Portugal cities list with latitude and longitude in Excel, CSV, XML, SQL, JSON formats
Last update : 15 February 2026.
Below is a list of 100 prominent cities in Portugal. Each row includes a city's latitude, longitude, region and other variables of interest. This is a subset of all 16267 places in Portugal 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 Portugal is Lisbon.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2743007 | Alvações do Tanha | PT | Vila Real | Peso da Régua | 41.19162 | -7.74355 | 0 | Europe/Lisbon | populated place | ||
| 2265531 | Ninho de Águia | PT | Santarém | Ourém | 39.71708 | -8.66847 | 101 | Europe/Lisbon | populated place | ||
| 2267330 | Joinal | PT | Faro | Silves | 37.23179 | -8.2846 | 0 | Europe/Lisbon | populated place | ||
| 2735457 | Rande | PT | Porto | Felgueiras | 41.33499 | -8.23061 | 0 | Europe/Lisbon | populated place | ||
| 2734339 | Coronado | Coronado,Sao Romao do Coronado,São Romão do Coronado | PT | Porto | Trofa | 41.28544 | -8.5632 | 8697 | Europe/Lisbon | populated place | |
| 2741429 | Carrazedo | PT | Aveiro | Sever do Vouga | 40.69237 | -8.33238 | 0 | Europe/Lisbon | populated place | ||
| 2736853 | Pagade | PT | Viana do Castelo | Vila Nova de Cerveira | 41.88372 | -8.684 | 0 | Europe/Lisbon | populated place | ||
| 2261870 | Valongo | PT | Castelo Branco | Sertã | 39.76833 | -8.15863 | 0 | Europe/Lisbon | populated place | ||
| 2734224 | Sedielos | PT | Vila Real | Peso da Régua | 41.20281 | -7.8618 | 0 | Europe/Lisbon | populated place | ||
| 3372941 | Lapa de Cima | PT | Azores | Vila do Porto | 36.95 | -25.03333 | 0 | Atlantic/Azores | populated place | ||
| 2743062 | Aljuriça | PT | Coimbra | Cantanhede | 40.32152 | -8.65726 | 0 | Europe/Lisbon | populated place | ||
| 2262119 | Vale de Paraíso | PT | Madeira | Santa Cruz | 32.66667 | -16.86667 | 0 | Atlantic/Madeira | populated place | ||
| 2741755 | Cãis | PT | Viana do Castelo | Valença | 42.01797 | -8.61711 | 0 | Europe/Lisbon | populated place | ||
| 8504582 | Poça Carvalha | PT | Braga | Vila Verde | 41.74676 | -8.39498 | 410 | 0 | Europe/Lisbon | populated place | |
| 2262549 | Touris | PT | Évora | Estremoz | 38.90726 | -7.53425 | 0 | Europe/Lisbon | populated place | ||
| 2743141 | Aldeia Nova do Cabo | PT | Castelo Branco | Fundão | 40.13291 | -7.53228 | 0 | Europe/Lisbon | populated place | ||
| 2270786 | Boisias | PT | Leiria | Caldas da Rainha | 39.41074 | -9.05649 | 0 | Europe/Lisbon | populated place | ||
| 2735814 | Póvoa da Várzea | PT | Porto | 41.05181 | -8.48078 | 0 | Europe/Lisbon | populated place | |||
| 2271803 | Alvarrões | PT | Lisbon | Alenquer | 39.06793 | -9.02194 | 0 | Europe/Lisbon | populated place | ||
| 2738934 | Gondiléu | PT | Coimbra | Coimbra | 40.25949 | -8.40376 | 0 | Europe/Lisbon | populated place | ||
| 2265265 | Palhavã | PT | Santarém | Tomar | 39.60029 | -8.39814 | 0 | Europe/Lisbon | populated place | ||
| 2738376 | Lavacolhos | PT | Castelo Branco | Fundão | 40.13133 | -7.61926 | 0 | Europe/Lisbon | populated place | ||
| 2268360 | Famalicão | Famalicao,Famalicão | PT | Leiria | Nazaré | 39.53642 | -9.08308 | 1740 | Europe/Lisbon | populated place | |
| 2266376 | Miranda | PT | Beja | 38.16381 | -8.32154 | 0 | Europe/Lisbon | populated place | |||
