This dataset contains gridded human population with a spatial resolution of 1 km x 1 km for the UK based on Census 2021 (Census 2022 for Scotland) and Land Cover Map 2021 input data. Data on population distribution for the United Kingdom is available from statistical offices in England, Wales, Northern Ireland and Scotland and provided to the public e.g. via the Office for National Statistics (ONS). Population data is typically provided in tabular form or, based on a range of different geographical units, in file types for geographical information systems (GIS), for instance as ESRI Shapefiles. The geographical units reflect administrative boundaries at different levels of detail, from Devolved Administration to Output Areas (OA), wards or intermediate geographies. While the presentation of data on the level of these geographical units is useful for statistical purposes, accounting for spatial variability for instance of environmental determinants of public health requires a more spatially homogeneous population distribution. For this purpose, the dataset presented here combines 2021/2022 UK Census population data on Output Area level with Land Cover Map 2021 land-use classes 'urban' and 'suburban' to create a consistent and comprehensive gridded population data product at 1 km x 1 km spatial resolution. The mapping product is based on British National Grid (OSGB36 datum).

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsPopulation DensityDefinition: This dataset provides Census 2021 estimates that classify usual residents in England and Wales by population density (number of usual residents per square kilometre). The estimates are as at Census Day, 21 March 2021.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Mauritius: (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).

This dataset contains the average weekly shipping density for the whole of the UK at a 2km grid resolution. For each year, AIS datasets were s&led from the first seven days of each month, commencing with January, at two-month intervals. The total value for all 6 weeks was divided by 6 to determine the weekly average, therefore decimal values may occur for certain cells. The weekly average was also multiplied by 52 to provide the estimated annual average.

The field headings in the attribute table are as follows:

0 - Unknown Vessels 1 - Non-Port service craft 2 - Port service craft 3 - Vessels engaged in dredging or underwater operations 4 - High Speed Craft 5 - Military or Law enforcement 6 - Passenger 7 - Cargo 8 - Tankers 9 - Fishing vessels 10 - Recreational vessels Week_Ave - Weekly Average Density Annual_Ave - Estimated annual density

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

India data available from WorldPop here.

In 2023, almost nine million people lived in Greater London, making it the most populated ceremonial county in England. The West Midlands Metropolitan County, which contains the large city of Birmingham, was the second-largest county at 2.98 million inhabitants, followed by Greater Manchester and then West Yorkshire with populations of 2.95 million and 2.4 million, respectively. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with around 1.89 million people. A patchwork of regions England is just one of the four countries that compose the United Kingdom of Great Britain and Northern Ireland, with England, Scotland and Wales making up Great Britain. England is therefore not to be confused with Great Britain or the United Kingdom as a whole. Within England, the next subdivisions are the nine regions of England, containing various smaller units such as unitary authorities, metropolitan counties and non-metropolitan districts. The counties in this statistic, however, are based on the ceremonial counties of England as defined by the Lieutenancies Act of 1997. Regions of Scotland, Wales, and Northern Ireland Like England, the other countries of the United Kingdom have their own regional subdivisions, although with some different terminology. Scotland’s subdivisions are council areas, while Wales has unitary authorities, and Northern Ireland has local government districts. As of 2022, the most-populated Scottish council area was Glasgow City, with over 622,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.

Understanding the size and spatial distribution of material stocks is crucial for sustainable resource management and climate change mitigation. This study presents high-resolution maps of buildings and mobility infrastructure stocks for the United Kingdom (UK) and the Republic of Ireland (IRL) at 10 m, combining satellite-based Earth observations, OpenStreetMaps, and material intensities research. Stocks in the UK and IRL amount to 19.8 Gigatons or 279 tons/cap, predominantly aggregate, concrete and bricks, as well as various metals and timber. Building stocks per capita are surprisingly similar across medium to high population density, with only the lowest population densities having substantially larger per capita stocks. Infrastructure stocks per capita decrease with higher population density. Interestingly, for a given building stock within an area, infrastructure stocks are substantially larger in IRL than in the UK. These maps can provide useful insights for sustainable urban planning and advancing a circular economy.

