This is a repository for PDF files that are linked on the OCHA Centre for Humanitarian Data's website, https://centre.humdata.org. Please note that if you wish to access these files, we recommend you use the Resources section of the Centre's website rather than downloading from HDX.
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.
This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University
Development assistance data from AFD - French Development Agency
The dataset covers French development assistance, on ongoing projects in 2015. The data are disclose as receivers agreed France to share it. AFD aims at updating the data every trimester to take into account the flow of new project being funded.
Cumulative fundings were update December the 30th 2015 and respect IATI standards.
Données de l'aide au développement de l' AFD - Agence Française de Développement
Les données portent sur l’aide au développement française sur les projets réalisés en souverain et en cours d’exécution en 2015. Ces données peuvent être publiées dès lors que l'accord de la contrepartie a été obtenu.L'Agence Française de Développement visera une actualisation trimestrielle de la publication de ces données, notamment pour prendre en compte les nouveaux projets de développement financés par l’Agence. Il est à noter que les montants cumulés des versements ont été mis à jour le 30 décembre 2015. Ces données respectent le standard IATI (Initiative internationale pour la transparence de l’aide).
We have provided the 3 word addresses of each health centre within the West African Region.
what3words is a simple, real-time, location referencing system which solves many of the key logistical issues facing aid and humanitarian organisations, for whom street addresses, GPS co-ordinates, and other systems don't exist or are problematic.
Using words means non-technical people can find any location more accurately and most importantly, communicate it more quickly, more easily and with less ambiguity than any other system.
For more information, to get our API or batch encode your coordinates visit http://www.developer.what3words.com
This dataset depicts the Health Infrastructure of Nepal as points with 3 word addresses so that whoever is on ground can easily communicate the location of these centres.
The Syria Cultural Sites dataset contains geographic location (point geometry), name, type, and area name of over 1000 cultural heritage sites and museums in Syria compiled by the Cultural Heritage Center, Bureau of Educational and Cultural Affairs, U.S. Department of State (http://eca.state.gov/cultural-heritage-center) as of Spring 2013. The sites are categorized by type, which include but not limited to, archaeological sites, roman ruins, mosques, schools, churches, cemeteries, and towns. The data contained herein is entirely unclassified.
Data as of June 11, 2015. The "Syria Border Crossings" dataset contains verified data about the geographic location (point geometry) and name of border crossings for Syria. Compiled by the U.S. Department of State, Humanitarian Information Unit (https://hiu.state.gov/), each attribute in the dataset is verified against multiple sources. Locations are only accurate down to the city level. The data contained herein is entirely unclassified and is current as of 16 April 2015. The data is updated as needed.
This dataset is primarily hosted on the State GeoNode, the open geographic data platform of the U.S. Department of State.
Data as of early 2016. The "Syria IDP Sites" dataset is compiled by the U.S. Department of State, Humanitarian Information Unit (INR/GGI/HIU). This dataset contains open source derived data about the geographic locations (point geometry) of identified tent camps and other locations, such as collective centers, schools, mosques, sports facilities, host families, etc. in towns inside Syria where displacement has taken place. Sources of this information include the United Nations, the Assistance Coordination Unit, the Syria Needs Assessment Project, NGOs, and media reports. Location coordinates are at the city level and are plotted using the Syria P-Code system (http://www.mapaction.org/map-catalogue/mapdetail/2753.html) and NGA GEOnet Names Server (http://earth-info.nga.mil/gns/html) datasets. The field "PCode" is a combination of the all the administrative level and community level P-Codes for a specific location. Camp locations are verified using high-resolutions commercial satellite imagery. In the "Designation" field "IDP Site" refers to informal or formal settlements for specific IDP use. This dataset will be updated as needed and is current as of late June 2015.
This dataset is primarily hosted on the State GeoNode, the open geographic data platform of the U.S. Department of State.
The dataset is based on the assessments and Health Resources Availability and Mapping (HeRAM) carried out by World Health Organization (WHO) in collaboration with health cluster partners during different emergencies in Pakistan. Please note that it is not necessary that the assessment covered all the health facilities in a particular district. These have now been provided with a 3 word address so those on the ground can communicate the location of each facility.
This lists all humanitarian contributions to Gambia in 2015 as reported to FTS .
The resource listed here is the output from the FTS api in IATI v2 format.
For more information on this dataset visit our website
UNOSAT code FL20230807BGD This map illustrate the number of affected buildings within specific district boundaries of interest in Bandarban, Cox's Bazar, Chattogram, and Rangamati Districts, located in Chattogram Division, Bangladesh as of 12 to August 2023. And using an automated analysis with Artificial Intelligence based methods.
Within the analyzed area of about 17,000 km2 and, about 350km2 of lands appear to be flooded. Based on Worldpop population data from 2020, the flood water extent and Microsoft building footprint , ~415,000 people are potentially exposed or living close to flooded areas and about 932 building potentially affected by floods.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).