Timor Leste Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 23 March 2026.
Here you’ll find a curated sample of 100 key cities from Timor Leste, each with essential data points such as latitude, longitude, administrative region, and other relevant attributes.
This preview is extracted from our full dataset, which includes a total of 3310 geographic locations across Timor Leste.
Whether you’re working on mapping, analytics, or app development, the data is available for both personal and commercial use.
All entries can be downloaded in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML.
Capital Highlight: The official capital city of Timor Leste is Dili.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1944669 | Pohei | TL | Ermera | Ermera Villa | -8.75722 | 125.42028 | 0 | Asia/Dili | populated place | ||
| 1943836 | Aisahe | TL | Viqueque | Viqueque | -8.96444 | 126.26889 | 0 | Asia/Dili | populated place | ||
| 1944964 | Loti | TL | Manufahi | Same | -9.08278 | 125.68917 | 0 | Asia/Dili | populated place | ||
| 1943220 | Leo | TL | Viqueque | Ossu | -8.6575 | 126.47056 | 0 | Asia/Dili | populated place | ||
| 1943178 | Matapati | TL | Aileu | Laulara | -8.64496 | 125.5741 | 0 | Asia/Dili | populated place | ||
| 1945543 | Sucairau | TL | Manufahi | Fatuberliu | -9.04667 | 125.9525 | 0 | Asia/Dili | populated place | ||
| 1943675 | Caraubalo | TL | Viqueque | Viqueque | -8.8725 | 126.37583 | 0 | Asia/Dili | populated place | ||
| 8630088 | Samaliu | TL | Viqueque | Ossu | -8.78333 | 126.38333 | 0 | Asia/Dili | populated place | ||
| 1944235 | Borolau | TL | Baucau | Laga | -8.48897 | 126.6468 | 0 | Asia/Dili | populated place | ||
| 1943070 | Tuhilu Craic | TL | Liquiçá | Bazartete | -8.63583 | 125.39528 | 0 | Asia/Dili | populated place | ||
| 8629842 | Baboi Leten | TL | Ermera | Atsabe | -8.90556 | 125.39639 | 0 | Asia/Dili | populated place | ||
| 1943342 | Uaimare | TL | Viqueque | Uatocarabau | -8.66583 | 126.66889 | 0 | Asia/Dili | populated place | ||
| 8714386 | Natarbora | TL | Manatuto | -9.10011 | 125.95036 | 0 | Asia/Dili | populated place | |||
| 1943760 | Tidibesse | TL | Ermera | Hatulia | -8.71306 | 125.34778 | 0 | Asia/Dili | populated place | ||
| 8643188 | Lore I | TL | Lautém | Lospalos | -8.64306 | 127.02 | 0 | Asia/Dili | populated place | ||
| 1944550 | Porema | TL | Ainaro | Ainaro | -8.98111 | 125.51861 | 0 | Asia/Dili | populated place | ||
| 1943814 | Bahafau | TL | Viqueque | Viqueque | -8.87611 | 126.36639 | 0 | Asia/Dili | populated place | ||
| 8629319 | Hatu-Builico | TL | Ainaro | Hatobuilico | -8.9 | 125.51667 | 0 | Asia/Dili | populated place | ||
| 8643674 | Ro-ulu | TL | Baucau | Baucau | -8.47061 | 126.41925 | 0 | Asia/Dili | populated place | ||
| 1945347 | Muapitine | TL | Lautém | Lospalos | -8.5 | 127.10083 | 0 | Asia/Dili | populated place | ||
| 8629924 | Bibileo | TL | Viqueque | Viqueque | -8.96667 | 126.26667 | 0 | Asia/Dili | populated place | ||
| 1943417 | Lisalara | TL | Liquiçá | Maubara | -8.64306 | 125.22694 | 0 | Asia/Dili | populated place | ||
| 1944663 | Hatolalan | TL | Manatuto | Laclubar | -8.74889 | 125.94111 | 0 | Asia/Dili | populated place | ||
| 1943126 | Aibutihun | TL | Aileu | Remexio | -8.67625 | 125.66898 | 0 | Asia/Dili | populated place | ||
| 8618045 | Taiboco | TL | Oecusse | Pante Makasar | -9.28333 | 124.33333 | 0 | Asia/Dili | populated place | ||
| 1943882 | Sulilako | TL | Bobonaro | Balibo | -8.92583 | 125.13111 | 0 | Asia/Dili | populated place | ||
| 8642869 | Suco Loro | TL | Cova Lima | Suai | -9.35 | 125.26667 | 0 | Asia/Dili | populated place | ||
| 1944167 | Tulaiduk | TL | Cova Lima | Tilomar | -9.3353 | 125.10434 | 0 | Asia/Dili | populated place | ||
