AndreaBozzo/ceres-open-data-index huggingface dataset:
State of Palestine - Population Density

<b>WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. 
Please make sure you have read our <a href="https://www.worldpop.org/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>
Datasets are available to download in Geotiff and ASCII XYZ format at a <u>resolution of 30 arc-seconds (approximately 1km at the equator)</u>
<br/> 

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding 
<a href="https://www.worldpop.org/geodata/listing?id=29">Unconstrained individual countries 2000-2020 population count datasets</a> by dividing the number of people in each pixel by the pixel surface area. 
These are produced using the <a href="https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained">unconstrained top-down modelling method</a>.
<br/> 
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding 
<a href="https://www.worldpop.org/geodata/listing?id=69">Unconstrained individual countries 2000-2020 population UN adjusted count datasets</a> by dividing the number of people in each pixel, 
adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. 
These are produced using the <a href="https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained">unconstrained top-down modelling method</a>.
  
Data for earlier dates is available directly from WorldPop.  
  
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

Tags: baseline population, geodata
Organization: WorldPop
Satellite detected waters in Thua Thien Hue Province of Viet Nam as of 22 October 2020

**UNOSAT code: TC20201013VNM**  This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 22 October 2020. Within the analyzed area of about 4,000 km2, a total of about 220 km2 of lands appear to be flooded. The water extent appears to have receded of about 90 km2 since 13 October 2020. Based on Worldpop population data and the detected surface waters, about 70,000 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 UNITAR-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.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Western Sahara, non-self-governing territory - Requirements and Funding Data

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](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: covid-19, funding, humanitarian financial tracking service-fts, hxl
Organization: OCHA Financial Tracking System (FTS)
Colombia: Estimaciones afectaciones por fenómenos hidrometeorológicos cuarto trimestre 2025

Con base en los escenarios de predicción del Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM), se identificaron las zonas con susceptibilidad a inundaciones y deslizamientos durante el cuarto trimestre de 2025.
El archivo de Excel que acompaña esta publicación contiene ocho hojas con información desagregada sobre personas, porcentaje de población, zonas de cultivos, instituciones educativas y centros de salud localizados en zonas susceptibles. Además, para cada municipio se incluye el nivel de riesgo estimado, calculado mediante el Índice Municipal de Riesgo Ajustado por Capacidades, desarrollado por el Departamento Nacional de Planeación (DNP).

Tags: affected area, affected population, agriculture-livestock, climate hazards, climate-weather, damage assessment, education facilities-schools, flooding, health facilities, natural disasters
Organization: 3iS
Global International Boundaries - OSM

Original site: https://fieldmaps.io/data/adm0

International boundaries in two versions using US DoS LSIB for boundaries and OpenStreetMap for coastline data.

International: Balanced world view for use by international non-governmental organizations. Disputed areas follow recommended representation used by the UN Clear Map. UN agencies should use official layers at the UN Geospatial Hub.

All: Conservative world view that dissagregates all disputed areas. Useful if applying customized area aggregations.

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: FieldMaps
Global International Boundaries - USGS

Original site: https://fieldmaps.io/data/adm0

International boundaries in two versions using US DoS LSIB for boundaries and U.S. Geological Survey for coastline data.

International: Balanced world view for use by international non-governmental organizations. Disputed areas follow recommended representation used by the UN Clear Map. UN agencies should use official layers at the UN Geospatial Hub.

All: Conservative world view that dissagregates all disputed areas. Useful if applying customized area aggregations.

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: FieldMaps
Global Edge-matched Subnational Boundaries - Humanitarian

Original site: https://fieldmaps.io/data

Uses Common Operational Datasets (COD) when available, falling back to geoBoundaries for regions without coverage of subnational administrative geodata. Represents the latest available data for humanitarian operational use. Polygons contain only data for the most detailed admin level available, which may not be ADM4 depending on the source. Higher admin levels can be obtained by dissolving by attributes. Lines and points are intended for cartographic applications.

