A weekly dataset providing the total number of reported political violence, civilian-targeting, and demonstration events in South Georgia and the South Sandwich Islands. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
Resource has no data rows! No conflict and disaster population movement (flows) data recorded for South Georgia and the South Sandwich 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.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap contains roughly 27 km of roads in this region. Based on AI-mapped estimates, this is approximately 100 % of the total road length in the dataset region. The average age of data for the region is 3 years ( Last edited 23 days ago ) and 0% 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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
This dataset updates: Every month
This dataset is part of the data series [?]: HOTOSM - Roads
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap contains roughly 311 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 3 years ( Last edited 23 days ago ) and 0% 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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
South Georgia and the South Sandwich 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.
South Georgia And South S.S. 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.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
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.
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