| 8629862 | Iliomar I | TL | Lautém | Iliomar | -8.71522 | 126.89312 | 0 | Asia/Dili | populated place | ||
| 1942888 | Guruca | TL | Baucau | Quelicai | -8.54306 | 126.56472 | 0 | Asia/Dili | populated place | ||
| 1944064 | Sumlili | TL | Oecusse | Pante Makasar | -9.19554 | 124.38513 | 0 | Asia/Dili | populated place | ||
| 1943028 | Poalete | TL | Aileu | Aileu Villa | -8.72833 | 125.48333 | 0 | Asia/Dili | populated place | ||
| 8643778 | Genu Lai | TL | Bobonaro | Cailaco | -8.9 | 125.28333 | 0 | Asia/Dili | populated place | ||
| 1944858 | Puruqua | TL | Bobonaro | Bobonaro | -8.95778 | 125.32556 | 0 | Asia/Dili | populated place | ||
| 1945243 | Boropai | TL | Lautém | Iliomar | -8.70556 | 126.78917 | 0 | Asia/Dili | populated place | ||
| 11856537 | Manutane | TL | Aileu | Remexio | -8.57071 | 125.71859 | 0 | Asia/Dili | populated place | ||
| 1942528 | Lailaileso | Lailaileso,Lialaileso | TL | Baucau | Baucau | -8.44883 | 126.38821 | 0 | Asia/Dili | populated place | |
| 8200401 | Senaf | TL | Oecusse | Nitibe | -9.36196 | 124.29225 | 0 | Asia/Dili | populated place | ||
| 1944907 | Keorudu | TL | Ainaro | Hatobuilico | -8.89389 | 125.52278 | 0 | Asia/Dili | populated place | ||
| 1943628 | Lebuhai | TL | Liquiçá | Liquiçá | -8.66028 | 125.33583 | 0 | Asia/Dili | populated place | ||
| 1945233 | Tirilolo | TL | Lautém | Iliomar | -8.69694 | 126.81278 | 0 | Asia/Dili | populated place | ||
| 1943297 | Larigua | TL | Baucau | Baguia | -8.62639 | 126.63806 | 0 | Asia/Dili | populated place | ||
| 1943465 | Siamado | TL | Liquiçá | Maubara | -8.73694 | 125.2 | 0 | Asia/Dili | populated place | ||
| 1945044 | Lelemanu | TL | Ermera | Hatulia | -8.7975 | 125.33528 | 0 | Asia/Dili | populated place | ||
| 1943807 | Meuai | TL | Viqueque | Viqueque | -8.86028 | 126.35222 | 0 | Asia/Dili | populated place | ||
| 1944165 | Kotafoun | TL | Cova Lima | Tilomar | -9.34408 | 125.11956 | 0 | Asia/Dili | populated place | ||
| 8630037 | Mau-Ulo | TL | Ainaro | Ainaro | -9 | 125.48333 | 0 | Asia/Dili | populated place | ||
| 1944518 | Bambai | TL | Oecusse | Oesilo | -9.37833 | 124.33472 | 0 | Asia/Dili | populated place | ||
| 1943580 | Tautalo | TL | Liquiçá | Liquiçá | -8.63917 | 125.30889 | 0 | Asia/Dili | populated place | ||
| 1944676 | Kartolo | TL | Ainaro | Maubisse | -8.8675 | 125.56944 | 0 | Asia/Dili | populated place | ||
| 1943325 | Docoate | TL | Viqueque | Uatolari | -8.70417 | 126.63444 | 0 | Asia/Dili | populated place | ||
| 1942999 | Luarai | TL | Lautém | Lospalos | -8.43083 | 127.03417 | 0 | Asia/Dili | populated place | ||
| 1943839 | Fatuhosa | TL | Viqueque | Viqueque | -8.96556 | 126.27083 | 0 | Asia/Dili | populated place | ||
| 1945522 | Lale | TL | Ainaro | Hato-Udo | -9.12583 | 125.65944 | 0 | Asia/Dili | populated place | ||
| 8644075 | Fatuwaque | TL | Manatuto | Barique | -8.97167 | 126.05889 | 0 | Asia/Dili | populated place | ||
| 1944043 | Beko | TL | Cova Lima | Fatululik | -9.18861 | 125.13889 | 0 | Asia/Dili | populated place | ||
| 1943373 | Vatunau | TL | Liquiçá | Maubara | -8.60417 | 125.28972 | 0 | Asia/Dili | populated place | ||
| 1943980 | Lakonalbabu | TL | Cova Lima | Suai | -9.33722 | 125.20639 | 0 | Asia/Dili | populated place | ||
| 1944793 | Leulara | TL | Ermera | Atsabe | -8.88056 | 125.38278 | 0 | Asia/Dili | populated place | ||
| 1942965 | Laherubi | TL | Baucau | Baucau | -8.51278 | 126.47417 | 0 | Asia/Dili | populated place | ||
| 1945231 | Lourba | TL | Bobonaro | Bobonaro | -9.01583 | 125.355 | 0 | Asia/Dili | populated place | ||
| 1943263 | Borolalo | TL | Viqueque | Uatolari | -8.79194 | 126.55944 | 0 | Asia/Dili | populated place | ||
| 1942840 | Pairara | TL | Lautém | Lautem | -8.37972 | 126.92056 | 0 | Asia/Dili | populated place | ||
