AndreaBozzo/ceres-open-data-index huggingface dataset:
Satellite detected landslide extent in Marigne-kokota Constituency, Isabel  Province, Solomon Island as of 12 December 2023

**UNOSAT code: TC20231206SLB, GDACS ID: 1001038**  This map illustrates satellite-detected landslides in Maringe-Kokota Constituency, Isabel Province, Solomon Islands, as observed from a Sentinel-2 satellite acquired on 12 December 2023 at 10:48 local time. Within the analyzed area of 50 km², about 2 km² of mudflow extent is observed. UNOSAT identified 24 potentially affected structures.  
  
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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
7 October 2023 M6.3 Western Afghanistan Herat, Preliminary Satellite-Based Comprehensive Damage Assessment Report

**UNOSAT code: EQ20231008AFG, GDACS ID: 1394952**  On the 7th of October 2023, a 6.3 magnitude earthquake struck the Herat province in the western part of Afghanistan. The epicentre was located 40 km north-west of Herat City and caused damage and destruction that triggered humanitarian needs for the local populations. The situation worsened when a second and a third strong earthquakes struck the region few days later, respectively on the 11th and 15th of October. The local government reported that the number of deaths was above 2000 people.   
After the earthquake, UNOSAT quickly estimated that more than a million people were living with the intensity zones above V. It was also estimated that between 150,000 and 230,000 buildings were located within the affected zones. The United Nation Office for the Coordination of Humanitarian Affairs (UNOCHA) reported that the worst affected districts correspond to Herat, Injil and Zindajan district with more than 21,500 destroyed homes. Furthermore in the Herat Province more than 230,000 homes have been impacted by the earthquake and 37,139 families have been left without home living in temporary shelter or open spaces (UNOCHA).  
At least 40 health facilities were affected during the earthquake, hampering the access to healthcare for an estimated of 580,000 people. One month after the earthquake people displaced from their home still suffer as the winter is approaching and temperatures are dropping (UNHCR).

Tags: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extent in Bardere City, Baardheere District, Gedo Region, Somalia, 22 November 2023

**UNOSAT code: FL20231105SOM**  This map illustrates satellite-detected surface waters in Bardere City, Baardheere District, Gedo Region, Somalia as observed from a WorldView-3 image acquired on 22 November 2023. Within the analysed area of about 32 km2 about 6 km2 of land appears to be flooded. The water extent appears to have been stable since 13 November 2023. Furthermore, within the analysed area about 2,600 buildings are identified as potentially affected by the floods.  
  
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)
Floods in Kenya, November 2023 - UNOSAT Live webmap

**UNOSAT code: FL20231124KEN**  This application provides geospatial information about the ongoing floods in Kenya.  
Important note: The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Montenegro - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1.  
  
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 Valdesia Region, Dominican Republic as of 21 November 2023

**UNOSAT code: FL20231120DOM, GDACS ID: 1102342**  This map illustrates cumulative satellite-detected water extent in 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 320 km² , less than 5 km² of land appears to be affected with flood waters and 2,500 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)
Mauritania Medium Term Projection  FEWS NET Acute Food Insecurity Classifications Geographic Data for 2017

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived.

Mauritania Medium Term Projection  FEWS NET Acute Food Insecurity Classifications Geographic data for 2017

Tags: food security, integrated food security phase classification-ipc
Organization: FEWS NET
Satellite detected water extent in Juba Dhexe and Jhuba Hoose Regions, Somalia as of 07 November 2023

**UNOSAT code FL20231105SOM**  This map illustrates satellite-detected surface waters in Bu'aaler and Saakow District, Juba Dhexe Region and Afmadow District, Juba Hoose Region Somalia as observed from a Sentinel-1 image acquired on 07 November 2023 at 02:54 UTC. Within the analysed area of about 7,600 km², about 180 km² of land 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).  
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)
Damage assessment over Antonivka City and Dachi City, Khersonskyi Region, Khersonska Oblast, Ukraine as of 07 June 2023

**UNOSAT code FL20230606UKR**  This map illustrates satellite-detected flood waters and affected structures over Antonivka City and Dachi City, Khersonskyi Region, Khersonska Oblast (Ukraine) as observed from a WorldView-3 image acquired on 7 June 2023 at 08:19 UTC; and ICEYE image acquired on 7 June 2023. Within the analysed area of 15 km², about 100% (2 km²) of Dachi City area appears to be flooded. 1,366 structures and 93 harbours are affected. About 23% (3 km²) of Antonivka City area appears to be flooded. 659 structures and 2 harbours are affected.   
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)
Surface Waters Monitoring In Pakistan - Evolution - 17 May 2023

**UNOSAT code FL20221121PAK**  Status: Overall decrease in the observed surface waters  
Further action(s): continue monitoring  
  
