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  • Updated 30 June 2022 | Dataset date: January 31, 2017-July 01, 2022
    This dataset updates: Every week
    Congo, The Democratic Republic of the Weekly staple food price data collected by FEWS NET since 2017.
  • 10+ Downloads
    Updated 30 June 2022 | Dataset date: January 31, 1995-July 01, 2022
    This dataset updates: Every month
    Somalia Monthly staple food price data collected by FEWS NET since 1995.
  • Updated 30 June 2022 | Dataset date: January 31, 2005-July 01, 2022
    This dataset updates: Every month
    Kenya Monthly staple food price data collected by FEWS NET since 2005.
  • Updated 30 June 2022 | Dataset date: June 11, 2021-July 01, 2022
    This dataset updates: Every week
    South Sudan Weekly staple food price data collected by FEWS NET since 2021.
  • Updated 30 June 2022 | Dataset date: December 18, 2019-July 01, 2022
    This dataset updates: Every week
    Ethiopia Weekly staple food price data collected by FEWS NET since 2019.
  • Updated 30 June 2022 | Dataset date: January 31, 2002-July 01, 2022
    This dataset updates: Every week
    Chad Weekly staple food price data collected by FEWS NET since 2002.
  • 4600+ Downloads
    Updated 30 June 2022 | Dataset date: May 31, 2020-May 31, 2020
    This dataset updates: Every day
    Aggregated figures for Natural Disasters in EM-DAT More on the EM-DAT database : ( website / data portal ). Each line corresponds to a given combination of year, country, disaster subtype and reports figures for : number of disasters total number of people affected total number of deaths economic losses (original value and adjusted)
  • 10000+ Downloads
    Updated 30 June 2022 | Dataset date: June 30, 2022-June 30, 2022
    This dataset updates: Every day
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
  • 100+ Downloads
    Updated 30 June 2022 | Dataset date: April 09, 2020-April 09, 2020
    This dataset updates: Every day
    This map displays continuously updated data from the USGS Earthquakes and Shakemaps. This map is provided by the Esri Disaster Response Program.
  • 20+ Downloads
    Updated 30 June 2022 | Dataset date: May 06, 2020-May 06, 2020
    This dataset updates: Every day
    This includes layers for detectable thermal activity from VIIRS satellites for the last 7 days and MODIS satellites for the last 48 hours. VIIRS Thermal Hotspots and Fire Activity is a product of NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) Earth Observation Data, while MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), both a part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World. The application includes live feed sources for US wildfire reports (I-209), perimeters, MODIS hot spots, wildfire conditions / red flag warnings, wildfire potential and weather radar. Each of these layers provides insight into where a fire is located, its intensity and the surrounding areas susceptibility to wildfire.
  • 30+ Downloads
    Updated 30 June 2022 | Dataset date: May 05, 2020-May 05, 2020
    This dataset updates: Every day
    Living Atlas live feed sources for hurricane path, observed path, forecast path, and intensity of tropical cyclone activity (hurricanes, typhoons, cyclones) from the National Hurricane Center and Joint Typhoon Warning Center
  • 800+ Downloads
    Updated 30 June 2022 | Dataset date: January 04, 1999-July 01, 2022
    This dataset updates: Every day
    Reference historic FX rates quoted by the European Central Bank (ECB) converted to USD base currency. There are two resources - one with USD as the quote currency (more standard x/USD) and another with USD as the base currency (USD/x). Note that where the rate is 0 or NaN, it means that the currency existed in the past but no longer exists.
  • 20+ Downloads
    Updated 30 June 2022 | Dataset date: May 06, 2020-May 06, 2020
    This dataset updates: Every day
    Live feed sources on severe weather across the United States. The Current Weather and Wind Station Data layer is created from hourly METAR station data provided from NOAA and contains approximately 11 weather variables for each location.
  • 90+ Downloads
    Updated 30 June 2022 | Dataset date: March 13, 2020-July 01, 2022
    This dataset updates: Every day
    Number of COVID-19 confirmed cases by region and date
  • The "GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of settlement points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: settlement point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_settlements_names_V01.gdb The following layers are included in the gdb: codebook__settlements_names GRID3_DRC_settlements_names_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/pvdz-4x94. Accessed DAY MONTH YEAR.
