AndreaBozzo/ceres-open-data-index huggingface dataset:
Lava flow and geological information in NordKivu Province, DR Congo and Western Province, Rwanda as of 01 June 2021

**UNOSAT code: VO20210523COD**  This map illustrates the lava flow extent and the related geological information north of Goma airport, Nord-Kivu province, D.R. of the Congo as detected by satellite images acquired after the eruption of the Mount Nyiragongo on 22 May 2021. UNITAR-UNOSAT analysis used Sentinel-1 acquired on 25 May 2021, Sentinel-2 & Pleiades images acquired on 1 June 2021, at respectively 16:21 UTC,  08:30 UTC and 11:35 UTC, to extract the lava flow extent. Within this map, three vents have been identified along the hillside south of Nyiragongo caldera. In addition, about 10 km of fissures have been mapped and are mainly in NNE-SSW and NNW-SSE directions. 
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Tags: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)
Damage Assessment in Tani district, Khost province as of 23 June 2022

**UNOSAT code: EQ20220622AFG**  This map illustrates potentially damaged buildings and damaged buildings in Tani district, Khost province of Afghanistan as detected by Worldview-3 image acquired on 23 June 2022. Within the analyzed area, UNOSAT has identified 156 potentially damaged buildings, 70 damaged buildings and 58 shelters.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).


Tags: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
North Kharkiv Rapid Damage Assessment Overview Map

**UNOSAT code: CE20220223UKR**  This map illustrates a satellite imagerybased Rapid Damage Building Assessment (RDBA) in the North of Kharkiv, Ukraine. The RDBA divides the area of interest into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell.

Based on imagery collected on 21, 22 and 23 March 2022, analysts found that 72 cells out of 1,866 cells in the North of Kharkiv sustained visible damage. This represents approximately 4% of the cells over the city.

This analysis is based on structures visibly damaged as of 21, 22 and 23 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. 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: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage Assessment in Les Anglais commune, South department as of 23 August 2021

**UNOSAT code: EQ20210814HTI**  This map illustrates potentially damaged structures/buildings in Les Anglais Commune, South department of Haiti as detected by Pleiades image acquired on 23 August 2021. Within the analyzed area, UNOSAT has identified 3 damaged structures, 41 potentially damaged structures, 4 road obstacles and 8 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)
Geodata of Damage Assessment of West Sundar Bazar Area, Western Region, Nepal

This map illustrates satellite-detected damage and destruction in the the western Sundar Bazar area of Nepal. Located roughly 29 to 33 kilometers west of the 25 April 2015 earthquake epicenter, the western Sundar Bazar area was impacted by this event. Using satellite imagery acquired 29 April 2015 UNITAR / UNOSAT identified a total of 121 affected structures. Approximately 26 of these were destroyed, 77 severely damaged, and 18 moderately damaged. 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)
Impact des feux de forêts le 01 août 2021, gouvervorats de Jendouba et Le Kef, Tunisie

**UNOSAT code: FR20210729TUN**  Cette carte illustre les zones d'incendies observées à partir d'une image satellite PlanetScope acquise le 01 août 2021, au sud-ouest de la ville de Ghardimaou.
Dans les 9,700 ha de zone analysée, environ 530 ha et 2,100 ha de végétation semblent avoir brûlé dans les délégations de Ghardimaou et Sakiet Sidi Youssef.
Ceci est une analyse préliminaire et n'a pas encore été validée sur le terrain. Ne pas hésiter à envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

Tags: disaster risk reduction-drr, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents between 14 and 18 May 2022 over South Sudan

**UNOSAT code: FL20220424SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 20 to 24 April 2022 compared with the period from 14 to 18 May 2022. Within the cloud free analyzed areas of about 630,000 km2, a total of about 9,000 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased of about 800 km2 since the period between 20 to 24 April 2022. Based on Worldpop population data and the maximal flood water coverage, ~220,000 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)
Landslide and flash floods impact analysis in Umdloti village, eThekwini Metropolitan Municipality, KwaZulu-Natal

