Resource has no data rows! No conflict and disaster population movement (flows) data recorded for Kiribati in the last 180 days.
Internally displaced persons are defined according to the 1998 Guiding Principles (https://www.internal-displacement.org/publications/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.
The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD), accessible at https://www.internal-displacement.org/database/displacement-data. The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.
We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook.
Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.facebook.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259).
Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.
A collaborative project between SPC, the World Fish Centre and the University of Wollongong has produced the first detailed population estimates of people living close to the coast in the 22 Pacific Island Countries and Territories (PICTs). These estimates are stratified into 1, 5, and 10km zones.
More information about this dataset: https://sdd.spc.int/mapping-coastal
Access this dataset from the Pacific Data Hub
Statistics from SPC's Public Health Division (PHD) on COVID-19 vaccination in Pacific Island Countries and Territories. Monitoring the impact of COVID-19 and the effectiveness of prevention and control strategies remains a public health priority. With the COVID-19 Public Health Emergency of International Concern declaration ending, some metrics have changed in frequency, source, or availability (i.e vaccination data). SPC will no longer continue to provide updated information on vaccination. The last update for this dataset was the 09 May 2023.
Find more Pacific data on PDH.stat.
Access this dataset from the Pacific Data Hub
Proportion of population living in 1, 5 and 10km buffer zones for Pacific Island Countries and Territories, determined using most recent Population and Housing Census. Number of people living in 1,5 and 10km buffer zones determined by apportioning population projections.
Find more Pacific data on PDH.stat.
Access this dataset from the Pacific Data Hub
Proportion of population in Pacific Island Countries and Territories (PICTs) living in Low Elevation Coastal Zones (LECZ) of 0-10 and 0-20 meters above sea level. LECZ were delineated using the bathub method overlaid on the Advanced Land Observing Satellite (ALOS) Global Digital Surface Model (AW3D30). Populations within the LECZs were estimated using the Pacific Community (SPC) Statistics for Development Division’s 100m2 population grids.
Find more Pacific data on PDH.stat.
Access this dataset from the Pacific Data Hub
Population projections for Pacific Island Countries and territories from 1950 to 2050, by sex and by 5-years age groups.
Find more Pacific data on PDH.stat.
Access this dataset from the Pacific Data Hub
Kiribati population density for 400m H3 hexagons.
Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.
Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.
This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2022).
Kiribati 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
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
Live list of active aid activities for Kiribati 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 https://d-portal.org
Kiribati administrative level 0-3 sex and age disaggregated 2020 projected population statistics
REFERENCE YEAR: 2020
These tables are suitable for database or GIS linkage to the Kiribati - Subnational Administrative Boundaries.
This data was developed as part of the Modelling Exposure Through Earth
Observation Routines (METEOR) project and is a Level 1, or a global-quality
exposure data set. Minimal country-specific data was collected. The data is
intended for CAT modeling and loss estimation. Repurposing this data for any
reason other than assessing risk is not recommended. The data presents the
estimated number of buildings, building area, and rebuilding value at a
15-arcsecond grid resolution (approximately 500 meters at the equator). This
data set is in point shapefile format where the points represent the centroids
of the 15-arcsecond grid. The results were created through a process of
spreading the number of buildings to the 15-arcsecond level by a statistical
assessment of moderate resolution EO data, which is described in more detail
in the dasymetric mapping lineage processing step. The estimated building count
at any given area is a result of statistical processes and should not be
mistaken as a building count. The structural classes of buildings used for risk
assessment are estimated given the building wall, floor, and roof material
classes surveyed through 2002 Population and Housing Census - Volume 1.
Analytical report. Additionally, the data is provided in Open Exposure Data
(OED) import format, as a pair of CSV files. One CSV file contains the
location details, and the other is an "account" file that is filled with
default information to satisfy OED format requirements. The OED input files
are set to use "All perils" (i.e. "AA1"). All required OED account-related
fields are populated with "1" by default (such as PortNumber, AccNumber,
PolNumber).
If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes:
https://forms.gle/DQjhE89CRegNKB3X8
Please see the METEOR project page for information about the METEOR Project:
http://meteor-project.org/
Please see the METEOR map portal for interactive maps:
https://maps.meteor-project.org/
For more information about the Open Exposure Data (OED) standard, please see
https://github.com/OasisLMF/OpenDataStandards
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
Kiribati administrative level 0 (country), 1 (group), 2 (island) boundaries
These boundaries are suitable for database or GIS linkage to the Kiribati - Subnational Population Statistics tables.
The disbursed nature of this archipelago country does not make it suitable for EMF mapping.
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Kiribati: (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).
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. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined
here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
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/WP00646
