Colombia GIS data

Shapefiles and data of the Information Management Toolbox from Chocó

El siguiente mapa ilustra el recorrido de las observaciones directas colectadas en campo por el equipo UNDAC en apoyo a la emergencia provocada por el derrame de petróleo producido el 2 de marzo de 2018 por el pozo Lizama 158 (propiedad Ecopetrol), a lo de la quebrada Lizama y Caño Muerto hasta su confluencia con el rio Sogamoso, en Barrancabermeja, Colombia. Dichas observaciones fueron tomadas durante los días 15 y 18 de abril 2018 utilizando la aplicación UN-ASIGN que permite colectar fotos georreferenciadas y su información asociada desde el terreno. UNOSAT en apoyo al equipo UNDAC, ha integrado dicha información que incluye por un lado la localización y distribución espacial de los distintos puntos de control visitados - visibles en el mapa de referencia – y a su vez las distintas fotos tomadas en terreno durante fichas visitas de control. Por favor, envíen sus comentarios a UNITAR-UNOSAT.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

This map illustrates areas potentially affected by the mudflow, extracted from a Pleiades and GeoEye-1 satellite images acquired on the 10 April 2017 over Mocoa city and its outskirts, in Putumayo Department, Colombia. Inside some neighbourhoods of the city of Mocoa, flood waters and mudflow have receded compared with previous analysis performed by UNOSAT using an image from 4 April 2017. The situation as of 10 April 2017 reveals: 22 km of roads seem potentially affected and about 1,300 buildings are within areas which are still experiencing floods and mud flow. It is likely that flood waters and mudflow could have been systematically under or overestimated along highly vegetated areas and within built-up urban areas. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Posterior al deslizamiento de tierra que sembró el caos en la ciudad de Mocoa (Departamento de Putumayo, Colombia) el 31 de marzo de 2017 como consecuencia de las fuertes lluvias, el International Charter Space & Major Disasters fue activado bajo la petición de la Unidad Nacional para la Gestión del Riesgo de Desastres, IDEAM. En respuesta a la emergencia, UNITAR-UNOSAT ha llevado a cabo análisis visible de daño en las edificaciones causado por el deslizamiento de tierra, usando imágenes satelitales de alta resolución. Este mapa ilustra edificaciones dañadas detectadas en imágenes satelitales y la densidad de daño asociada en la ciudad de Mocoa y sus alrededores. El análisis ha sido conducido utilizando como imágenes post emergencia las adquiridas por los satélites Pleiades y GeoEye-1 el 7 y el 10 de abril de 2017 y como imágenes pre emergencia las adquiridas por los satélites WorldView-2 y WorldView-1 en las fechas del 21 de diciembre de 2016 y 26 de diciembre de 2013. El resultado del análisis conducido por UNOSAT revela un total de 1,082 edificaciones dañadas, de las cuales 736 aparecen como destruidas en la imagen o arrastradas por el deslizamiento de tierra y 346 presentan daño severo. Debido al acusado ángulo y la cobertura de nubes de las imágenes satelitales, UNITAR-UNOSAT ha utilizado orthophotos colectadas por Corpoamazonia como fuente auxiliar de validación del análisis realizado con las imágenes satélites. Las orthophotos y otros datos secundarios fueron provistos por OpenStreetMap & la Unidad de Mapeo Humanitario y UMAIC (Unidad de Manejo y Análisis de Información de Colombia), quienes también han provisto apoyo en la coordinación y gestión de la información durante esta emergencia. Por favor, note que el número de estructuras dañadas ha podido ser infra-estimado como consecuencia de los parámetros de las imágenes satelitales utilizadas. Este es un análisis preliminar que aún no ha sido validado en el terreno. Por favor, envíen sus comentarios a UNITAR-UNOSAT.

This map illustrates satellite-detected water bodies and inundated areas in Mocoa city, Putumayo department in Colombia as seen on Resourcesat-2 satellite imagery collected 04 April 2017. Heavy rainfall in the area caused flooding, landslides and mudflow that affected the city. UNOSAT extracted a water index from the satellite image to determine areas of standing water as well as soils with varying levels of water content (i.e. mud). Within the city of Mocoa and the current map extent, about 18 km of roads are potentially affected. About 2900 buildings are within areas which experienced floods and mudflow. It is likely that flood waters and inundation have been systematically underestimated along highly vegetated areas and within built-up urban areas because of the special characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.

