Timor Leste cities list with latitude and longitude in Excel, CSV, XML, SQL, JSON formats
Last update : 05 December 2025.
Below is a list of 100 prominent cities in Timor Leste. Each row includes a city's latitude, longitude, region and other variables of interest. This is a subset of all 3310 places in Timor Leste 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 Timor Leste is Dili.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1944746 | Lelobere | TL | Ermera | Atsabe | -8.91222 | 125.40389 | 0 | Asia/Dili | populated place | ||
| 1944812 | Talite | TL | Bobonaro | Bobonaro | -8.99194 | 125.33111 | 0 | Asia/Dili | populated place | ||
| 1944700 | Manonia | TL | Bobonaro | Bobonaro | -8.9875 | 125.38583 | 0 | Asia/Dili | populated place | ||
| 1944791 | Ramiah | TL | Ermera | Atsabe | -8.88917 | 125.37611 | 0 | Asia/Dili | populated place | ||
| 1945225 | Rumotau | TL | Lautém | Iliomar | -8.69861 | 126.86194 | 0 | Asia/Dili | populated place | ||
| 1945468 | Vailana | TL | Lautém | Lospalos | -8.64722 | 127.02111 | 0 | Asia/Dili | populated place | ||
| 8643817 | Lakonak | TL | Cova Lima | Suai | -9.33333 | 125.2 | 0 | Asia/Dili | populated place | ||
| 1944882 | Tatiri Baru | TL | Ainaro | Hatobuilico | -8.92 | 125.57528 | 0 | Asia/Dili | populated place | ||
| 1945157 | Jimelai | TL | Bobonaro | Bobonaro | -9.08139 | 125.26444 | 0 | Asia/Dili | populated place | ||
| 1943648 | Dualanok | TL | Bobonaro | Balibo | -8.91306 | 125.09139 | 0 | Asia/Dili | populated place | ||
| 1943276 | Cucodere | TL | Viqueque | Uatolari | -8.77528 | 126.61111 | 0 | Asia/Dili | populated place | ||
| 1944861 | Hatomalos | TL | Manatuto | Laclubar | -8.74639 | 125.93528 | 0 | Asia/Dili | populated place | ||
| 1943496 | Irabinleteria | TL | Viqueque | Uatocarabau | -8.74722 | 126.70222 | 0 | Asia/Dili | populated place | ||
| 1942865 | Aimetahun | TL | Viqueque | Lacluta | -8.84389 | 126.20389 | 0 | Asia/Dili | populated place | ||
| 1945034 | Likitura | TL | Aileu | Aileu Villa | -8.81611 | 125.59972 | 0 | Asia/Dili | populated place | ||
| 1943876 | Limanaro | TL | Bobonaro | Atabae | -8.79306 | 125.14556 | 0 | Asia/Dili | populated place | ||
| 1945538 | Nobularan | TL | Manufahi | Alas | -9.05556 | 125.87722 | 0 | Asia/Dili | populated place | ||
| 1943596 | Ulolaco | TL | Baucau | Baguia | -8.66972 | 126.61528 | 0 | Asia/Dili | populated place | ||
| 1937249 | Audian | TL | Cova Lima | Suai | -9.32754 | 125.28154 | 0 | Asia/Dili | populated place | ||
| 1942812 | Reissoro | TL | Lautém | Lospalos | -8.49806 | 126.96278 | 0 | Asia/Dili | populated place | ||
| 1942810 | Gombei | TL | Ermera | Ermera Villa | -8.73278 | 125.43417 | 0 | Asia/Dili | populated place | ||
| 1944101 | Kanete | TL | Oecusse | Pante Makasar | -9.23694 | 124.35278 | 0 | Asia/Dili | populated place | ||
| 1944086 | Najalu | TL | Oecusse | Pante Makasar | -9.22278 | 124.27806 | 0 | Asia/Dili | populated place | ||
| 1942638 | Fatumanaro | TL | Aileu | Remexio | -8.61776 | 125.66627 | 0 | Asia/Dili | populated place | ||
| 1945246 | Tebabui | TL | Bobonaro | Bobonaro | -9.01215 | 125.37551 | 0 | Asia/Dili | populated place | ||
| 1945197 | Maucugun | TL | Bobonaro | Bobonaro | -9.05223 | 125.34537 | 0 | Asia/Dili | populated place | ||
