{"geometry": {"type": "MultiPolygon", "coordinates": [[[[16.81916, 79.87221], [18.74249, 79.53415], [18.91819, 79.16693], [21.54042, 78.84054], [18.96993, 78.452], [17.20097, 76.69942], [14.46722, 77.17165], [13.67666, 77.86415], [11.33701, 78.96054], [10.70597, 79.51221], [16.81916, 79.87221 ] ]], [[ [ 20.03514, 80.4636], [21.76111, 80.17748], [25.28944, 80.27499], [27.2293, 80.09652], [25.97527, 79.50777], [23.75916, 79.17415], [20.79305, 79.37679], [18.77139, 79.71748], [18.41555, 80.17249], [20.03514, 80.4636 ] ]], [[ [ 23.33611, 78.19748], [24.335, 77.88415], [23.90236, 77.50464], [20.89277, 77.44304], [21.645, 77.91249], [23.33611, 78.19748]]]]}, "type": "Feature", "properties": {"url": "/group/sjm", "name": "Svalbard and Jan Mayen Islands"}, "id": "SJM"}
Svalbard and Jan Mayen Islands
20
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Time Period of the Dataset [?]: September 27, 2023-March 25, 2024
... More
Modified [?]: 25 March 2024
Dataset Added on HDX [?]: 14 December 2023
This dataset updates: Every day
Resource has no data rows! No conflict and disaster population movement (flows) data recorded for Svalbard and Jan Mayen Islands in the last 180 days.
Internally displaced persons are defined according to the 1998 Guiding Principles (
https://www.internal-displacement.org/publications/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD), accessible at
https://www.internal-displacement.org/database/displacement-data. The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.
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Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['railway'] IN ('rail','station')
Features may have these attributes:
name
name:en
railway
ele
operator:type
layer
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['amenity'] IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office')
Features may have these attributes:
name
name:en
amenity
operator
network
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['healthcare'] IS NOT NULL OR tags['amenity'] IN ('doctors', 'dentist', 'clinic', 'hospital', 'pharmacy')
Features may have these attributes:
name
name:en
amenity
building
healthcare
healthcare:speciality
operator:type
capacity:persons
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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10+ Downloads
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay')
Features may have these attributes:
name
name:en
waterway
covered
width
depth
layer
blockage
tunnel
natural
water
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap contains roughly 852 km of roads in this region. Based on AI-mapped estimates, this is approximately 84 % of the total road length in the dataset region. The average age of data for the region is 4 years ( Last edited 15 days ago ) and 17% of roads were added or updated in the last 6 months.
Read about what this summary means : indicators , metrics
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['highway'] IS NOT NULL
Features may have these attributes:
name
name:en
highway
surface
smoothness
width
lanes
oneway
bridge
layer
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap contains roughly 2.0 thousand buildings in this region. Based on AI-mapped estimates, this is approximately 100% of the total buildings.The average age of data for this region is 4 years ( Last edited 15 days ago ) and 14% buildings were added or updated in the last 6 months.
Read about what this summary means : indicators , metrics
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['building'] IS NOT NULL
Features may have these attributes:
name
name:en
building
building:levels
building:materials
addr:full
addr:housenumber
addr:street
addr:city
office
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['aeroway'] IS NOT NULL OR tags['building'] = 'aerodrome' OR tags['emergency:helipad'] IS NOT NULL OR tags['emergency'] = 'landing_site'
Features may have these attributes:
name
name:en
aeroway
building
emergency
emergency:helipad
operator:type
capacity:persons
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
10+ Downloads
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['amenity'] = 'ferry_terminal' OR tags['building'] = 'ferry_terminal' OR tags['port'] IS NOT NULL
Features may have these attributes:
name
name:en
amenity
building
port
operator:type
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city')
Features may have these attributes:
name
name:en
place
population
is_in
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['amenity'] IS NOT NULL OR tags['man_made'] IS NOT NULL OR tags['shop'] IS NOT NULL OR tags['tourism'] IS NOT NULL
Features may have these attributes:
name
name:en
amenity
man_made
shop
tourism
opening_hours
beds
rooms
addr:full
addr:housenumber
addr:street
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
Time Period of the Dataset [?]: March 05, 2024-March 05, 2024
... More
Modified [?]: 5 March 2024
Dataset Added on HDX [?]: 15 May 2020
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :
tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university')
Features may have these attributes:
name
name:en
amenity
building
operator:type
capacity:persons
addr:full
addr:city
source
name:no
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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Time Period of the Dataset [?]: July 10, 2023-November 01, 2023
... More
Modified [?]: 31 October 2023
Dataset Added on HDX [?]: 30 June 2022
This dataset updates: As needed
Svalbard and Jan Mayen Islands population density for 400m H3 hexagons.
Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.
Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.
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Time Period of the Dataset [?]: July 10, 2023-July 10, 2023
... More
Modified [?]: 10 July 2023
Dataset Added on HDX [?]: 10 July 2023
This dataset updates: As needed
Svalbard and Jan Mayen Islands administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Gobal version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
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Time Period of the Dataset [?]: January 01, 2021-December 31, 2021
... More
Modified [?]: 17 April 2023
Dataset Added on HDX [?]: 30 May 2022
This dataset updates: Every year
Internally displaced persons are defined according to the 1998 Guiding Principles (
http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"People Displaced" refers to the number of people living in displacement as of the end of each year.
"New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
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Time Period of the Dataset [?]: January 01, 1970-December 31, 2012
... More
Modified [?]: 21 December 2022
Dataset Added on HDX [?]: 4 August 2021
This dataset updates: Every three months
Education indicators for Svalbard and Jan Mayen Islands.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September)
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Time Period of the Dataset [?]: January 01, 2019-March 29, 2024
... More
Modified [?]: 4 December 2021
Dataset Added on HDX [?]: 14 February 2019
This dataset updates: Live
Live list of active aid activities for Svalbard and Jan Mayen Islands shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from
http://www.d-portal.org
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10+ Downloads
Time Period of the Dataset [?]: January 01, 2000-December 31, 2020
... More
Modified [?]: 16 September 2020
Dataset Added on HDX [?]: 27 May 2019
This dataset updates: Every year
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below.
These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country.
They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method,
with either the unconstrained or constrained top-down disaggregation method used.
Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):
- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national
population estimates (UN 2019).
Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.
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/WP00645
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10+ Downloads
Time Period of the Dataset [?]: January 01, 2000-December 31, 2020
... More
Modified [?]: 22 June 2020
Dataset Added on HDX [?]: 24 November 2020
This dataset updates: Every year
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)
-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
-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
Unconstrained individual countries 2000-2020 population UN adjusted count datasets 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 unconstrained top-down modelling method.
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
-
Time Period of the Dataset [?]: January 01, 2000-December 31, 2020
... More
Modified [?]: 1 November 2018
Dataset Added on HDX [?]: 27 May 2019
This dataset updates: Every year
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
A description of the modelling methods used for age and sex structures can be found in
Tatem et al and
Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined
here. 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