Following a large mudflow that hit the city of Mocoa (Department of Putumayo, Colombia) on 31 March 2017 as a consequence of the heavy rains, the International Charter Space and Major Disasters has been activated upon the request of the National Unit for Disaster Risk Management (UNGRD) / Unidad Nacional para la Gestion del Riesgo de Desastres, IDEAM. In response to this emergency, UNITAR-UNOSAT has carried out satellite based damage analysis to assess (visible) building structural damage caused by mudflows. This map illustrates satellite-detected damaged structures including building damage density in Mocoa city and its surroundings. Analysis has been undertaken by using post satellite imagery acquired by Pleiades and Geoeye-1 satellites on the 7 and 10 April 2017 and pre satellite images acquired by Worldview-2 & 1 satellites on the 21 December 2016 and 26 December 2013. As result of UNOSAT satellite analysis, a total of 1,082 buildings were detected as damaged of which 736 observed as destroyed or washed out by mudflow and 346 observed as severely damaged. Due to the pronounced incident angle and cloud cover of the satellite images, UNITAR-UNOSAT has also used orthophotos collected by Corpoamazonia in order to validate satellite based analysis. Orthophotos and additional baseline data were provided by OSM Humanitarian Mapping Unit and UMAIC (Unidad de Manejo y Analisis de Informacion de Colombia) who is also providing information management coordination support for this event. Kindly note that the number of damaged structures could have been underestimated due to the parameters of the images. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Información cartográfica de la Red Vial Nacional de Carreteras No Concesionada a cargo del INVIAS, carreteras concesionadas bajo administración ANI y carreteras secundarias (Programa Plan Vial Regional - PVR)

Archivo contiene las construcciones mapeadas durante el mapatón nacional de Colombia 2025

**UNOSAT code: FL20241112COL, GDACS ID: 1102988** This map illustrates satellite-detected water extent in Riosucio Municipality, Chocó Department & Vuigía del Fuerte Municipality, Antioquia Department Colombia as observed from a TanDEM-X radar image acquired on the 17 November 2024. Within the analysed area of about 1,130km², a total of about 25 km² of lands appear to be affected with flood waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis based on radar images may underestimate the extent of standing water in built-up or densely vegetated areas due to the radar signal's backscattering properties.

**UNOSAT code: FL20241112COL, GDACS ID: 1102988** This map illustrates satellite-detected water extent in Riosucio Municipality, Chocó Department, Colombia as observed from a TanDEM-X radar image acquired on the 17 November 2024. Within the analysed area of about 1,130km², a total of about 12 km² of lands appear to be affected with flood waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis based on radar images may underestimate the extent of standing water in built-up or densely vegetated areas due to the radar signal's backscattering properties.

**UNOSAT code: FL20241112COL, GDACS ID: 1102988** This map illustrates potentially affected structures in Riosucio Municipality, Chocó Department, Colombia as observed from a Pleiades satellite image acquired on 20 November 2024 at 11:07 Local Time. Within the analysis extent, UNOSAT identified 60 potentially affected structures amongst a total of 2,085 structures observed. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

**UNOSAT code: FL20241112COL, GDACS ID: 1102988** This map illustrates potentially affected structures in Bojayá Municipality, Chocó Department, Colombia as observed from a Pleiades satellite image acquired on 17 November 2024 at 10:40 Local Time. Within the analysis extent, UNOSAT identified 13 affected structures and 3 potentially affected structures amongst a total of 2,165 structures observed. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

**UNOSAT code: FL20241112COL, GDACS ID: 1102988** This map illustrates satellite-detected water extent in Uribia Municipality, La Guajira Department, Colombia as observed from a Sentinel-2 satellite image acquired on 15 November 2024 at 10:17 Local Time. Within the analysed area of about 220 km², a total of about 24 km² of lands appear to be affected with flood waters. UNOSAT identified 529 structures that appear to be not affected by flood waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

Colombia administrative level 0-3 boundaries (COD-AB) dataset version 02. This dataset is structured into 3 levels: - Admin 1: 33 Departement - Admin 2: 1122 Municipality (municipio or distrito) - Admin 3: 31880 corregimiento or comuna, partial coverage Dates associated with this dataset: - 20 November 2024: dataset reviewed for accuracy and completeness - 16 April 2020: valid for use by the humanitarian community - 01 December 2019: last edit to the dataset before publishing - 01 December 2019: boundaries created by the source Contributed by OCHA Latin America and the Caribbean (ROLAC). Quality assured, configured, and published by OCHA Field Information Services (FIS) and HDX. Part of the dataset: Global Subnational Administrative Boundaries

