• Time Period of the Dataset [?]: September 21, 2017-September 21, 2017 ... More
    Modified [?]: 21 September 2017
    Dataset Added on HDX [?]: 21 September 2017
    Hurricane Maria peak 3-sec gust footprints in kml format (through 9UT 21st Sept 2017) Credit - Tropical Storm Risk/UCL
    100+ Downloads
    This dataset updates: Every year
  • Time Period of the Dataset [?]: September 20, 2017-October 03, 2017 ... More
    Modified [?]: 4 November 2018
    Dataset Added on HDX [?]: 4 November 2018
    This resource is comprised of Twitter data collected and processed by the AIDR system during the 2017 hurricane Maria. The data contains information about number of people affected, injured, dead, reports of damages, missing people and so on. Please contact us if you need full dataset with tweets content.
    100+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: February 04, 2018-March 02, 2018 ... More
    Modified [?]: 2 March 2023
    Dataset Added on HDX [?]: 23 March 2018
    This data is the result of interviews conducted with 444 Dominicans impacted by Hurricane Maria. This round of interviews took place between 4 February and 2 March 2018, roughly four and a half months after Hurricane Maria made landfall. This is the third of five rounds of surveys in Dominica.
    This data is by request only
  • Time Period of the Dataset [?]: January 27, 2018-January 27, 2018 ... More
    Modified [?]: 17 September 2018
    Dataset Added on HDX [?]: 23 February 2018
    Displacement Tracking Matrix (DTM) Dominica- Hurricane Maria Response
    100+ Downloads
    This dataset updates: Never
    This dataset is part of the data series [?]: IOM - DTM Site and Location Assessment
  • Time Period of the Dataset [?]: November 01, 2017-November 01, 2017 ... More
    Modified [?]: 1 December 2017
    Confirmed [?]: 7 March 2024
    Dataset Added on HDX [?]: 1 December 2017
    Third Round, Displacement Tracking Matrix (DTM) Dominica- Hurricane Maria Response
    100+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: January 01, 2014-December 31, 2017 ... More
    Modified [?]: 6 January 2022
    Dataset Added on HDX [?]: 6 January 2022
    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.
    500+ Downloads
    This dataset updates: Live
    This dataset is part of the data series [?]: geoBoundaries - Subnational Administrative Boundaries
  • Time Period of the Dataset [?]: July 11, 2023-March 28, 2024 ... More
    Modified [?]: 11 July 2023
    Dataset Added on HDX [?]: 11 July 2023
    These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work. In-country engagements were done by David Kyalo, Olena Borkovska ( GRID3 , Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and sex and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem. Recommended citations Gadiaga A. N., Abbott T. J., Chamberlain H., Lazar A. N., Darin E., Tatem A. J. 2023. Census disaggregated gridded population estimates for Kenya (2022), version 2.0. University of Southampton. doi:10.5258/SOTON/WP00762 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.
    40+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: October 14, 2017-October 14, 2017 ... More
    Modified [?]: 18 October 2017
    Confirmed [?]: 7 March 2024
    Dataset Added on HDX [?]: 18 October 2017
    The Ministry of Education announced the first phase of school reopening on 16 October 2017. Therefore, IOM prioritized schools currently housing the displaced population in the first round of DTM assessment. 43 of the pre-identified collective centers were schools and 33 of these were housing displaced individuals on 6 October. IOM aims to provide basic information on these targeted schools to inform the government and general humanitarian community of the situation in these collective centers and support provision of assistance. This report presents the results of assessments carried out from 11-14 October in 19 schools that are scheduled to reopen in the coming days.
    30+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: July 22, 2022-March 28, 2024 ... More
    Modified [?]: 20 December 2022
    Dataset Added on HDX [?]: 20 December 2022
    These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network CIESIN in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and sex and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem. For further details, please, read the Release Statement. Release content KEN_population_v1_0_gridded.tif KEN_population_v1_0_agesex.zip KEN_population_v1_0_mastergrid.tif Recommended citations Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. Census disaggregated gridded population estimates for Kenya (2021), version 1.0 University of Southampton. doi:10.5258/SOTON/WP00747 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.
    60+ Downloads
    This dataset updates: As needed