Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.
"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
Cabo Verde administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
Cabo Verde administrative level 0-1 and island sex and age disaggregated 2021 projected population statistics
UPDATED 24 January 2023 to correctly assign ADM1 feature "São Salvador do Mundo" [CV19] to island "Santiago" [CV6].
REFERENCE YEAR: 2022
Gazetteer available to administrative level 4
The administrative level 0, 1, and island tables are suitable for database or GIS linkage to the Cabo Verde - Administrative Boundaries administrative level 0, 1, and 2 shapefiles using the ADM0, ADM1, and ISL_PCODE items.
The dataset consists of settlement extents across Cabo Verde, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent.
Updates in this version include:
(1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets
(2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate
(3) Building count ranges have been included
(4) Predicted false positives have been included
(5) Population data have been removed until new constrained population numbers are available
(6) Settlement status has been included, as it pertains to Version 01 of the settlement extents
This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.
The International Federation of Red Cross and Red Crescent Societies (IFRC) is the world’s largest humanitarian network. Our secretariat supports local Red Cross and Red Crescent action in more than 192 countries, bringing together almost 15 million volunteers for the good of humanity.
We launch Emergency Appeals for big and complex disasters affecting lots of people who will need long-term support to recover. We also support Red Cross and Red Crescent Societies to respond to lots of small and medium-sized disasters worldwide—through our Disaster Response Emergency Fund (DREF) and in other ways.
There is also a global dataset.
30+ Downloads
This dataset updates: Every week
This dataset is part of the data series [?]: IFRC - Appeals
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Cabo Verde: (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).
The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following:
Microestimates of wealth for all low- and middle-income countries
Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock
Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119
More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/
Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119
Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid
An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
Education indicators for Cabo Verde.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
Cabo Verde - administrative level 0-2 and island boundaries with level 0-4 and islands gazetteer.
The administrative level 0, 1, and island shapefiles are suitable for database or GIS linkage to the Cabo Verde - Subnational Population Statistics using the ADM0, ADM1, and ISL_PCODE items.
Note that island feature "SANTA LUZIA" [CV0] is uninhabited and does not have a corresponding COD-PS record. Santa Luiza does not belong to any administrative level 1-4 features and is excluded from the attached gazetteer.
In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey, providing policymakers, research institutions, and nonprofits with an international view of public climate change opinion.
For more information please see https://dataforgood.facebook.com/dfg/tools/climate-change-opinion-survey
If you're interested in becoming a research partner and accessing record level data, please email dataforgood@fb.com.
This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at:
https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
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.
West and Central Africa Administrative boundaries, administrative level 0 to 2. Notice: The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations.
West and Central Africa settlements with administrative capitals
Live list of active aid activities for Cabo Verde shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results.
These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below.
These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country.
They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method,
with either the unconstrained or constrained top-down disaggregation method used.
Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):
- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national
population estimates (UN 2019).
Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)
-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel,
adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
This dataset contains many indicators related to population and migration such as Average annual population growth rate, Population 15-19 , Annual rate of change of the migrant stock, International migrant stock at mid-year, etc. The whole list and their description can be find in this link https://bit.ly/2ODhFQh
This dataset contains many indicators in education such as as Net enrolment rate in primary education, Ratio of girls to boys in primary education, etc. The whole list and their description can be find in this link https://bit.ly/2NWP6Z1
This dataset contains many health indicators such as Infant mortality rate, Proportion of population with advanced HIV infection with access to antiretroviral drugs, Death rate associated with malaria per 100,000 population, Tuberculosis prevalence rate per 100,000 population, etc. The whole list and their description can be find in this link https://bit.ly/2NZBRH3
The AFDB Statistical Data Portal has been developed in response to the increasing demand for statistical data and indicators relating to African Countries. The Portal provides multiple customized tools to gather indicators, analyze them, and export them into multiple formats.
With the Data Portal, you can visualize Socio-Economic indicators over a period of time, gain access to presentation-ready graphics and perform comprehensive analysis on a Country and Regional level