| 2270496 | Cachofarra | PT | Setúbal | Setúbal | 38.51251 | -8.85835 | 0 | Europe/Lisbon | populated place | ||
| 2265404 | Orjariça | PT | Lisbon | Torres Vedras | 39.06312 | -9.23545 | 0 | Europe/Lisbon | populated place | ||
| 6559436 | Vila Nova De Cacela | PT | Faro | Vila Real de Santo António | 37.17391 | -7.53169 | 3902 | Europe/Lisbon | populated place | ||
| 2733527 | Torgal | PT | Leiria | Castanheira de Pêra | 40.01602 | -8.19307 | 0 | Europe/Lisbon | populated place | ||
| 2742648 | Assamassa | PT | Coimbra | Soure | 40.0923 | -8.60889 | 0 | Europe/Lisbon | populated place | ||
| 2269775 | Casal da Fonte | PT | Leiria | Figueiró Dos Vinhos | 39.86948 | -8.24518 | 0 | Europe/Lisbon | populated place | ||
| 2271641 | Andreus | PT | Santarém | Sardoal | 39.55611 | -8.1655 | 0 | Europe/Lisbon | populated place | ||
| 2734792 | Sanfins | PT | Vila Real | Chaves | 41.79412 | -7.25043 | 0 | Europe/Lisbon | populated place | ||
| 2734093 | Serafão | PT | Braga | Fafe | 41.52957 | -8.20332 | 0 | Europe/Lisbon | populated place | ||
| 2267516 | Grossinhos | PT | Lisbon | Mafra | 38.94022 | -9.35123 | 0 | Europe/Lisbon | populated place | ||
| 2735385 | Rebordochão | PT | Vila Real | Vila Pouca de Aguiar | 41.54306 | -7.61507 | 0 | Europe/Lisbon | populated place | ||
| 2739438 | Fontela | PT | Braga | Guimarães | 41.5091 | -8.23841 | 0 | Europe/Lisbon | populated place | ||
| 2741139 | Casal do Redinho | PT | Coimbra | Soure | 40.13835 | -8.63693 | 0 | Europe/Lisbon | populated place | ||
| 2737969 | Malta | PT | Bragança | Macedo de Cavaleiros | 41.48282 | -6.91362 | 0 | Europe/Lisbon | populated place | ||
| 2263900 | Ribeira da Janela | Ribeira da Janela | PT | Madeira | Porto Moniz | 32.84648 | -17.15546 | 0 | Atlantic/Madeira | populated place | |
| 2733819 | Soutilha | PT | Bragança | Vinhais | 41.72531 | -7.1023 | 0 | Europe/Lisbon | populated place | ||
| 2263383 | São Bento do Zambujal | PT | Évora | Redondo | 38.67184 | -7.60598 | 0 | Europe/Lisbon | populated place | ||
| 2270064 | Carregueiro | PT | Beja | Aljustrel | 37.82197 | -8.10339 | 0 | Europe/Lisbon | populated place | ||
| 2267040 | Lobata | PT | Santarém | Sardoal | 39.58241 | -8.16191 | 0 | Europe/Lisbon | populated place | ||
| 2269783 | Casal da Clara | PT | Leiria | Pombal | 39.93103 | -8.76955 | 0 | Europe/Lisbon | populated place | ||
| 2741449 | Carragosa | PT | Bragança | Bragança Municipality | 41.86594 | -6.80004 | 190 | Europe/Lisbon | populated place | ||
| 2265806 | Montes Novos | PT | Évora | Alandroal | 38.61405 | -7.44913 | 0 | Europe/Lisbon | populated place | ||
| 2737349 | Mosteirinho | PT | Viseu | Viseu | 40.65131 | -7.99525 | 0 | Europe/Lisbon | populated place | ||
| 2262213 | Vale de Cebolas | PT | Setúbal | Montijo | 38.74369 | -8.56039 | 0 | Europe/Lisbon | populated place | ||
| 2739498 | Fontão | PT | Coimbra | Tábua | 40.24981 | -8.04712 | 0 | Europe/Lisbon | populated place | ||
| 2735592 | Quinta de Santo Amaro | PT | Viseu | Mangualde | 40.59256 | -7.6275 | 0 | Europe/Lisbon | populated place | ||
| 2266523 | Meca | PT | Lisbon | Alenquer | 39.08178 | -9.03459 | 1719 | Europe/Lisbon | populated place | ||
