Wallis and Futuna 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 Wallis and Futuna. Each row includes a city's latitude, longitude, region and other variables of interest. This is a subset of all 90 places in Wallis and Futuna 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 Wallis and Futuna is Mata-Utu.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 11880901 | Tuatafa | Tuatafa | WF | Alo | -14.25467 | -178.1515 | 0 | Pacific/Wallis | populated place | ||
| 4034856 | Halalo | Ha’alalo,Halalo | WF | Uvea | -13.3454 | -176.21464 | 563 | Pacific/Wallis | populated place | ||
| 10632136 | Fakapepe | Fakapepe | WF | Uvea | Hihifo | -13.22669 | -176.21218 | 0 | Pacific/Wallis | populated place | |
| 11880892 | Toloke | Toloke | WF | Sigave | -14.25349 | -178.18093 | 0 | Pacific/Wallis | populated place | ||
| 4034766 | Tufuone | WF | Uvea | Hihifo | -13.22449 | -176.21088 | 240 | Pacific/Wallis | populated place | ||
| 4034772 | Tavai | Tauai,Tavai | WF | Sigave | -14.24495 | -178.16902 | 244 | Pacific/Wallis | populated place | ||
| 4034831 | Liku | WF | Uvea | -13.26852 | -176.16586 | 696 | Pacific/Wallis | populated place | |||
| 10632472 | Kafika Tu’utahi | Kafika Tu’utahi | WF | Uvea | Hahake | -13.28231 | -176.19021 | 0 | Pacific/Wallis | populated place | |
| 10632470 | Taumata | Taumata | WF | Uvea | Hahake | -13.29347 | -176.18599 | 0 | Pacific/Wallis | populated place | |
| 11880101 | Suma | Suma | WF | Alo | Alo | -14.26862 | -178.12335 | 0 | Pacific/Wallis | populated place | |
| 11880100 | Pouma | Pouma | WF | Alo | Alo | -14.26209 | -178.13086 | 0 | Pacific/Wallis | populated place | |
| 10632354 | Siaina | Siaina | WF | Uvea | Hihifo | -13.23144 | -176.18584 | 0 | Pacific/Wallis | populated place | |
| 4034839 | Lano | WF | Alo | -13.25632 | -176.16792 | 0 | Pacific/Wallis | populated place | |||
| 10632148 | Mala’e | Mala’e | WF | Alo | -13.24435 | -176.19346 | 0 | Pacific/Wallis | populated place | ||
| 11880105 | Sisia | Sisia | WF | Alo | -14.30687 | -178.11367 | 0 | Pacific/Wallis | populated place | ||
| 11880863 | Muli | Muli | WF | Alo | Alo | -14.31162 | -178.08227 | 0 | Pacific/Wallis | populated place | |
| 4034845 | Kolia | WF | Alo | -14.30751 | -178.09683 | 437 | Pacific/Wallis | populated place | |||
| 4034815 | Mua | Alofitai,Mua | WF | Alo | Alo | -14.32632 | -178.05688 | 0 | Pacific/Wallis | populated place | |
| 4034757 | Vailala | Vailala | WF | Uvea | -13.22173 | -176.20551 | 451 | Pacific/Wallis | populated place | ||
| 11880862 | Aletafa | Aletafa | WF | Alo | Alo | -14.30784 | -178.08997 | 0 | Pacific/Wallis | populated place | |
| 4034761 | Utuloa | WF | Uvea | Hahake | -13.26667 | -176.18333 | 0 | Pacific/Wallis | populated place | ||
| 4034755 | Vaimalau | Vaimalau,Vaimatau | WF | Uvea | -13.31322 | -176.24167 | 0 | Pacific/Wallis | populated place | ||
| 10632471 | Havelu | Havelu | WF | Uvea | -13.28429 | -176.18298 | 0 | Pacific/Wallis | populated place | ||
| 4034843 | Kolopopo | Kolopopo | WF | Uvea | -13.34703 | -176.21512 | 171 | Pacific/Wallis | populated place | ||
| 11880106 | Kolopelu | Kolopelu | WF | Alo | Alo | -14.30902 | -178.11854 | 0 | Pacific/Wallis | populated place | |
