Ukraine

Data Grid Completeness Expand
Affected People
3 Datasets
50%  25%  25% 
Coordination & Context
4 Datasets
40%  20%  40% 
Food Security & Nutrition
1 Datasets
50%  50% 
Geography & Infrastructure
4 Datasets
50%  50% 
Health & Education
2 Datasets
100% 
Population & Socio-economy
2 Datasets
100% 
What is Data Grid Completeness?
Data Grid Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Grid Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
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Presence, freshness, and quality of dataset
  • Dataset fully matches criteria and is up-to-date
  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
  • Updated 6 April 2022 | Dataset date: April 06, 2022-April 06, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery-based Rapid Damage Building Assessment (RDBA) in Donetsk City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 18 and 26 March 2022, analysts found that 6 cells out of 3507 in the City of Donetsk sustained visible damage. This represents 0.17% of the cells over the city. This does not include damage occurring before the current ongoing conflict. This analysis is based on structures visibly damaged as of 18 and 26 March 2022 as seen in moderately degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    20+ Downloads
    This dataset updates: Never
  • Updated 6 April 2022 | Dataset date: April 06, 2022-April 06, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery-based Rapid Damage Building Assessment (RDBA) in the Bucha City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 31 March 2022, analysts found that 82 cells out of 305 cells in the City of Bucha sustained visible damage. This represents approximately 27% of the cells over the city. This analysis is based on structures visibly damaged as of 31 March 2022 as seen in marginally degraded satellite imagery affected by light clouds and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    20+ Downloads
    This dataset updates: Never
  • Updated 6 April 2022 | Dataset date: April 05, 2022-April 05, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery- based Rapid Damage Building Assessment (RDBA) of the Mariupolska Hromada, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 03 April 2022, analysts found that 767 cells out of 3,459 sustained visible damage. This represents approximately 22% of the cells over the Hromada. This represents an increase of 6 percentage points since 26 March 2022. Note that not all 3,459 cells include buildings. Numerous craters are also visible in the fields but were not taken into account for this analysis. This analysis is based on structures visibly damaged as of 03 April 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    40+ Downloads
    This dataset updates: Never
  • Updated 4 April 2022 | Dataset date: March 30, 2022-March 30, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagerybased Rapid Damage Building Assessment (RDBA) in the North of Kharkiv, Ukraine. The RDBA divides the area of interest into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 21, 22 and 23 March 2022, analysts found that 72 cells out of 1,866 cells in the North of Kharkiv sustained visible damage. This represents approximately 4% of the cells over the city. This analysis is based on structures visibly damaged as of 21, 22 and 23 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    90+ Downloads
    This dataset updates: Never
  • Updated 4 April 2022 | Dataset date: March 30, 2022-March 30, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery based Rapid Damage Building Assessment (RDBA) in Sumy City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 20 and 22 March 2022, analysts found that 5 cells out of 1,111 cells sustained visible damage. This represents approximately 0.4% of the cells over the city. This analysis is based on structures visibly damaged as of 20 and 22 March 2022 as seen in marginally degraded satellite imagery. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    80+ Downloads
    This dataset updates: Never
  • UNOSAT code: CE20220223UKR This map illustrates a satellite imagery- based Rapid Damage Building Assessment (RDBA) of a 2 km buffer zone on either side of the national highway H20 connecting Mariupol City and Donetsk City, in Donetska Oblast, Ukraine. The RDBA divides the area of interest (AOI) into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 23 and 26 March 2022, analysts found that 66 cells out of 2,869 cells near the national highway H20 connecting Mariupol City and Donetsk City sustained visible damage. This represents approximately 2,3% of the cells of the AOI. The most affected populated places are Volnovakha, Novotroitske and Berezove. This analysis is based on structures visibly damaged as of 23 and 26 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    10+ Downloads
    This dataset updates: Never
  • Updated 4 April 2022 | Dataset date: April 01, 2022-April 01, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery-based Rapid Damage Building Assessment (RDBA) of the Mariupolska Hromada, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 26 March 2022, analysts found that 556 cells out of 3,456 sustained visible damage. This represents approximately 16% of the cells over the Hromada. Note that not all 6,456 cells include buildings. Numerous craters are also visible in the fields but were not taken into account for this analysis. This analysis is based on structures visibly damaged as of 26 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    20+ Downloads
    This dataset updates: Never
  • Updated 4 April 2022 | Dataset date: April 03, 2022-April 03, 2022
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery- based Rapid Damage Building Assessment (RDBA) in the Chernihiv City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 22 March 2022, analysts found that 191 cells out of 901 cells in the City of Chernihiv sustained visible damage. This represents approximately 21% of the cells over the city. This analysis is based on structures visibly damaged as of 22 March 2022. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    10+ Downloads
    This dataset updates: Never
  • Updated 31 March 2022 | Dataset date: August 06, 2019-August 13, 2022
    The geodatabase contains boundaries for the national and first- and second- order administrative divisions, aligned to the Large Scale International Boundaries dataset from the U.S. Department of State. The feature classes are suitable for linking to the attribute data provided. The tabular data contain total population for 2001 (census) and 2017 (population estimates), as well as five-year age group and sex, language, ethnicity/nationality, and characteristics relating to households, information and communication technology, and income and poverty.
