Updated
November 25, 2020
| Dataset date: Jan 1, 2020-Dec 31, 2020
This dataset updates: Every week
The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
Updated
November 23, 2020
| Dataset date: Jan 1, 2000-Dec 31, 2020
This dataset updates: Every year
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 3 and 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.
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
Updated
November 23, 2020
| Dataset date: Jan 1, 2000-Dec 31, 2020
This dataset updates: Every year
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.
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
Updated
October 28, 2020
| Dataset date: Sep 21, 2020
This dataset updates: Every year
This data contains aggregated weighted statistics at the regional level by gender for the Survey on Gender Equality At Home fielded in July 2020. Facebook’s 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. If you're interested in becoming a Survey on Gender Equality research partner, please email gendersurvey@fb.com.
Updated
October 13, 2020
| Dataset date: Oct 13, 2020
This dataset updates: Every day
FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
Updated
September 7, 2020
| Dataset date: Jan 1, 1970-Dec 31, 2019
This dataset updates: Every three months
Education indicators for Falkland Islands (Malvinas).
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: Students and Teachers (made 2020 February), Demographic and Socio-economic (made 2020 February)
Updated
Live
| Dataset date: Jan 1, 2019-Jan 1, 2020
This dataset updates: Live
Live list of active aid activities for Falkland Islands (Malvinas) 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
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL
Features may have these attributes:
beds
rooms
addr:full
source
addr:city
opening_hours
addr:housenumber
amenity
addr:street
name
tourism
man_made
shop
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL
Features may have these attributes:
port
operator:type
addr:full
addr:city
amenity
building
name
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay')
Features may have these attributes:
covered
tunnel
blockage
depth
natural
water
width
waterway
name
source
layer
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university')
Features may have these attributes:
operator:type
addr:full
addr:city
amenity
building
name
source
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
building IS NOT NULL
Features may have these attributes:
addr:full
building:materials
addr:city
addr:housenumber
building:levels
office
addr:street
building
name
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy')
Features may have these attributes:
operator:type
addr:full
source
addr:city
healthcare
amenity
building
name
healthcare:speciality
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office')
Features may have these attributes:
addr:full
addr:city
network
amenity
name
source
operator
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
place IN ('isolated_dwelling','town','village','hamlet','city')
Features may have these attributes:
place
is_in
population
name
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
railway IN ('rail','station')
Features may have these attributes:
operator:type
addr:full
addr:city
ele
name
source
layer
railway
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
highway IS NOT NULL
Features may have these attributes:
smoothness
oneway
width
surface
bridge
highway
lanes
name
source
layer
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site'
Features may have these attributes:
operator:type
addr:full
addr:city
emergency
aeroway
emergency:helipad
building
name
source
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
June 29, 2020
| Dataset date: Jan 1, 2000-Dec 31, 2020
This dataset updates: Every year
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.
A description of the modelling methods used for age and sex structures can be found in
Tatem et al and
Pezzulo et al.
The 'Unconstrained global per country 2000-2020' datasets represent the outputs from a project focused on construction of
consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency.
These are produced using the unconstrained top-down modelling method.
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/WP00646
Updated
June 29, 2020
| Dataset date: Jan 1, 2017-Dec 31, 2017
This dataset updates: Every year
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al..
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Falkland Islands 1km pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00521
Updated
June 29, 2020
| Dataset date: Jan 1, 2017-Dec 31, 2017
This dataset updates: Every year
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al..
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Falkland Islands 1km births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00413
Updated
January 29, 2016
| Dataset date: Dec 31, 2015
This dataset updates: Never
The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.
