Dominican Republic GIS data

geoBoundaries ADM2 boundaries for Dominican Republic: 155 units, representing 2020. Source: Caribbean GeoPortal, N/A.

satellite imagery by Diana Hoyos, acquired 2025-11-05 to 2025-11-05, 18.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Diana Hoyos, acquired 2025-11-05 to 2025-11-05, 18.8 cm per pixel, published on OpenAerialMap.

geoBoundaries ADM1 boundaries for Dominican Republic: 32 units, representing 2022. Source: Natural Earth.

geoBoundaries ADM0 boundaries for Dominican Republic: 1 units, representing 2020. Source: Caribbean GeoPortal, N/A.

**ADAM ID: FL-20231120-DOM-00** Flood covering 47475.0 sq m on Nov 20 2023 in Dominican Republic. It impacted 349525 people.

Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Dominican Republic: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Dominican Republic administrative level 0-4 boundaries (COD-AB) dataset version 01. This dataset is structured into 4 levels: - Admin 1: 10 region - Admin 2: 32 province or national district (distrito nacional) - Admin 3: 155 municipio - Admin 4: 386 dm(?) Dates associated with this dataset: - 17 February 2025: dataset reviewed for accuracy and completeness - 29 June 2021: valid for use by the humanitarian community - 06 September 2017: last edit to the dataset before publishing - 06 September 2017: boundaries created by the source Quality assured, configured, and published by OCHA Field Information Services (FIS) and HDX. Part of the dataset: Global Subnational Administrative Boundaries

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

This dataset contains annual, 100m-resolution above ground biomass (AGB) estimates from CTrees, a NASA-affiliated forest-carbon monitoring organization, clipped to this country's boundary from CTrees' global AGB raster. Pixel values are stored as int16, scaled x10 relative to the true value in megagrams per hectare (Mg/ha) -- divide by 10 to get Mg/ha. See the caveats field and resource description for details on how this scale factor is recorded and why it isn't applied automatically by most tools.

Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - Part of the country exports on HDX by HOT

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT

Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT

Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT

Points of interest: public-facing amenities, shops, tourist attractions, and landmarks tagged via `amenity`, `shop`, `tourism`, or `man_made`. Useful for general POI reference, urban analysis, and basemap detail. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, shop, tourism, man_made - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, healthcare - Part of the country exports on HDX by HOT

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons. Fields available: SID: A unique storm identifier (SID) assigned by IBTrACS algorithm. ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss) BASIN: Basin of the current storm position SUBBASIN: Sub-basin of the current storm position NATURE: Type of storm (a combination of the various types from the available sources) NUMBER: Number of the storm for the year (restarts at 1 for each year LAT: Mean position - latitude (a combination of the available positions) LON: Mean position - longitude (a combination of the available positions) WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.

Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027.  A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Dominican Republic Provincia Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.  The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Oficina Nacional de Estadística, República Dominicana. These were published in September 2023. Other administrative boundaries for this country are also available:Country   Regione   Municipio

Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027.  A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Dominican Republic Country Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.  The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Oficina Nacional de Estadística, República Dominicana. These were published in September 2023. Other administrative boundaries for this country are also available:Regione   Provincia   Municipio

Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027.  A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Dominican Republic Regione Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.  The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Oficina Nacional de Estadística, República Dominicana. These were published in September 2023. Other administrative boundaries for this country are also available:Country   Provincia   Municipio

Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027.  A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Dominican Republic Municipio Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.  The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Oficina Nacional de Estadística, República Dominicana. These were published in September 2023. Other administrative boundaries for this country are also available:Country   Regione   Provincia

.A large scale landslide inventory was carried out by a team from the University of Twente, use of 5 scenes of Pléiades satellite imageries with resolution of 0.5m, which were obtained in September 23 and October 5 after the hurricane, made available through UNITAR-UNOSAT. Apart from these also a series of Digital Globe Images were used that were collected for the Google Crisis Response through a KML layer. The images were visually interpreted by image interpretation experts, and landslides were mapped as polygons, separating scarp, transport and accumulation areas, and classifying the landslides in types. A total of 9,960 landslides were identified, which include 8,576 debris slides, 1,010 debris flows and 374 rock falls, with area of 7.30km2, 2.50km2, and 0.50 km2 respectively. The whole area of landslide is 10.30 km2, which covers 1.37 percent of the island. The source of landslides is 3.30km2, and the other 7.0 km2 is transportation and deposition area. Almost all of the rivers flooded due to intensive precipitation. The flooded area is 13.03km2, which covers 1.74% of the island. Dominica will face some new problems for mountain hazards in the coming years, as many of the fresh scarps may produce more debris, and many tree trunks are still on the slopes or in the river channels. With so many fresh landslides in the upper catchments, it is likely that debris flows will be triggered with rainfall thresholds that are substantially lower than before the hurricane. Hurricane Maria damaged the forest cover dramatically, which changed the conditions for hazard initiation. Without the protection of vegetation, more new shallow landslides could happen in the near future. A series of cascading hazards may happen, for example landslides or debris flow blocking rivers and resulting in outburst floods. Therefore more detailed evaluation of the post-Maria hazard and risk situation is very important.

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342** This map illustrates cumulative satellite-detected water extent in Cibao Nordeste Region, Dominican Republic as observed from a Sentinel-2 image acquired on the 21 November 2023 at 11:17 local time. Within the cloud free analysed area of about 920 km² , about 190 km² of land appears to be affected with flood waters and 13,000 people are potentially exposed to 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).

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342** This map illustrates cumulative satellite-detected water extent in Valdesia Regions, Dominican Republic as observed from a Sentinel-2 image acquired on the 21 November 2023 at 11:17 local time. Within the cloud free analysed area of about 320 km² , less than 5 km² of land appears to be affected with flood waters and 2,500 people are potentially exposed to 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).

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342** This map illustrates cumulative satellite-detected water extent in CIbao Nordeste and Cibao Sur Regions, Dominican Republic as observed from a Sentinel-1 image acquired on the 18 November 2023 at 18:53 local time. Within the extent of this map, about 55 km² of land appears to be affected with flood waters and about 10,500 people are potentially exposed to 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 from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342** This application provides geospatial information about the ongoing floods in Dominican Republic 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

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342** This map illustrates cumulative satellite-detected water extent in Higuamo & Valdesia Regions, Dominican Republic as observed from a Sentinel-2 image acquired on the 21 November 2023 at 11:17 local time. Within the cloud free analysed area of about 1,800 km² , about 35 km² of land appears to be affected with flood waters and 14,000 people are potentially exposed to 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).