most common formats for storing tabular data. It allows for the easy organization of city information, such as population, area, or infrastructure details, in a simple and accessible way. CSV is ideal for users who need to conduct basic data analysis or visualization using spreadsheet tools or data analysis software.
- **SQL (Structured Query Language)** is used to manage and query relational databases. SQL provides a powerful tool for organizing and analyzing large sets of geographic data. By storing data about Guinea-Bissau’s cities, regions, and departments in a relational database, researchers can easily perform complex queries, track changes over time, and generate detailed reports based on specific criteria.
- **JSON (JavaScript Object Notation)** is commonly used in web applications and APIs. JSON allows for easy transmission of geographic data across platforms, making it ideal for developing interactive maps or location-based services. For web developers working with Guinea-Bissau’s geographic data, JSON offers a flexible and lightweight format that can be used to build dynamic applications.
- **XML (Extensible Markup Language)** is another widely used format for exchanging structured data. It is particularly useful for organizing hierarchical data, such as the relationship between cities, regions, and departments. XML’s flexibility makes it a great choice for integrating geographic data across various systems, allowing for easy sharing and collaboration.
How Geographic Data Can Support Development and Research in Guinea-Bissau
Geographic data about Guinea-Bissau’s cities, regions, and departments is essential for supporting both urban development and environmental research in the country. By obtaining accurate data, decision-makers can better plan for infrastructure projects, urban growth, and the sustainable use of resources.
For example, urban planners can use geographic data to identify areas of high population density that may require new infrastructure, such as roads, healthcare facilities, or schools. Similarly, data about Guinea-Bissau’s rural areas can help policymakers understand how to allocate resources for agriculture, water management, and rural development.
Environmental researchers can also benefit from geographic data. By mapping the locations of cities, towns, and natural resources, they can study the effects of environmental changes, such as deforestation or soil erosion. Additionally, understanding the geographic distribution of Guinea-Bissau’s cities and regions can help researchers predict the impact of climate change and plan for disaster preparedness.
Conclusion
Guinea-Bissau offers a rich and diverse geographical landscape that is essential for research and development. By obtaining detailed data on the country’s cities, regions, and departments, including their precise latitude and longitude coordinates, geographers, planners, and researchers can gain valuable insights into the country’s urbanization, resource management, and development needs. With access to this data in formats such as CSV, SQL, JSON, and XML, users can seamlessly integrate it into their analysis and decision-making processes, enabling better planning and sustainable development for Guinea-Bissau’s future.