AndreaBozzo/ceres-open-data-index huggingface dataset:
Preliminary Satellite Derived Flood Evolution Assessment, Islamic Republic of Pakistan-4 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 (15 - 21 September Vs 26 September-2 October 2022):  
  
Between 26 September and 2 October 2022 approximately 15 million people remain potentially exposed or living close to flooded areas;  
Based on satellite observations between 15 to 21 September 2022 and compared with observations between 26 September  and 2 October 2022, the overall flood water extents appear to continue to decrease with approximately 600 km² in Balochistan, ~Punjab 500 km²  and  ~2,600 km² in Sindh.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents over Pinar del Río province, Cuba as of 28 September 2022

**UNOSAT code TC20221001CUB, GDACS Id: 1000923**  This map illustrates satellite-detected surface waters in Pinar del Río province, Cuba as observed from a Sentinel-1 imagery acquired on 28 September 2022 at 07:27 local time. Within the analyzed area of about 1,300 km², a total of about 27 km² of lands appear to be affected with flood waters amongst which 13 km² are flooded croplands. Based on Worldpop population data and the detected surface waters, about 4,200 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).  
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Preliminary Satellite Derived Flood Evolution Assessment, Islamic Republic of Pakistan-19 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 (03-09 October 2022 Vs 11-17 October 2022):  
  
Between 11 and 17 October 2022 approximately 11 million people remain potentially exposed or living close to flooded areas;  
Based on satellite observations between 03 and 09 October 2022 and compared with observations between 11 and 17 October 2022, the overall flood water extent appears to continue to decrease with approximately 200 km² in Balochistan, ~Punjab 100 km²  and  ~2,700 km² in Sindh.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent between 30 October 2022 and 31 October 2018 in Hadjer-Lamis & Lac Regions, Chad

**UNOSAT code FL20221019TCD**  This map illustrates satellite-detected surface waters in Hadjer-Lamis & Lac Regions, Chad as observed from a Sentinel-2 acquired on 30 October 2022 at 10:37 local time. Within the cloud free analyzed area of about 17,000 km2, the surface waters appears to have increased of about 700 km2 since 31 October 2018. Based on Worldpop population data and the detected surface waters, the potentially exposed population is mainly located in Mamdi Department with ~28,000 people, Haraze-Al-Biar Department with ~9,700 people and Wayi department with ~9,300 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).

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

**UNOSAT code: FL20200713BGD**  This map illustrates satellite-detected surface waters over Bangladesh as observed from a TanDEM-X image acquired on 19 July 2020 due to the current monsoon rains. Within the analyzed area of about 14,000 km2, a total of about 6,800 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 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)
Satellite detected water extent over Banke District, Lumbini Province, Nepal as of 25 & 30 October 2022

**UNOSAT code FL20221117NPL**  This map illustrates satellite-detected surface waters in Banke District, Lumbini Province, Nepal as observed from Sentinel-2 images acquired on 25 & 30 October 2022 (Cumulative). Within the analyzed area of about 4,000 km², a combined 33 km² of lands appear to be flooded on the 25th and the 30th of October 2022. Water extent appears to have decreased of about 26 km² since the 15th October 2022. Based on Worldpop population data and the detected surface waters, about 1,400 people are potentially exposed or living close to flooded areas, of which 1,400 are located in Duduwa and Narainapur 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)
Eaux de surface détectées par satellite entre le 24 novembre et le 05 décembre 2022 dans la province de Tshopo, République Démocratique du Congo

**UNOSAT code FL20221125COD**  Cette carte illustre l'étendue des eaux de surface détectées par satellite en utilisant de l'imagerie satellite VIIRS dans la province de Tshopo (République Démocratique du Congo) entre le 24 novembre et le 05 décembre 2022. Dans la zone analysée d'environ 200 000 km², un total d'environ 1 600 km² de terres semblent être inondées. L'étendue des eaux de surface semble être du même niveau qu'entre les dates du 25 novembre au 05 décembre 2019. D'après les données démographiques de Worldpop et les eaux de surface détectées par satellite, environ  70 000 personnes sont potentiellement exposées ou vivent à proximité de zones inondées.  
Prière de bien vouloir noter que ceci est une analyse préliminaire qui 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)
Preliminary Satellite Derived Flood Evolution Assessment, Islamic Republic of Pakistan - 3 January 2023

**UNOSAT code FL20221121PAK**  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 (14-20 November 2022 Vs 25-31 December 2022):  
- Between 25 and 31 December 2022 approximately 5 million people remain potentially exposed or living close to flooded areas;  
- Based on satellite observations between 14 and 20 November 2022 and compared with observations between 25 and 31 November 2022, the overall flood water extent appears to continue to decrease with approximately ~ -6,000 km² in Sindh, ~ -1,300 km² in Punjab and ~ - 500 km² in Balochistan.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage Assessment in Lilawa Village, Jarablus District, Aleppo Governorate, Syria as of 7 February 2023

**UNOSAT code EQ20230206SYR, GDACS Id: 1357372**  This map illustrates potentially damaged structures/buildings by the 06th of February 2023 earthquake in Lilawa Village, Jarablus District, Aleppo Governorate, Syria as detected by a Worldview-3 Very high-resolution satellite image acquired on 7 February 2023. Within this village, UNOSAT identified 30 damaged structures and 68 potentially damaged structures.   
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)
Food Insecurity Mapping - Central Asia (October - December 2013)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **Central Asia**.