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: FieldMaps
Global Edge-matched Subnational Boundaries - Open

Original site: https://fieldmaps.io/data

Uses geoBoundaries exclusively, representing data suitable for most purposes, academic or commercial. Requires attribution to geoBoundaries. Polygons contain only data for the most detailed admin level available, which may not be ADM4 depending on the source. Higher admin levels can be obtained by dissolving by attributes. Lines and points are intended for cartographic applications.

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: FieldMaps
Syria Border Crossings

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/](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](http://geonode.state.gov/layers/geonode%3ASyria_BorderCrossings_2015Apr16_HIU_USDoS) is primarily hosted on the [State GeoNode](http:geonode.state.gov), the open geographic data platform of the U.S. Department of State.

Tags: border crossings, geodata, logistics
Organization: U.S. Department of State - Humanitarian Information Unit (inactive)
Syria IDP Sites

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](http://geonode.state.gov/layers/geonode%3ASyria_IDPSites_2015LateJun_HIU_DoS) is primarily hosted on the [State GeoNode](http:geonode.state.gov), the open geographic data platform of the U.S. Department of State.

Tags: geodata, internally displaced persons-idp, populated places-settlements
Organization: U.S. Department of State - Humanitarian Information Unit (inactive)
WorldRiskIndex

The WorldRiskIndex is a statistical model that provides an assessment of the latent risk of 193 countries falling victim to a humanitarian disaster caused by extreme natural events and the negative impacts of climate change. 
Based on peer-reviewed concepts of risk, hazard and vulnerability, it is assumed that disaster risks are not solely shaped by the occurrence, intensity, and duration of extreme natural events, but that social factors, political conditions, and economic structures are equally responsible for whether disasters occur in the context of extreme natural events. Accordingly, both main spheres of disaster risk, exposure and vulnerability, are treated as equals.

The WorldRiskIndex was initially developed in 2011 by the United Nations University Institute for Environment and Human Security (UNU-EHS) for [Bündnis Entwicklung Hilft]( https://weltrisikobericht.de/en/)
 as a model with 27 indicators to analytically link and relate the two spheres of disaster risks – exposure to natural hazards such as earthquakes, storms or droughts, and societal capacities to respond to these kinds of events. The methodology of the WorldRiskIndex has been continuously revised and developed by the [Institute for International Law of Peace and Armed Conflict (IFHV)]( https://www.ifhv.de/)
since 2018. In 2022, a new, fully revised model of the WorldRiskIndex was published, enabling more accurate analyses by incorporating more than 100 high-quality indicators, new data sources, and more robust statistical methods, thus finally replacing the previously used model.

Tags: climate hazards, development, hazards and risk, indicators, natural disasters, population
Organization: Institute for International Law of Peace and Armed Conflict
Somalia - Rapid Needs Assessment for El Nino Flooding in Baardheere District

Baardheere district in Jubaland State also experienced extreme flash flooding in March 2023, which caused 14 deaths, displaced thousands, and destroyed property.  The Inter-Cluster Coordination Group (ICCG) emergency response and preparedness plan anticipated that this cycle of flooding will affect nearly 400,000 – 500,000 people in Jowhar and Belet Weyne, and approximately 42,305 people in Baardheere. 
REACH's rapid needs assessment of key informants (KIs) in Belet Weyne and Baardheere districts focuses on locations with high influx of displaced people evacuating their flooded communities, aiming to cover all evacuation sites with affected populations, dependent on accessibility.

Tags: affected area, affected population, displacement, el nino-el nina, flooding
Organization: OCHA Somalia
Somalia - Population Living in Poverty

Nearly 7 of 10 Somalis live in poverty, making Somalia one of the poorest countries in Sub-saharan Africa. About 69 percent of the population lived in poverty in 2017 as compared to 71 percent in 2019. Somalia has the sixth highest poverty rate in the region, only after the Democratic Republic of Congo, Central African Republic, Madagascar, Burundi and South Sudan. Poverty incidence is lower in other urban areas, excluding Mogadishu, compared to nomadic households, IDPs in settlements, and those in rural areas and Mogadishu. Nearly half of the population is not even able to meet the average consumption of food items, confirming the dire living standards of most Somalis.