| 11880091 | Tufu’one | Tufu’one | WF | Alo | Alo | -14.28702 | -178.1024 | 0 | Pacific/Wallis | populated place | |
| 11880093 | Olu | Olu | WF | Alo | -14.27848 | -178.11151 | 0 | Pacific/Wallis | populated place | ||
| 4034859 | Gamua | WF | Uvea | Hihifo | -13.24855 | -176.17813 | 0 | Pacific/Wallis | populated place | ||
| 11880097 | Kapau | Kapau | WF | Alo | Alo | -14.25598 | -178.14342 | 0 | Pacific/Wallis | populated place | |
| 10632355 | Nefunefu | Nefunefu | WF | Uvea | Hihifo | -13.22924 | -176.18557 | 0 | Pacific/Wallis | populated place | |
| 4034872 | Falaleu | Falaleu | WF | Uvea | -13.29266 | -176.18328 | 626 | Pacific/Wallis | populated place | ||
| 11880886 | Pito | Pito | WF | Sigave | Sigave | -14.26103 | -178.17769 | 0 | Pacific/Wallis | populated place | |
| 10632357 | Suva | Suva | WF | Uvea | Hihifo | -13.22423 | -176.1915 | 0 | Pacific/Wallis | populated place | |
| 4034857 | Haatofo | WF | Uvea | -13.32807 | -176.19058 | 236 | Pacific/Wallis | populated place | |||
| 4034867 | Fineveke | Fineveke | WF | Uvea | -13.32624 | -176.2213 | 0 | Pacific/Wallis | populated place | ||
| 11881005 | Keu | Keu | WF | Alo | Alo | -14.33546 | -178.06897 | 0 | Pacific/Wallis | populated place | |
| 10632334 | Afala | Afala | WF | Uvea | -13.26799 | -176.17921 | 0 | Pacific/Wallis | populated place | ||
| 10632358 | Polata | Polata | WF | Uvea | Hihifo | -13.22211 | -176.19661 | 0 | Pacific/Wallis | populated place | |
| 11880099 | Afaga | Afaga | WF | Alo | Alo | -14.25939 | -178.13414 | 0 | Pacific/Wallis | populated place | |
| 10632474 | Tekolo | Tekolo | WF | Uvea | Hihifo | -13.23061 | -176.19247 | 0 | Pacific/Wallis | populated place | |
| 10632467 | Lavegahau | Lavegahau | WF | Uvea | -13.31367 | -176.18825 | 0 | Pacific/Wallis | populated place | ||
| 4034887 | Akaka | WF | Uvea | Hahake | -13.27729 | -176.17066 | 589 | Pacific/Wallis | populated place | ||
| 10632356 | Fakavaka | Fakavaka | WF | Uvea | Hihifo | -13.22665 | -176.18674 | 0 | Pacific/Wallis | populated place | |
| 10632473 | Apaogo | Apaogo | WF | Uvea | Hahake | -13.27077 | -176.16591 | 0 | Pacific/Wallis | populated place | |
| 4034768 | Tepa | WF | Uvea | -13.32381 | -176.18826 | 244 | Pacific/Wallis | populated place | |||
| 4034770 | Teesi | Teesi,Teesse,Téessé | WF | Uvea | -13.35096 | -176.20585 | 284 | Pacific/Wallis | populated place | ||
| 4034763 | Utufua | Utufua | WF | Uvea | -13.34261 | -176.19435 | 622 | Pacific/Wallis | populated place | ||
| 11880085 | Vilamalia | Vilamalia | WF | Sigave | Sigave | -14.2984 | -178.1563 | 0 | Pacific/Wallis | populated place | |
| 10632437 | Lotoalahi | Lotoalahi | WF | Uvea | Mua | -13.34089 | -176.20857 | 0 | Pacific/Wallis | populated place | |
| 11880084 | Luanuku | Luanuku | WF | Sigave | Sigave | -14.30138 | -178.15689 | 0 | Pacific/Wallis | populated place | |
| 11880937 | Laloua | Laloua | WF | Alo | -14.29941 | -178.08029 | 0 | Pacific/Wallis | populated place | ||
| 10649227 | Golf de Ololiki | Golf de Ololiki | WF | Uvea | Hihifo | -13.25922 | -176.20562 | 0 | Pacific/Wallis | populated place | |
| 10632475 | Ala | Ala | WF | Uvea | Hihifo | -13.24465 | -176.18024 | 0 | Pacific/Wallis | populated place | |