This dataset features a detailed map of material stocks in the United Kingdom and the Republic of Ireland on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

Spatial extent
This dataset covers the whole British Isles. Due to processing reasons, the dataset is internally structured into the Island of Ireland, and the Island of Great Britain.

Temporal extent
The map is representative for ca. 2018.

Data format
The data are organized by nations. Within each nation, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

• t at 10m x 10m
• kt at 100m x 100m
• Mt at 1km x 1km
• Gt at 10km x 10km

For each nation, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

Additionally, the grand total mass per nation is tabulated for each island in mass_grand_total_t_10m2.tif.csv. County code and the ID in this table can be related via zones_name_pop.csv.

Material layers
Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials).

Further information
For further information, please see the publication.
Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Publication

D. Wiedenhofer, F. Schug, H. Gauch, M. Lanau, M. Drewniok, A. Baumgart, D. Virág, H. Watt, A. Cabrera Serrenho, D. Densley Tingley, H. Haberl, D. Frantz (2024): Mapping material stocks of buildings and mobility infrastructure in the United Kingdom and the Republic of Ireland. Resources, Conservation and Recycling 206, 107630. https://doi.org/10.1016/j.resconrec.2024.107630

Funding
This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

Acknowledgments
We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.

This dataset contains observational frequency maps of internal waves (IW) within the UK Continental Shelf (UKCS) region. The maps were generated by automatic processing of the ENVISAT Advanced Synthetic Aperture Radar (ASAR) data archive covering the period from 2006 to 2012. The IW frequency maps were combined with bathymetry and mixed layer depth modelling data to estimate the interaction of IWs with the sea bed. The results are presented in monthly, seasonal, annual and climatology maps.

This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at August 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2021 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations) for England and Wales. Scotland and Northern Ireland has the 2011 Census Output AreasIt supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 184 MB).

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Uzbekistan data available from WorldPop here.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Japan data available from WorldPop here.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Iraq data available from WorldPop here.

Mid-year (30 June) estimates of the usual resident population for Lower layer Super Output Areas (LSOAs) in England and Wales by single year of age and sex.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

South Sudan data available from WorldPop here.

raster containing information on the spatial distribution of soil bulk density at OAL-UK. The raster was generated following a digital soil mapping approach implemented through the random forest algorithm. More detail on the map creation can be found here: https://doi.org/10.1016/j.ecoleng.2017.04.066

Aryandoust, A., van Vliet, O. & Patt, A. City-scale car traffic and parking density maps from Uber Movement travel time data. Scientific Data 6, 158 (2019). https://doi.org/10.1038/s41597-019-0159-6

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Mali data available from WorldPop here.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Singapore data available from WorldPop here.

This low-resolution image has been produced from BGS land and marine gravity data. The colour was generated using the BGS COLMAP software package. Colour levels are defined by histogram equalisation. Combining this image with the grey shaded relief image produces a similar image to the colour shaded relief image. The measured gravity values have been corrected in order to show the anomalies attributable to variations in crustal density. In broad terms the blues are attributable to large volumes of low density rocks, the reds to high density rocks. Significant lows occur, for instance, over areas of thick, low density sedimentary rocks(e.g. Cheshire Basin, Wessex Basin), or large granites (eg Cornwall). For marine data, free-air anomalies have been calculated from observed gravity values along marine survey lines. Line intersection errors between crossing lines and overlapping surveys have been used using network adjustment techniques. Free air anomalies have been calculated for sea-bottom stations. For land data, bouguer anomalies have been calculated from gravity observations at points of known height. In order to minimise the effect of topography, Bouguer corrections for the British Mainland have been applied using a density estimated for each station. Elsewhere a correction density of 2.67 Mg/m3 has been used. Corrections for the gravitational effect of terrain have been made where significant, and in a general extent to a radius of 48.6km. The data have been interpolated onto a 1km x 1km grid using a variable tension technique, and smoothed.

The main entity of this document is a structure with accession number 4uqj