Geodata Humanitarian Datasets | Find Crisis Data

OpenStreetMap GIS data on Guinea, Liberia, and Sierra Leone

HDX

1600+ Downloads

Time Period of the Dataset [?]: January 01, 2018-January 01, 2019 ... More

This dataset updates: Never

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.

SHP

WFP and FAO Overview of Countries Affected by the El Niño

HDX

100+ Downloads

Time Period of the Dataset [?]: April 21, 2016-April 21, 2016 ... More

This dataset updates: Never

This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.

CSV
GeoJSON

Pakistan Health Facilities with 3 Word Addresses

what3words (inactive)

100+ Downloads

Time Period of the Dataset [?]: September 01, 2012-September 01, 2012 ... More

This dataset updates: Never

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.

Web App
CSV

Syria Cultural Sites

U.S. Department of State - Humanitarian Information Unit (inactive)

100+ Downloads

Time Period of the Dataset [?]: May 01, 2013-May 01, 2013 ... More

This dataset updates: Never

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.

West African Health Centres - 3 word addresses

what3words (inactive)

50+ Downloads

Time Period of the Dataset [?]: November 03, 2014-November 03, 2014 ... More

This dataset updates: Never

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

Web App
JSON

Health Infrastructure Nepal 3 word Addresses

what3words (inactive)

300+ Downloads

Time Period of the Dataset [?]: August 31, 2015-August 31, 2015 ... More

This dataset updates: Never

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.

Syria Border Crossings

U.S. Department of State - Humanitarian Information Unit (inactive)

700+ Downloads

Time Period of the Dataset [?]: June 11, 2015-June 11, 2015 ... More

This dataset updates: Never

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.

Syria IDP Sites

U.S. Department of State - Humanitarian Information Unit (inactive)

11000+ Downloads

Time Period of the Dataset [?]: June 30, 2015-June 30, 2015 ... More

This dataset updates: Never

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.

IDP Camps Nepal - 3 Word Addresses

what3words (inactive)

200+ Downloads

Time Period of the Dataset [?]: May 05, 2015-May 05, 2015 ... More

This dataset updates: Never

Using OSM's extracts, we have addressed the IDP camps in Nepal to assist those on ground to communicate the location of the camps easily and quickly.

Ebola Treatment Units - 3 Word Addresses

what3words (inactive)

40+ Downloads

Time Period of the Dataset [?]: December 12, 2014-December 12, 2014 ... More

This dataset updates: Never

The Ebola Treatment Units collected by UNMEER now with 3 word addresses so that partners can communicate the precise location of each unit quickly and easily.

Geoservice

Gridded Population Estimates for Yemen using UN COD-PS Estimates 2019, 2023...

WorldPop

100+ Downloads

Time Period of the Dataset [?]: July 01, 2024-March 16, 2025 ... More

This dataset updates: Never

These data were produced by WorldPop at the University of Southampton and World Bank Group . These data include gridded estimates of population at approximately 100m for 2019, 2023 and 2024 along with estimates of the number of people belonging to individual age-sex groups. These results were produced using subnational population estimates for Yemen provided in the Common Operational Dataset on Population Statistics (2019, 2023 COD-PS and 2024 COD-PS ) and Subnational Administrative Boundaries for Yemen provided by OCHA. For further details, please, read the Release Statement. Recommended citations WorldPop and World Bank Group. 2024 Gridded population estimates for Yemen using UN COD-PS estimates 2019, 2023 and 2024, version 1.0. https://data.worldpop.org/repo/prj/WP_WB/YEM/v1/ 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@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@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.

GeoTIFF
PDF

Egypt - Water Courses

OCHA Middle East and North Africa (ROMENA)

20+ Downloads

Time Period of the Dataset [?]: January 01, 2006-January 01, 2006 ... More

This dataset updates: Never

Egypt rivers with classification.

SHP

Kenya - Schools under Digital Literacy Programme

Kenya Open Data Initiative (inactive)

200+ Downloads

Time Period of the Dataset [?]: December 24, 2018-December 24, 2018 ... More

This dataset updates: Never

DLP is targeted at learners in all public primary schools in Kenya and will cover all the 21,729 primary schools, and nearly 1 million 2016 Class 1 pupils.

