AndreaBozzo/ceres-open-data-index huggingface dataset:
Martinique (France) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Montserrat - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Saint Martin (France) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Guam - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Guadeloupe (France) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Falkland Islands (Malvinas) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Cayman Islands - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Saint Barthélemy (France) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Burkina Faso health districts (districts de santé)

Burkina Faso health districts (districts de santé) P-coded and fitting below [Burkina Faso administrative level 0-3 boundaries](https://data.humdata.org/dataset/burkina-faso-administrative-boundaries) administrative level 2 (department).

Example P-code:  BFDS130001
  
BF is the ADM0_FR,  representing Burkina Faso

  DS means "District de santé"

 13 is from ADM1_PCODE BF13

 00 is from ADM2_PCODE BF1300

 01 means District de santé number 01 within BF1300  




Tags: gazetteer, health facilities
Organization: OCHA Burkina Faso
Tanintharyi Region Mangrove Forest dataset

Geotiff download link : http://bit.ly/2PHtJyf

This is a Landsat 8-based classification of the extent and condition of mangrove forests in Tanintharyi Region. The classification is derived from satellite images which were acquired in 2014. The classification is based on ground truth data, which was collected in May and June 2015. In addition, further training polygons were digitized based on high-resolution Google Maps and Bing Maps data. This dataset is a filtered version of the initial classification result. The classified mangrove classes are ‘Intact to slightly degraded mangroves’, ‘Degraded mangroves’, ‘Heavily degraded mangroves’ and ‘Nipa monoculture’.

suggested citiation: Stephani, A.; Oswald, P.; Koellner, T.; Wegmann, M., 2016. Tanintharyi Region Mangrove Forest dataset (2014). 
Point of contact: annastephani@gmx.de and patrickoswald@fauna-flora.org

Tags: geodata, topography
Organization: Myanmar Information Management Unit (MIMU)
Tanintharyi Region Land Cover (Original)

Geotiff download link: http://bit.ly/2IjLZtw

This dataset is the result of a land cover analysis for Myanmar's Tanintharyi Region based on March, 2016 Landsat 8 OLI imagery. The primary purpose of the study was to map natural forest for each of four ecological forest types (Mangrove, Mixed Deciduous, Lowland Evergreen, Upland Evergreen). A number of other land use/land cover types are also included in the dataset, including human settlement areas, rice paddyfields, and agroforestry plantations. This dataset is the original version generated according to the methodology outlined in the corresponding manuscript.  [Citation: Connette, G., P. Oswald, M. Songer, and P. Leimgruber. 2016. Mapping distinct forest types improves overall forest identification based on multi-spectral Landsat imagery. Remote Sensing 8: 882.]  [Spatial reference: WGS84 UTM47N]

Original dataset title: Tanintharyi Region Land Cover - March 2016 (Original)

Tags: geodata, topography
Organization: Myanmar Information Management Unit (MIMU)
Tanintharyi Region Land Cover (Improved)

Geotiff download link: http://bit.ly/2ToMIjL

This dataset is the result of a land cover analysis for Myanmar's Tanintharyi Region based on March, 2016 Landsat 8 OLI imagery. The primary purpose of the study was to map natural forest for each of four ecological forest types (Mangrove, Mixed Deciduous, Lowland Evergreen, Upland Evergreen). A number of other land use/land cover types are also included in the dataset, including human settlement areas, rice paddyfields, and agroforestry plantations. This dataset is a REVISED version of the land cover map generated according to the methodology outlined in the corresponding manuscript (see below for citation).  This version has been manually edited to fill cloud holes using 2015 data and to fix a number of obvious mis-classifications, particularly for oil palm and settlement areas.  [Citation: Connette, G., P. Oswald, M. Songer, and P. Leimgruber. 2016. Mapping distinct forest types improves overall forest identification based on multi-spectral Landsat imagery. Remote Sensing 8: 882.] [Spatial reference: WGS84 UTM47N]

Original dataset title: Tanintharyi Region Land Cover - March 2016 (Improved)

Tags: geodata, topography
Organization: Myanmar Information Management Unit (MIMU)
Tanintharyi Region Forest Cover Change

Geotiff download link : http://bit.ly/2wq7KFy
Metadata download link: http://geonode.themimu.info/documents/26

A Landsat-based classification of forest cover in Tanintharyi Region with a focus on changes in intact forest between 2002 and 2014.