Health Facilities and services offered by Health Services Providers registered at the Ministry of Health and Social Protection. The following data was downloaded from the Special Registry of Health Service Providers (REPS in Spanish). Please consult the official website to get the most updated data at https://prestadores.minsalud.gov.co/habilitacion/ __________ Instituciones y servicios ofrecidos por las Instituciones Prestadoras de Servicios de Salud (IPS) registradas ante el Ministerio de Salud y Protección Social. Los siguientes datos fueron descargados del Registro Especial de Prestadores de Servicios de Salud (REPS). Por favor consulte la página oficinal para obtener los datos más actualizados en https://prestadores.minsalud.gov.co/habilitacion/

The paths correspond with the smallest admin level named "vereda" (Country - Department - Municipality - "Vereda") It was produced in coordination with UNOCHA Colombia, OpenStreetMap, and ESRI Colombia. Veredas de Colombia - Levantadas en coordinación con UNOCHA Colombia y ESRI. Información extraoficial. http://datosabiertos.esri.co/datasets/veredas-de-colombia/data?geometry=-90.321%2C-5.168%2C-56.944%2C2.515

Acceso a Agua y Saneamiento en zonas rurales de Colombia según el SIASAR

Indicadores WASH para áreas metropolitanas de Colombia según la GEIH 2020

Indicadores WASH para áreas metropolitanas de Colombia según la GEIH 2019

**ADAM ID: **sm\_us6000qixr Magnitude 6.3 earthquake at 10.0 depth occurred on Jun 08 2025 68km NE of Villavicencio. The epicentre of the earthquake was located at latitude 4.5125 longitude -73.1444. It impacted 64113 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **sm\_us6000pj4s Magnitude 5.6 earthquake at 16.31 depth occurred on Jan 10 2025 29 km SW of Bahía Solano, Colombia. The epicentre of the earthquake was located at latitude 6.0156 longitude -77.5689. It impacted 13390 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **sm\_us6000rtuk Magnitude 5.5 earthquake at 140.692 depth occurred on Dec 10 2025 18km S of Piedecuesta. The epicentre of the earthquake was located at latitude 6.8277 longitude -73.0581. It impacted 831835 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **sm\_us7000qw4k Magnitude 5.4 earthquake at 50.192 depth occurred on Sep 14 2025 12km SE of Dabeiba. The epicentre of the earthquake was located at latitude 6.9494 longitude -76.1732. It impacted 78452 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**UNOSAT code: TC20201123COL** This map illustrates potentially damaged structures and buildings in Providencia Island, Providencia and Santa Catalina Department of Colombia as detected by satellite image acquired after landfall of the Tropical Cyclone IOTA on 17 November 2020. UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 21 November 2020 as a post-event image. Within the Island boundary, UNITAR-UNOSAT identified in the cloud-free zones 1,110 damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 90% of the total number of structures within the analyzed cloud-free areas.

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM), distinguishing between **paved** and **unpaved** roads across the region. Surface classification is derived using a hybrid deep learning approach. For methodological details, see: http://arxiv.org/abs/2410.19874 Recently, we also published a new country-level dataset based on PlanetScope satellite imagery with near-complete coverage of all arterial roads. It is available on HDX under the name Colombia **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.5115 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.0762 million km (14.8974%) - Unpaved roads: 0.1379 million km (26.956%) About 0.2974 million km (58.1467%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0073 million km (2.448%) of the missing surface information. Intended Use This dataset supports transportation planning, infrastructure analysis, climate emissions assessment, and GIS applications. AI Features - **pred_class**: Model-predicted surface class ("paved" or "unpaved") - **pred_label**: Binary label (0 = paved, 1 = unpaved) - **osm_surface_class**: Surface classification derived from OSM tags - **combined_surface_osm_priority**: Combined classification prioritizing OSM - **combined_surface_DL_priority**: Combined classification prioritizing DL prediction - **n_of_predictions_used**: Number of predictions used for estimation - **predicted_length**: Predicted length based on DL estimation (meters) - **DL_mean_timestamp**: Mean timestamp of predictions used OSM Attributes - **name** - **name:en** - **name:* (local language)** - **highway** - **surface** - **smoothness** - **width** - **lanes** - **oneway** - **bridge** - **layer** - **source** Urban Classification Attributes - **continent** - **country_iso_a2** - **urban** (0 = rural, 1 = urban) - **urban_area** - **osm_id** - **osm_type** Data Sources The dataset originates from OpenStreetMap (OSM) and is augmented with deep learning predictions based on Mapillary street-level imagery, combined with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS 2020 urban layer. More HeiGIT datasets: https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology More information: https://heigit.org/ Contact: communications@heigit.org

