• Updated 14 January 2022 | Dataset date: November 30, 2018-November 30, 2018
    The aim of the Sub-Area Assessment is to track and monitor IDP and returnee populations in Yemen. Information is collected on population size, area of origin, current location, duration of displacement, shelter types, priority needs and movement trends. Among the main outputs of the Sub-Area Assessment, is a list of locations where IDPs and/or returnees are present that can be used to inform more detailed assessments at the location level, including the annual Multi-Cluster Location Assessment (MCLA). DTM field staff, along with KIs, use the Sub-Area Assessment tool to capture locations, which are matched to the identified locations in the OCHA Common Operational Dataset (P-Codes).
    1200+ Downloads
    This dataset updates: Never
  • Updated 9 July 2020 | Dataset date: May 01, 2018-March 31, 2022
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    10+ Downloads
    This dataset updates: As needed
  • Updated 9 July 2020 | Dataset date: February 01, 2017-June 30, 2022
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    30+ Downloads
    This dataset updates: As needed
  • Updated 9 July 2020 | Dataset date: October 01, 2019-March 31, 2022
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    This dataset updates: As needed
  • Updated 9 July 2020 | Dataset date: March 01, 2017-August 31, 2022
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    10+ Downloads
    This dataset updates: As needed
  • Updated 14 January 2022 | Dataset date: June 01, 2015-September 30, 2021
    Projets en cours d'execution en RD Congo, ainsi que le nombre de personnes ciblées durant la période aggrégées par zone de santé et par secteur. Seuls les projets humanitaires sont repris dans ce fichier.
    3100+ Downloads
    This dataset updates: Every three months
  • Updated 14 January 2022 | Dataset date: January 09, 2021-January 09, 2021
    Drone orthomosaic. Post Tropical Storm Chalane Mapping, Malawi conducted with Crowddroning by GLOBHE. More maps and data available on demand upon request from locations globally at: https://globhe.com/drone-data-request MORE CROWDDRONING BY GLOBHE Webb: https://globhe.com/ Facebook: https://www.facebook.com/Crowddroning Twitter: https://twitter.com/globhedrones Instagram: https://www.instagram.com/globhedrones/ LinkedIn: https://www.linkedin.com/company/globhedrones/
    This dataset updates: Never
  • Updated 13 January 2022 | Dataset date: January 01, 2021-June 22, 2021
    Consolidated 4W data (Who does What, Where, and When) from OCHA Colombia, collected from the clusters and organizations involved in the response.
    1000+ Downloads
    This dataset updates: Every six months
  • Updated 13 January 2022 | Dataset date: October 10, 2021-October 10, 2021
    The Who does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in Burundi at Admin 1.
    1700+ Downloads
    This dataset updates: Every six months
  • These data consist of modelled gridded population estimates produced at a spatial resolution of approximately 100m across the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (DRC). The estimates comprise total population counts created using a Bayesian statistical model and post-hoc breakdowns in 40 age and sex groups. The main input data were derived from a dedicated microcensus survey carried out in the targeted provinces throughout March and April 2021. The microcensus was led by the Flowminder Foundation, the École de Santé Publique de Kinshasa, the WorldPop Research Group at the University of Southampton and the Bureau Central du Recensement, which is part of the Institut National de la Statistique of the DRC. Other essential input data include metrics derived from building footprints, which were automatically delineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010 and 2021. The modelled population estimates represent the period of the microcensus but their consistency may be impacted by the accuracy of the building footprints, particularly in the areas where the satellite imagery used for automatic delineation was outdated. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 Mapping for Health Project. This project was delivered under the leadership of the Ministry of Public Health, Hygiene and Prevention of the DRC and funded by Gavi, the Vaccine Alliance (RM 867204 20A2). The project was led by the Flowminder Foundation and the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the University of Southampton and national partners including, but not limited to, the École de Santé Publique de Kinshasa and both the Bureau Central du Recensement and the Institut National de la Statistique. This work was a continuation of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). The study was approved by the Faculty Ethics Committee of the University of Southampton (ERGO II 62716). The production of these data was led by Gianluca Boo (WorldPop](https://www.worldpop.org/) ) with support from Roland Hosner (Flowminder Foundation), Pierre Z Akilimali (École de Santé Publique de Kinshasa), Edith Darin (WorldPop), Heather R Chamberlain (WorldPop), Warren C Jochem (WorldPop), Patricia Jones (WorldPop), Roger Shulungu Runika (Institut National de la Statistique), Henri Marie Kazadi Mutombo (Bureau Central du Recensement), Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). The authors acknowledge the support of their respective institutions in the completion of this work. Recommended citation: G Boo, R Hosner, PZ Akilimali, E Darin, HR Chamberlain, WC Jochem, P Jones, R Shulungu Runika, HM Kazadi Mutombo, AN Lazar and AJ Tatem. 