| 1944677 | Manosahe | TL | Ainaro | Maubisse | -8.86917 | 125.59583 | 0 | Asia/Dili | populated place | ||
| 1944778 | Raebou | TL | Ermera | Letefoho | -8.88583 | 125.4125 | 0 | Asia/Dili | populated place | ||
| 1945202 | Mausama | TL | Bobonaro | Bobonaro | -9.04018 | 125.31133 | 0 | Asia/Dili | populated place | ||
| 1945200 | Dena | TL | Bobonaro | Bobonaro | -9.04639 | 125.34361 | 0 | Asia/Dili | populated place | ||
| 1944760 | Katraikraik | Catrai Craic,Katraikraik | TL | Ermera | Letefoho | -8.88917 | 125.44 | 0 | Asia/Dili | populated place | |
| 8714386 | Natarbora | TL | Manatuto | -9.10011 | 125.95036 | 0 | Asia/Dili | populated place | |||
| 1942862 | Mauama | TL | Viqueque | Lacluta | -8.84167 | 126.20833 | 0 | Asia/Dili | populated place | ||
| 8629289 | Cowa | TL | Bobonaro | Balibo | -9.04243 | 124.98116 | 0 | Asia/Dili | populated place | ||
| 1942689 | Berukulun | TL | Díli | Cristo Rei | -8.54714 | 125.67183 | 0 | Asia/Dili | populated place | ||
| 1944992 | Narlolo | TL | Ermera | Hatulia | -8.81778 | 125.34722 | 0 | Asia/Dili | populated place | ||
| 1943730 | Kakamata | TL | Bobonaro | Atabae | -8.77111 | 125.20111 | 0 | Asia/Dili | populated place | ||
| 1942486 | Luliheni | TL | Baucau | Baucau | -8.48833 | 126.3475 | 0 | Asia/Dili | populated place | ||
| 8629253 | Lahane Ocidental | TL | Díli | Vera Cruz | -8.57848 | 125.58172 | 0 | Asia/Dili | populated place | ||
| 1945226 | Malilait | TL | Bobonaro | Bobonaro | -9.02909 | 125.32125 | 0 | Asia/Dili | populated place | ||
| 1944835 | Atolara | TL | Bobonaro | Bobonaro | -8.99139 | 125.37222 | 0 | Asia/Dili | populated place | ||
| 1942912 | Maukiki | TL | Baucau | Quelicai | -8.59083 | 126.60306 | 0 | Asia/Dili | populated place | ||
| 1945142 | Holmeser | TL | Bobonaro | Bobonaro | -9.09138 | 125.34181 | 0 | Asia/Dili | populated place | ||
| 8618045 | Taiboco | TL | Oecusse | Pante Makasar | -9.28333 | 124.33333 | 0 | Asia/Dili | populated place | ||
| 1945600 | Manikin | TL | Cova Lima | Suai | -9.31778 | 125.27972 | 0 | Asia/Dili | populated place | ||
| 1942327 | Caidenulale | TL | Baucau | Vemasse | -8.58694 | 126.33722 | 0 | Asia/Dili | populated place | ||
| 1943734 | Caicassico | TL | Liquiçá | Liquiçá | -8.68639 | 125.34639 | 0 | Asia/Dili | populated place | ||
| 1945319 | Kampungcina | TL | Lautém | Lospalos | -8.5225 | 126.99972 | 0 | Asia/Dili | populated place | ||
| 1945002 | Nunufu | TL | Manufahi | Same | -9.02 | 125.64444 | 0 | Asia/Dili | populated place | ||
| 1944910 | Lientuto | TL | Ainaro | Maubisse | -8.885 | 125.60611 | 0 | Asia/Dili | populated place | ||
| 1945173 | Binani | TL | Manufahi | Turiscai | -8.88944 | 125.71528 | 0 | Asia/Dili | populated place | ||
| 1944505 | Ukbatan | TL | Oecusse | Oesilo | -9.39639 | 124.36 | 0 | Asia/Dili | populated place | ||
| 8643187 | Laline | TL | Viqueque | Lacluta | -8.83444 | 126.2075 | 0 | Asia/Dili | populated place | ||
| 1944411 | Baqui | TL | Oecusse | Pante Makasar | -9.28333 | 124.35111 | 0 | Asia/Dili | populated place | ||
| 1944461 | Meta | TL | Oecusse | Passabe | -9.455 | 124.33694 | 0 | Asia/Dili | populated place | ||