| 4034874 | Fakauita | WF | Uvea | Hihifo | -13.25 | -176.18333 | 0 | Pacific/Wallis | populated place | ||
| 4034778 | Leava | Leava,Sigave,Sigavé,Singave | WF | Sigave | -14.29333 | -178.15833 | 480 | Pacific/Wallis | seat of a first-order administrative division | ||
| 11880092 | Tamana | Tamana | WF | Alo | Alo | -14.28439 | -178.10431 | 0 | Pacific/Wallis | populated place | |
| 11880094 | Fikavi | Fikavi | WF | Alo | Alo | -14.27124 | -178.12006 | 0 | Pacific/Wallis | populated place | |
| 4034888 | Ahoa | Ahoa | WF | Uvea | -13.28745 | -176.23803 | 495 | Pacific/Wallis | populated place | ||
| 10632476 | Tukifatu | Tukifatu | WF | Uvea | Hihifo | -13.22775 | -176.18957 | 0 | Pacific/Wallis | populated place | |
| 10632468 | Makeke | Makeke | WF | Uvea | Hahake | -13.30308 | -176.18898 | 0 | Pacific/Wallis | populated place | |
| 11880098 | Ogea | Ogea | WF | Alo | Alo | -14.25683 | -178.14128 | 0 | Pacific/Wallis | populated place | |
| 10632353 | Kaleva | Kaleva | WF | Uvea | Hihifo | -13.24234 | -176.1808 | 0 | Pacific/Wallis | populated place | |
| 11880938 | Ava | Ava | WF | Alo | -14.29661 | -178.08968 | 0 | Pacific/Wallis | populated place | ||
| 11880066 | Kaleveleve | Kaleveleve | WF | Alo | Alo | -14.30817 | -178.13323 | 0 | Pacific/Wallis | populated place | |
| 11881004 | Sologa | Sologa | WF | Alo | Alo | -14.32449 | -178.04063 | 0 | Pacific/Wallis | populated place | |
| 4034821 | Mata-Utu | Mata Utu,Mata’utu,Mata-Outou,Mata-Utu,Matauto,Matautu,Matâutu,Matāʻutu,ma ta wu tu,mata-atw,mata-awtw,mata-utu,mata-xu tu,matautou,matautu,Μάτα-Ούτου,Мата-Уту,ماتا-اتو,ماتا-اوتو,மாதா-உது,มาตา-อูตู,მატა-უტუ,マタウトゥ,马塔乌图,마타우투 | WF | Uvea | -13.28163 | -176.17453 | 1200 | Pacific/Wallis | capital of a political entity | ||
| 11880917 | Nuku | Nuku | WF | Sigave | -14.29104 | -178.16536 | 0 | Pacific/Wallis | populated place | ||
| 11880934 | Siku | Siku | WF | Alo | Alo | -14.31024 | -178.06529 | 0 | Pacific/Wallis | populated place | |
| 11880072 | Fiua | Fiua | WF | Sigave | -14.27069 | -178.17378 | 0 | Pacific/Wallis | populated place | ||
| 11880079 | Vaisei | Vaisei | WF | Sigave | -14.27772 | -178.17048 | 0 | Pacific/Wallis | populated place | ||
| 10632339 | Malelapa | Malelapa | WF | Uvea | Hihifo | -13.2353 | -176.18288 | 0 | Pacific/Wallis | populated place | |
| 10632460 | Mala’etoli | Mala’etoli | WF | Uvea | -13.31964 | -176.2289 | 0 | Pacific/Wallis | populated place | ||
| 4034816 | Mua | Loto Mua,Mua | WF | Uvea | Mua | -13.34169 | -176.18701 | 0 | Pacific/Wallis | populated place | |
| 4034886 | Alele | Alele | WF | Uvea | -13.24667 | -176.18341 | 629 | Pacific/Wallis | populated place | ||
| 4034865 | Foi | WF | Sigave | -14.29445 | -178.09289 | 0 | Pacific/Wallis | populated place | |||
| 4034753 | Vele | WF | Alo | -14.31021 | -178.06538 | 309 | Pacific/Wallis | populated place | |||
| 4034854 | Halamaitai | WF | Uvea | Hahake | -13.28184 | -176.19045 | 0 | Pacific/Wallis | populated place | ||
| 4034858 | Haafusia | WF | Uvea | Hahake | -13.30034 | -176.18362 | 426 | Pacific/Wallis | populated place | ||