| 2263457 | Santiais | PT | Leiria | Pombal | 39.81511 | -8.55454 | 0 | Europe/Lisbon | populated place | ||
| 2739937 | Escariz | PT | Vila Real | Chaves | 41.66653 | -7.48535 | 0 | Europe/Lisbon | populated place | ||
| 2737153 | Nogueira | PT | Viseu | Resende | 41.11581 | -7.89987 | 0 | Europe/Lisbon | populated place | ||
| 2737747 | Melcões | PT | Viseu | Lamego | 41.05042 | -7.81787 | 0 | Europe/Lisbon | populated place | ||
| 2272404 | A das Carreiras | PT | Lisbon | Torres Vedras | 39.06667 | -9.15 | 0 | Europe/Lisbon | populated place | ||
| 2734232 | Sebal Grande | Sebal,Sebal Grande | PT | Coimbra | Condeixa-A-Nova | 40.12007 | -8.5351 | 0 | Europe/Lisbon | populated place | |
| 2738063 | Macieira | PT | Viseu | Sernancelhe | 40.98916 | -7.48614 | 0 | Europe/Lisbon | populated place | ||
| 2272162 | Alcaria do João | PT | Faro | Loulé | 37.24112 | -8.19505 | 0 | Europe/Lisbon | populated place | ||
| 3373262 | Cais do Galego | PT | Azores | Lajes do Pico | 38.43416 | -28.04962 | 0 | Atlantic/Azores | populated place | ||
| 2271517 | Arneiros | PT | Lisbon | Torres Vedras | 39.07417 | -9.22583 | 0 | Europe/Lisbon | populated place | ||
| 2736488 | Pena | PT | Coimbra | Góis | 40.11077 | -8.13506 | 0 | Europe/Lisbon | populated place | ||
| 8199024 | Luz de Tavira | PT | Faro | Tavira | 37.0896 | -7.71395 | 0 | Europe/Lisbon | populated place | ||
| 2742310 | Beduido | PT | Aveiro | Albergaria-A-Velha | 40.62836 | -8.49406 | 0 | Europe/Lisbon | populated place | ||
| 2737143 | Nogueira | PT | Viana do Castelo | Ponte de Lima | 41.79055 | -8.52301 | 0 | Europe/Lisbon | populated place | ||
| 2264157 | Quinta do Espinheiro | PT | Évora | Évora | 38.6 | -7.88333 | 0 | Europe/Lisbon | populated place | ||
| 2738914 | Gongeva | PT | Aveiro | 41.03333 | -8.48333 | 0 | Europe/Lisbon | populated place | |||
| 2742793 | Arcozelo | PT | Viana do Castelo | Ponte de Lima | 41.79384 | -8.59416 | 0 | Europe/Lisbon | populated place | ||
| 3372613 | São Francisco | Francisco das Almas,Sao Francisco,São Francisco | PT | Azores | Angra do Heroísmo | 38.66667 | -27.26667 | 0 | Atlantic/Azores | populated place | |
| 2261481 | Zambujeiro | Zambujeiro | PT | Lisbon | Cascais | 38.74399 | -9.43484 | 0 | Europe/Lisbon | populated place | |
| 2271445 | Arroteia | PT | Leiria | Leiria | 39.85753 | -8.8322 | 227 | Europe/Lisbon | populated place | ||
| 2264424 | Porto de Mouros de Cima | PT | Beja | Ferreira do Alentejo | 38.03333 | -8.33333 | 0 | Europe/Lisbon | populated place | ||
| 2741208 | Casal | PT | Viana do Castelo | Arcos de Valdevez | 41.94328 | -8.45618 | 0 | Europe/Lisbon | populated place | ||
| 2267409 | Ilha do Farol | PT | Faro | Faro | 36.97545 | -7.86609 | 0 | Europe/Lisbon | populated place | ||
| 2739875 | Espinheiro | PT | Guarda | Celorico da Beira | 40.66033 | -7.41019 | 0 | Europe/Lisbon | populated place | ||
| 2265006 | Pedrógão | Pedrogao,Pedrógão | PT | Beja | Vidigueira | 38.11868 | -7.64782 | 0 | Europe/Lisbon | populated place | |
| 2264292 | Quatrim | PT | Faro | Olhão | 37.05506 | -7.8127 | 0 | Europe/Lisbon | populated place | ||
| 2732223 | Zambujal | PT | Coimbra | Condeixa-A-Nova | 40.05587 | -8.44568 | 0 | Europe/Lisbon | populated place | ||
| 2735774 | Póvoa dos Sobrinhos | PT | Viseu | Viseu | 40.64828 | -7.87228 | 0 | Europe/Lisbon | populated place | ||