| 8629499 | Uma Boot | Uma Boot (West) | TL | Viqueque | Viqueque | -8.94975 | 126.19761 | 0 | Asia/Dili | populated place | |
| 1943411 | Lakmade | TL | Liquiçá | Maubara | -8.64167 | 125.20389 | 0 | Asia/Dili | populated place | ||
| 1943604 | Afaloicai | TL | Baucau | Baguia | -8.65778 | 126.61 | 0 | Asia/Dili | populated place | ||
| 1944963 | Babulu | TL | Manufahi | Same | -9.08861 | 125.68861 | 0 | Asia/Dili | populated place | ||
| 1944838 | Tuquetin | TL | Manatuto | Manatuto | -8.67611 | 125.99056 | 0 | Asia/Dili | populated place | ||
| 1944141 | Ilinamu | TL | Díli | Atauro Island | -8.19667 | 125.625 | 0 | Asia/Dili | populated place | ||
| 1944214 | Uthautfoo | TL | Oecusse | Nitibe | -9.28333 | 124.17222 | 0 | Asia/Dili | populated place | ||
| 8629121 | Loidahar | TL | Liquiçá | Liquiçá | -8.6 | 125.33333 | 0 | Asia/Dili | populated place | ||
| 1945290 | Maliseran | TL | Cova Lima | Zumalai | -9.16556 | 125.44306 | 0 | Asia/Dili | populated place | ||
| 1944680 | Lauhili | TL | Ainaro | Maubisse | -8.86389 | 125.585 | 0 | Asia/Dili | populated place | ||
| 1943553 | Oehoso | TL | Oecusse | Nitibe | -9.34804 | 124.08317 | 0 | Asia/Dili | populated place | ||
| 1942517 | Fatunaba | Fatonaba,Fatunaba | TL | Díli | Vera Cruz | -8.59461 | 125.57916 | 0 | Asia/Dili | populated place | |
| 1942454 | Uaicuha | TL | Baucau | Baucau | -8.46911 | 126.29392 | 0 | Asia/Dili | populated place | ||
| 1942369 | Libaulelo | TL | Liquiçá | Bazartete | -8.57 | 125.49222 | 0 | Asia/Dili | populated place | ||
| 8643421 | Boklelo | TL | Aileu | Laulara | -8.62 | 125.53 | 0 | Asia/Dili | populated place | ||
| 1945274 | Baordaikun | TL | Cova Lima | Zumalai | -9.20013 | 125.41239 | 0 | Asia/Dili | populated place | ||
| 1635225 | Maubisse | Mau-Bessi,Maubesse,Maubisse,Mindelo | TL | Manufahi | Turiscai | -8.89389 | 125.70444 | 0 | Asia/Dili | populated place | |
| 8643549 | Lepa | TL | Liquiçá | Liquiçá | -8.70117 | 125.29094 | 0 | Asia/Dili | populated place | ||
| 1942891 | Maebu | TL | Baucau | Quelicai | -8.52639 | 126.5775 | 0 | Asia/Dili | populated place | ||
| 1943620 | Kribasbarique | TL | Manatuto | Barique | -8.84639 | 126.06194 | 0 | Asia/Dili | populated place | ||
| 8630106 | Macadique | TL | Viqueque | Uatolari | -8.84917 | 126.51333 | 0 | Asia/Dili | populated place | ||
| 1944502 | Binau | TL | Oecusse | Oesilo | -9.41111 | 124.35583 | 0 | Asia/Dili | populated place | ||
| 1637023 | Luro | Luro | TL | Lautém | Luro | -8.51028 | 126.83389 | 0 | Asia/Dili | populated place | |
| 1943486 | Uatobita | TL | Viqueque | Uatocarabau | -8.69722 | 126.71111 | 0 | Asia/Dili | populated place | ||
| 1942356 | Macadaicima | TL | Baucau | Baucau | -8.51167 | 126.35639 | 0 | Asia/Dili | populated place | ||
| 1943460 | Lepalaka | TL | Liquiçá | Maubara | -8.73167 | 125.13639 | 0 | Asia/Dili | populated place | ||
| 1943030 | Halalmeta | TL | Aileu | Aileu Villa | -8.71833 | 125.49056 | 0 | Asia/Dili | populated place | ||
| 1622481 | Vemasse | Vemasse | TL | Baucau | Vemasse | -8.51056 | 126.21056 | 0 | Asia/Dili | populated place | |
| 1937245 | Loo | TL | Cova Lima | Suai | -9.34833 | 125.27655 | 0 | Asia/Dili | populated place | ||
| 1944745 | Lauabe | TL | Ermera | Atsabe | -8.91083 | 125.39889 | 0 | Asia/Dili | populated place | ||