  • The "GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of school points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work. the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS and Novel-T. GRID3 Mapping for Health in DRC is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: schools point data and a table with the field descriptions for the layer. File name: GRID3_DRC_schools_V01.gdb The following layers are included in the gdb: codebook_schools GRID3_DRC_schools_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces- Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/a3d6-m921. Accessed DAY MONTH YEAR
  • The "GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of religious centre points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). This dataset is one of five (5) datasets (along with the Settlements, Health Facilities, Health Catchment Area Boundaries, and Schools datasets)included in this Version 01 release. To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one geospatial layer: religious centre point data and a table with the field descriptions for the layer. File name: GRID3_DRC_religious_centers_V01.gdb The following layers are included in the gdb: codebook__religious_centers GRID3_DRC_religious_center_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces - Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/z4vq-h095. Accessed DAY MONTH YEAR
  • 10+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-July 01, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health facility points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of four layers: health facility point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_health_facilities_V01.gdb The following layers are included in the gdb: codebook_health_facilities GRID3_DRC_bcz_5_prov_V01 (The “BCZ” refers to the Bureau central de la Zone de Santé (Central Office of the Health Zone), which constitutes the framework structure for the organization and operation of the health zone. It is located either within the Hôpital Général de Référence (General Reference Hospital), or outside it but inside the health zone. The BCZ is the operational level of the DRC Health System and level of implementation of strategies from the Ministry of Health.) GRID3_DRC_health_facilities_5_prov_V01 (Government, NGO, or private health facilities that offer vaccination or public health services.) GRID3_DRC_KN_secondary_health_facilities_1_prov_V01 (The main goal of data collection conducted for the EPI was to identify health facilities (public and private) that provided services for public health and routine immunisations. However, at the demand of the DSNIS, all the facilities, public or private, were also geo-referenced. The healthcare services density is such in Kinshasa (with various facilities for private services, specialists, and faith healers opening and closing quite frequently) that GRID3 created a secondary health facilities layer to be able to differentiate the main public structures from others.) Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/0bvp-kp75. Accessed DAY MONTH YEAR.
  • 10+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-July 01, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health area boundary polygons with names and attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative delivered in partnership with Flowminder and CIESIN (Columbia University), in collaboration with WorldPop at the University of Southampton, the Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: health catchment area polygon data and a table with the field descriptions for the layers. Filename: GRID3_DRC_health_catchment_area_boundaries_V01.gdb The following layers are included in the gdb: GRID3_DRC_health_catchment_zone_boundaries_5_prov_V01 GRID3_DRC_health_catchment_area_boundaries_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hzrd-yq54. Accessed DAY MONTH YEAR.
  • 20+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-July 01, 2022
    This dataset updates: Every year
    Cameroon administrative level 0-3 sex and age disaggregated projected 2022 population statistics REFERENCE YEAR 2022 These tables are suitable for database or GIS linkage to the Cameroon - Subnational Administrative Boundaries layers using the ADM0, and ADM1_PCODE fields.
  • 500+ Downloads
    Updated 29 June 2022 | Dataset date: February 24, 2022-July 01, 2022
    This dataset updates: Every week
    Data collected by the OCHA/UNDP Connecting Business initiative (CBi) on cash and in-kind donations made by private sector entities (corporations and corporate-affiliated foundations) to help support the the humanitarian response in Ukraine. This data is used to power the Ukraine Private Sector Donations Tracker, available at bit.ly/Biz4UkraineTracker.
  • 1000+ Downloads
    Updated 29 June 2022 | Dataset date: September 01, 2017-September 30, 2021
    This dataset updates: Never
    The dataset contains number of IDPs, Returnees (households and individuals) at sub national levels. Their place of origin and date. The dataset also has sectoral needs information e.g. Shelter, Education etc.
  • 3200+ Downloads
    Updated 29 June 2022 | Dataset date: February 13, 2019-July 01, 2022
    This dataset updates: Every year
    Nepal administrative levels 0-2 sex and age disaggregated projected 2022 population statistics REFERENCE YEAR: 2022 These CSV tables are suitable for database or GIS linkage to the Nepal - Subnational Administrative Boundaries polygon shapefiles using the ADM0, ADM1, and ADM2_Pcode fields.
  • 300+ Downloads
    Updated 29 June 2022 | Dataset date: January 01, 2022-June 28, 2022
    This dataset updates: Every week
    Number of Refugees returning to Afghanistan for the period of 01 January 2022 to 28 June 2022 by district of destination and origin.
  • 400+ Downloads
    Updated 29 June 2022 | Dataset date: April 01, 2021-June 27, 2022
    This dataset updates: Every week
    This dataset contains the number of confirmed cases, recoveries and deaths by Governorate due to the Coronavirus pandemic in Palestine.