| 2266178 | Monte da Capela | PT | Portalegre | Sousel | 38.9873 | -7.84196 | 0 | Europe/Lisbon | populated place | ||
| 2261743 | Vendas do Rijo | PT | Santarém | Tomar | 39.63748 | -8.30449 | 0 | Europe/Lisbon | populated place | ||
| 2263353 | São Domingos de Ana Loura | PT | Évora | Borba | 38.86692 | -7.49701 | 0 | Europe/Lisbon | populated place | ||
| 2734029 | Serzedo | Serzedo | PT | Porto | Vila Nova de Gaia | 41.05105 | -8.61605 | 7891 | Europe/Lisbon | populated place | |
| 3372615 | São Caetano | Sao Caetano,São Caetano | PT | Azores | Madalena | 38.43107 | -28.4273 | 0 | Atlantic/Azores | populated place | |
| 2742002 | Brejas do Barco | PT | Castelo Branco | Oleiros | 40.05563 | -7.8542 | 0 | Europe/Lisbon | populated place | ||
| 2270436 | Caldas de Monchique | Caldas de Monchique | PT | Faro | Monchique | 37.28562 | -8.55706 | 0 | Europe/Lisbon | populated place | |
| 2738381 | Lata | PT | Coimbra | Miranda do Corvo | 40.16286 | -8.33269 | 0 | Europe/Lisbon | populated place | ||
| 2734429 | São Martinho | PT | Coimbra | Góis | 40.17872 | -8.09439 | 0 | Europe/Lisbon | populated place | ||
| 2742570 | Avilhoso | PT | Porto | Matosinhos | 41.24896 | -8.7023 | 0 | Europe/Lisbon | populated place | ||
| 2733976 | Silveira | PT | Aveiro | Sever do Vouga | 40.67492 | -8.32626 | 0 | Europe/Lisbon | populated place | ||
| 3372612 | São João | Sao Joao,São João | PT | Azores | Lajes do Pico | 38.41493 | -28.3396 | 0 | Atlantic/Azores | populated place | |
| 2734687 | Santa Maria de Émeres | PT | Vila Real | Valpaços | 41.54562 | -7.37957 | 0 | Europe/Lisbon | populated place | ||
| 2270244 | Cansados | PT | Beja | Almodôvar | 37.37853 | -8.09365 | 0 | Europe/Lisbon | populated place | ||
| 2743296 | Aguda | Aguda | PT | Porto | Vila Nova de Gaia | 41.05223 | -8.651 | 0 | Europe/Lisbon | populated place | |
| 2739286 | Frazão | Frazao,Frazão | PT | Porto | Paços de Ferreira | 41.25866 | -8.40014 | 4314 | Europe/Lisbon | populated place | |
| 2269569 | Cassoaria | PT | Lisbon | Alenquer | 39.06816 | -9.05722 | 0 | Europe/Lisbon | populated place | ||
| 3411325 | Santa Bárbara | PT | Azores | Povoação | 37.75 | -25.25 | 0 | Atlantic/Azores | populated place | ||
| 2262439 | Vala | PT | Faro | Silves | 37.15262 | -8.41729 | 0 | Europe/Lisbon | populated place | ||
| 2262626 | Torrão | Torran,Торран | PT | Setúbal | Alcácer do Sal | 38.29304 | -8.22661 | 0 | Europe/Lisbon | populated place | |
| 2742611 | Aveiro | Abeiro,Aveiro,Avejru,ZAV,Αβέιρο,Авейру | PT | Aveiro | Aveiro | 40.64427 | -8.64554 | 54162 | Europe/Lisbon | seat of a first-order administrative division |
**Exploring Portugal: A Geographer's Perspective**
Introduction**
As a geographer delving into the intricate geography of Portugal, one unravels a tapestry of diverse landscapes, rich history, and vibrant culture. From the bustling cities of Lisbon and Porto to the tranquil villages of the Alentejo region, Portugal offers a captivating array of geographical features waiting to be explored. In this article, we embark on a journey to obtain data on the cities of Portugal, including their regions and departments, as well as the latitude and longitude coordinates of each city.
