AndreaBozzo/ceres-open-data-index huggingface dataset:
UNOSAT Tropical Cyclone Fiona-22, Population Exposure Analysis in the Dominican Republic - 20 September 2022

**UNOSAT code TC20220920DOM, GDACS Id: 1000916**  Tropical cyclone FIONA-22 formed on 14 September 2022 over the Caribbean Sea east of Guadeloupe with the maximum sustained winds up to 220 km/h. The category 4 tropical cyclone FIONA-22 reached the coast of the Dominican Republic on 19 September 2022. According to GDACS, Tropical Cyclone FIONA-22 can have a high humanitarian impact based on the maximum sustained wind speed, exposed population, and vulnerability.  
Based on data of the forecasted tropical cyclone path of wind speeds zones from Joint Research Centre (Issued on 20 September 2022 09:00 UTC), and population data from WorldPop Unconstrained 2020, UNITAR-UNOSAT has prepared a population exposure analysis for the Dominican Republic. About 66% of population of the Dominican Republic living inside wind speed zone below 60 km/h, 19% living inside wind speed zone of 60-120 km/h and 10% living inside wind speed zone above 120 km/h.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent over Dagahaley Refugee Camp, Garissa County, Kenya as of 26 March 2023

**UNOSAT code FL20230321KEN**  This map illustrates satellite detected surface waters in Dagahaley Refugee Camp, Dadaab sub-county, Garissa county, Kenya as observed from a Sentinel-2 image acquired on 26 March 2023 at 07:49 UTC. Within the analyzed area of about 45 km2, about 8 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, 8600 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 United Nations Satellite Centre (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent over Shabelle Zone, Somali Region, Ethiopia and Beledweyne District, Hiraan Region of Somalia as of 29 April 2023

**UNOSAT code FL20230327SOM**  This map illustrates satellite-detected surface waters in Shabelle Zone, Somali Region of Ethiopia and Beledweyne District, Hiraan Region of Somalia as observed from a Sentinel-2 image acquired on 29 April 2023 at 07:06 UTC. Within the analyzed area of about 5,300 km², about 180 km² of land appear to be flooded. Water extent appears to have increased by about 60 km² since 19 April 2023.  
Based on Worldpop population data and the detected surface waters in the analyzed area, 7,500 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 United Nations Satellite Centre (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Impact des glissements de terrain le 7 mai 2023 en Territoire de Kalehe, Province du Sud-Kivu, République Démocratique du Congo

**UNOSAT code FL20230508COD, GDACS Id: 1101981**  Cette carte illustre l'étendue des glissements de terrain le 07 mai 2023 en Territoire de Kalehe, Province du Sud-Kivu, République Démocratique du Congo. Dans la zone analysée de 9,000 ha, environ 90 ha d'escarpements de glissements de terrain sont visibles.  
Ceci est une analyse préliminaire et n'a pas été validée sur le terrain. Merci d'envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage assessment in Chabondo village, Kalehe Territory, Sud-Kivu Province, DR. of the Congo as of 09 May 2023

**UNOSAT code FL20230508COD, GDACS Id: 1101981**  This map illustrates the potentially damaged structures/buildings affected by landslides in Chabondo village, Kalehe Territory, Sud-Kivu Province, DR. of the Congo as detected from a Pleiades image acquired on the 09th May 2023.  
Within the extent of this map, at least 544 structures appear to be affected or potentially affected by landslides.  
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).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood impact assessment in Derna dams, East Province, Libya

**UNOSAT code FL20230912LBY, GDACS Id: 1102204**  This map illustrates satellite-detected flood impact in the 2 Derna dams over Benghazi Governorate, East pronvce, Libya, as observed from optical very-high resolution satellite imagery. Dam wall reservoirs appears to be destroyed in both the upstream and the downstream Derna dams.  
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).

Tags: flooding, geodata, libya-floods
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent in Jowhar City, Jowhar District, Middle Shabelle Region, Somalia as of 20 November 2023

**UNOSAT code: FL20231105SOM**  This map illustrates satellite-detected surface waters in Jowhar City, Jowhar District, Middle Shabelle Region, Somalia as observed from a Sentinel-2 image acquired on 20 November 2023. Within the analysed area of about 170 km2 about 27 km2 of land appears to be 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).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent as of 19 July 2020 of Bangladesh

**UNOSAT code: FL20200713BGD**  This map illustrates satellite-detected surface waters in the central parts of Bangladesh as observed from a Sentinel-1 image acquired on 19 July 2020 and 13 July 2020. Within the analyzed area of about 40,000 km2, a total of about 8,700 km2 of lands appear to be flooded.