GeoJSON

Satellite detected water and landslide extents in Kinshasa Province,...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: January 18, 2024-January 18, 2024 ... More

This dataset updates: Never

UNOSAT code: FL20231229COD This map illustrates satellite-detected surface waters and landslide location in Kinshasa Province, Democratic Republic of The Congo, as observed from a WorldView-3 image acquired on 13 January 2024, at 10:36 local time. Within the analysed area of 130km2, approximately 4 km2 of land appear to be flooded and a landslide location observed. Within the analysed area 9,352 buildings are identified as potentially affected by the floods and landslide. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

Réunion: Cyclone - Category 2 - Jan 2024

WFP Advanced Disaster Analysis & Mapping

80+ Downloads

Time Period of the Dataset [?]: January 12, 2024-January 15, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: WFP Advanced Disaster Analysis and Mapping - Cyclone Data

ADAM ID: 1001041_8 Cyclone (category 2) during the period Jan 12 2024-Jan 15 2024 in Miscellaneous (French) Indian Ocean Islands, Madagascar. It impacted 871751 people.

SHP
CSV

Satellite detected water extent in Manakara Atsimo District, Vatovavy...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: January 08, 2024-January 08, 2024 ... More

This dataset updates: Never

UNOSAT code: TC20240102MDG, GDACS ID: 1001040 This map illustrates satellite-detected water extent in Manakara Atsimo District, Vatovavy Fitovinany Region as observed from a Sentinel-1 image acquired on 05 January 2024 at 05:20 local time. Within the extent of this map of about 300 km², a total of about 20 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the detected surface waters, about 6,300 people are potentially exposed or living close to flooded areas. 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). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Satellite detected water extents between 29 December 2023 and 2 January...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: January 08, 2024-January 08, 2024 ... More

This dataset updates: Never

UNOSAT code: FL20240102COG This map illustrates cumulative satellite-detected minimum floodwater using VIIRS in Republic of Congo between 29 December 2023 and 2 January 2024. Within the cloud free analysed area of about 330,000 km2, a total of about 1,000 km2 of lands appear to be affected with flood waters. Based on Worldpop population data and the minimum flood water coverage, ~114,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Minimum floodwater extent indicates the portion of the pixel (375m) covered by 80 to 100% of flood water.

Satellite detected water extent in Vohipeno District, Vatovavy Fitovinany...

United Nations Satellite Centre (UNOSAT)

Time Period of the Dataset [?]: January 05, 2024-January 05, 2024 ... More

This dataset updates: Never

UNOSAT code: TC20240102MDG, GDACS ID: 1001040 This map illustrates satellite-detected water extent in Vohipeno District, Vatovavy Fitovinany Region as observed from a Sentinel-1 image acquired on 05 January 2024 at 05:20 local time. Within the extent of this map of about 600 km², a total of about 50 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the detected surface waters, about 17,700 people are potentially exposed or living close to flooded areas. 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). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Satellite detected water extent in Manja, Morombe & Ankazoabo Districts,...

United Nations Satellite Centre (UNOSAT)

20+ Downloads

Time Period of the Dataset [?]: January 04, 2024-January 04, 2024 ... More

This dataset updates: Never

UNOSAT code: TC20240102MDG, GDACS ID: 1001040 This map illustrates cumulative satellite-detected water extent in Manja, Morombe & Ankazoabo Districts, Madagascar as of 03 January 2024 as observed from a Sentinel-1 image acquired on 03 January 2024 at 05:36 local time. Within the cloud free analysed area of about 5,500 km², a total of about 670 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the detected surface waters, about 18,000 people are potentially exposed or living close to flooded areas. 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). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Madagascar: Cyclone - Tropical storm - Jan 2024

WFP Advanced Disaster Analysis & Mapping

100+ Downloads

Time Period of the Dataset [?]: December 31, 2023-January 03, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: WFP Advanced Disaster Analysis and Mapping - Cyclone Data

ADAM ID: 1001040_10 Cyclone (tropical storm) during the period Dec 31 2023-Jan 03 2024 in Madagascar. It impacted 0 people.

