AndreaBozzo/ceres-open-data-index huggingface dataset:
United States Minor Outlying Islands: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Pakistan Health Facilities with 3 Word Addresses

The dataset is based on the assessments and Health Resources Availability and Mapping (HeRAM) carried out by World Health Organization (WHO) in collaboration with health cluster partners during different emergencies in Pakistan. Please note that it is not necessary that the assessment covered all the health facilities in a particular district. These have now been provided with a 3 word address so those on the ground can communicate the location of each facility.

Tags: geodata, health, health facilities, operational capacity
Organization: what3words (inactive)
Novel Coronavirus (COVID-19) Cases Data

######JHU Has Stopped Collecting Data As Of 03/10/2023
>###### After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations. 
>######The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics.

Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the [2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository](https://github.com/CSSEGISandData/COVID-19) on Github.  
  
Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths.   

On 23/03/2020, a new data structure was released. The current resources for the latest time series data are:  

-  time_series_covid19_confirmed_global.csv  
-  time_series_covid19_deaths_global.csv 
-  time_series_covid19_recovered_global.csv


---DEPRECATION WARNING---  
The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020:  

-  time_series_19-covid-Confirmed.csv  
-  time_series_19-covid-Deaths.csv  
-  time_series_19-covid-Recovered.csv  


Tags: affected population, covid-19, disease, epidemics-outbreaks, fatalities, health, hxl
Organization: Johns Hopkins University Center for Systems Science and Engineering
Uganda - Ujana Coffee Project Database

This dataset contains information from the Ujana Coffee Project, a five-year program implemented by Sawa World in partnership with the Lavazza Foundation. The project offers a solution to diversify the income of smallholder coffee farmers in Uganda by providing access to locally-created, eco-friendly, and easy-to-start income skills that allow them to start small-scale businesses with low start-up costs and rapidly improve their livelihoods, those of their families, and support sustainable coffee farming. This additional revenue from the income skills and motivates them to stay in the agricultural sector for the long-term.

Tags: education, employment, livelihoods, socioeconomics, women, youth
Organization: Sawa World
Satellite detected water extents between 04 and 08 October 2022 over South Sudan

**UNOSAT code FL20220424SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 04 to 08 October 2022 compared with the period from 10 to 14 September 2022. Within the cloud free analyzed areas of about 620,000 km², a total of about 48,000 km² of lands appear to be affected with flood waters in which ~16,500 km² are herbaceous wetlands. Water extent appears to have increased of about 18,000 km² since the period between 10 to 14 September 2022. Based on Worldpop population data and the maximal flood water extent ~940,000 people are potentially exposed or living close to flooded areas. By considering the maximal flood water extent and landcover from ESA we estimate to ~16,500 ha of croplands which are potentially affected by floods.  
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents between 12 and 16 October 2022 over Region Autonoma del Atlantico Norte, Nicaragua

**UNOSAT code TC20221014NIC**  This map illustrates cumulative satellite-detected water using VIIRS in Region Autonoma del Atlantico Norte, Nicaragua between 12 to 16 October 2022 compared with the period from 27 September to 01 October 2022. Within the cloud free analyzed areas of about 30,000 km², a total of about 1,900 km² of lands appear to be affected. Water extent appears to have increased of about 1,400 km² since the period between 27 September to 01 October 2022. Based on Worldpop population data and the maximal flood water extent ~8,500 people are potentially exposed or living close to flooded areas amongst the 29,000 people living in cloud free 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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Preliminary Satellite Derived Flood Evolution Assessment, Islamic Republic of Pakistan - 20 January 2023

**UNOSAT code FL20221121PAK**  Status: Overall decrease of flood waters observed  
Further action(s): continue monitoring  
Evolution of Cumulative Flood Waters over I.R. of Pakistan (01-07 January 2023 Vs 09-15 January 2023):  
Between 09 and 15 January 2023 approximately 4.5 million people remain potentially exposed or living close to maximum floodwaters areas(*);  
Approximately 1.3 million people are potentially exposed or living close to minimum floodwaters areas(**) between 09 and 15 January 2023;  
Based on satellite observations between 01 and 07 January 2023 and compared with observations between 09 and 15 January 2023 , the maximum flood water extent appears to continue to retract with approximately ~ -1,800 km² in Sindh , ~ - 250 km² in Balochistan, ~ -200 km²  in Khyber Pakhtunkhwa and ~ -200 km²  in Gilgit Baltistan.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Eaux de surface détectées par satellite entre le 01 et le 28 novembre 2022 dans les provinces de l'Equateur, du Nord-Ubangi et du Sud-Ubangi, 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 au-dessus des provinces de l'Equateur, du Nord-Ubangi et du Sud-Ubangi (République Démocratique du Congo) entre le 1er et le 28 novembre 2022. Dans la zone analysée d'environ 210 000 km², un total d'environ 6 800 km² de terres semblent être inondées. L'étendue des eaux de surface semble être plus petite d'environ 4 000 km² comparé à la période du 1er au 30 novembre 2019. D'après les données démographiques de Worldpop et les eaux de surface détectées par satellite, environ 245 000 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)
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - French Polynesia

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-pyf)_

Tags: demographics, population
Organization: Pacific Community
Nicaragua - 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
Human Development Data (1990-2021)

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities.
The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

Tags: development
Organization: UNDP Human Development Reports Office (HDRO)
Myanmar - Subnational Edge-matched Administrative Boundaries

Myanmar administrative level 0-5 edge-matched gazetteer, shapefiles, and geodatabase.