It was last updated on June 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 April-June 2013
* xx201304_ML2	Most likely food security outcome for July-September 2013

Where xx is one of the region codes listed above. 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
Antarctica - 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
Turkmenistan - Pregnancies

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in <a href="https://ij-healthgeographics.biomedcentral.com/articles/10.1186/1476-072X-13-2"  target="_blank">Tatem et al</a> and <a href="https://www.nature.com/articles/sdata201890"  target="_blank">James et al.</a>.  
Data for earlier dates is available directly from WorldPop.  
  
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Turkmenistan 1km Pregnancies. Version 1.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00637

Tags: geodata, maternity
Organization: WorldPop
Food Insecurity Mapping - West Africa (April - June 2013)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **West Africa**.

It was last updated on June 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 April-June 2013
* xx201304_ML2	Most likely food security outcome for July-September 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
China, Hong Kong Special Administrative Region - 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
Congo - 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 - East Africa (April - June 2014)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **East Africa**.

It was last updated on July 17, 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:

* eastafrica201304_ML1	Most likely food security outcome for April-June 2014
* eastafrica201304_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 - Southern Africa (January - March 2013)

This Archive contains shapefiles for FEWS NET Food Security Outlook for **Southern 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:

* southernafrica201304_ML1	Most likely food security outcome for January-March 2013
* southernafrica201304_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
Satellite detected water comparative analysis between mid-September to mid-October 2020 and 2021 over South Sudan

**UNOSAT code: FL20211015SSD**  This map illustrates historical comparative cumulative satellite-detected water using VIIRS in South Sudan between 19 Sep. to 18 Oct. 2021 and 20 Sep. to 19 Oct. 2020 . Within the analyzed extent not covered by clouds, a total of about 70,000 km2 appear to be flooded. Based on Worldpop population data and the detected surface water, about 2,000,000 people are exposed or living close to flooded area.
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)
Preliminary Satellite-Derived Flood Assessment, Central and Western Part of Thailand

**UNOSAT code: FL20210928THA**  Summary Of Findings;

Floodwaters observed in 17 provinces as of 2 November 2021;

Receding flood waters observed in Central Region as of 2 November 2021;

Standing flood waters observed in Sukhothai, Phitsanulok, Kamphaeng Phet, Phichit, Phetchabun, Nakhon Sawan, Uthai Thani, and Kanchanaburi provinces as of 2 November 2021; 

Increased standing flood waters observed in Chai Nat, Suphan Buri, Sing Buri, Ang Thong, Saraburi, Lop Buri, Ayutthaya, Nakhon Pathom and Pathum Thani provinces as of 2 November 2021. 


Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage Assessment in Chardonnieres commune, South department as of 23 August 2021

**UNOSAT code: EQ20210814HTI**  This map illustrates potentially damaged structures/buildings in Chardonnieres commune, South department of Haiti as detected by Pleiades image acquired on 23 August 2021. Within the analyzed area, UNOSAT has identified 27 damaged structures, 107 potentially damaged structures, 9 landslide locations.

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)
Damage assessment in City of Carcar and San Fernando municipalities, Cebu Province, Region VII, Philippines

**UNOSAT code: TC20211216PHL**  This map illustrates potentially damaged structures and buildings in City of Carcar and San Fernando  municipalities, Cebu province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 23 December 2021 & a GeoEye-1 image acquired on 20 December 2021. Within the analyzed area, UNOSAT identified 1929 damaged structures.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Syria - Damage density 2016 of Deir Ez Zor, Deir Ez Zor Governorate

This map illustrates satellite-detected damage density in a portion of the city of Deir Ez Zor, Syrian Arab Republic. Using satellite imagery acquired 25 May 2016, 10 May 2015, 13 May 2014, and 24 October 2013, UNITAR - UNOSAT identified a total of 4,595 affected structures within the city. Approximately 786 of these were destroyed, 1,386 severely damaged, and 2,423 moderately damaged. While much of the city was damaged by 10 May 2015, 1,344 structures were newly damaged and 67 structures experienced an increase in damage between that date and 25 May 2016. This analysis does not include pre-war military bases and facilities. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Geodata of Damage Assessment of Puli Khumri Area, Baghlan Province, Afghanistan

This map illustrates satellite-detected potentially damaged structures in the area of Puli Khumri, Baghlan Province, Afghanistan. The Puli Khumri area is located approximately 190 kilometers southwest of the 26 October 2015 earthquake epicenter. Using Pleiades satellite imagery acquired 03 November 2015 and WorldView-2 imagery from 01 September 2014, UNITAR - UNOSAT identified 133 potentially damaged structures.  Note that some areas heavily damaged in the south of Qahwakhana appear to have also been affected by a limited landslide. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Venezuela (Bolivarian Republic of) - Spatial Distribution of Population (2015-2025)

Constrained estimates, total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.&nbsp;  
  
More information can be found in the [Release Statement](https://data.worldpop.org/repo/prj/Global_2015_2030/R2024B/doc/Global2_Release_Statement_R2024B_v1.pdf)  
  
The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

Tags: baseline population, geodata
Organization: WorldPop