    80+ Downloads
    This dataset updates: As needed
  • Updated 30 March 2022 | Dataset date: March 28, 2022-August 13, 2022
    These data were produced by WorldPop at the University of Southampton and the ‘Smart Cities and Spatial Development’ team at the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR). These data include gridded estimates of population at approximately 100m and 1km resolution for 2020, along with estimates of the number of people belonging to individual age-sex groups. These results were produced using subnational population estimates for Ukraine in 2020 provided in the Common Operational Dataset on Population Statistics (COD-PS) and building height/area/fraction/volume covariates extracted from the World Settlement Footprint (WSF) imperviousness and WSF-3D by DLR. The constrained top-down disaggregation method was used to produce the datasets. The modelling work and geospatial data processing was led by Bondarenko M., Palacios-Lopez D., Sorichetta A., Leasure D.R., ,Zeidler J., Marconcini M., and Esch T.. Oversight was provided by Tatem A.J. Internal WorldPop peer reviews that helped to improve the results and documentation was provided by Lazar A.N.. Main data sources The German Aerospace Centre’s (DLR) WSF imperviousness and WSF 3D products (WSF-3D). Subnational population estimates for Ukraine in 2020 provided in the Common Operational Dataset on Population Statistics (COD-PS). The subnational population estimates were produced using baseline information from the 2001 Population Census of Ukraine and annual birth and death registration data since then. Subnational Administrative Boundaries for Ukraine provided by OCHA . Geospatial covariate layers available at WorldPop. For further details, please, read the Release Statement. Release content ukr_pop_2020_100m_constrained_v2.zip ukr_pop_2020_1km_constrained_v2.zip ukr_agesex_2020_100m_constrained_v2.zip ukr_agesex_2020_1km_constrained_v2.zip ukr_agesex_0_18_2020_100m_constrained_v2.zip ukr_agesex_0_18_2020_1km_constrained_v2.zip Recommended citations Bondarenko M., Palacios-Lopez D., Sorichetta A., Leasure D.R., Zeidler J., Marconcini, M., Esch T., and Tatem A.J. 2022 Gridded population estimates for Ukraine using UN COD-PS estimates 2020, version 2.0. WorldPop and DLR, University of Southampton. doi:10.5258/SOTON/WP00735 License These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.
    90+ Downloads
    This dataset updates: As needed
  • Updated 28 March 2022 | Dataset date: March 07, 2022-August 13, 2022
    This document is compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to compile the figures relevant to Humanitarian Health response at global levels. The information is compiled from the last available data in public validated sources. See detailed info below. The data is mostly compiled from HRP and follows the structure of the Global Humanitarian Overview. For any ideas, updates, or corrections please contact Luis Hernando AGUILAR R (aguilarl@who.int) GHCU-IM team-lead. The data used as populations, names, and other designations are used only as a reference and do not imply any endorsement. The compilation is made by the Global Health Cluster IM team and it is expected to be updated. Not all the fields are available in the reviewed documents and it is expected to be complemented. Please see the version control table in the document
    100+ Downloads
    This dataset updates: Every six months
  • Updated 25 March 2022 | Dataset date: December 31, 2001-December 31, 2001
    Language data drawn from the 2001 government census. Includes the percentage of the population for whom this is their main language, English speaking rates, and literacy rates of people age 15 and older. Available at the admin 0, 1, and 2 levels.
    900+ Downloads
    This dataset updates: As needed
  • Updated 25 March 2022 | Dataset date: January 01, 2022-August 13, 2022
    SURVEILLANCE SYSTEM FOR ATTACKS ON HEALTH CARE (SSA) The SSA displays data from countries with complex humanitarian emergencies, as mandated in resolution [WHA 65.20] This dataset contains 119 verified attacks against health activities. Is taken from the SSA system coordinated and maintained by WHO. For more information contact ssa@who.int http://ssa.who.int Dates 2022/01/01 - 2022/03/25
    30+ Downloads
    This dataset updates: Every six months
  • Updated 25 March 2022 | Dataset date: February 25, 2017-December 31, 2022
    SURVEILLANCE SYSTEM FOR ATTACKS ON HEALTH CARE (SSA) The SSA displays data from countries with complex humanitarian emergencies, as mandated in resolution [WHA 65.20] http://ssa.who.int This dataset contains 3018 verified attacks against health activities. Is taken from the SSA system coordinated and maintained by WHO. For more innformation contact ssa@who.int Dates 31/12/2021 25/02/2017
    20+ Downloads
    This dataset updates: As needed
  • Updated 23 March 2022 | Dataset date: January 01, 2020-December 31, 2020
    This Common Operational Dataset on Population Statistics (COD-PS) is estimated using baseline information from the 2001 Population Census of Ukraine and annual birth and death registration data since the last census. REFERENCE YEAR: 2020 The COD-PS is age- and sex-disaggregated at ADM-1 level (i.e. Oblast) and has a reference date of 1 January, 2020. This common operational dataset is constructed using the cohort-component method of population projection. The 2001 population census data are projected forward to account for population change due to natural increase (using vital event registration data) and net migration (using administrative data sources on migration) at the ADM-1 level and for major cities (with population size of more than 100,000 people). These tables are suitable for database or GIS linkage to the Ukraine - Subnational Administrative Boundaries tables at administrative levels 0 and 1, using the established P-codes.
