AndreaBozzo/ceres-open-data-index huggingface dataset:
Food Insecurity Mapping - Southern Africa (January - March 2015)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **Southern Africa**.

It was last updated on February 10, 2015. The classification used is [IPC V2.0 Compatible](http://www.fews.net/nosso-trabalho/nosso-trabalho/classifica%C3%A7%C3%A3o-integrada-de-fases), aimed to address acute food insecurity.

The two shapefiles represent the two analytic periods:

* southernafrica201304_ML1	Most likely food security outcome for January-March 2015
* southernafrica201304_ML2	Most likely food security outcome for April-June 2015

Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used:

* 66 = water
* 88 = parks, forests, reserves
* 99 = missing data (usually urban centers).

Tags: agriculture-livestock, climate-weather, complex emergency-conflict-security, food security
Organization: HDX
Dominican Republic - 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
Gibraltar - 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
Tonga - 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
Guernsey - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0.  
  
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
American Samoa - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, 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
Satellite detected water extent as of 21 July 2020 over Northwestern region of Bangladesh

**UNOSAT code: FL20200713BGD**  This map illustrates satellite-detected surface waters over Khulna, Rajshahi and Rangpur Division of Bangladesh of Bangladesh as observed from a Sentinel-1 image acquired on 9 July 2020 and 21 July 2020. Within the analyzed area of about 15,000 km2, a total of about 3,600 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 2,507,000 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 Sentinel-1 image acquired on 9 July 2020 and 21 July 2020 may underestimate the presence of standing

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent as of 18 July 2020 over Eastern part of Sylhet Division, Bangladesh

**UNOSAT code: FL20200713BGD**  This map illustrates satellite-detected surface waters over the Eastern part of the Sylhet division of Bangladesh as observed from a TerraSAR-X image acquired on 18 July 2020 due to the current monsoon rains. Within the analyzed area of about 8,600 km2, a total of about 2,200 km2 of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Based on WorldPop population data and the detected surface waters, about 2,000,000 people area potentially exposed or living close to flooded areas. 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: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Fiji - 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 landslide extent in Mogitu & Ganana Ward, Hanang District, Tanzania as of 19 December 2023

**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).

Tags: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent over Greater Accra & Volta Region, Ghana as of 23 October 2023

**UNOSAT code FL20231018GHA**  This map illustrates cumulative satellite-detected water extent as observed from a Sentinel-1 imagery acquired on the 23 October 2023 at 18:10 local time. Within the analysed area of about 4,300 km², a total of about 53 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the detected surface waters, about 12,000 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 the backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
10 September 2023 Mediterranean Sea Storm Daniel in Libya, Preliminary Satellite-Based Comprehensive Damage Assessment Report

**UNOSAT code FL20230912LBY, GDACS Id: 1102204**  On the night of the 10th of September 2023, after its journey through the Mediterranean Sea, the storm Daniel brought heavy rains that triggered floods in Benghazi, Almarj, Al Jabal Al Akhdar and Derna Governorates, in northeastern Libya. The increase of water levels in the region caused the collapse of two dams located upstream Derna River and the consequences was tremendous. The dam breach released a massive amount of water and a huge flood wave wiped out entire neighbourhoods in the city of Derna. Hundreds of people were reported missing by the Libyan Red Crescent Society.   
According to the Libyan National Meteorological Centre, the storm reached its peak with winds going up to 70-80 km/h. This led to the falling of electricity towers and tress causing communications interruption. Between 150 – 240 mm were reported and caused flash floods in several cities. Al-Bayda have recorded the highest daily rainfall rate: 414.1 mm in the night of the 10 to 11 September 2023.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Assessment of Flooded Buildings in Bandarban, Cox's Bazaar, Chattogram, and Rangamati Districts, Chattogram Division, Bangladesh as of  12 to 22 August 2023

**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).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite Flood water Extent between the Nova Kakhovka Dam Wall and the Dnipro River mouth, Khersonska Oblast, Ukraine as of 21 June 2023

**UNOSAT code FL20230606UKR**  This map illustrates satellite-detected flood waters along the 90km downstream of Dnipro River between the damaged Nova Kakhovka Dam wall and the Dnipro River mouth in Ukraine as observed from a Sentinel-1 images acquired on 21 June 2023 at 15:36 UTC. Within the analysed area of about 10,800 km², about 20 km² of land appear to remain flooded.  
  
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 southern Hiraan Region and Jowhar CIty, Middle Shabelle Region, Somalia as of 24 May 2023

**UNOSAT code FL20230327SOM, GDACS Id: 1101908**  This map illustrates satellite-detected surface waters over southern Hiraan Region and Jowhar CIty, Middle Shabelle Region, Somalia observed from a Sentinel-2 image acquired on 24 May 2023 at 07:06 UTC. Within the analysed area of 8,600km², about 430 km² of land appear to be flooded.  
Based on Worldpop population data and the detected surface waters in the analysed area, at least 47,000 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 United Nations Satellite Centre (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Estonia - 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
Romania - 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
Mount Semeru volcanic eruption, Jawa Timur Province, Indonesia - UNOSAT Live Web Map

**UNOSAT code VO20221206IDN, GDACS Id: 1000057**  Live web map providing geospatial information potentially affected areas  
by pyroclastic flow/deposits after the December 2022 Mount Semeru volcanic eruption in East Java. This web map gives an updated overview over potentially affected structures and affected structures based on very high-resolution satellite images and also Pyroclastic flow/deposits.

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