SHP
CSV

Satellite detected water and landslide/mudflow extents in Brazzaville and...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: January 03, 2024-January 03, 2024 ... More

This dataset updates: Never

UNOSAT code: FL20240102COG This map illustrates satellite-detected surface waters and landslides/mudflow extent in Brazzaville and Pool Departments, Republic of Congo, as observed from a Sentinel-2 image acquired on 28 December 2023, at 10:21 local time. Within the analysed area of 30,000 ha, approximately 190 ha of landslide scars/mudflow extent are observed and about 230 ha of land appear to be flooded. Based on Worldpop population data, the detected surface waters and the landslide scar/mudflow extent, about 15,000 people are potentially exposed or living close to landslide and flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT).

Satellite detected water and landslide extents in Kinshasa Province,...

United Nations Satellite Centre (UNOSAT)

Time Period of the Dataset [?]: January 02, 2024-January 02, 2024 ... More

This dataset updates: Never

UNOSAT code: FL20231229COD This map illustrates satellite-detected surface waters and landslides in Kinshasa Province, Democratic Republic of The Congo, as observed from a Sentinel-2 image acquired on 28 December 2023, at 10:21 local time. Within the analysed area of 44,000 ha, approximately 3 ha of landslide scars are observed and about 460 ha of land appear to be flooded. Based on Worldpop population data, the detected surface waters and the landslide scar extent, about 25,000 people are potentially exposed or living close to landslide and flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT).

Bottom-up gridded population estimates for Nigeria, version 2.1

WorldPop

60+ Downloads

Time Period of the Dataset [?]: August 22, 2023-March 16, 2025 ... More

This dataset updates: Never

This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-sex groups. Version 2.1 is an update to the previous version 2.0 gridded population estimates and is based on a correction of the settlement map. These model-based population estimates most likely represent the time period around 2019, corresponding to the period when the satellite imagery was processed to generate building footprints. Populations are mapped only into areas where residential settlements are predicted. These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 Bridge Funding project with funding from the Bill and Melinda Gates Foundation (INV-045694). Project partners included the GRID3 Inc and the Center for International Earth Science Information Network in the Earth Institute at Columbia University. Statistical modelling was originally led by Chris Jochem and Doug Leasure with additional support and oversight from Attila Lazar and Andy Tatem. Ortis Yankey led the population map update with additional support from Edith Darin. 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@worldpop.org. SUGGESTED CITATIONS WorldPop. 2023. Bottom-up gridded population estimates for Nigeria, version 2.1. WorldPop, University of Southampton. DOI: 10.5258/SOTON/WP00765

PDF
GeoTIFF

Satellite detected landslide extent in Mogitu & Ganana Ward, Hanang...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: December 20, 2023-December 20, 2023 ... More

This dataset updates: Never

UNOSAT code: LS20231208TZA This map illustrates satellite detected landslides in Hanang District, Manyara Region, Tanzania as observed from a Sentinel-2 acquired on 19 December 2023 at 11:01 local time. Within the analyzed area of 5,800 ha, about 55 ha of mudflow scars are observed. 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).

Satellite detected landslide extent in the Nggela Constituency, Central...

United Nations Satellite Centre (UNOSAT)

Time Period of the Dataset [?]: December 14, 2023-December 14, 2023 ... More

This dataset updates: Never

UNOSAT code: TC20231206SLB, GDACS ID: 1001038 Satellite detected landslide extent in the Nggela Constituency, Central Province, Solomon Island as of 14 December 2023 This map illustrates satellite-detected landslides in Nggela Constituency, Central Province, Solomon Islands, as observed from a Sentinel-2 satellite acquired on 14 December 2023 at 10:39 local time. Within the analyzed area of 400 ha about 12 ha of landslide extent is observed. UNOSAT identified 7 potentially affected structures. 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).