| 1944993 | Babulu | TL | Manufahi | Same | -9.02361 | 125.65611 | 0 | Asia/Dili | populated place | ||
| 8629042 | Lour | TL | Bobonaro | Bobonaro | -9.07091 | 125.35812 | 0 | Asia/Dili | populated place | ||
| 8629065 | Hauba | TL | Bobonaro | Bobonaro | -8.99222 | 125.38704 | 0 | Asia/Dili | populated place | ||
| 1943150 | Sidole | TL | Aileu | Aileu Villa | -8.72071 | 125.58773 | 0 | Asia/Dili | populated place | ||
| 1943338 | Assafadae | TL | Viqueque | Uatocarabau | -8.68389 | 126.69778 | 0 | Asia/Dili | populated place | ||
| 1946110 | Uarau | TL | Baucau | Baguia | -8.59111 | 126.69361 | 0 | Asia/Dili | populated place | ||
| 1942335 | Nunoti | TL | Baucau | Vemasse | -8.57028 | 126.33722 | 0 | Asia/Dili | populated place | ||
| 8630002 | Palimano | TL | Ermera | Railaco | -8.71667 | 125.45 | 0 | Asia/Dili | populated place | ||
| 1944776 | Hohulu | TL | Ermera | Letefoho | -8.88444 | 125.41778 | 0 | Asia/Dili | populated place | ||
| 1942956 | Afacaimau | TL | Baucau | Baucau | -8.52639 | 126.43333 | 0 | Asia/Dili | populated place | ||
| 1944396 | Kuangkot | TL | Oecusse | Pante Makasar | -9.28889 | 124.29361 | 0 | Asia/Dili | populated place | ||
| 1942839 | Kaporo | TL | Lautém | Lautem | -8.39167 | 126.91389 | 0 | Asia/Dili | populated place | ||
| 1943905 | Samelau | TL | Bobonaro | Maliana | -8.95972 | 125.21444 | 0 | Asia/Dili | populated place | ||
| 1944942 | Railuli | TL | Ermera | Hatulia | -8.88444 | 125.33889 | 0 | Asia/Dili | populated place | ||
| 1945154 | Pugu | TL | Bobonaro | Bobonaro | -9.08444 | 125.26889 | 0 | Asia/Dili | populated place |
**Exploring Timor-Leste: A Geographer's Perspective**
Nestled in the southeastern corner of Asia, Timor-Leste is a nation of rugged beauty, cultural diversity, and historical significance. As a geographer delving into the complexities of this young nation, the pursuit of data on its cities, regions, and geographical coordinates unveils a narrative of resilience, exploration, and geographical significance waiting to be unraveled.
Cities of Timor-Leste: Nuclei of Culture and Progress**
Timor-Leste's cities are not just urban centers but vibrant expressions of the country's cultural heritage and developmental aspirations. From the coastal capital of Dili to the historic town of Baucau and the picturesque enclave of Same, each urban hub embodies a unique blend of tradition and modernity. Gathering data on these cities provides insights into their demographic composition, economic activities, and infrastructural development, which are crucial for understanding the dynamics of contemporary Timor-Leste.
Regions and Districts of Timor-Leste: Exploring the Country's Ecological Tapestry**
Beyond the urban landscape, Timor-Leste's regions and districts showcase the diversity of its natural landscapes and ecological riches. From the rugged mountains of Ainaro to the lush forests of Lautem and the pristine beaches of Oecusse, each region boasts its own unique biodiversity and cultural heritage. Obtaining data on these regions sheds light on their environmental resources, conservation efforts, and sustainable development initiatives aimed at preserving Timor-Leste's natural heritage for future generations.
