Cape Verde GIS data

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.

**UNOSAT code: FL20250812CPV** This map illustrates satellite-detected mudflow extent in Mindelo City, Sao Vicente Municipality, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 13 August 2025 at 11:01 local time (12:01 UTC). Within the analyzed area of approximately 30 km², about 5 km² of land appears to be affected by flood. Based on WorldPop population data and the flood extent, approximately 6,600 people are potentially exposed or living close to the flooded areas. Additionally, UNOSAT identified around 2,500 damaged buildings, five damaged bridges, and approximately 44 km of affected roads. 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: FL20250812CPV** This map illustrates satellite-detected mudflow extent in Porto Novo Town, Porto Novo Municipality, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 13 August 2025 at 11:01 local time (12:01 UTC). Within the analyzed area of approximately 2 km², about 0.3 km² of land appears to be affected by flood. UNOSAT identified around 300 damaged buildings and approximately 1 km of affected roads. 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: FL20250812CPV** This map illustrates satellite-detected mudflow extent in East Sao Vicente Municipality, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 14 August 2025 at 11:43 local time (12:43 UTC). Within the analyzed area of approximately 35 km², about 3 km² of land appears to be affected by flood.  UNOSAT identified around 1,000 affected/potentially affected buildings and approximately 15 km of affected roads.

**UNOSAT code: FL20250812CPV** Status: No major damage was observed Further action(s): Continue monitoring Summary of findings: No major damage was observed in Ponta do Sol Town, Cruzinha Village, and Ribeira da Cruz Village in northern Santo Antão Island as of 16 August 2025. Possible flood evidence was observed along the waterways in Ribeira Grande Town and Coculi Town in northern Santo Antão Island as of 16 August 2025.

**UNOSAT code: FL20250812CPV** This application provides flood impact assessments in Cabo Verde, Islands of Sao Vicente and Santo Antao 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 designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

**UNOSAT code: FL20250812CPV** This map illustrates satellite-detected mudflow extent in Sao Vicente Island, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 13 to 16 August 2025. Within the analyzed area of approximately 270 km², about 12 km² of land appears to be affected by flood. Based on WorldPop population data and the flood extent, approximately 12,600 people are potentially exposed or living close to the flooded areas. Additionally, UNOSAT identified around 4,000 damaged buildings, five damaged bridges, and approximately 80 km of affected roads. 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: FL20250812CPV** This map illustrates satellite-detected mudflow extent in Santo Antao Island, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 13 to 16 August 2025. Within the analyzed area of approximately 700 km², about 3 km² of land appears to be affected by flood. Additionally, UNOSAT identified around 460 damaged buildings, two damaged bridges, and approximately 5 km of affected roads. 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: FL20250812CPV** This map illustrates satellite-detected mudflow extent in Sao Vicente and Santo Islands, Cabo Verde as observed from Pleiades very high-resolution satellite image acquired on 13 to 16 August 2025. Within the analyzed area, approximately, about 16 km² of land appears to be affected by flood. Based on WorldPop population data and the flood extent, approximately 13,600 people are potentially exposed or living close to the flooded areas. Additionally, UNOSAT identified around 4,660 damaged buildings, five damaged bridges, and approximately 85 km of affected roads. 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: FL20250812CPV** This map shows possible damage to cultural heritage was detected 1.3 km west of the park based on a very high resolution satellite image collected 16 August 2025 when compared to very high resolution satellite imagery from 9 February 2025. Specifically, possible damage was detected to a section of traditional, terraced agricultural fields (inset 1). This traditional form of agriculture is named under Criterion (v) as one of the justifications for the area's Outstanding Universal Value and its inclusion on the UNESCO Tentative List. Additionally, water and mud flows were detected both within and around the park. 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: FL20250812CPV** Este mapa mostra possíveis danos no património cultural, detetados a 1,3 km a oeste do parque, com base numa imagem de satélite de alta resolução obtida em 16 de Agosto de 2025, quando comparada com uma imagem de satélite de alta resolução de 9 de fevereiro de 2025. Mais especificamente, foram detetados possíveis danos numa secção de campos agrícolas tradicionais em socalcos (Figura 1). Esta forma tradicional de agricultura é referida no Critério (v) como uma das justificações para o Valor Universal Excecional da área e a sua inclusão na Lista Provisória da UNESCO. Também foram detetados fluxos de água e lama tanto dentro como em torno do parque. Esta é uma análise preliminar e ainda não foi validada no terreno. Qualquer informação, por favor, envie para o Centro de Satélites das Nações Unidas (UNOSAT).

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**ADAM ID: **1001328\_8 Tropical storm during the period Sep 25 2026-Sep 26 2026 in Cape Verde. The center of the storm was located near latitude 19.3 longitude -23.3. 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.