**UNOSAT code: FL20220418ZAF**  This map illustrates satellite-detected landslides/mudflow in Umdloti village, eThekwini Metropolitan Municipality, KwaZulu-Natal Province, South Africa as observed from a NewSat image acquired on 13 April 2022.
Within the analyzed area, 14 buildings appear to be affected and 13 are potentially affected. Affected roads were also identified. 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)
Damage Assessment in Tayum Town, Abra Province, Cordillera Administrative Region, Philippines

**UNOSAT code: EQ20220727PHL**  This map illustrates potentially damaged buildings and damaged buildings in Tayum Town, Abra Province, Cordillera Administrative Region, Philippines as detected by Pléiades satellite image acquired on 29 July 2022. Within the analyzed area, UNOSAT has identified 37 potentially damaged buildings and 1 damaged buildings. 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 of Old City, Mosul, Ninawa Governorate, Iraq (30 June 2017)

This map illustrates satellite-detected damage in Old City, Mosul, Ninawa Governorate, Iraq. Using satellite imagery acquired 30 June 2017, UNITAR - UNOSAT identified a total of 5,536 affected structures within this part of city. This marks an overall increase of 37% in damage affected structures from the assessment fourteen days prior on 16 June. Approximately 490 of these were destroyed (9% of the total affected buildings), 3,310 severely damaged (60% of the total affected buildings) and 1,736 moderately damaged (31% of the total affected buildings). This marks a 150% increase in destroyed buildings, 0% in moderately damaged buildings and 57% severely damaged buildings from the 16 June assessment.  The most heavily impacted area appears to be the Ammu Baqqal neighbourhood (see inset). Due to the densely constructed nature of this part of the city, these values might be underestimated. 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)
Satellite detected water extents in Banjul, Kanifing, and Brikama Regions, Gambia as of 10 August 2022

**UNOSAT code: FL20220801GMB**  This map illustrates satellite-detected surface waters in Satellite detected water in Banjul, Kanifing, and Brikama Regions, Gambia 
as observed from a Sentinel-2 image acquired on 10 Aug 2021 at 18:18 local time. Within the analyzed cloud free zones of about 960 km2, about 26 km2 of lands 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 the districts of Kanifing with ~ 7,300 people, Kombo North/St Marie with ~ 7,000 and Kombo South with ~ 4,100 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)
Landslide analysis in Mount Talakmau in Pasaman & Pasaman Barat districts, Indonesia as of 04 March 2022

**UNOSAT code: LS20220308IDN**  This map illustrates satellite-detected landslides in Mount Talakmau, Pasaman & Pasaman Barat dsitricts, Indonesia as observed from a Sentinel-2 satellite imagery acquired on 04 March 2022 at 10:48 local time.
Within the analyzed area, about 6 km2 of landslides are observed. 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: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)
Geodata of Damage Assessment of Manbu Area, Western Region, Nepal

This map illustrates satellite-detected damage and destruction in the Manbu area of Nepal. Located roughly 10 to 25 kilometers east of the 25 April 2015 earthquake epicenter, the Manbu area was significantly impacted by this event. Using satellite imagery acquired 03 May 2015 and 29 April 2015 UNITAR / UNOSAT identified a total of 1,524 affected structures in the Manbu area. Approximately 786 of these were destroyed, 375 severely damaged, and 363 moderately damaged. 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)
Geodata of Satellite based damage assessment of Gaza Strip, Occupied Palestinian Territory

This map illustrates satellite-detected damage and destruction in Gaza Strip, resulting from recent violence in the area. Using a satellite image collected 27 & 28 August 2014 by the Pleiades satellite, and compared with a pre-crisis Pleiades image collected 6 July 2014, UNOSAT analysis has identified 6,769 destroyed structures, 3,565 severely damaged structures, and 4,938 moderately damaged structures in the analysed area. In addition, 7,473 craters on roads and in agricultural and non-urbanized areas are also visible in the crisis images. Note that a few areas along the border with Israeli were analysed in less detail as imagery was downsampled. 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)
Satellite detected water extents in Maganja Da Costa & Namacurra Districts, Mozambique as of 16 March 2022