| 11880065 | Fuga Alo | Fuga Alo | WF | Alo | Alo | -14.30452 | -178.12422 | 0 | Pacific/Wallis | populated place | |
| 10632459 | Mala’efo’ou | Mala’efo’ou | WF | Uvea | -13.34544 | -176.2016 | 0 | Pacific/Wallis | populated place | ||
| 10632438 | Ha’apai | Ha’apai | WF | Uvea | Mua | -13.34733 | -176.21172 | 0 | Pacific/Wallis | populated place | |
| 4034885 | Alo | Alo,Malae,Ono | WF | Alo | -14.31096 | -178.11094 | 239 | Pacific/Wallis | seat of a first-order administrative division | ||
| 11880064 | Taoa | Taoa | WF | Alo | -14.30871 | -178.12683 | 0 | Pacific/Wallis | populated place | ||
| 11880864 | Vaotea | Vaotea | WF | Alo | Alo | -14.31034 | -178.08439 | 0 | Pacific/Wallis | populated place | |
| 11880916 | Sausau | Sausau | WF | Sigave | -14.28854 | -178.16746 | 0 | Pacific/Wallis | populated place | ||
| 10632436 | Tutu’ila | Tutu’ila | WF | Uvea | Mua | -13.34315 | -176.21751 | 0 | Pacific/Wallis | populated place | |
| 4034860 | Gahi | Gahi | WF | Uvea | -13.33793 | -176.18774 | 280 | Pacific/Wallis | populated place | ||
| 11881006 | Sa’avaka | Sa’avaka | WF | Alo | -14.3502 | -178.02841 | 0 | Pacific/Wallis | populated place | ||
| 4034754 | Vaitupu | WF | Uvea | -13.227 | -176.18834 | 601 | Pacific/Wallis | populated place | |||
| 11880089 | Fakaki | Fakaki | WF | Alo | Alo | -14.29262 | -178.09573 | 0 | Pacific/Wallis | populated place |
**Exploring the Unique Geography of Wallis and Futuna**
Introduction**
Welcome to Wallis and Futuna, a remote French territory in the South Pacific Ocean. As a geographer, delving into the data of Wallis and Futuna's cities, regions, and departments, while acquiring the latitude and longitude coordinates of each urban area, provides valuable insights into the geographical landscape of this archipelago.
Unveiling the Island Terrain**
Wallis and Futuna consist of three main islands—Wallis, Futuna, and Alofi—each with its own distinct geography and cultural identity. From the volcanic peaks of Futuna to the coral reefs surrounding Wallis, the islands offer a diverse range of landscapes to explore and study.
Mapping Geographic Coordinates**
Mapping the latitude and longitude coordinates of Wallis and Futuna's cities allows us to navigate its scattered islands with precision. From the capital of Mata-Utu on Wallis to the village of Leava on Futuna, these geographic coordinates serve as essential markers in understanding the spatial distribution of population and resources in the territory.
Exploring Island Communities**
The communities of Wallis and Futuna are tightly knit, with strong ties to traditional culture and customs. Villages are often centered around communal spaces such as churches and meeting halls, reflecting the importance of social cohesion and collective identity in island life.
Understanding Environmental Vulnerabilities**
Despite their remote location, Wallis and Futuna are not immune to environmental challenges. Rising sea levels, coastal erosion, and cyclones pose significant threats to the islands' fragile ecosystems and infrastructure. As geographers, it is crucial to study these vulnerabilities and work towards sustainable solutions that mitigate the impacts of climate change on the territory.