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['railway'] IN ('rail','station') Features may have these attributes: - name - name:en - railway - ele - operator:type - layer - addr:full - addr:city - source - name:km - name:pt This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

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

The dataset represents suitable areas for offshore mariculture of gilthead seabream (sparus aurata) in Cabo Verde, produced under the scope of the Hand-in-Hand initiative, using publicly accessible data. The geospatial analysis adopts Kapetsky and Aguilar-Manjarrez study (Kapetsky et al., 2013(*)) methodology, where suitability is estimated based on the assumptions: 1. Activity develops within the exclusive economic zones (EEZs). 2. Uses cages for fish. 3. Employs species with proven mariculture technologies and established markets or identified as having good prospects for future development. Analytical criteria and thresholds are defined based on technical limits on cages, cost-effective farming, and species habitat: 1. Depths (25–100 m). 2. Current speeds (10–100 cm/s). 3. Cost limits on distance from shore to offshore installations (25 nm (46.3 km)). 4. Reliable access to a port. 5. Habitat gilthead seabream (sparus aurata). (*) Kapetsky, J. M., Aguilar-Majarrez, J., & Jenness, J. (2013). A global assessment of offshore mariculture potential from a spatial perspective. In FAO Fisheries and Aquaculture Technical Paper (Issue No. 549, pp. 0–181). Food and Agriculture Organization of the United Nations. **Data creation:** 2022-04-21 **Contact points:** Metadata Contact: [FAO-Data](mailto:FAO-data@fao.org) **Data lineage:** lineage source statement The assessment analysis is developed using publicly accessible data. FAO Map Catalogue data 1. FAO aquatic species distribution map of Sparus aurata (Gilthead seabream 2. Regions with HYCOM current speeds at 30m depth between 1 - 10, 10 - 100 and > 100 cm/s for all months in the year - Based on HYCOM NCODA (HYbrid Coordinate Ocean Model (HYCOM) and Navy Coupled Ocean Data Assimilation (NCODA)) 8.9 km 2004-2008 3. Sea Ports Web available data 4. EEZ - VLIZ Flanders Maritime Institute - Maritime boundaries geodatabase version 5 (2009 5. Bathymetry – GEBCO – General Bathymetric Chart of the oceans - Gridded bathymetric data sets are global terrain models for ocean and land 2021 **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Download documentation working paper/report on offshore mariculture suitability geospatial analysis Cabo Verde Download gilthead seabream offshore mariculture suitability data for Cabo Verde

The dataset represents suitable areas for offshore mariculture of yellowfin tuna (thunnus albacares) in Cabo Verde, produced under the scope of the Hand-in-Hand initiative, using publicly accessible data. The geospatial analysis adopts Kapetsky and Aguilar-Manjarrez study (Kapetsky et al., 2013(*)) methodology, where suitability is estimated based on the assumptions: 1. Activity develops within the exclusive economic zones (EEZs). 2. Uses cages for fish. 3. Employs species with proven mariculture technologies and established markets or identified as having good prospects for future development. Analytical criteria and thresholds are defined based on technical limits on cages, cost-effective farming, and species habitat: 1. Depths (25–100 m). 2. Current speeds (10–100 cm/s). 3. Cost limits on distance from shore to offshore installations (25 nm (46.3 km)). 4. Reliable access to a port. 5. Habitat yellowfin tuna (thunnus albacares). (*) Kapetsky, J. M., Aguilar-Majarrez, J., & Jenness, J. (2013). A global assessment of offshore mariculture potential from a spatial perspective. In FAO Fisheries and Aquaculture Technical Paper (Issue No. 549, pp. 0–181). Food and Agriculture Organization of the United Nations. **Data creation:** 2022-04-21 **Contact points:** Metadata Contact: [FAO-Data](mailto:FAO-data@fao.org) **Data lineage:** lineage source statement The assessment analysis is developed using publicly accessible data. FAO Map Catalogue data 1. FAO aquatic species distribution map of thunnus albacares (yellowfin tuna 2. Regions with HYCOM current speeds at 30m depth between 1 - 10, 10 - 100 and > 100 cm/s for all months in the year - Based on HYCOM NCODA (HYbrid Coordinate Ocean Model (HYCOM) and Navy Coupled Ocean Data Assimilation (NCODA)) 8.9 km 2004-2008 3. Sea Ports Web available data 4. EEZ - VLIZ Flanders Maritime Institute - Maritime boundaries geodatabase version 5 (2009 5. Bathymetry – GEBCO – General Bathymetric Chart of the oceans - Gridded bathymetric data sets are global terrain models for ocean and land 2021 **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Download documentation working paper/report on offshore mariculture suitability geospatial analysis Cabo Verde Download yellowfin tuna (thunnus albacares) offshore mariculture suitability data for Cabo Verde

Retirement Notice: This item is in mature support as of October 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. Cabo Verde Island Boundaries provides a 2023 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 2023 boundaries are provided by Michael Bauer Research GmbH. They are sourced from INGT. These were published in October 2023. Other administrative boundaries for this country are also available: Country Municipality

Retirement Notice: This item is in mature support as of October 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. Cabo Verde Country Boundaries provides a 2023 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 2023 boundaries are provided by Michael Bauer Research GmbH. They are sourced from INGT. These were published in October 2023. Other administrative boundaries for this country are also available: Island Municipality

Retirement Notice: This item is in mature support as of October 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. Cabo Verde Municipality Boundaries provides a 2023 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 2023 boundaries are provided by Michael Bauer Research GmbH. They are sourced from INGT. These were published in October 2023. Other administrative boundaries for this country are also available: Country Island