This dataset expands upon the Myanmar 2002-2014 Forest Cover Change raster*, by differentiating oil palm plantations from other plantations.

Developed by: ALARM, Smithsonian Institution, GMAP and American Museum of Natural History

*http://geonode.themimu.info/layers/geonode%3Amyanmar_forestcoverchange

See the recommended style file (.txt) in the documents section for associating raster values and creating the legend.

Original dataset title: Tanintharyi Region 2002-2014 Forest Cover Change

Tags: geodata, topography
Organization: Myanmar Information Management Unit (MIMU)
Kachin State and Sagaing Region Forest Cover Change

Geotiff download link : http://bit.ly/2VOvrlD
Metadata Download link: http://geonode.themimu.info/documents/27

A Landsat-based classification of forest cover in Kachin State and Sagaing Region with a focus on changes in intact forest between 2002 and 2014.

This dataset expands upon the Myanmar 2002-2014 Forest Cover Change raster*, by differentiating mining from other non-forest land cover classes.

Developed by: ALARM, Smithsonian Institution, GMAP and American Museum of Natural History

*http://geonode.themimu.info/layers/geonode%3Amyanmar_forestcoverchange

See the recommended style file (.txt) in the documents section for associating raster values and creating the legend.

Original dataset title: Kachin State and Sagaing Region 2002-2014 Forest Cover Change

Tags: geodata, topography
Organization: Myanmar Information Management Unit (MIMU)
El Salvador - 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
Suriname - 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
Belarus - 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
United Republic of Tanzania: Integrated Context Analysis (ICA), 2019


    The ICA is a process of consultations supported by mapped-out data that produces a strategic plan describing where different combinations of programme themes are appropriate to achieve goals of reducing food insecurity and climate related shock risk.

The ICA combines multi-year food security trends with natural shock risk data to highlight sub-national areas where different programme strategies make sense. Food security trend maps shows areas where safety nets can address regular food insecurity, and others where shocks make recovery more important. Climate-related natural shock risk maps show where DRR, preparedness and early warning efforts can complement food-security objectives. Atop this core foundation, mapped data on subjects including nutrition, gender, livelihoods and resilience can enrich theme-level strategic planning in which all pieces work together. The full group of ICA partners discuss these analytical results to arrive at strategic programmatic directions.
    

Tags: geodata, hazards and risk
Organization: WFP - World Food Programme
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 and 06 September 2014, UNITAR / UNOSAT identified a total of 3,167 affected structures within the area of this map. Approximately 1,167 of these were destroyed, 1,155 severely damaged, and 845 moderately damaged. The city-wide analysis of Kobane revealed a total of 3,247 affected structures, of which 1,206 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. 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 Deir Ez Zor, Deir Ez Zor Governorate, Syria

This map illustrates satellite-detected damage and destruction in a portion of the city of Deir Ez Zor, Deir Ez Zor Governorate, Syria. Using satellite imagery acquired 13 May 2014, 24 October 2013, and 06 December 2010, UNITAR / UNOSAT identified a total of 3,004 affected structures within the area of this map. Approximately 417 of these were destroyed, 1,023 severely damaged, and 1,564 moderately damaged. The city-wide analysis of Deir Ez Zor revealed a total of 3,112 affected structures, of which 454 were destroyed, 1,045 severely damaged, and 1,613 moderately damaged. While much of the city was damaged by 24 October 2013, 1,149 structures were newly damaged and 106 structures experienced an increase in damage between that date and 13 May 2014. This analysis was done 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)
Damage density of Damascus, Kafr Batna and Irbin subdistricts, Damascus Governorate, Syria

This map illustrates satellite-detected damage density in the subdistricts of Kafr Batna and Irbin and in the eastern part of Damascus city, Syrian Arab Republic. Using satellite imagery acquired 3 December 2017 and 2 April 2016, UNITAR - UNOSAT identified a total of 12,541 affected structures. Approximately 3,853 of these were destroyed, 5,141 severely damaged, and 3,547 moderately damaged. Comparison with the previous UNOSAT analysis using imagery from 2 April 2016 shows an overall increase of 6% in the number of damaged buildings since 2016. The areas with a higher increase in the percentage of damage are Ein Tarma (14% increase), Hammura (15% increase) and Kafr Batna (17 % increase). Moreover, approximately 7% of the buildings damaged as of April 2016 have been targeted again and suffered additional damage. The majority of these buildings are located in Ein Tarma, Jobar and Al Maamouniye. 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)
Bonaire, Saint Eustatius and Saba (The Netherlands) - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Mongolia - Subnational Administrative Boundaries

Mongolia administrative level 0-2 boundaries (COD-AB) dataset version 01.  
  