**UNOSAT code: TC20220311MOZ**  This map illustrates satellite-detected surface waters in Nante, Macuze & Namacurra posto, Zambezia Province, Mozambique as observed from a TerraSAR-X image acquired on 16 March 2022 at 05:10 local time. Within the analyzed area of about 12,400 ha, about 3,180 ha of lands appear to be flooded. Based on GRID3 settlement extent data and the detected surface waters, about 60 ha of the urban area is potentially exposed to floodwaters.
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)
Geodata of Damage Assessment in Gaza Strip, Occupied Palestinian Territory

This map illustrates satellite-detected damage and destruction of health facilities in Gaza Strip, resulting from recent conflicts in the area. Using satellite imagery collected 14 August 2014 and 27-28 August 2014 by the Pleiades satellite, and compared with a pre-crisis Pleiades image collected 6 July 2014, UNOSAT analysis has identified  4 destroyed structures, 1 severely damaged structures, 13 moderately damaged structures and 5 possibly damaged structures from a total of 101 hospitals in the Gaza Strip. The Governorate of Gaza represents 74% of the total damaged hosptial structures. 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)
Satellite detected waters in Quang Tri Province of Viet Nam as of 29 October 2020

**UNOSAT code: TC20201028VNM**  This map illustrates satellite-detected surface waters in Quang Tri Province of Viet Nam as observed from a Sentinel-1 image acquired on 29 October 2020 at about 05:43 local time. Within the analyzed area of about 4,600 km2, a total of about 230 km2 of lands appear to be flooded. The water extent appears to have increased of about 90 km2 since 25 October 2020. Based on Worldpop population data and the detected surface waters, about 65,000 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 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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Geodata of Damage Assessment of Kobane, Aleppo Governorate, Syria

This map illustrates satellite-detected damage and destruction in a portion of the city of Kobane, Aleppo Governorate, Syria. Using satellite imagery acquired 22 January 2015, 6 December 2014, and 6 September 2014, UNITAR / UNOSAT identified a total of 3,247 affected structures by 22 January 2015 within the area analyzed. Approximately 1,206 of these were destroyed, 1,169 severely damaged, and 872 moderately damaged. A total of 979 impact craters were also identified within Kobane and its immediate surroundings. The inset images show craters likely caused by air strikes. By 6 December 2014 UNOSAT identified a total of eight craters possible caused by air strikes in the neighborhoods of Sanayi and Kaniya Kurdan and by 22 January 2015 an additional twelve were identified in the neighborhoods of Kaniya Kurdan and Saredari, a possible indicator of ongoing bombardment in the area. 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)
Guyana: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
Landslide detection in Mbale district, eastern region, Uganda as of 9 August 2022

**UNOSAT code: FL20220803UGA**  This map illustrates satellite-detected landslides in Budwale, Lwasso, Wanale, Bungokho Mutoto sub-countries and Wanale Division and Northern Division, Mbale district, eastern region, Uganda as observed from a Sentinel-2 image aquired on 9 August 2022. Within the analyzed area, 27ha landslide scars are observed. Based on Wordlpop population data about 200,700 people live inside the analyzed 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)
Algeria - 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
Ecuador: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Ecuador: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
French Guiana: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in French Guiana: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Guyana: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Guyana: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Peru: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Peru: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, births, children, demographics, elderly, geodata, health, maternity, men, women, youth
Organization: AI for Good at Meta
Paraguay: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Paraguay: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, births, children, demographics, elderly, geodata, health, maternity, men, women, youth
Organization: AI for Good at Meta
Suriname: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Suriname: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, births, children, demographics, elderly, geodata, health, maternity, men, women, youth
Organization: AI for Good at Meta
Aruba: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Aruba: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: baseline population, children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta