The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Dominican Republic: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Roads in Ukraine from:

• UN Global Logistics Cluster (Ukraine: Logistics Datasets - Humanitarian Data Exchange (humdata.org))
• Contains highways and primary roads
• Humanitarian Open Street Map (HOTOSM Ukraine Roads (OpenStreetMap Export) - Humanitarian Data Exchange (humdata.org))

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Tonga: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

NOTE: We plan to no longer update this dataset after May 22 2022.

These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day.

Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/

This is an excel mapping tool that was built based on Dominican Republic administrative boundaries (admin3). Available on HDX: Available on HDX: https://data.humdata.org/dataset/dominican-republic-administrative-boundaries-levels-0-6.. The population dataset is a sample data. The tool is built to help people to quickly map their datasets.

The ERCC (Emergency Response Coordination Center), as part of DG ECHO, coordinates the EU response to natural and man-made disasters. The ERCC, in close cooperation with JRC, publishes on a daily basis a product called ‘ECHO Daily Map’. The maps are reflecting data on various emergency situations, such as floods, earthquakes, forest fires, pandemics; climate change related topic such as sea-ice anomalies and humanitarian aid topics such as migration in third countries. The source of the data is mentioned in the maps.

This dataset contains South Sudan data for the Map Explorer that is derived from other data.
WARNING: Derived data - go to original sources!
Sources:
South Sudan Administrative Boundaries
2017 Humanitarian Needs Overview for South Sudan
ACLED Conflict Data for Africa Realtime
ACLED Conflict Data for Africa 1997-2017
WFP VAM MarketMonitor
CBPF Allocations and Contributions

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Marshall Islands: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.

This is an excel mapping tool that was built based on Cuba administrative boundaries (admin2) - extracted from the GADM database (www.gadm.org), version 2.8, November 2015. Available on HDX: https://data.humdata.org/dataset/cuba-administrative-boundaries-levels-0-and-1-from-gadm). The population dataset is a sample data. The tool is built to help people to quickly map their datasets.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

MapAction knows that providing geospatial expertise to humanitarian situations can greatly improve outcomes for the people affected. Over 20 years, in 140+ humanitarian emergencies in 80 countries as well as many hundreds of disaster preparedness events, MapAction has provided disaster response agencies with the mapping, geospatial and data capabilities necessary to make the vital decisions to support vast numbers of people. What we do We are a non-profit organisation collaborating with partners around the world to prepare for and respond to humanitarian emergencies. We strive to ensure global, regional, national and local disaster management and humanitarian agencies have access to the maps, visualised data, information and analysis that they need to make key decisions, at the right times, to save lives and reduce suffering. People already vulnerable to humanitarian crises face the greatest threats from a changing climate, which compounds existing challenges. MapAction works to ensure that they, and the agencies and governments who support them, have access in critical moments, to the information and analysis that they need. In a humanitarian crisis response coordinators need to quickly understand who is most affected, where they are, what those people need, how to provide it and much more besides. The picture changes by the hour, and the faster and more effectively the incoming data can be mapped and visualised, to get a clearer understanding of the transformed landscape, the more efficient and targeted the response can be.

Sea Ports in Ukraine from UN Global Logistics Cluster (Ukraine: Logistics Datasets - Humanitarian Data Exchange (humdata.org)) and ports (including inland) from Humanitarian Open Street Map (HOTOSM Ukraine Sea Ports (OpenStreetMap Export) - Humanitarian Data Exchange (humdata.org)). Downloaded 31 March 2022.

NCDOT Helene Humanitarian Emergency 2024This map contains many civic, medical, safetly, resource locations within the Wester North Carolina Region impacted by Tropical Storm Helene. The layers come from a diverse area of sources. One is a Crowd-sourced layer and should be regarded with caution.Layers included in this application are as follow:Asheville Crowdsourced Disaster ****This is Crowd Sourced and should be used with high caution. ****Shelters WebEOC Prod - Listing available shelters and their current capacity. Shelters and Water Distribution - WebEOC layer showing available water and sheltersNCDOT Statewide Fuel Depot Sites - For NCDOT vehicles refueling.Open Shelters - FEME Showing Only Open Shelters - made available from https://spartagis.ncem.org/arcgiPublic Water Supply Sources - An NCONE Map service.Law Enforcement and Medical Services and Facilities - NCONE map services for each (Law, medical, & medical emergencies)NCDOT Rally Sites - a layer made available to NCDOT field crews for their edit purposes, if needed.NCDOT Roadway linework from the NCDOT GIS-T Unit.NCDOT City BoundariesNCDOT Division BoundariesNC County BoundariesThis data was last revised at 4pm Oct. 3, 2024. Specifically, the Crowd Source layer was updated to reflect newly added locations.SPECIAL USE CONSTRAINTSThese layers were pulled together for a natural disaster emergency humanitarian aid effort. They were put into the map together under extraordinary conditions when time constraints were critical. Data sources were assembled in an ad hoc fashion to meet the crisis need.Contact Information: NCDIT-T GIS Unit -- Geospatial Services Group https://apps.ncdot.gov/dot/directory/authenticated/UnitPage.aspx?id=18918

OpenStreetMap exports for use in GIS applications.

This theme includes all OpenStreetMap features in this area matching:

highway IS NOT NULL

Features may have these attributes:

• highway
• surface
• name
• smoothness
• lanes
• width
• source
• layer
• oneway
• bridge

This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Admin3 boundaries (national divisions) The Administrative Boundaries used by the Data in Emergencies Hub are the result of a collection of international and subnational divisions currently used by FAO country offices for mapping and reporting purposes. With only a few exceptions, they are mostly derived from datasets published on The Humanitarian Data Exchange (OCHA). The dataset consists of national boundaries, first subdivision and second subdivision for Bangladesh, Madagascar, Mali, Philippines, Senegal, Sri Lanka, Tchad, Uganda and Ukraine.In the Feature Layer, the administrative boundaries are represented by closed polygons, administrative levels are nested and multiple distinct polygons are represented as a single record. The Data in Emergencies Hub team is responsible for keeping the layer up to date, so please report any possible errors or outdated information. The boundaries and names shown and the designations used on these map(s) do not imply the expression of any opinion whatsoever on the part of FAO concerning the legal status of any country, territory, city, or area or of its authorities, or concerning the delimitation of its frontiers and boundaries. Dashed lines on maps represent approximate border lines for which there may not yet be full agreement. The final boundary between the Sudan and South Sudan has not yet been determined. The final status of the Abyei area is not yet determined. The dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. The final status of Jammu and Kashmir has not yet been agreed upon by the parties.

The world population data sourced from Meta Data for Good is some of the most accurate population density data in the world. The data is accumulated using highly accurate technology to identify buildings from satellite imagery and can be viewed at up to 30-meter resolution. This building data is combined with publicly available census data to create the most accurate population estimates. This data is used by a wide range of nonprofit and humanitarian organizations, for example, to examine trends in urbanization and climate migration or discover the impact of a natural disaster on a region. This can help to inform aid distribution to reach communities most in need. There is both country and region-specific data available. The data also includes demographic estimates in addition to the population density information. This population data can be accessed via the Humanitarian Data Exchange website.

Country Population (Admin0) using aggregated Facebook high resolution population density data (https://data.humdata.org/organization/facebook).The world population data sourced from Facebook Data for Good is some of the most accurate population density data in the world. The data is accumulated using highly accurate technology to identify buildings from satellite imagery and can be viewed at up to 30-meter resolution. This building data is combined with publicly available census data to create the most accurate population estimates. This data is used by a wide range of nonprofit and humanitarian organizations, for example, to examine trends in urbanization and climate migration or discover the impact of a natural disaster on a region. This can help to inform aid distribution to reach communities most in need. There is both country and region-specific data available. The data also includes demographic estimates in addition to the population density information. This population data can be accessed via the Humanitarian Data Exchange website.

Mines remaining from the Homeland War are a huge problem in Croatia. The joint work of experts in humanitarian demining and military doctrines in certain geographical areas, and scientists of various profiles, has resulted in a concept for producing mine danger maps, which show areas and levels of potential hazards from mines, i.e. suspected hazardous areas. This paper presents the concept for producing mine danger maps for a suspected hazardous area (Svilaja, Croatia). The input data comprise information stored in mine information systems and additional data collected on the suspected hazardous area (e.g. bunkers and shelters for tanks, artillery and people). The resulting maps (Main Map) seek to improve the identification of areas where there is no threat so that parts of suspected hazardous areas can be proposed for mine reduction, or suspected hazardous areas can be better defined.

OHDR has published Natural Areas in Guinea on their website in support of the Ebola crisis. Data collected for the 2014 West Africa Ebola Response, an Activation of the Humanitarian OSM Team to provide map data to assist the response to this disease outbreak. OpenStreetMap offers an online map (and spatial database) which is updated by the minute. Various online maps are based on OpenStreetMap including Navigation tools such as OSRM. Tools and services allow data extracts for GIS specialists, Routable Garmin GPS data, Smartphone GPS navigation, and other device-compatible downloads. With an internet connection, regular syncing is possible with open access to the community contributed data as it comes in, with OpenStreetMap's bulk data downloads ideal for use offline. In addition, maps can also be printed to paper.Browse the Activation Area to get a feel for the data that is currently available. Different map styles including an Humanitarian style can be selected on the right side, and some data may not render (appear) on the map, but could be exported from the underlying database (See export section below).