This dataset is structured into 2 levels:  
- Admin 1: 22 Aimag  
- Admin 2: 339 Soum  
  
  
Dates associated with this dataset:  
- 30 October 2025: dataset reviewed for accuracy and completeness  
- 19 October 2020: valid for use by the humanitarian community  
- 26 October 2020: last edit to the dataset before publishing  
- 26 October 2020: boundaries created by the source  
  
Contributed by [OCHA Regional Office for Asia and the Pacific (ROAP)](https://data.humdata.org/organization/ocha-roap).  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

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

Myanmar administrative level 0-5 boundaries (COD-AB) dataset version 01.  
  
This dataset is structured into 5 levels:  
- Admin 1: 18 State/Region  
- Admin 2: 80 District  
- Admin 3: 330 Township  
- Admin 4: 14174 Town / Village tract, partial coverage  
- Admin 5: 1999 , partial coverage  
  
  
Dates associated with this dataset:  
- 30 October 2025: dataset reviewed for accuracy and completeness  
- 15 February 2024: valid for use by the humanitarian community  
- 11 March 2024: last edit to the dataset before publishing  
- 11 March 2024: boundaries created by the source  
  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

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

Mali administrative level 0-2 boundaries (COD-AB) dataset version 03.  
  
This dataset is structured into 2 levels:  
- Admin 1: 20 Région  
- Admin 2: 160 Cercle  
  
  
Note: The normal administrative level 2 feature type(s) are region (20 features) and cercle (160units).  
  
  
Dates associated with this dataset:  
- 10 June 2025: dataset reviewed for accuracy and completeness  
- 04 September 2025: valid for use by the humanitarian community  
- 13 May 2025: last edit to the dataset before publishing  
- 20 February 2025: boundaries created by the source  
  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: OCHA Field Information Services Section (FISS)
American Samoa - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Libya - Subnational Administrative Boundaries

Libya administrative level 0-2 boundaries (COD-AB) dataset version 01.  
  
This dataset is structured into 2 levels:  
- Admin 1: 3 province  
- Admin 2: 22 governorate (muhafazat)  
  
  
Dates associated with this dataset:  
- 19 December 2024: dataset reviewed for accuracy and completeness  
- 07 May 2018: valid for use by the humanitarian community  
- 13 November 2018: last edit to the dataset before publishing  
- 13 November 2018: boundaries created by the source  
  
Contributed by [OCHA Middle East and North Africa (ROMENA)](https://data.humdata.org/organization/ocha-romena).  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

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

Lebanon administrative level 0-3 boundaries (COD-AB) dataset version 02.  
  
This dataset is structured into 3 levels:  
- Admin 1: 8 Governorate (Mouhafaza)  
- Admin 2: 26 District (Kaza)  
- Admin 3: 1627 Cadaster (Manatek Ikaria)  
  
  
Dates associated with this dataset:  
- 30 October 2025: dataset reviewed for accuracy and completeness  
- 13 November 2024: valid for use by the humanitarian community  
- 02 May 2014: last edit to the dataset before publishing  
- 02 May 2014: boundaries created by the source  
  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

Tags: administrative boundaries-divisions, crisis-greater-middle-east, gazetteer, geodata
Organization: OCHA Field Information Services Section (FISS)
Lao People's Democratic Republic - Subnational Administrative Boundaries

Lao People's Democratic Republic administrative level 0-2 boundaries (COD-AB) dataset version 01.  
  
This dataset is structured into 2 levels:  
- Admin 1: 18 province (khoueng) or prefecture (kampheng nakhon)  
- Admin 2: 148 district (muang)  
  
  
Dates associated with this dataset:  
- 30 October 2025: dataset reviewed for accuracy and completeness  
- 12 November 2019: valid for use by the humanitarian community  
- 01 January 2019: last edit to the dataset before publishing  
- 01 January 2019: boundaries created by the source  
  
Contributed by [OCHA Regional Office for Asia and the Pacific (ROAP)](https://data.humdata.org/organization/ocha-roap).  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: OCHA Field Information Services Section (FISS)