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  • Updated May 27, 2019 | Dataset date: Jan 1, 2019-Dec 31, 2019
    This dataset updates: Every year
    Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The '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. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. 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).
  • Updated May 27, 2019 | 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. Dominica 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/WP00522
  • Updated May 27, 2019 | 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. Dominica 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/WP00414
  • Updated May 27, 2019 | 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. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Stevens et al. The '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. These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map populations for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets 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 April 16, 2019 | Dataset date: Jan 1, 2019-Jan 1, 2020
    This dataset updates: Live
    Live list of active aid activities for Dominica 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
  • 200+ Downloads
    Updated November 4, 2018 | Dataset date: Sep 20, 2017-Oct 3, 2017
    This dataset updates: Every year
    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.
  • 70+ Downloads
    Updated September 28, 2018 | Dataset date: Jan 1, 1950-Dec 31, 2050
    This dataset updates: Every year
    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.
  • 300+ Downloads
    Updated September 17, 2018 | Dataset date: Jan 27, 2018
    This dataset updates: Every three months
    Displacement Tracking Matrix (DTM) Dominica- Hurricane Maria Response
  • 10+ Downloads
    Updated July 6, 2018 | Dataset date: Sep 27, 2017
    This dataset updates: Live
    This map illustrates potentially damaged structures and buildings in Southern Dominica as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 23 September 2017 as post imagery. Within the extent of this map UNITAR-UNOSAT identified in the cloud free areas of southern Dominica 2482 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represent about 80 % of the total number of structures within the analysed area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in Portsmouth  (Saint John Parish) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 20 September 2017 as post imagery. UNITAR-UNOSAT identified in the analysed area (Portsmouth and surroundings) 782 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents 55% of the total number of structures within the cloud free analysed area. The analysis could have been underestimated due to cloud cover. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in Marigot(Saint Andrew Parish) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 23 September 2017 as post imagery. UNITAR-UNOSAT identified in the analysed area Marigot (Saint Andrew Parish) 1,345 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represent about 83 % of the total number of structures within the analysed area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in South Roseau (Saint Georges Parish) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 21 September 2017 as post imagery. UNITAR-UNOSAT identified in the analysed area Roseau South (Castle Comfort, Citronnier and Loubiere) 863 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 70 % of the total number of structures within the analysed area. Evidences of floods and mudflow could be also observed in the area of Wallhouse. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in Pointe Michel (Saint Luke Parish) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 23 September 2017 as post imagery. UNITAR-UNOSAT identified in the analysed area Pointe Michel (St. Luke Parish) 550 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represent about 70 % of the total number of structures within the analysed area. Evidences of floods and mudflow could be also observed along the two rivers that cross the town of Pointe Michel. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in the Central and Southern parts of Dominica (St. Patrick, St. Mak, St. George, St. Luke, St. David & St. Paul Parishes) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. The UNITAR-UNOSAT analysis combined with Copernicus analysis, identified 12,873 potentially damaged structures in this zone. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 70 % of the total number of structures within the analyzed areas. Please note that some areas could not be analyzed due to the cloud cover. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in the north-western part of Dominica (St. John, St. Andrew, St. Peter & St. Joseph Parishes) as detected by satellite images acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades images acquired on 20 and 23 September 2017 as post imagery. Within the extent of this map UNITAR-UNOSAT identified in the cloud free zones about 3723 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 70 % of the total number of structures within the analysed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in the north-western part of Dominica (St. Andrew, St. Joseph & St. David Parishes) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 23 September 2017 and a WorldView-3 image acquired on 1 October 2017 as post imagery. Within the extent of the analyzed areas, UNITAR-UNOSAT identified in the cloud free zones 5,609 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 90 % of the total number of structures within the analysed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in the Southern part of Dominica (St. Luke, St. Mark, St. Georges & St. Patrick Parishes) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades images acquired on 20 and 23 September 2017 as post imagery. Within the extent of this map UNITAR-UNOSAT identified in the cloud free zones about 5032 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represent about 75 % of the total number of structures within the analysed area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates potentially damaged structures and buildings in the southeastern part of Dominica (St. Patrick & St. David Parishes) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. The UNITAR-UNOSAT analysis combined with Copernicus analysis, identified 1304 potentially damaged structures within the extent of this map. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 56 % of the total number of structures within the analysed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 400+ Downloads
    Updated December 1, 2017 | Dataset date: Nov 1, 2017
    This dataset updates: Every month
    Third Round, Displacement Tracking Matrix (DTM) Dominica- Hurricane Maria Response
  • 100+ Downloads
    Updated October 18, 2017 | Dataset date: Oct 14, 2017
    This dataset updates: Every month
    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.
  • Updated October 5, 2017 | Dataset date: Oct 5, 2017
    This dataset updates: Every week
    This dataset contains distribution tracking data for water, food, NFIs and shelter items in Dominica in the aftermath of Hurricane Irma. The coordination team in Dominica has been working with partners to make the data as accurate as possible. Please share your distribution to any locations directly to the available dataset created by the team in Dominica or send your information or queries to hurricanemaria2017@undac.org
  • 100+ Downloads
    Updated October 4, 2017 | Dataset date: Sep 20, 2017
    This dataset updates: Every year
    This file contains 143 populated places in Dominica, with P-codes to administrative level 1. (This file replaces "dma_stle_stl_pt_s1_dominode_pp_V3.zip" uploaded 2017 09 20.) The file can be joined to the Dominica Population Statistics COD found on HDX.
  • 800+ Downloads
    Updated October 4, 2017 | Dataset date: Sep 20, 2017
    This dataset updates: Every year
    Dominica population statistics for populated places and administrative level 1
  • 80+ Downloads
    Updated September 22, 2017 | Dataset date: Sep 29, 2017
    This dataset updates: Every day
    This dataset contains data on who is doing what where (3W) in the Caribbean Hurricanes response.
  • 300+ Downloads
    Updated September 21, 2017 | Dataset date: Sep 21, 2017
    This dataset updates: Every year
    Hurricane Maria peak 3-sec gust footprints in kml format (through 9UT 21st Sept 2017) Credit - Tropical Storm Risk/UCL