Tags: population, poverty
Organization: OCHA Somalia
Densité des foyers d'incendies dans les wilayas de Bejaia et Tizi Ouzou entre le 11 et le 13 août 2021

**UNOSAT code: FR20210811DZA**  Cette carte illustre la densité des foyers d'incendies détectés à partir des données VIIRS acquise entre le 11 et le 13 août 2021. Les wilayas de Bejaia, Tizi Ouzou et Ain-Defla semblent compter le plus grand nombre de foyers d'incendie avec respectivement 1,080; 573 et 190. En se basant sur les données démographique Worldpop, environ 70,000 personnes dans la wilaya de Tizi Ouzou; 25,000 personnes dans la wilaya de Bejaia et 13,000 personnes dans la wilaya de Skikda vivent à proximité des foyers d'incendie. Ceci est une analyse préliminaire et n'as pas encore été validée sur le terrain. Ne pas hésiter à envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

Tags: disaster risk reduction-drr, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Cameroon - Analysis and Refinement of Targeting Mechanisms for Food and Multipurpose Cash Assistance to Central African Republic Refugees - 2016

Due to persistent instability in the region, Cameroon hosts refugees and asylum seekers from neighboring countries, mainly from the Central African Republic and Nigeria. In 2015, nearly 259,000 Central African refugees arrived in Cameroon, of whom the vast majority settled in the Northern, Eastern and Adamaoua regions. Within these regions, the study identified 11 subsistence zones, of which the 5 zones with the highest refugee concentration were surveyed, in order to inform UNHCR's Livelihoods Strategy 2017-2020 targeting these refugees and to provide a baseline against which to measure the success of its implementation. The survey was conducted among 2,206 refugee households in November 2016. The household data is supplemented with UNHCRs progress data for the purpose of refining the targeting approach of both WFP and UNHCR.

Tags: asylum seekers, conflict-violence, displacement, livelihoods, refugees
Organization: UNHCR - The UN Refugee Agency
Satellite detected water extent along the Rupununi river, Upper Takutu-Upper Essequibo, Guyana as of 26 May 2022

**UNOSAT code: FL20220526GUY**  This map illustrates satellite-detected surface waters along the Rupununi river in Upper Takutu-Upper Essequibo Region of Guyana as observed from a Sentinel-1 image acquired on 26 May 2022 at 09:45 UTC. Within the analyzed area of about 14,000 km2, a total of about 320 km2 of lands were observed as flooded.
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

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected waters in Quang Nam Province of Viet Nam as of 30 October 2020

**UNOSAT code: TC20201028VNM**  This map illustrates satellite-detected surface waters in Quang Nam Province of Viet Nam as observed from a Sentinel-1 image acquired on 30 October 2020 at about 05:35 am local time. Within the analyzed area of about 8,000 km2, a total of about 80 km2 of lands appear to be flooded. The water extent appears to have increased of about 50 km2 since 25 October 2020 Based on Worldpop population data and the detected surface waters, about 45,000 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 UNITAR-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.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
DR Congo - Affected Persons Locations

Personnes déplacées internes, retour de population, refugiés et rapatriés en RDC. Chiffres/ lieux de déplacement des presonnes déplacées internes, retournés, réfugiés et rapatriés en RDC.


Tags: displacement, internally displaced persons-idp, populated places-settlements, refugees
Organization: OCHA Democratic Republic of the Congo (DRC)
Vanuatu - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2, ADM3.  
  
Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database [www.geoboundaries.org](https://www.geoboundaries.org) is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.  

