A PDF map that shows the counties and unitary authorities in the United Kingdom as at 1 April 2023. (File Size - 583 KB)

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 file contains the digital vector boundaries for Counties, in England, as at December 2024.The boundaries available are: (BFC) Full resolution - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.

REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_December_2024_Boundaries_EN_BFC/FeatureServerREST URL of WFS Server –https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_December_2024_Boundaries_EN_BFC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Map Server –https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_December_2024_Boundaries_EN_BFC/MapServer

The Land Cover Map of Great Britain 1990 (1km percentage target class, GB), is a raster digital dataset, providing a classification of land cover types into 25 classes, at a 1km resolution. The dataset consists of a set of 1km bands, each containing one of 25 target classes (or 'sub' classes). Each band of the dataset contains the percentage of the specified habitat class per 1km, derived from a higher resolution (25m) dataset. The map was produced using supervised maximum likelihood classifications of Landsat 5 Thematic Mapper satellite data. The 25 mapped classes include sea and inland waters, bare, suburban and urban areas, arable farmland, pastures and meadows, rough grass, grass heaths and moors, bracken, dwarf shrub heaths and moorland, scrub, deciduous and evergreen woodland, and upland and lowland bogs. It can potentially be used to plan, manage or monitor agriculture, ecology, conservation, forestry, environmental assessment, water supplies, urban spread, transport, telecommunications, recreation and mineral extraction. The map was produced in the early 1990s by a forerunner of the Centre for Ecology & Hydrology, the Institute of Terrestrial Ecology, at Monks Wood. Note: The bands in the dataset run from 1-26, not 0-25 as stated in the documentation. Hence '1' is unclassifed (not '0'), '2' is sea/estuary and so on. Full details about this dataset can be found at https://doi.org/10.5285/0172cc8c-8b5c-46cf-b08a-785ab832e88c

This file contains the digital vector boundaries for Counties and Unitary Authorities, in the United Kingdom, as at May 2023.The boundaries available are: (BFC) Full resolution - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.

REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_May_2023_UK_BFC/FeatureServerREST URL of WFS Server –https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_May_2023_UK_BFC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Map Server –https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_May_2023_UK_BFC/MapServer

The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.

The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable.

Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes.

Datasets used: Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate Data

The BGS database of geological maps is an index into BGS holdings of modern and historical published geological maps, geological standards and field slips, and also contains a range of other map series, including geophysical maps, geochemical maps, hydrogeological maps, thematic maps and other small-scale miscellaneous non-series maps. Historical vertical and horizontal sections, as well as indices to colours, are also included. The database comprises map metadata, including the title, theme, survey and revision years, publication years, mapped geological theme, base material, map function, colouration, approval status and the spatial extent of each map sheet. An accompanying file store contains high-resolution JPEG2000 scans for delivery, as well as various digital master and delivery formats. For a small number of maps, no scan exists. In total, the database contains over 240,000 scans of over 130,000 maps and field slips. The majority of the maps in the database cover Great Britain, but other regions are also represented, including a historical series of 1-inch maps of Ireland, 6-inch maps of the Isle of Man, 1:25 000 scale maps of the Channel Islands, and various overseas maps. The database contains a record of all geological maps produced by the British Geological Survey and its predecessors since the commencement of systematic geological mapping in the 1830s. The BGS Maps Database is mostly an archive of previous BGS maps, and is not the same as the latest BGS digital mapping. The maps within the database may differ significantly from BGS digital vector mapping. Further information about BGS digital vector mapping is available on the BGS website, under 'BGS Datasets'. The database has evolved over time, originally being a series of discrete databases. These databases have now been aggregated into a single dataset. BGS published maps, as well as 1:10 560 and 1:10 000 large-scale geological maps of England and Wales, and Scotland, are available through the BGS Maps Portal. Field slips and some thematic maps are not included on the BGS Maps Portal. The information about a map is normally a transcription from the map itself. Sometimes key information such as the title may not be actually printed on the map. Where this is the case the information is supplied in square brackets, e.g. [Kirk Maiden]. Information in square brackets means the information is supplied by the cataloguer and is not transcribed from the item.

Surface features are produced as a result of internal deformation of active landslides, and are continuously created and destroyed by the movement. The detailed mapping of the evolution of bare ground patches and vegetation cover pattern over time provides useful insights on the mass movements and the most vulnerable areas. Monitoring the evolution of the latter, in turn, could help to describe the benefits of NBS past their implementation by observing a reduction of vulnerable areas and the increase of the extent of stable vegetation as a result of the interventions. The preliminary analysis of satellite data on OAL-UK was devoted to the analysis of a time series of very high resolution multispectral satellite data (<1 m) in the period prior to the implementation of NBS. The goal was to explore the potential of remote sensing to describe the pattern and extent of vegetation cover and plant cover regeneration, as well as to observe the self-organisation of landslide scars - i.e. re-distribution of bare ground patches over time.