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 Sentinel-1 imagery acquired on 19 July 2020 and 13 July 2020 may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Spain - 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
Gabon - 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
Kenya - Age and gender structures

<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="/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>   

A description of the modelling methods used for age and gender structures can be found in 
<a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al</a> and 
<a href="https://dx.doi.org/10.1038/sdata.2017.89" target="_blank">Pezzulo et al</a>. Details of the input population count datasets used can be found <a href="https://www.worldpop.org/project/categories?id=3" target="_blank">here</a>, and age/gender structure proportion datasets <a href="https://www.portal.worldpop.org/demographics/data/global_agegender_proportions_totals_2020.zip" target="_blank">here</a>. 
<br/>
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined 
<a href="/methods/top_down_constrained_vs_unconstrained" target="_blank">here</a>. The  datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.  
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.  
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/WP00646

Tags: baseline population, demographics, geodata
Organization: WorldPop
Italy Financial Services (OpenStreetMap Export)



This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['amenity'] IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [name:en](http://wiki.openstreetmap.org/wiki/Key:name:en)
- [amenity](http://wiki.openstreetmap.org/wiki/Key:amenity)
- [operator](http://wiki.openstreetmap.org/wiki/Key:operator)
- [network](http://wiki.openstreetmap.org/wiki/Key:network)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)
- [name:it](http://wiki.openstreetmap.org/wiki/Key:name:it)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: economics, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Indonesia - Age and gender structures

<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="/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>   

A description of the modelling methods used for age and gender structures can be found in 
<a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al</a> and 
<a href="https://dx.doi.org/10.1038/sdata.2017.89" target="_blank">Pezzulo et al</a>. Details of the input population count datasets used can be found <a href="https://www.worldpop.org/project/categories?id=3" target="_blank">here</a>, and age/gender structure proportion datasets <a href="https://www.portal.worldpop.org/demographics/data/global_agegender_proportions_totals_2020.zip" target="_blank">here</a>. 
<br/>
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined 
<a href="/methods/top_down_constrained_vs_unconstrained" target="_blank">here</a>. The  datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.  
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.  
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/WP00646

Tags: baseline population, demographics, geodata
Organization: WorldPop
Republic of Korea - Age and gender structures

<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="/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>   

A description of the modelling methods used for age and gender structures can be found in 
<a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al</a> and 
<a href="https://dx.doi.org/10.1038/sdata.2017.89" target="_blank">Pezzulo et al</a>. Details of the input population count datasets used can be found <a href="https://www.worldpop.org/project/categories?id=3" target="_blank">here</a>, and age/gender structure proportion datasets <a href="https://www.portal.worldpop.org/demographics/data/global_agegender_proportions_totals_2020.zip" target="_blank">here</a>. 
<br/>
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined 
<a href="/methods/top_down_constrained_vs_unconstrained" target="_blank">here</a>. The  datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.  
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.  
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/WP00646

Tags: baseline population, demographics, geodata
Organization: WorldPop
Timor-Leste - Age and gender structures

<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="/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>   

A description of the modelling methods used for age and gender structures can be found in 
<a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al</a> and 
<a href="https://dx.doi.org/10.1038/sdata.2017.89" target="_blank">Pezzulo et al</a>. Details of the input population count datasets used can be found <a href="https://www.worldpop.org/project/categories?id=3" target="_blank">here</a>, and age/gender structure proportion datasets <a href="https://www.portal.worldpop.org/demographics/data/global_agegender_proportions_totals_2020.zip" target="_blank">here</a>. 
<br/>
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined 
<a href="/methods/top_down_constrained_vs_unconstrained" target="_blank">here</a>. The  datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.  
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.  
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/WP00646

Tags: baseline population, demographics, geodata
Organization: WorldPop
Goma , Republic of the Congo Education Facilities (OpenStreetMap Export)


OpenStreetMap exports for use in GIS applications.

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [name:en](http://wiki.openstreetmap.org/wiki/Key:name:en)
- [amenity](http://wiki.openstreetmap.org/wiki/Key:amenity)
- [building](http://wiki.openstreetmap.org/wiki/Key:building)
- [operator:type](http://wiki.openstreetmap.org/wiki/Key:operator:type)
- [capacity:persons](http://wiki.openstreetmap.org/wiki/Key:capacity:persons)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Goma , Republic of the Congo Railways (OpenStreetMap Export)


OpenStreetMap exports for use in GIS applications.

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['railway'] IN ('rail','station')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [name:en](http://wiki.openstreetmap.org/wiki/Key:name:en)
- [railway](http://wiki.openstreetmap.org/wiki/Key:railway)
- [ele](http://wiki.openstreetmap.org/wiki/Key:ele)
- [operator:type](http://wiki.openstreetmap.org/wiki/Key:operator:type)
- [layer](http://wiki.openstreetmap.org/wiki/Key:layer)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: facilities-infrastructure, geodata, railways, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)