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: geoBoundaries
Geodata of Minkaman IDP Site, Awerial County, Lakes State, South Sudan

This map illustrates satellite-detected shelters and other buildings at the Minkaman IDP Site in Lakes State, South Sudan, as seen by the WorldView-2 satellite on 3 July 2014. People displaced by ongoing instability in the region of Bor have established multiple IDP camps on the west bank of the White Nile in Awerial County. Imagery acquired on 10 May 2014 showed approximately 9,391 shelters and 450 infrastructure or support buildings occupying multiple areas along the White Nile. Imagery also showed an area being prepared for accommodating new shelters. As of 3 July 2014 this ground has been partially covered by shelters as well as other areas of the IDP site, and approximately 13,492 shelters and 572 infrastructure or support buildings have been detected. Note that IDPs sheltering under trees are not detected by this analysis. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
16th of December 2021 Tropical Cyclone RAI-21, Philippines. Preliminary Satellite-Based Comprehensive Damage Assessment

**UNOSAT code: TC20211216PHL**  A category 5 Tropical Cyclone RAI-21 struck the Philippines on the 16th of December 2021, causing damage, devastation, and destruction. The Tropical Cyclone RAI-21 made landfall north of General Luna city on Siargao Island, the easternmost island of the Philippines, and continued westward through the central part of the country.  
The Philippines National Disaster Risk Reduction and Management Council (NDRRMC) has stated that 2,182,791 families have been affected in 11 out of 17 regions of the Philippines. About 3M people, ~ 30% of the affected area population – need emergency humanitarian assistance. 
According to OCHA, the death toll has reached 177 persons, with more than 275 persons injured and 630,000 displaced. More than 159,000 houses have been damaged, 61,900 have been destroyed. These figures are likely to rise as the after-effects of the Tropical Cyclone are fully realized.
Preliminary assessment has shown devastating damage to houses, roads, and bridges disrupting aid movement into the affected areas. 
This report summarizes satellite-derived building damage analysis covering the most affected areas within Region IV-B (Mimaropa), Region VII (Central Visayas), Region VIII (Eastern Visayas), and Region XIII (Caraga) of the Philippines. 

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Mount Agung Update - Bali, Indonesia

On 22 September 2017 at 20.30 hrs. Indonesia’s Centre of Volcanology and Geological Hazard Mitigation (PVMBG) increased the status of Mt. Agung in  Karangasem District, Bali Province from Level 3 (High Alert) to Level 4 (Danger), the highest level for a volcano. And on 29 October 2017, at 16.00 hrs, the status of Mt. Agung has been lowered from Level IV (dangerous) to Level III (alert).
The no activity zone has also been reduced from 9 Km radius with additional sectoral expansion of 12km north-northwest and south-southwest  become 6 km radius from the volcano with additional sectoral expansion of 7.5 km north-northwest and south-southwest.  The displaced people who lived outside of the no activity zone start to return back home but advised to remain cautious. 

Tags: hxl, natural disasters
Organization: OCHA Indonesia (inactive)
Geodata of Gaza Damage Assessment 2014: UNOSAT Satellite Derived Geospatial Analysis

This report documents damage over the Gaza Strip following the July-August 2014 conflict. It is based on analysis of commercial satellite imagery and quantifies damage to overall building structures, health facilities, education facilities, agricultural fields and greenhouses. The study also compares damage from the 2014 conflict to that of the 2009 conflict. The analysis is supplemented by ground photos following UNOSAT deployment to Gaza in September 2014.

Tags: complex emergency-conflict-security, damage assessment, education, education facilities-schools, geodata, health, health facilities
Organization: United Nations Satellite Centre (UNOSAT)
Damage assessment in Mango Island, Mu'omu'a district, Ha'apai division, Tonga as of 18 January 2022 V2

**UNOSAT code: VO20220115TON**  This map illustrates effects of the Hunga Tonga-hunga Ha'apai volcanic eruption and the subsequent tsunami in Mango island (Mu'omu'a district, Tonga) and damage assessment as detected from a Kompsat-3 image acquired on 18 January 2022, 14:22 local time. In this island, UNOSAT identified 26 structures as damaged and/or destroyed and 1 structure as potentially damaged. The entire island appears to be covered with ashes. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Tags: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)