| 8629853 | Coilate-Letelo | TL | Ermera | Hatulia | -8.83167 | 125.37278 | 0 | Asia/Dili | populated place | ||
| 1942796 | Eduquele | TL | Baucau | Quelicai | -8.61722 | 126.52194 | 0 | Asia/Dili | populated place | ||
| 8644032 | Natarae | TL | Liquiçá | Bazartete | -8.65 | 125.36667 | 0 | Asia/Dili | populated place | ||
| 1942338 | Kaitcho | TL | Liquiçá | Bazartete | -8.56611 | 125.42583 | 0 | Asia/Dili | populated place | ||
| 1945379 | Ulturo | TL | Lautém | Lautem | -8.50583 | 126.83389 | 0 | Asia/Dili | populated place | ||
| 1944843 | Mauchiga | TL | Ainaro | Hatobuilico | -8.935 | 125.57111 | 0 | Asia/Dili | populated place | ||
| 1943014 | Serelau | TL | Lautém | Lautem | -8.43861 | 126.85417 | 0 | Asia/Dili | populated place | ||
| 1944187 | Nanu | TL | Cova Lima | Fatumean | -9.27233 | 125.03241 | 0 | Asia/Dili | populated place | ||
| 1943897 | Harema | TL | Bobonaro | Cailaco | -8.88722 | 125.22833 | 0 | Asia/Dili | populated place | ||
| 1945637 | Fohonaro | TL | Manufahi | Turiscai | -8.83278 | 125.72722 | 0 | Asia/Dili | populated place | ||
| 1942652 | Aidabahare | TL | DÃli | Cristo Rei | -8.57032 | 125.62845 | 0 | Asia/Dili | populated place | ||
| 1946061 | Loilari | TL | Baucau | Laga | -8.55028 | 126.69722 | 0 | Asia/Dili | populated place | ||
| 1942891 | Maebu | TL | Baucau | Quelicai | -8.52639 | 126.5775 | 0 | Asia/Dili | populated place | ||
| 1943997 | Megir | TL | Bobonaro | Atabae | -8.86778 | 125.04361 | 0 | Asia/Dili | populated place | ||
| 1943018 | Barleo | TL | Lautém | -8.42083 | 126.76167 | 0 | Asia/Dili | populated place | |||
| 1943522 | Uluisi | TL | Baucau | Quelicai | -8.63889 | 126.5325 | 0 | Asia/Dili | populated place | ||
| 1943871 | Maleteten | TL | Bobonaro | Atabae | -8.81444 | 125.18111 | 0 | Asia/Dili | populated place | ||
| 1943657 | Aimalai | TL | Bobonaro | Balibo | -8.88111 | 125.03139 | 0 | Asia/Dili | populated place | ||
| 8644031 | Caileulema | TL | Liquiçá | Bazartete | -8.63333 | 125.36667 | 0 | Asia/Dili | populated place | ||
| 1942315 | Rauhassa | TL | Liquiçá | Bazartete | -8.57028 | 125.38167 | 0 | Asia/Dili | populated place | ||
| 1945584 | Tesigele | TL | Bobonaro | Lolotoe | -9.14056 | 125.2925 | 0 | Asia/Dili | populated place | ||
| 1946095 | Samagata | TL | Baucau | Laga | -8.55861 | 126.69778 | 0 | Asia/Dili | populated place | ||
| 8643578 | Uma Rentau | TL | Manatuto | Laleia | -8.53206 | 126.16207 | 0 | Asia/Dili | populated place | ||
| 1944869 | Hatoquero | TL | Ainaro | Hatobuilico | -8.92944 | 125.58056 | 0 | Asia/Dili | populated place | ||
| 1944169 | Palaban | TL | Oecusse | Pante Makasar | -9.20331 | 124.34516 | 0 | Asia/Dili | populated place | ||
| 8629063 | Holsa | TL | Bobonaro | Maliana | -8.9975 | 125.21944 | 0 | Asia/Dili | populated place | ||
| 1943632 | Raihun | TL | Bobonaro | Balibo | -8.97722 | 125.05194 | 0 | Asia/Dili | populated place | ||
| 1944070 | Soin | TL | Oecusse | Pante Makasar | -9.175 | 124.41167 | 0 | Asia/Dili | populated place | ||
| 1943640 | Manufatia | TL | Liquiçá | Liquiçá | -8.66472 | 125.35833 | 0 | Asia/Dili | populated place | ||
| 1943315 | Caiualita | TL | Viqueque | Uatocarabau | -8.65667 | 126.62861 | 0 | Asia/Dili | populated place | ||
| 1945343 | Muapitine | TL | Lautém | Lospalos | -8.51111 | 127.12333 | 0 | Asia/Dili | populated place | ||
| 1943496 | Irabinleteria | TL | Viqueque | Uatocarabau | -8.74722 | 126.70222 | 0 | Asia/Dili | populated place | ||
| 1943456 | Dato | TL | Liquiçá | Liquiçá | -8.595 | 125.32778 | 0 | Asia/Dili | populated place | ||
| 1945412 | Charano | TL | Lautém | Lospalos | -8.59472 | 126.88889 | 0 | Asia/Dili | populated place | ||