2021. Modelled gridded population estimates for the HautKatanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (2021), version 3.0. WorldPop, University of Southampton, Flowminder Foundation, École de Santé Publique de Kinshasa, Bureau Central du Recensement and Institut National de la Statistique. doi:10.5258/SOTON/WP00720
    This dataset updates: As needed
  • Updated 13 January 2022 | Dataset date: January 01, 2021-December 31, 2021
    These datasets contains incidents in which aid access, education and healthcare services were impacted by explosive weapons. Insecurity Insight collaborates with the International Network on Explosive Weapons (INEW) in producing research and analysis on the harm and use of explosive weapons for the Explosive Weapons Monitor by documenting their effects on health care, education, and aid access. Every month the Explosive Weapons Monitor publishes a bulletin with incidents from around the world as reported in open sources.
    100+ Downloads
    This dataset updates: As needed
  • Updated 6 December 2021 | Dataset date: January 01, 2018-January 01, 2019
    This dataset contains shapefiles for Guinea, Liberia, and Sierra Leone from the OpenStreetMap (OSM) project. Each country has its individual file. The dataset counts with contributions of hundreds of users. This dataset is updated daily. The original dataset can be downloaded from the OSM West Africa Ebola response wiki.
    2000+ Downloads
    This dataset updates: Never
  • The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    10+ Downloads
    This dataset updates: As needed
  • Updated 8 July 2020 | Dataset date: April 01, 2017-March 31, 2022
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    20+ Downloads
    This dataset updates: As needed
  • Governments are taking a wide range of measures in response to the COVID-19 outbreak. The Oxford COVID-19 Government Response Tracker (OxCGRT) aims track and compare government responses to the coronavirus outbreak worldwide rigorously and consistently. The OxCGRT systematically collects information on several different common policy responses governments have taken, scores the stringency of such measures, and aggregates these scores into a common Stringency Index. For more, please visit > https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker
    6300+ Downloads
    This dataset updates: Live
  • Updated 6 January 2022 | Dataset date: May 28, 2020-January 25, 2022
    The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset, currently at version 10.2 (published 28 May 2021). Sources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery of the data involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground. Attributes -- The dataset uses the following attributes: Country Code: Country-level codes are from the Geopolitical Entities, Names, and Codes Standard (GENC). The Q2 code denotes a line representing a boundary associated with an area not in GENC. Country Names: Names approved by the U.S. Board on Geographic Names (BGN). Names for lines associated with a Q2 code are descriptive and are not necessarily BGN-approved. Label: Required text label for the line segment where scale permits. Rank/Status: Rank 1: International Boundary, Rank 2: Other Line of International Separation, Rank 3: Special Line Notes: Explanation of any applicable special circumstances. Cartographic Usage -- Depiction of the LSIB requires a visual differentiation between the three categories of boundaries: International Boundaries (Rank 1), Other Lines of International Separation (Rank 2), and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Additional cartographic information can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues (https://hiu.state.gov/data/cartographic_guidance_bulletins/). Questions -- Direct inquiries to internationalboundaries@state.gov. Additional formats and web services can be found on the State Department Data Catalog: https://geonode.state.gov
    200+ Downloads
    This dataset updates: Every year
  • Updated 5 January 2022 | Dataset date: October 01, 2021-December 16, 2022
    A comprehensive surveys of existing schools in the Fond-des-Blancs commune and surrounding areas.