Latitude and Longitude of Timor-Leste: Navigating the Country's Coordinates**
As a geographer, obtaining precise latitude and longitude data for each city of Timor-Leste is essential for understanding its geographical layout and spatial distribution. These coordinates serve as navigational markers, guiding explorers through the country's diverse terrain and maritime boundaries. From the rugged cliffs of Atauro Island to the winding rivers of Bobonaro and the remote villages of Lautém, each point on the map tells a story of geographical significance and cultural heritage, shaping Timor-Leste's identity as a nation of resilience and exploration.
Conclusion: Mapping Timor-Leste's Geographical Legacy**
In the pursuit of data on Timor-Leste's cities, regions, and geographical coordinates, a deeper narrative emerges—one of diversity, resilience, and geographical significance. It is a narrative that celebrates the intrinsic connection between the Timorese people and their natural surroundings, reflecting a profound respect for the land and its resources. As a geographer, unraveling this tapestry of geographical intricacies is not just a scholarly pursuit but a journey of discovery and appreciation for the wonders of our planet.
Timor-Leste beckons—a land of endless exploration, waiting to be understood, cherished, and celebrated for its geographical marvels and cultural treasures.

Download data files for Timor Leste's cities in Excel (.xlsx), CSV, SQL, XML and JSON formats
Understanding the Geography of Timor-Leste: The Power of Geographic Data in Shaping Future Growth
Timor-Leste, located in Southeast Asia, is a nation with a unique geographical makeup, rich history, and strategic position in the Timor Sea. As a small island country, it faces both opportunities and challenges tied to its geography, ranging from its rugged mountainous terrain to its extensive coastline. For geographers, urban planners, and policymakers, accurate geographic data is crucial for sustainable development, resource management, and environmental protection. This article explores the geography of Timor-Leste, emphasizing the critical role geographic data plays in supporting the nation’s long-term planning and growth.
Timor-Leste’s Geographical Landscape: Mountains, Coastlines, and Biodiversity
Timor-Leste is situated on the eastern half of the island of Timor, with its western portion belonging to Indonesia. The country’s geography is defined by its mountainous interior, which accounts for much of the landscape, and its coastline, which stretches along the Timor Sea and the Banda Sea. The country’s unique topography has significant implications for its climate, agriculture, and settlement patterns.
The rugged mountains of Timor-Leste are home to diverse ecosystems, with lush forests and steep valleys. These areas are vital for water catchment and biodiversity conservation but present challenges for infrastructure development and population settlement. The highlands are less densely populated, and many of the country’s rural communities rely on subsistence agriculture, often in remote and difficult-to-access areas.
On the other hand, the coastal regions of Timor-Leste, which feature a combination of pristine beaches, cliffs, and fishing villages, are home to a larger portion of the population. The coasts are essential for the country's fishing industry, which contributes significantly to the economy. Additionally, these areas have been developed for tourism, with Timor-Leste’s natural beauty, including coral reefs and marine life, becoming a major attraction for international visitors.
The country’s biodiversity, which ranges from tropical rainforests to marine ecosystems, is a significant asset but also requires careful management. Timor-Leste's landscapes provide the country with various natural resources that are crucial for agriculture, energy, and tourism, making geographic data a valuable tool for understanding how to best manage these resources for long-term sustainability.
Administrative Divisions and Urban Centers in Timor-Leste
Timor-Leste is divided into 13 administrative districts, which serve as the primary governance units for the country. Each district is further divided into sub-districts and villages, with a focus on decentralizing power to local governments to ensure equitable development across the nation. Dili, the capital and largest city, is located on the northern coast, and it is the political, economic, and cultural center of the country.
Dili is home to the central government and many international organizations. It is also the hub for trade, services, and infrastructure development. The city has seen rapid growth in recent years, partly due to its central role in government and international aid, which presents challenges related to urbanization, infrastructure demand, and resource distribution.
Other major cities and towns, such as Baucau, the second-largest city in the country, and Maliana, serve as regional centers for trade and services. While Dili remains the focal point for economic activity, the surrounding regions, including the districts of Aileu and Ermera, are essential for agricultural production, with rural communities largely relying on subsistence farming and small-scale commercial agriculture.