**UNOSAT code: TC20201123COL** This map illustrates potentially damaged structures and buildings in San Andres Island, Providencia and Santa Catalina department of Colombia as detected by satellite image acquired after landfall of the Tropical Cyclone IOTA on 17 November 2020. UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 18 November 2020 as a post-event image. Within the Island boundary, UNITAR-UNOSAT identified in the cloud-free zones 220 Potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 6% of the total number of structures within the analyzed cloud-free areas.

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**UNOSAT code: EQ20260810COL, GDACS ID: 1557236** This map illustrates structures and buildings affected by the magnitude 7.4 earthquake with an epicentre south of San José del Palmar town in Colombia, with analysis focused on Viterbo in Caldas Department, approximately 50 km from the mainshock epicentre. Damage and destruction were identified primarily using Pleiades very-high-resolution satellite imagery acquired on 12 August 2026. In this area 55 buildings were identified as damaged and 99 were identified potentially damaged buildings. This is a preliminary analysis and has not yet been validated in the field. Ground verification is encouraged, and feedback can be sent to the United Nations Satellite Centre.

**UNOSAT code: EQ20260810COL, GDACS ID: 1557236** This application provides geospatial information from an ongoing satellite-based assessment of the magnitude 7.4 earthquake that occurred south of San José del Palmar, Colombia, on 10 August 2026 at 12:34:28 UTC.2026-06-24 22:04:33 ( Important note: The boundaries and names shown, and the designations used on this map do not imply official endorsement or acceptance by the United Nations. The United Nations Satellite Centre -UNOSAT is not responsible for the misuse or misrepresentation of the map.

**UNOSAT code: EQ20260810COL, GDACS ID: 1557236** SUMMARY OF FINDING Satellite imagery dated 11 August 2026 confirms visible structural damage on one building and possible debris in San José del Palmar municipality. Satellite imagery dated 11 August 2026 confirms possibly induced landslide along the departmental route, San José del Palmar-Ansermanuevo / RD48-02, in San José del Palmar municipality. No other visible widespread structural damage could be observed from satellite imagery in San José del Palmar town within the cloud-free areas as of 11 August 2026.

**UNOSAT code: EQ20260810COL, GDACS ID: 1557236** This map illustrates satellite-based damage assessment density in the city of Zarzal, Valle del Cauca Department, approximately 50 km from the epicentral area of the magnitude 7.4 earthquake of 10 August 2026 in Colombia. Damage was identified primarily using Pléiades very-high-resolution satellite imagery acquired on 13 August 2026. Within the analysed area, 21 buildings were identified as damaged and 180 were identified as potentially damaged. The high incidence angle (>40°) of the satellite imagery used for this analysis can affect the accuracy of the analysis. Damage estimates from such high-incidence-angle satellite imagery should therefore be interpreted with caution. This is a preliminary analysis and has not yet been validated in the field. Ground verification is encouraged, and feedback can be sent to the United Nations Satellite Centre.

**UNOSAT code: EQ20260810COL, GDACS ID: 1557236** Este mapa presenta una evaluación de daños basada en imágenes satelitales de la ciudad de Zarzal, departamento Valle del Cauca, ubicada aproximadamente a 50 km del área epicentral del terremoto de magnitud 7,4 ocurrido el 10 de agosto de 2026 en Colombia. Los daños fueron identificados principalmente en una imágen satelital Pléiades de muy alta resolución, adquirida el 13 de agosto de 2026. Dentro del área analizada, se identificaron 21 edificaciones con daños y 180 edificaciones como potencialmente dañadas. El alto ángulo de incidencia (>40°) de las imágenes satelitales utilizadas para este análisis puede afectar la precisión de los resultados. Por lo tanto, las estimaciones de daños derivadas de imágenes satelitales con un ángulo de incidencia tan elevado deben interpretarse con precaución. Este es un análisis preliminar que aún no ha sido validado en campo. Se recomienda realizar una verificación en terreno. Los comentarios y observaciones pueden enviarse al Centro de Satélites de las Naciones Unidas.