Unveiling the Urban Fabric**
Portugal's cities are not only centers of population and economic activity but also repositories of history and culture. From the ancient streets of Lisbon's Alfama district to the modern architecture of Porto's riverside, each city tells a unique story shaped by centuries of human interaction with the landscape. Obtaining data on the cities of Portugal allows us to understand their spatial distribution, population dynamics, and socioeconomic characteristics in greater detail.
Mapping Latitude and Longitude**
The latitude and longitude coordinates of Portugal's cities provide crucial spatial information for geographic analysis and mapping. From the northernmost city of Bragança to the southernmost city of Faro, these coordinates delineate the geographic extent of each city and its relationship to surrounding natural features and urban centers. By mapping latitude and longitude data, geographers can visualize spatial patterns, analyze geographic trends, and identify areas of interest for further research and exploration.
Exploring Regional Variation**
Portugal's diverse geography encompasses a range of natural landscapes, from the rugged mountains of the Serra da Estrela to the sun-drenched beaches of the Algarve. Each region has its own unique climate, vegetation, and land use patterns, influenced by factors such as altitude, proximity to the coast, and historical development. By obtaining data on the regions and departments of Portugal, geographers can explore the spatial distribution of these environmental characteristics and understand their implications for human settlement and economic activity.
Challenges and Opportunities**
Like all countries, Portugal faces a range of geographic challenges, from environmental sustainability to urban development and regional disparities. By obtaining data on the cities, regions, and departments of Portugal, geographers can contribute to evidence-based policymaking and planning, addressing issues such as land use management, transportation infrastructure, and environmental conservation. By understanding the geographic context of these challenges, policymakers can develop more effective strategies for sustainable development and inclusive growth.
Conclusion**
In conclusion, the geography of Portugal offers a fascinating lens through which to explore the complexities of human-environment interaction. By obtaining data on the cities, regions, and departments of Portugal, geographers can uncover valuable insights into the spatial patterns, processes, and dynamics that shape the country's landscapes and livelihoods. As stewards of Portugal's geographic heritage, it is our responsibility to use this knowledge to inform decision-making, promote sustainable development, and preserve the natural and cultural heritage of this remarkable country for future generations.

Download data files for Portugal's cities in Excel (.xlsx), CSV, SQL, XML and JSON formats
Exploring the Geography of Portugal: A Geographical and Data-Driven Perspective
Portugal, situated on the Iberian Peninsula in southwestern Europe, is a country of rich historical and geographical significance. From its stunning Atlantic coastline to the mountain ranges that define its interior, Portugal’s diverse landscape has shaped its culture, economy, and urban development. As a geographer, analyzing the distribution of cities, regions, and departments across the country provides crucial insights into the spatial dynamics of urban growth, regional development, and environmental management. By leveraging detailed geographic data, including latitude and longitude coordinates of cities and towns, it is possible to enhance our understanding of the country's geographic complexities and provide effective solutions for sustainable development.
The Administrative Structure of Portugal and Its Geographic Diversity
Portugal is divided into 18 administrative districts (distritos) and two autonomous regions, Madeira and Azores, each offering distinct geographic and cultural characteristics. Lisbon, the capital, is situated in the Lisbon District and serves as the heart of the country’s political and economic activities. Other major cities such as Porto, Faro, and Coimbra play critical roles in Portugal’s history, culture, and modern-day economy. The country’s regions range from coastal urban centers to rural interior areas, each with specific developmental and environmental challenges.
Portugal’s physical geography includes varied landscapes: the mountainous regions of the north, including the Serra da Estrela, the lush forests and rolling hills of the interior, and the vast plains of the Alentejo in the south. The coastal regions, particularly in the west and south, have historically been central to Portugal’s maritime activities, while the northern mountains and river valleys support agricultural activities. Understanding the relationship between urban settlements and their surrounding geography is essential for sustainable urbanization and regional planning across the country.
Latitude and Longitude: Mapping the Cities and Regions of Portugal
Latitude and longitude coordinates are indispensable tools for accurately mapping Portugal’s cities and regions. These geographic coordinates provide precise locations for major cities such as Lisbon, Porto, Braga, and Funchal, as well as for smaller towns across the country.