These layers are suitable for database or GIS linkage to the [Myanmar - Subnational Population Statistics tables](https://data.humdata.org/dataset/cod-ps-mmr).

Vetting by Information Technology Outreach Services (ITOS) with funding from USAID.

This edge-matched product is based on the [Myanmar - Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-mmr) (COD-AB).


Tags: administrative boundaries-divisions, crisis-myanmar-earthquake, gazetteer, geodata
Organization: OCHA Field Information Services Section (FISS)
Armenia - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.  
  
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
Saint Lucia - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.  
  
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
Kazakhstan - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.  
  
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
Jamaica - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2, ADM3.  
  
Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database [www.geoboundaries.org](https://www.geoboundaries.org) is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.  

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: geoBoundaries
Dominica - 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
Lava flow and affected structures caused by Nyiragongo volcanic eruption, Nord-Kivu Province, DR Congo

**UNOSAT code: VO20210523COD**  This map illustrates potentially affected structures and buildings in Nyiragongo district, Nord-Kivu province, DR Congo as detected by satellite image acquired after the eruption of Mount Nyiragongo volcano on 22 May 2021. UNITAR-UNOSAT analysis used a TerraSAR-X image acquired on 24 May 2021, at 16:13 UTC, to observe the lava flow. Within the analysis extent, about 1,600 structures are potentially affected by the lava flow.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
Important Note: Lava flow analysis from radar images may overestimate the presence of the lava tract due to the backscattering properties of the radar signal.

Tags: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)
Geodata of Damage Assessment of Sadah, Saada Governorate, Yemen

This map illustrates satellite-detected damage and destruction in the city of Sadah, Saada Governorate, Yemen. Using satellite imagery acquired 17 May 2015 and 7 January 2015, UNITAR-UNOSAT identified a total of 1,171 affected structures, approximately 273 structures were destroyed, 271 were severely damaged, and 627 were moderately damaged. Additionally, 35 impact craters were found within the city, the majority of which were located along the runway of Sadah City Airport. A total of 4 medical facilities were identified within 100 meters of damaged and destroyed buildings, and it is possible that these facilities also sustained some damage. 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)
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - Palau

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-plw)_

Tags: demographics, population
Organization: Pacific Community
Geodata of Damage Assesment in Bangui, Central African Republic

This map illustrates locations of destroyed structures within the arrondissements of Bangui, Central African Republic. Using satellite imagery acquired 16 November 2013, 22 February 2014, and 6 June 2014 UNOSAT reviewed the city of Bangui to locate signs of destroyed structures. By 22 February 2014, a total of 1,872 structures were destroyed in the area of Bangui, with 1,341 structures detected in the 8 arrondissements and an additional 531 located in the surrounding area. As of 6 June 2014 a total of 368 damaged structures have been reconstructed and 871 additional structures have been severely damaged or destroyed since 22 February 2014. Pre-crisis imagery used for this analysis was collected on 16 November 2013, and thus structures destroyed previous to 16 November 2013 are not indicated on this map. This is a preliminary analysis & 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 Sinjar Area, Nineveh Province, Iraq

This map illustrates satellite-detected damage and destruction in the Sinjar area of Nineveh Province, Iraq. Using satellite imagery acquired 18 and 28 November 2015, 30 December 2014, and 07 August 2014, UNITAR - UNOSAT identified a total of 2,383 potentially affected structures. Approximately 810 of these were destroyed, 685 severely damaged, 519 moderately damaged, and 369 possibly damaged. Note that due to less-than-ideal imagery characteristics the error margin for this analysis is likely higher than usual, and due to terrain distortion the spatial accuracy is +/- 15 meters. 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)
Análisis en terreno: Visitas de control y reconocimiento a lo largo de la quebrada Lizama y Caño Muerto, Barrancabermeja

El siguiente mapa ilustra el recorrido de las observaciones directas colectadas en campo por el equipo UNDAC en apoyo a la emergencia provocada por el derrame de petróleo producido el 2 de marzo de 2018 por el pozo Lizama 158 (propiedad Ecopetrol), a lo de la quebrada Lizama y Caño Muerto hasta su confluencia con el rio Sogamoso, en Barrancabermeja, Colombia. Dichas observaciones fueron tomadas durante los días 15 y 18 de abril 2018 utilizando la aplicación UN-ASIGN que permite colectar fotos georreferenciadas y su información asociada desde el terreno. UNOSAT en apoyo al equipo UNDAC, ha integrado dicha información que incluye por un lado la localización y distribución espacial de los distintos puntos de control visitados - visibles en el mapa de referencia – y a su vez las distintas fotos tomadas en terreno durante fichas visitas de control. Por favor, envíen sus comentarios a UNITAR-UNOSAT.

Tags: geodata
Organization: United Nations Satellite Centre (UNOSAT)
Hungary - 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