AndreaBozzo/ceres-open-data-index huggingface dataset:
New Zealand - 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
Damage assessment in Nyabibwe Town, 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 Nyabibwe Town, 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 623 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)
Italy - 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
Satellite detected water extent over Ferfer Woreda, Shabelle District, Shabelle Region, Ethiopia as of 30 March 2023

**UNOSAT code FL20230327SOM**  This map illustrates satellite detected surface waters in Ferfer Woreda, Shabelle District, Shabelle Region, Ethiopia as observed from a SPOT-6 image acquired on 30 March 2023 at 07:01 UTC. Within the analyzed area of about 260km2, about 4 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 United Nations Satellite Centre (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood Impact assessment of Vilankulo Town, Inhambane Province, Mozambique  as of 13 March 2023

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961**  This map illustrates satellite-detected surface waters in Vilankulo Town, Inhambane Province, Mozambique as observed from a WorldView-3 image acquired 13 March 2023 at 09:40 local time and Pleiades image acquired 10 March 2023 at 09:48 local time. Within the analysis extent of about 2,800 hectares, approximately 35 hectares of land appear to be flooded. Based on Worldpop population data and the detected surface waters within the analysis extent, approximately 350 people are potentially exposed to or living close to flooded areas along with 71 structures and potentially affected road 290 meter by flooding.  
  
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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent over Sofala and Zambezia Provinces, Mozambique as of 13 Mar. 2023

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961**  This map illustrates satellite-detected surface waters in Sofala and Zambezia Provinces, Mozambique as observed from an RCM-2 image acquired on 13 Mar. 2023 at 05:01 local time. Within the analyzed area of about 24,000 km2, about 900 km2 of land appear to be flooded.   
  
Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in Zambezia province, including the district of Namacurra, with ~27,200 people, Nicoadala with ~22,500 people, and Cidade De Quelimane with ~ 15,600 people.  
  
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to 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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood Impact Analysis along the Orontes River (Al Assi), Syrian-Türkyie boarder, as of 9 February 2023

**UNOSAT code EQ20230206SYR, GDACS Id: 1357372**  This map illustrates satellite-detected water along the Orontes (Al Assi) River on the Syria-Türkyie boarder close to the Al Tloul and Jakara towns from a Sentinel-2 imagery acquired on 9 February 2023, and from a Worldview-2 imagery aquired on the 13 February 2023. Within the analyzed area of 210 km2 about 18 km2 appears to be flooded. The floods may have been likely triggered by the opening of dams and the damage induced to certain water infrastructures along the river by the tremors. 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: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent Higuamo & Valdesia Regions, Dominican Republic as of 21 November 2023

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342**  This map illustrates cumulative satellite-detected water extent in Higuamo & Valdesia Regions, Dominican Republic as observed from a Sentinel-2 image acquired on the 21 November 2023 at 11:17 local time. Within the cloud free analysed area of about 1,800 km² , about 35 km² of land appears to be affected with flood waters and 14,000 people are potentially exposed to flood waters.  
  
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 in Khairpur Nathan Shah Town, Sindh Province, Pakistan as of 31 August 2022

**UNOSAT code FL20220808PAK, GDACS Id: 1101522**  This map illustrates satellite-detected surface waters in Sindh Province, Pakistan as observed from a Sentinel-2 image acquired on 31 August 2022 at 10:56 local time. Khairpur Nathan Shah town appears to be surrounded by flood waters. Within the extent of this map of 1,300 km2, about 845 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the map extent, about 440,000 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)
Satellite detected water extents between 10 and 14 September 2022 over South Sudan

**UNOSAT code FL20220424SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 10 to 14 September 2022 compared with the period from 30 August to 03 September 2022. Within the cloud free analyzed areas of about 605,000 km², a total of about 30,000 km² of lands appear to be affected with flood waters. Water extent appears to have decreased of about 13,000 km² since the period between 30 August to 03 September 2022. Based on Worldpop population data and the maximal flood water coverage, ~615,000 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).  
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.  
Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - Solomon Islands

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-slb)_

Tags: demographics, population
Organization: Pacific Community
Preliminary Satellite Derived Flood Evolution Assessment, Islamic Republic of Pakistan-11 October 2022

**UNOSAT code FL20220808PAK, GDACS Id: 1101522**  Status: Overall decrease of flood waters observed  
Further action(s): continue monitoring  
  
Summary of findings;  
  
Evolution of Cumulative Flood Waters over I.R. of Pakistan (26 September-2 October 2022 Vs 03-09 October 2022):  
  
Between 03 and 09 October 2022 approximately 13 million people remain potentially exposed or living close to flooded areas;  
  
Based on satellite observations between 26 September and 02 October 2022 and compared with observations between 03 and 09 October 2022, the overall flood water extent appears to continue to decrease with approximately 300 km² in Balochistan, ~Punjab 900 km²  and  ~4,000 km² in Sindh.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents between 14 and 18 October 2022 over Chad

**UNOSAT code FL20221019TCD**  This map illustrates cumulative satellite-detected water using VIIRS in Chad between 14 to 18 October 2022. Within the cloud free analysed areas of about 1,200,000 km², a total of about 24,300 km² of land appears to be affected.  Based on Worldpop population data and the maximal flood water extent ~1.4 million people are potentially exposed or living close to flooded areas amongst the 16.5 million people living in the analysed zone.  
  
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)
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - Federated States of Micronesia

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-fsm)_

Tags: demographics, population
Organization: Pacific Community
Satellite detected water extent over Lumbini and Sudurpaschim Provinces, Nepal as of 15 October 2022

**UNOSAT code FL20221117NPL**  This map illustrates satellite-detected surface waters in Sudurpaschim and Lumbini Provinces, Nepal as observed from a Sentinel-2 image acquired on 15 October 2022. Within the total analyzed area of about 4,700 km², ~70 km² of lands appear to be flooded. Based on Worldpop population data and the detected surface waters about 35,000 people are potentially exposed or living close to flooded areas, of which 18,000 are located In Janaki, Tikapur, Geruwa, Rajapur, Thakurbaba & Madhuwan Palikas.  
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 extents between 19 and 23 October 2022 over Nigeria

**UNOSAT code FL20221019NGA**  This map illustrates cumulative satellite-detected water using VIIRS in Nigeria between 19 to 23 October 2022 compared with the period from 13 to 17 October 2022. Within the cloud free analysed areas of about 873,000 km², a total of about 25,000 km² of land appears to be affected. In the analysed areas, 664 health facilities and 1,160 schools are identified to be within or close to a flooded zone. In comparison with the period between 13 to 17 October 2022, water extent appears to have decreased of about 5,000 km². Based on Worldpop population data and the maximal flood water extent ~5,200,000 people are potentially exposed or living close to flooded areas amongst the 197 million people living in the analysed zone.  
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)
Norfolk Island - 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
Argentina - 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 - Central Asia (April - June 2014)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **Central Asia**.

It was last updated on April 2014. 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:

* xx201404_ML1	Most likely food security outcome for April-June 2014
* xx201404_ML2	Most likely food security outcome for July-September 2014

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
Food Insecurity Mapping - Central Asia (January - March 2013)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **East Africa**.

It was last updated on January 14, 2013. 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:

* xx201304_ML1	Most likely food security outcome for January-March 2013
* xx201304_ML2	Most likely food security outcome for April-June 2013

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