Preserving Cultural Heritage**
The cultural heritage of Wallis and Futuna is rich and diverse, rooted in centuries-old traditions and practices. From traditional dance and music to intricate tapa cloth designs, the islands' cultural heritage is a testament to the resilience and creativity of its people. As geographers, we must advocate for the preservation of this cultural heritage and support efforts to promote cultural exchange and understanding.
Conclusion**
In conclusion, our exploration of Wallis and Futuna's geography has revealed a territory of unique beauty and cultural significance. By obtaining data on its cities, regions, and geographic coordinates, we have gained valuable insights into the spatial dynamics of this remote archipelago. As Wallis and Futuna continue to navigate environmental challenges and preserve their cultural heritage, the role of geographers in understanding and addressing these issues becomes increasingly important. By leveraging our knowledge and expertise, we can contribute to the sustainable development and resilience of Wallis and Futuna for generations to come.

Download data files for Wallis and Futuna's cities in Excel (.xlsx), CSV, SQL, XML and JSON formats
Exploring Wallis and Futuna: A Geographer’s View of City-Level Data
Wallis and Futuna, a French overseas collectivity located in the South Pacific Ocean, offers a unique geographical landscape for study. Comprised of several islands, including Wallis, Futuna, and the smaller islands of Alofi, this remote archipelago is part of the Polynesian region. While it may not be as well-known as other Pacific islands, Wallis and Futuna’s geographic and cultural richness makes it an intriguing subject for geographers and researchers. The ability to access detailed geographic data about the cities, regions, and departments of this fascinating territory is essential for a deeper understanding of its spatial dynamics, development needs, and challenges. This article delves into how acquiring data on cities in Wallis and Futuna—including their exact latitude, longitude, and regional divisions—can unlock valuable insights. Additionally, it highlights how this data can be accessed in various formats such as CSV, SQL, JSON, and XML.
The Geographic Layout of Wallis and Futuna
Wallis and Futuna consists of three main islands: Wallis, Futuna, and Alofi, along with several smaller islands. Located to the east of Fiji and north of Tonga, the archipelago is strategically positioned in the heart of Polynesia. The largest island, Wallis Island, serves as the political and administrative center, with its main city, Mata-Utu, acting as the capital. Futuna, the second-largest island, is located to the southeast of Wallis Island, and is divided into several districts, each with its own local governance.
Wallis and Futuna’s geography is defined by its volcanic origins, with highlands and mountainous terrain that characterize much of the islands. The coastal areas are home to lush forests, coral reefs, and white sandy beaches, making it an ecologically diverse area. Understanding the geography of the islands is vital for comprehending their population distribution, infrastructure, and regional administrative needs. With a population spread across several small cities and villages, precise geographic data helps to map out these areas and provides insights into urban development and resource management.
The Need for City-Level Geographic Data in Wallis and Futuna
While Wallis and Futuna is a relatively small territory, the availability of accurate and detailed city-level data is essential for researchers, urban planners, and anyone working on development projects. The cities and towns of Wallis and Futuna, including the capital Mata-Utu, are spread across the islands and are typically smaller in size compared to larger urban centers, but they still face challenges related to infrastructure, transportation, and population growth.
City-level geographic data, such as the latitude and longitude of each city, along with information about surrounding regions and departments, is crucial for several reasons. First, it allows for accurate mapping and visualization of the islands’ urban and rural areas. Second, it provides key data for planning infrastructure projects, such as roads, schools, and hospitals, which are essential for improving the quality of life on the islands. Third, it can be used for environmental management, helping researchers and policymakers to understand how urban areas interact with natural ecosystems.
The ability to access such data can support everything from urbanization studies to environmental conservation projects and disaster risk management—particularly important for an island region that faces natural threats such as cyclones and sea-level rise.
How to Access City Data for Wallis and Futuna
Obtaining city-level geographic data for Wallis and Futuna is essential for anyone looking to conduct thorough geographic analysis of the region. This data typically includes the coordinates of each city, along with its regional and departmental classification. For instance, in addition to Mata-Utu, which serves as the capital, other cities and villages on the islands are equally important for understanding the demographic and infrastructural layout of the territory.