Timor-Leste’s geography, with its uneven distribution of population and resources, requires data-driven approaches to manage the disparities between urban and rural areas, especially in terms of infrastructure, education, and healthcare access.
The Importance of Geographic Data for Timor-Leste’s Development
In a country like Timor-Leste, where the landscape is diverse and infrastructure is still developing, geographic data is essential for shaping effective development strategies. Geographic data allows for the mapping and analysis of urban growth, natural resource distribution, and environmental conditions. This data enables policymakers to plan strategically, ensuring that resources are allocated effectively and that sustainable practices are incorporated into development projects.
Latitude and longitude data for cities and regions in Timor-Leste are vital for creating accurate maps, which can be used to guide planning for infrastructure, agriculture, and urban development. Geographic data allows for spatial analysis, helping to identify areas of need, including underserved regions that require more access to services and facilities.
Data in formats like CSV, SQL, JSON, and XML are key to integrating geographic information into geographic information systems (GIS), where spatial data can be analyzed, visualized, and shared. These formats allow for the efficient processing of large datasets, enabling better decision-making and collaboration among government bodies, international partners, and local communities.
Practical Applications of Geographic Data in Timor-Leste
The practical applications of geographic data in Timor-Leste span various sectors, from urban development and agriculture to environmental management and disaster preparedness. The accurate use of geographic data is crucial for tackling some of the country’s most pressing challenges, including managing resources, planning for future growth, and responding to natural disasters.
1. **Urban and Infrastructure Planning**: As Timor-Leste continues to urbanize, especially in cities like Dili, geographic data plays an essential role in planning for sustainable infrastructure. By understanding where population growth is concentrated and where infrastructure gaps exist, planners can design efficient systems for transportation, waste management, water supply, and electricity. Geographic data also helps identify flood-prone areas, ensuring that infrastructure is built to withstand environmental challenges.
2. **Agricultural Development and Resource Management**: Agriculture is a vital sector in Timor-Leste, with most of the population relying on farming for their livelihoods. Geographic data is instrumental in understanding land suitability, water resources, and climate patterns, which is critical for improving agricultural productivity. GIS tools can assist in optimizing land use for crops such as rice, maize, and vegetables, while also helping to monitor soil health and manage irrigation systems more effectively.
3. **Environmental Conservation**: With its rich biodiversity and natural resources, Timor-Leste faces the challenge of balancing development with environmental conservation. Geographic data is crucial for tracking deforestation, protecting wildlife habitats, and managing marine ecosystems. By using spatial data, conservationists can monitor changes in land use, identify areas at risk of environmental degradation, and develop strategies to protect the country’s natural heritage.
4. **Disaster Preparedness and Climate Change Adaptation**: Timor-Leste is prone to natural disasters, including earthquakes, tsunamis, and flooding, particularly in coastal areas. Geographic data plays a crucial role in disaster risk management by identifying high-risk zones, planning evacuation routes, and optimizing emergency response strategies. It also helps in modeling the impacts of climate change, enabling the government to prepare for rising sea levels, altered rainfall patterns, and extreme weather events.
Leveraging Geographic Data for Timor-Leste’s Future Growth
Timor-Leste’s development relies on harnessing the full potential of geographic data to inform decision-making, manage resources, and ensure the sustainability of both urban and rural areas. By obtaining geographic data for cities, regions, and departments, the country can better plan for the future, prioritize infrastructure projects, and allocate resources effectively.
Data in formats such as CSV, SQL, JSON, and XML allows for easy sharing and integration, ensuring that stakeholders from different sectors, including government agencies, development organizations, and local communities, can collaborate and make data-driven decisions. These formats enable the use of GIS tools, making geographic information accessible for a wide range of applications and analyses.
Conclusion
Timor-Leste’s diverse and complex geography presents both opportunities and challenges for sustainable development. By obtaining and utilizing accurate geographic data, Timor-Leste can ensure that its development is inclusive, efficient, and resilient to future challenges. Geographic data, in formats such as CSV, SQL, JSON, and XML, provides the tools necessary for informed decision-making in urban planning, agriculture, environmental conservation, and disaster management. As Timor-Leste continues to grow and modernize, the use of geographic data will be crucial in shaping a prosperous and sustainable future.