The dataset includes Land Cover maps obtained by Worldview 2 satellite images acquired between 2011 and 2016 in different seasons, notably on 29 Jun 2011, 22 April 2014, 08 June 2014 and 22 Feb 2016.

After the pre-processing phase, Principal Component Analysis (PCA) was applied on the pansharpened multispectral bands to reduce the dimensionality of each dataset (pansharpened multispectral bands), while retaining as much as possible its information content. (Richardson, 2009).

A machine learning unsupervised classification (K-means) was applied to the first three PC found by PCA. K-means is an unsupervised classification algorithm that groups objects into k groups based on their characteristics. The mean spectral reflectance values of the samples assigned to each cluster was analyzed to identify typical spectral profiles of land features as well as eventual similarities between the classes and successively used to assign labels to the unsupervised classes. In cases of spectral similarity between two or three clusters, thy were merged in a unique class.

The results of k-means classification were analyzed to define typical spectral profiles of land cover features found in OAL-UK. First, the mean and standard deviation of the spectral bands of each cluster and image were calculated and compared with spectral libraries of land features. This led to identify 11 land cover classes with typical and recurrent spectral profiles within the OAL:

1. Bare soil

2. urban materials and sea foam (uniform spectra)

3. water saturated soil

4. water logged soil/vegetation

5. vegetation (grass)

6. dense vegetation (shrubs)

7. vegetation with exposed soil

8. soil with sparse vegetation

9. mixed wet soil/vegetation

10. Water

11. Turbid Water

This relates to: M.E. Jarvis et al. 2019, MNRAS, 485, 2710, "Prevalence of radio jets associated with galactic outflows and feedback from quasars". Available on the pre-print archive: arxiv.org/abs/1902.07727This contains:- The Low Resolution ("LR") image and High Resolution ("HR") image from the Very Large Array (VLA) (see Table 3 and Section 3.1)- The eMERLIN image (see Section 3.2).- The IFU data cube used (see Section 3.3)- One file containing the four [O III] maps as four separate fits extensions (SNR, v50, W80 and A; see Section 4.2). Note the units for the v50 and W80 maps is angstroms.The details of how the images, data cubes and maps were produced are in the paper. The data files also contain extensive meta-data in the header following the standard for astronomical images.

Coastline for Antarctica created from various mapping and remote sensing sources, consisting of the following coast types: ice coastline, rock coastline, grounding line, ice shelf and front, ice rumple, and rock against ice shelf. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. High resolution versions of ADD data are suitable for scales larger than 1:1,000,000. The largest suitable scale is changeable and dependent on the region.

Major changes in v7.5 include updates to ice shelf fronts in the following regions: Seal Nunataks and Scar Inlet region, the Ronne-Filchner Ice Shelf, between the Brunt Ice Shelf and Riiser-Larsen Peninsula, the Shackleton and Conger ice shelves, and Crosson, Thwaites and Pine Island. Small areas of grounding line and ice coastlines were also updated in some of these regions as needed.

Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.

Further information and useful links

Map projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.

The currency of this dataset is May 2022 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.

For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.

A related medium resolution dataset is also published via Living Atlas, as well medium and high resolution polygon datasets.

For background information on the ADD project, please see the British Antarctic Survey ADD project page.

Lineage

Dataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry checks, but does not contain strict topology. Quality varies across the dataset and certain areas where high resolution source data were available are suitable for large scale maps whereas other areas are only suitable for smaller scales. Each line has attributes detailing the source which can give the user further indications of its suitability for specific uses. Attributes also give information including 'surface' (e.g. grounding line, ice coastline, ice shelf front) and revision date. Compiled from sources ranging in time from 1990s-2022 - individual lines contain exact source dates.

The high-resolution airborne surveys shown on the map based index (GeoIndex) are classed as those flown with low terrain clearance (typically below 200m) and flight line spacing of less than 300m. The surveys were flown with various combinations of magnetic, radiometric and EM techniques, and include; Surveys flown for the DTI mineral reconnaissance programme, Commercial surveys flown for mineral exploration and subsequently donated to the BGS and Surveys flown for the BGS for research and other purposes.