The ability to obtain this data in digital formats allows for integration into geographic systems, such as Geographic Information Systems (GIS), or for use in more manual forms of analysis. This data can be formatted in several ways, including CSV, SQL, JSON, and XML, making it compatible with a wide range of tools and software. Whether for academic research, urban planning, or environmental management, this data can be tailored to meet the specific needs of the user.
Formats for Geographic Data: CSV, SQL, JSON, and XML
Each format—CSV, SQL, JSON, and XML—offers distinct advantages, depending on the needs of the project or analysis.
- **CSV (Comma Separated Values):** CSV is a simple format that is easy to use and compatible with spreadsheet software like Microsoft Excel or Google Sheets. It allows users to organize data in a tabular format, making it ideal for analyzing city names, coordinates, regional data, and other basic geographic information. This format is especially useful for those working with small to medium-sized datasets or for those who need to perform quick, manual analysis.
- **SQL (Structured Query Language):** SQL is perfect for users who are dealing with larger datasets or need to query databases. By storing geographic data in a relational database, users can perform complex searches, filtering, and statistical analysis on the data. SQL is particularly useful for those managing large-scale geographic projects or when working with city-level data that needs to be organized and retrieved efficiently.
- **JSON (JavaScript Object Notation):** JSON is a flexible format used widely in web development and data exchange. It is particularly useful for integrating geographic data into applications or websites. JSON’s hierarchical structure allows for easy representation of nested data, making it ideal for projects that require dynamic integration of city-level data into real-time systems or location-based services.
- **XML (eXtensible Markup Language):** XML is used for representing structured data and is commonly used in applications that require data exchange between systems. Like JSON, XML is highly flexible, allowing for a detailed representation of geographic data, such as relationships between cities and their corresponding regions and departments. It is widely used in geospatial systems that require complex, structured datasets.
By offering these four formats, users can choose the one that best suits their specific project or analysis needs, making it easier to integrate and analyze data from Wallis and Futuna.
Why Geographic Data Matters for Understanding Wallis and Futuna
Geographic data is crucial for understanding the spatial organization of Wallis and Futuna, particularly given the challenges posed by its remote location and island geography. For example, the data can help to identify key areas for infrastructure development, such as roads and transportation networks that connect the islands. It can also inform decisions about disaster preparedness, particularly since the islands are vulnerable to cyclones and other natural events.
Furthermore, understanding the geographic relationships between cities, regions, and departments is essential for effective governance and resource management. With detailed data, policymakers and planners can better allocate resources, plan for population growth, and address environmental challenges.
Having access to such data also provides opportunities for research on issues like climate change, coastal erosion, and the protection of local ecosystems, all of which are critical for ensuring the long-term sustainability of Wallis and Futuna.
Leveraging Geographic Data for Development Projects
Whether for urban planning, environmental management, or community development, geographic data on Wallis and Futuna’s cities and regions can significantly enhance any project. By using city-level data, planners can optimize infrastructure, improve access to services, and ensure that growth is managed sustainably. In addition, researchers can use geographic data to model future scenarios and inform decision-making processes on both local and regional levels.
With the flexibility provided by formats such as CSV, SQL, JSON, and XML, users can integrate Wallis and Futuna’s city-level geographic data into their systems, software, or applications, making it easier to analyze trends, visualize data, and create solutions that are tailored to the unique needs of the islands.
Conclusion
Wallis and Futuna’s geographical and administrative structure offers valuable insights into the challenges and opportunities faced by small island communities. Accessing detailed city-level geographic data, including latitude and longitude coordinates, as well as regional and departmental information, is crucial for anyone interested in understanding and addressing the country’s spatial and developmental needs. By obtaining this data in formats like CSV, SQL, JSON, and XML, you gain the flexibility to integrate it into various systems and projects, whether for academic research, urban planning, or environmental management. With accurate and accessible geographic data, it is possible to support sustainable development and enhance the resilience of Wallis and Futuna’s cities and regions.