For example, obtaining the latitude and longitude of Lisbon allows researchers to analyze its proximity to the Atlantic Ocean, providing insight into its historical role as a global maritime power. Similarly, the coordinates of Porto can help examine its position relative to the Douro River, influencing its economic activities in wine production and trade. With accurate geographic data, it is possible to create detailed maps that highlight the connectivity between urban centers, transportation routes, and natural resources.
Furthermore, understanding the geographic location of cities in relation to Portugal’s environmental features, such as the mountainous regions in the north or the coastal zones in the south, helps urban planners manage issues like land use, population growth, and environmental sustainability. Latitude and longitude data also support disaster management efforts, particularly in assessing risks related to flooding or earthquakes, ensuring that local governments can plan accordingly.
The Importance of Accessible Geographic Data Formats
To ensure that geographic data is effectively used for research, analysis, and decision-making, it must be made available in formats that are compatible with a range of systems and tools. Offering geographic data for Portugal’s cities, regions, and departments in formats such as CSV, SQL, JSON, and XML ensures that the data can be integrated into diverse platforms for further analysis and practical application.
- **CSV (Comma-Separated Values):** CSV files are ideal for organizing geographic data in a simple, tabular format. They can store city names, population figures, latitude and longitude coordinates, and other essential attributes in a clear and easy-to-read structure. Researchers and planners can easily import CSV files into spreadsheet software or GIS systems to conduct basic analysis or visualize geographic trends.
- **SQL (Structured Query Language):** SQL is particularly useful for working with large datasets and performing advanced queries. By storing geographic data in relational databases, SQL enables users to run complex queries that can analyze urbanization patterns, track regional development, or compare population growth across different districts in Portugal. SQL’s capabilities allow for more sophisticated geographic analysis, making it a powerful tool for urban planning and resource management.
- **JSON (JavaScript Object Notation):** JSON is a lightweight and flexible data format commonly used for web applications and real-time data systems. Offering geographic data in JSON allows developers to create interactive maps or dynamic platforms that present live geographic information about Portugal’s cities and regions. JSON is especially well-suited for applications that require frequent updates or allow users to interact with the data in real time.
- **XML (Extensible Markup Language):** XML is a versatile format used to organize and exchange complex data structures. It is ideal for storing hierarchical geographic information, such as administrative divisions, environmental factors, and infrastructure networks. XML’s structured format makes it easy to share and integrate geographic data across different platforms and research systems.
By making geographic data available in these flexible formats, Portugal’s geographic information can be easily accessed and used by a wide range of stakeholders, including government agencies, urban planners, researchers, and developers. This accessibility fosters collaboration and enhances the ability to make data-driven decisions.
A Comprehensive Geographic Database for Portugal
A comprehensive geographic database for Portugal should include detailed information on the cities, regions, and departments, as well as key geographic features such as rivers, mountains, and coastlines. This database is essential for understanding how geographic features influence urban development, transportation networks, and resource management across the country.
For example, comparing the urban development of Lisbon with smaller cities in rural regions like Beja or Castelo Branco can provide insights into the challenges and opportunities for regional development. A geographic database allows for the analysis of factors such as infrastructure needs, population distribution, and the relationship between urban centers and surrounding natural resources.
Providing this data in flexible formats like CSV, SQL, JSON, and XML ensures that it can be easily integrated into various systems for research, planning, and decision-making. Whether used for tracking regional growth, managing natural resources, or assessing the impact of environmental policies, this data provides the foundation for effective and sustainable development in Portugal.
Conclusion
Portugal’s rich geographical diversity, from its bustling urban centers to its remote rural regions, presents both opportunities and challenges for urban planning, environmental conservation, and resource management. By obtaining accurate geographic data on the cities, regions, and departments—including latitude and longitude coordinates—geographers, urban planners, and policymakers can gain valuable insights into the spatial dynamics of the country. Offering this data in accessible formats such as CSV, SQL, JSON, and XML ensures that it is adaptable and useful for a wide range of applications, from research and infrastructure development to environmental conservation and disaster management. A data-driven approach to understanding Portugal’s geography supports informed decision-making, fosters sustainable development, and helps guide the country toward a balanced and prosperous future.