AndreaBozzo/ceres-open-data-index huggingface dataset:
State of Palestine - 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
Food Insecurity Mapping - Southern Africa (July - September 2015)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **Southern Africa**.

It was last updated on August 19, 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:

* SA201304_ML1	Most likely food security outcome for July-September 2015
* SA201304_ML2	Most likely food security outcome for October-December 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
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - New Caledonia

Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. 
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249
https://sdd.spc.int/mapping-coastal


_Access this dataset from the [Pacific Data Hub](https://pacificdata.org/data/dataset/coastal-population-dataset-ncl)_

Tags: demographics, population
Organization: Pacific Community
Pitcairn - 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
Damage Assessment in Cianjur district, Jawa Barat Province, Indonesia  as of 23 November 2022

**UNOSAT code EQ20221121IDN, GDACS Id: 1347183**  This map illustrates potentially damaged structures and damaged structures in Cianjur district, Jawa Barat Province, Indonesia as detected by a Pléiades image acquired on 23 November 2022 at 10:00 local time. Within the analyzed area, UNOSAT has identified 111 potentially damaged structures, 8 damaged structures and 10 temporary shelters.  
  
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: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents between 01 and 07 September 2022 over Pakistan

**UNOSAT code FL20220808PAK, GDACS Id: 1101522**  This map illustrates cumulative satellite-detected water using VIIRS in Pakistan between 01 to 07 September 2022. Within the analyzed area of about 880,000 km², a total of about 60,000 km² of lands appear to be affected with flood waters. Floodwaters seem to have decreased of about 25,000 km² since the period between the 01st July to 31rd of August 2022. Based on Worldpop population data and the maximum flood water coverage, at least 22 million people were potentially exposed or living close to flooded areas in August 2022.  
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).  
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 been agreed upon by the parties.  
The boundaries and names shown, and the designations used on this map do not imply official endorsement or acceptance by the United Nations. The United Nations Satellite Centre - UNOSAT is not responsible for the misuse or misrepresentation of the map.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood water extent evolution over Oleshky City in the east bank of the Dnipro (Dnieper) in Khersonska Oblast, Ukraine as of 09 June 2023; 08:37 UTC

**UNOSAT code FL20230606UKR**  This map illustrates satellite-detected flood waters over Oleshky City, in the east bank of the Dnieper/Dnipro River in Khersonska Oblast, Ukraine as observed from a Landsat-9 satellite images acquired on 9 June 2023 at 08:37 UTC. 50% (8km2) of Olehsky appears to be affected by flood waters. Water extent appeared to have decreased by about 2 km2 since 7 June 2023.  
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 extents between 10 and 14 June 2023 over South Sudan

**UNOSAT code FL20220424SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 10 to 14 June 2023 compared with the period from 01 to 05 June 2023. Within the cloud free analyzed areas of about 615,000 km², a total of about 11,000 km² of lands appear to be affected with flood waters. Water extent appears to have increased of about 1,000 km² since the period between 01 to 05 June 2023. Based on Worldpop population data and the maximal flood water extent ~205,000 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).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Zones incendiées le 25 juillet 2023 dans les communes de Melbou et Ziama Mansouria, Wilayas de Bejaia et Jijel, Algérie

**UNOSAT code FR20230724DZA, GDACS Id: 1015944**  Cette carte illustre les zones incendiées telles qu'observées à partir d'une image Sentinel-2 acquise le 25 juillet 2023 à 18:56 heure locale dans les communes de Melbou et Mansouria.  
Sur les 44 km² de la zone observée, environ 11 km² et 7 km² de végétation semblent avoir brûlé dans les communes de Melbou et Ziama Mansouria.  
En se basant sur les données démographiques Worldpop, dans les communes de Melbou et Ziama Mansouria environ 1,900 et 5,800 personnes sont potentiellement impactées par les feux de forêt.  
Ceci est une analyse préliminaire et n'a 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)
Power Supply Assessment in Benghazi (Libya) using Night-time Light Imagery

**UNOSAT code FL20230912LBY, GDACS Id: 1102204**  Status: Power outage observed.  
Further action(s): continue monitoring  
Compared with Derna and Al Bayda, power supply of Benghazi was less affected by the floods. No significant power outage could be observed in Benghazi.  
Only a few areas  east of the city of Benghazi suffered of power outage after the floods, in which the power supply has recovered to pre-floods level on 24 September 2023.

Tags: flooding, geodata, libya-floods
Organization: United Nations Satellite Centre (UNOSAT)
Azerbaijan - 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
Gridded Disaggregated Population Estimates for Kenya (version 1.0)

These data were produced by the [ WorldPop](https://www.worldpop.org/) Research Group at the University of Southampton. 
This work was part of the GRID3 project with funding from the United Nations Children's Fund ([ UNICEF ](https://www.unicef.org/)) - 
Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). 
Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton 
and the Center for International Earth Science Information Network [ CIESIN](http://www.ciesin.org/)  in the Columbia Climate School at Columbia University.  Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and gender and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem.

For further details, please, read the [Release Statement](https://data.worldpop.org/repo/wopr/KEN/population/v1.0/KEN_population_v1_0_README.pdf).

**Release content**

1.	KEN_population_v1_0_gridded.tif
2.	KEN_population_v1_0_agesex.zip
3.	KEN_population_v1_0_mastergrid.tif 

**Recommended citations**

Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022.  *Census disaggregated gridded population estimates for Kenya (2021), version 1.0* University of Southampton. doi:10.5258/SOTON/WP00747

**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[at]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[at]worldpop.org.

[WorldPop](https://www.worldpop.org/), 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.


Tags: demographics, gender and age disaggregated data-gadd, population
Organization: WorldPop
Northern Mariana Islands - 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
Botswana - 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
Mayotte - 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