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset consists of the 25m raster version of the Land Cover Map 1990 (LCM1990) for Great Britain. The 25m raster product consists of three bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information); Band 3 - percentage of the polygon covered by the majority class. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. The 25m raster is the most detailed of the LCM1990 raster products both thematically and spatially, and it is used to derive the 1km products. LCM1990 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. Full details about this dataset can be found at https://doi.org/10.5285/3d974cbe-743d-41da-a2e1-f28753f13d1e

[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

Under the Natural Capital and Ecosystem Assessment (NCEA) Pilot, Natural England and the Botanical Society of Britain and Ireland (BSBI) have been working in partnership to use BSBI's vast database of plant records to inform the evidence base for tree-planting activities. Poorly targeted tree planting risks damaging wildlife and carbon-rich habitats, therefore using these data we aim to ensure that areas of high conservation value are preserved in the landscape. The summarised botanical value map provides an easily interpretable output which categorises monads (1 x 1 km grid squares) as being of Low, Moderate or High botanical value according to the presence of Rare, Scarce and Threatened (RST) plant species and/or the proportion of Priority Habitat Positive Indicator (PHPI) species that were recorded within the 1 x 1 km grid square between 1970 and 2021. The PHPI species are a combination of BSBI axiophytes, positive indicators for common standards monitoring and ancient woodland indicators. The dataset includes an overall botanical value, as well as values based on only the presence of RST plant species, and a value for each broad habitat type based on the PHPI species records. By viewing the different attributes, you can gain insights into how valuable a monad is for different habitat types and for plant species of conservation concern, as well as an indication of how well a particular monad has been surveyed. The categories of 'No indicators, poor survey coverage' and 'No indicators, good survey coverage' indicate where no indicator species have been recorded and survey coverage either is above or below a threshold of 3 'recorder days'. A 'recorder day' is defined as being when 40 or more species have been recorded on a single visit and 3 recorder days is assumed sufficient to achieve good survey coverage within a 1 x 1 km grid square. This map is not intended to be used to carry out detailed assessments of individual site suitability for tree planting, for which the RST plant species heatmap at 100 x 100 m resolution and the PHPI heatmaps at 1 x 1 km resolution have been developed by BSBI and Natural England. However, the summarised botanical value map can provide useful insights at a strategic landscape scale, to highlight monads of high value for vascular plants and inform spatial planning and prioritisation, and other land management decision-making. These should be used alongside other environmental datasets and local knowledge to ensure decisions are supported by the appropriate evidence. Please get in contact if you have any queries about the data or appropriate uses at botanicalheatmaps@naturalengland.org.uk. Process Description: The main data sources were the botanical heatmaps which were developed as part of the NCEA pilot in collaboration with BSBI. BSBI provided summarised counts of Rare, Scarce and Threatened (RST) plant species and Priority Habitat Positive Indicators (PHPIs) present within each 1 x 1 km grid square (monads) between 1970 and 2021, which were then further processed by an automated workflow to subset to England and gap-fill where values were missing, taking into account the influence of survey coverage. To create the summarised botanical value map these heatmap data were then further categorised based on the number of RST plant species or PHPI species present indicating semi-natural habitat of high quality. The number of PHPIs present per monad within each broad habitat heatmap were compared to the total number of PHPIs present within their surrounding area We used a local benchmarking approach to categorise monads based on the proportion of the total PHPIs recorded in the monad. If a monad contained less than 10% of the regional species pool this was deemed as being Poor value, between 10-20% was defined as Moderate value and over 20% was High botanical value, from a vascular plant perspective. Where a monad had no indicator records and survey coverage was poor, it was classified as ‘no indicators, poor survey coverage’. Datasets used:BSBI botanical heatmap data - BSBIOS Grids - OSONS Country boundaries - ONSCommon Standards Monitoring guidance - JNCC 2004BSBI's Axiophyte list - Walker 2018Ancient Woodland Indicators - Glaves et al. 2009Plantatt - Hill et al. 2004Further information can be found in the technical report at:Botanical Heatmaps and the Botanical Value Map: Technical Report (NERR110)Full metadata can be viewed on data.gov.uk.

A new version of this dataset exists. To see the last version of the Antarctic Digital Database, have a look here: https://data.bas.ac.uk/collections/e74543c0-4c4e-4b41-aa33-5bb2f67df389/

Coastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with ''land'', ''ice shelf'', ''ice tongue'' or ''rumple'''' attribute. Covering all land and ice shelves south of 60S. Suitable for topographic mapping and analysis. High resolution versions of ADD data are suitable for scales larger than 1:1,000,000. The largest suitable scale is changeable and dependent on the region.

Major changes in v7.5 include updates to ice shelf fronts in the following regions: Seal Nunataks and Scar Inlet region, the Ronne-Filchner Ice Shelf, between the Brunt Ice Shelf and Riiser-Larsen Peninsula, the Shackleton and Conger ice shelves, and Crosson, Thwaites and Pine Island. Small areas of grounding line and ice coastlines were also updated in some of these regions as needed.

Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.