    This dataset updates: As needed
  • DTM is tracking in/out movement of displaced people in 4 Provinces hit by IDAI cyclone.
    6200+ Downloads
    This dataset updates: Never
  • Updated 12 January 2022 | Dataset date: August 17, 2020-January 25, 2022
    Admin Level 1 Boundaries (Provinces) and Admin Level 2 Boundaries (Districts) of São Tomé and Principé REFERENCE YEAR: 2020 The dataset represents the provinces and districts of São Tomé and Principé with harmonized PCODE of ROWCA and Humanitarian Response pcodes. These boundaries are suitable for database or GIS linkage to the Sao Tome and Principe - Subnational Population Statistics.
    1500+ Downloads
    This dataset updates: As needed
  • Updated Live | Dataset date: December 15, 2020-January 25, 2022
    This dataset contains data obtained from a variety of sources and transformed into a form suitable for driving the Covid-19 Data Explorer. The visual itself is driven by a JSON file which contains the same data as the resources in this dataset which point to published csvs from a Google spreadsheet.
    1300+ Downloads
    This dataset updates: Live
  • Updated 11 January 2022 | Dataset date: June 01, 2020-January 25, 2022
    This study includes information on the population of all cities and towns outside the control of the Regime in Syria. The study is updated monthly, in that IMU enumerators of ACU track the population in all areas outside the control of the regime, along with movements of displacement and return on a permanent basis. This study also presents the total number of population and gender ratio, the total number of IDPs and the types of shelters in which they are settled, the number of newly displaced people during the last month and the types of shelters in which they are settled, the number of those who left and the reasons that forced them to leave their home towns, the number of returnees during the last month with their most critical needs. The Study presents information on the situation of the local councils in areas to which the residents returned during the past month, availability of basic services in areas of return, evaluation of these services, decision-makers and primary service providers, and sources of income for returnees. The study data can be shown at different levels through the filter bar at the top of the page; it is also possible to display the graphic figures at three levels (district - sub-district - community) through the buttons at the bottom of the figures. Maps can be shown at two levels (district - sub-district) through the two buttons at the bottom of the map. Data can be downloaded from the last page of the study. For more details, please contact us through IMU email address: imu@acu-sy.org
    1000+ Downloads
    This dataset updates: Every month
  • Updated 11 January 2022 | Dataset date: June 01, 2017-January 25, 2022
    This dashboard highlights the living situation in Syria by showing the prices of basic market items. How to use this product: The first three pages track price change chronologically on governorate level, with ability to compare between them by choosing one or more. The subsequent pages show the prices of market items on the governorate and sub-district level with an item availability heat map of any selected item on any selected level and period. You can select one of the listed items in one sub-district or more. When you choose a governorate its subdistrict(s) will be highlighted according to the availability of the selected item in the selected governorate(s).
    5300+ Downloads
    This dataset updates: Every month
  • Updated 23 October 2020 | Dataset date: May 15, 2020-May 15, 2020
    Indicadores WASH para áreas metropolitanas de Colombia según la GEIH 2020
    50+ Downloads
    This dataset updates: As needed
  • Updated 24 November 2021 | Dataset date: November 23, 2021-January 25, 2022
    Esta base de datos contiene los cálculos de People in Need (PiN) del área de responsabilidad (AdR) de Violencia Basada en Género (que pertenece al Clúster de Protección) realizados en el marco del Ciclo de Programación Humanitaria de Colombia para 2022.
    90+ Downloads
    This dataset updates: As needed
  • Updated 11 January 2022 | Dataset date: January 01, 2022-December 31, 2022
    Turkey Refugee Camps
    600+ Downloads
    This dataset updates: Every year