| 1945026 | Poerema | TL | Ermera | Hatulia | -8.80333 | 125.3275 | 0 | Asia/Dili | populated place | ||
| 8644078 | Builale | TL | Viqueque | Ossu | -8.67494 | 126.37072 | 0 | Asia/Dili | populated place | ||
| 1943681 | Kailatulale | TL | Viqueque | Ossu | -8.78167 | 126.37806 | 0 | Asia/Dili | populated place |
Timor-Leste: Exploring the Geographic Essence of a Young Nation
Timor-Leste, a country marked by its resilience and rich cultural tapestry, presents a fascinating study for any geographer passionate about the intricate relationship between land and identity. Nestled in Southeast Asia, this island nation’s geography is a complex mosaic of rugged mountains, coastal plains, and diverse settlements that paint a vivid picture of both natural beauty and human adaptation.
Delving into Timor-Leste’s Urban and Regional Composition
The geographic identity of Timor-Leste is deeply tied to its towns and cities, each embedded within distinct regions and administrative departments. Understanding these divisions is vital to grasping how local governance, resource management, and cultural dynamics interplay. This spatial framework offers an invaluable context for policymakers, development experts, and researchers aiming to foster sustainable growth that respects the country’s unique landscape.
Access to detailed datasets listing cities along with their corresponding regions and departments opens the door to a deeper comprehension of Timor-Leste’s developmental geography.
The Importance of Latitude and Longitude in Mapping Timor-Leste
Precise geographic coordinates—latitude and longitude—are crucial in capturing the exact position of every city across Timor-Leste’s varied terrain. From the capital Dili’s vibrant coastal hub to the remote mountain communities, these data points allow for nuanced spatial analyses. They empower stakeholders in disaster risk management, infrastructure planning, environmental protection, and tourism development to make informed decisions grounded in geographic reality.
Excel Format: Empowering Access and Usability
While geographic data traditionally lives in formats like CSV, SQL, JSON, and XML—often reserved for technical users—the inclusion of the Excel (.xlsx) format dramatically increases accessibility. Excel’s familiar, user-friendly interface enables a broad spectrum of users to explore and manipulate city data with ease, enhancing the practical utility of geographic information for diverse applications.
This step bridges the gap between complex datasets and their everyday use by government officials, NGOs, and educators.
What Our Timor-Leste Database Offers
* Comprehensive city data tied to their specific regions and administrative departments
* Accurate latitude and longitude coordinates for reliable spatial referencing
* Multiple downloadable formats, with a special emphasis on Excel (.xlsx) for ease of use
Harnessing Geographic Data for Timor-Leste’s Future
In a nation where geography shapes livelihoods and culture, having access to detailed, structured data on its cities and regions is more than an academic pursuit—it is a catalyst for progress. Leveraging this information can facilitate smarter urban planning, resilient infrastructure development, and effective environmental stewardship that honors Timor-Leste’s rich natural heritage.
A Call to Explore and Understand
For geographers and data enthusiasts alike, Timor-Leste offers a compelling landscape that invites exploration beyond the surface. The availability of this meticulously organized data—especially in the accessible Excel format—provides a unique opportunity to engage with the country’s geographic narrative, supporting endeavors that contribute to its vibrant future.