Evolution of Cumulative Surface Waters over I.R. of Pakistan (21 to 25 Apr. 2023) Vs. (26 to 30 Apr. 2023)  
Between 26 to 30 April 2023 approximately 1 million people are potentially exposed or living close to maximum floodwaters areas(*);  
Approximately 230,000 people are potentially exposed or living close to minimum floodwaters areas(**) between 26 to 30 April 2023;  
Based on satellite observations between 21 to 25 April 2023 and compared with observations between 26 to 30 April 2023, the maximum flood water extent appears to continue to retract with approximately ~ -3,700 km² in Sindh, ~ - 1,500 km² in Punjab, ~ -160 km²  in Balochistan and ~ - 180 km²  in Khyber Pakhtunkhwa.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
6 February 2023 M 7.8 Marash/Antep (Kehramanmarash) Earthquake, Preliminary Satellite-Based Comprehensive Damage Assessment Report

**UNOSAT code EQ20230206SYR, GDACS Id: 1357372**  This report provides satellite-based comprehensive damage assessment results over Syria following the 06th of February 2023 Marash/Antep earthquakes sequence which struck southern Türkiye and north-western parts of Syria. The mainshock measured a magnitude of 7.8 and occurred at a crucial moment, 4:15 am local time, when most people were at home sleeping. It was a shallow depth earthquake with an epicentre located about 35 km north-west of the Turkish city of Gaziantep.  
These earthquakes caused more than 46,000 deaths in Türkyie and over 4,500 in northwest Syria. The humanitarian community estimated that 8.8 million people live in the most affected areas in Syria. Overall, 170 sub-districts in 43 districts in 10 of Syria’s governorates have been impacted by the earthquake.  
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 over Southern Region, Malawi as of 14 March 2023

**UNOSAT code TC20230314MWI, GDACS Id: 1000961**  This map illustrates satellite-detected surface waters in Southern Region, Malawi as observed from a RCM-2 image acquired on 14 Mar. 2023 at 05:10 local time. Within the analyzed area of about 7,200 km2, about 430 km2 of land appear to be flooded.  
Based on Worldpop population data and the detected surface waters in the analyzed area, ~75,000 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).  
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)
Satellite detected water extents between 01 and 05 March 2023 over South Sudan

**UNOSAT code FL20220424SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 01 to 05 March 2023 compared with the period from 20 to 24 February 2023. Within the cloud free analyzed areas of about 630,000 km², a total of about 30,000 km² of lands appear to be affected with flood waters. Water extent appears to have increased of about 5,000 km² since the period between 20 to 24 February 2023. Based on Worldpop population data and the maximal flood water extent ~480,000 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)
Satellittoppdaget overflatevann langs med Gudbrandsdalslågen, Ringebu, Sør-Fron og Nord-Fron Kommune, Innlandet Fylke, Norge

**UNOSAT code FL20230811NOR**  ette kartet viser kumulativt satellittoppdaget overflatevann langs med Gudbrandsdalslågen i Ringebu, Sør-Fron og Nord-Fron kommune, Innlandet fylke, Norge, observert fra et Sentinel-1 bilde tatt den 10. august 2023 kl. 17:03 UTC.  
Innenfor det analyserte området på omtrent 500 km², er omtrent 15 km² med land observert som oversvømt. Basert på befolkningsdata fra Worldpop og det kartlagte overflatevannet er omtrent 800 personer potensielt eksponert eller bor i nærheten av det oversvømte områder.  
Dette er en foreløpig analyse og er ennå ikke validert på feltet.  
Vennligst send tilbakemelding fra bakken til FNs satellittsenter (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Zambia - 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 extents over Chaiyaphum and Nakhon Ratchasima Provinces, Thailand as of  4 October 2022

**UNOSAT code TC20220928THA, GDACS Id: 1000922**  This map illustrates satellite-detected surface waters in Chaiyaphum and Nakhon Ratchasima Provinces, Thailand as observed from a RCM-2 image acquired on 4 October 2022 at 06:08 local time. Within the extent of this map of 1,100 km², about 240 km² of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the map extent, about 24,000 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).  
  
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)
Guinea health facility training activities

(English description follows.) Rapports sur les activités de formation des travailleurs de la santé de première ligne dans les établissements sanitaires en Guinée, rapportés par les partenaires de la cluster «prévention des infections» (PCI). Voir aussi la base de données [Guinea healthcare master data] (https://data.hdx.rwlabs.org/dataset/guinea-healthcare-master-data), qui contient les données de référence de base utilisées ici.  Voir aussi les liens vers des tableaux de bord, le modèle de tableurs, et le mode d'emploi dans la galerie.

(Voir la description française ci-dessus.) Reports on safety training activities for front-line health workers at facilities in Guinea, submitted by the implementing organisations within the Infection Prevention and Control (IPC) cluster.  See also the [Guinea healthcare master data](https://data.hdx.rwlabs.org/dataset/guinea-healthcare-master-data) dataset, which contains the base reference data used here. See also the links to dashboards, the reporting template, and usage instructions in the gallery.

Tags: health, hxl
Organization: IPC Cluster Guinea (inactive)
Liberia Near Term Projection  FEWS NET Acute Food Insecurity Classifications Geographic Data for 2015

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived.

Liberia Near Term Projection  FEWS NET Acute Food Insecurity Classifications Geographic data for 2015

Tags: food security, integrated food security phase classification-ipc
Organization: FEWS NET
Cyprus - 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
Micronesia (Federated States of) - 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
Wallis and Futuna 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