This dataset contains high resolution (HR) land cover (LC) and land cover change (LCC) maps of a subregion of Africa, produced by the ESA High Resolution Land Cover (HRLC) Climate Change Initiative (CCI) project. It consists of the following products:

1) HRLC30: High Resolution Land Cover Maps at 30m spatial resolution for years 1990, 1995, 2000, 2005, 2010, 2015, 2019. 2) HRLCC30: High Resolution Land Cover Change Maps at 30m spatial resolution of yearly changes. A map every 5 years (1990-1995, 1995-2000, 2000-2005, 2005-2010, 2010-2015,2015-2019) is provided which reports (high priority) changed pixels and their year within the 5-years temporal interval. 3) Associated uncertainty products.

They cover the geographic range (3.5°N – 16.3°N; 27.0°E – 43.3°E).

The data are provided as both GeoTIFF tiles following the Sentinel-2 MGRS tiling scheme and as a GeoTiff format mosaic. These maps are also referred to as historical maps.

Under the Natural Capital and Ecosystem Assessment (NCEA) Pilot, Natural England and the Botanical Society of Britain and Ireland (BSBI) have been working in partnership to use BSBI's vast database of plant records to inform the evidence base for tree-planting activities. Poorly targeted tree planting risks damaging wildlife and carbon-rich habitats, therefore using these data we aim to ensure that areas of high conservation value are preserved in the landscape. The summarised botanical value map provides an easily interpretable output which categorises monads (1 x 1 km grid squares) as being of Low, Moderate or High botanical value according to the presence of Rare, Scarce and Threatened (RST) plant species and/or the proportion of Priority Habitat Positive Indicator (PHPI) species that were recorded within the 1 x 1 km grid square between 1970 and 2022. The PHPI species are a combination of BSBI axiophytes, positive indicators for common standards monitoring and ancient woodland indicators. The dataset includes an overall botanical value, as well as values based on only the presence of RST plant species, and a value for each broad habitat type based on the PHPI species records. By viewing the different attributes, you can gain insights into how valuable a monad is for different habitat types and for plant species of conservation concern, as well as an indication of how well a particular monad has been surveyed. The categories of 'No indicators, poor survey coverage' and 'No indicators, good survey coverage' indicate where no indicator species have been recorded and survey coverage either is above or below a threshold of 3 'recorder days'. A 'recorder day' is defined as being when 40 or more species have been recorded on a single visit and 3 recorder days is assumed sufficient to achieve good survey coverage within a 1 x 1 km grid square. This map is not intended to be used to carry out detailed assessments of individual site suitability for tree planting, for which the RST plant species heatmap at 100 x 100 m resolution and the PHPI heatmaps at 1 x 1 km resolution have been developed by BSBI and Natural England. However, the summarised botanical value map can provide useful insights at a strategic landscape scale, to highlight monads of high value for vascular plants and inform spatial planning and prioritisation, and other land management decision-making. These should be used alongside other environmental datasets and local knowledge to ensure decisions are supported by the appropriate evidence. Please get in contact if you have any queries about the data or appropriate uses at botanicalheatmaps@naturalengland.org.uk.Datasets used:BSBI botanical heatmap data - BSBIOS Grids - OSONS Country boundaries - ONSCommon Standards Monitoring guidance - JNCC 2004BSBI's Axiophyte list - Walker 2018Ancient Woodland Indicators - Glaves et al. 2009Plantatt - Hill et al. 2004Further information can be found in the technical report at:Botanical Heatmaps and the Botanical Value Map: Technical Report (NERR110)Full metadata can be viewed on data.gov.uk.

This dataset consists of the 1km raster, dominant target class version of the Land Cover Map 1990 (LCM1990) for Northern Ireland. The 1km dominant coverage product is based on the 1km percentage product and reports the habitat class with the highest percentage cover for each 1km pixel. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UKCEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/d33593d7-5c4d-419e-924c-b341847fd6ae

This dataset consists of the 1km raster, dominant aggregate class version of the Land Cover Map 1990 (LCM1990) for Great Britain. The 1km dominant coverage product is based on the 1km percentage product and reports the aggregated habitat class with the highest percentage cover for each 1km pixel. The 10 aggregate classes are groupings of 21 target classes, which are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. The aggregate classes group some of the more specialised classes into more general categories. For example, the five coastal classes in the target class are grouped into a single aggregate coastal class. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UK CEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/84c07c67-88a4-439a-a339-b0577afd3886

This dataset consists of the 1km raster, dominant target class version of the Land Cover Map 1990 (LCM1990) for Great Britain. The 1km dominant coverage product is based on the 1km percentage product and reports the habitat class with the highest percentage cover for each 1km pixel. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UKCEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/f5e3bd00-efd0-4dc6-a454-aa597d84764a