    700+ Downloads
    This dataset updates: Every year
  • Updated 22 March 2022 | Dataset date: January 31, 2022-August 13, 2022
    Ukraine administrative level 0-4 gazetteer Ukraine generic information gathering spreadsheet
    100+ Downloads
    This dataset updates: Every year
  • Updated 21 March 2022 | Dataset date: March 11, 2022-March 11, 2022
    Estimates of the number of internally displaced persons (IDPs) in Ukraine. The estimates are based on data received from authorities, partners, and colleagues present in the field. It considers a clusterized approach (applying various estimation methodology based on geographic location and context), on top of the historical data from the past, and the refugee flows. For any queries, please contact: ukraineinfomanagement@unhcr.org or protectionclusterukraine@unhcr.org
    100+ Downloads
    This dataset updates: As needed
  • Updated 20 March 2022 | Dataset date: March 21, 2022-March 21, 2022
    These data were produced by the WorldPop Research Group at the University of Southampton. These data include gridded estimates of population at approximately 100m and 1km resolution for 2020, along with estimates of the number of people belonging to individual age-sex groups. These results were produced using Subnational Population Statistics 2020 for Ukraine provided in the Common Operational Dataset on Population Statistics (COD-PS) and ORNL LandScan HD for Ukraine 2022 settlement layer. The datasets are produced using the "top-down" method, with both the unconstrained and constrained top-down disaggregation methods used to produce two different datasets. The differences between constrained and un-constrained methods are described here . Main data sources Subnational Population Statistics for Ukraine provided by Common Operational Dataset on Population Statistics (COD-PS). The subnational population statistics were estimated using baseline information from the 2001 Population Census of Ukraine and annual birth and death registration data since the last census. Settlement layer ORNL LandScan HD for Ukraine. Subnational Administrative Boundaries for Ukraine provided by OCHA. Geospatial covariate layers available at WorldPop. For further details, please, read the Release Statement. Release content ukr_pop_2020_100m_unconstrained_v1_0.zip ukr_pop_2020_100m_constrained_v1_0.zip ukr_pop_2020_1km_unconstrained_v1_0.zip ukr_pop_2020_1km_constrained_v1_0.zip ukr_agesex_2020_100m_unconstrained_v1_0.zip ukr_agesex_2020_100m_constrained_v1_0.zip ukr_agesex_2020_1km_unconstrained_v1_0.zip ukr_agesex_2020_1km_constrained_v1_0.zip ukr_agesex_0_18_2020_1km_unconstrained_v1_0.zip ukr_agesex_0_18_2020_1km_constrained_v1_0.zip Recommended citations Bondarenko M., Sorichetta A., Leasure DR. and Tatem AJ. 2022 Gridded population estimates for Ukraine using UN COD-PS estimates 2020, version 1.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00734 License These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.
    100+ Downloads
    This dataset updates: As needed
  • Updated 16 March 2022 | Dataset date: March 02, 2022-August 13, 2022
    Information is compiled from a variety of sources. While every effort has been made to ensure that all statistical information is verified, figures on some arrivals represent an estimate. Triangulation of information and sources is performed on a continuous basis. Therefore, amendments in figures may occur, including retroactively.
    900+ Downloads
    This dataset updates: Every day
  • Updated 15 March 2022 | Dataset date: September 30, 2021-September 30, 2021
    This dataset shows the number of people in need(PiN), funds required and funds received by country and over the years, from 2010 to 2021. PIN figures for 2022 are available in this dataset: Interagency Response Plans in 2022
    700+ Downloads
    This dataset updates: Every year
  • The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Ukraine: (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).
    10+ Downloads
    This data is by request only
  • Updated 2 March 2022 | Dataset date: June 22, 2021-June 22, 2021
    Ukraine administrative level 4 population statistics based on data from 2001 state census.
    400+ Downloads
    This dataset updates: Never
  • Updated 2 March 2022 | Dataset date: December 20, 2021-December 31, 2022
    The attached dataset is from the 2022 Ukraine HRP and offers the number of targeted people by geozone and by population group. The data is also presented with SADD.
    200+ Downloads
    This dataset updates: Every year
  • Updated 15 February 2022 | Dataset date: January 01, 2017-December 31, 2021
    This page provides the data published in the Education in Danger Monthly News Brief. All data contains incidents identified in open sources. Categorized by country and with link to the relevant Monthly News Brief (where possible).
    6100+ Downloads
    This dataset updates: As needed
  • Updated 11 February 2022 | Dataset date: April 01, 2021-August 13, 2022
    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/
    15000+ Downloads
    This dataset updates: As needed