The UKSeaMap Predictive Habitats Map 2025 (version 1) is a broad-scale prediction that uses physical models of depth, light, sediment and energy to predict the physical seabed habitats for the whole UK seabed. This map covers the UK extended Continental Shelf as defined by the Continental Shelf (Designation of Areas) Order 2013, but excluding the intertidal zone, Dee Estuary and Morecambe Bay.

Two habitat classification systems are present in the final output:

EUNIS habitat classification system version 2007-11 The Marine Habitat Classification for Britain and Ireland (https://mhc.jncc.gov.uk/) version 22.04 The attribute table includes a column for each of level 2, level 3 and level 4 of each of these two classification schemes. In some cases, there were 2-3 options of habitat type, which were both included and separated by the word “OR“. There is also a column containing the most detailed unique habitat type for each of the two classification systems.

The habitats were determined by combining 4 categorical input layers called 'habitat descriptors', which are the basis for describing physical habitats in the Marine Habitat Classification for Britain and Ireland. These are also present in the geodatabase.

Habitat descriptor data layers:

Seabed substrate type - created using the British Geological Survey's national broad-scale predictive sediment map - Marchant et al. (2025) and the JNCC-BGS-Cefas national broad-scale predictive rock map (JNCC, 2019) Biological zone (also known as biozone) - created using the depth to seabed, wave disturbance at the seabed and amount of light reaching the seabed. Kinetic energy at the seabed - created using energy from tidal currents and energy from waves Salinity regime - created using the Annex I Habitats Regulations datasets for coastal lagoons and estuaries features A methods report will be published in due course.

The UKSeaMap Predictive Map forms part of the UK Atlas of Seabed Habitats (UKASH), a suite of mapping products, offering the most complete characterisation of seabed habitats in the UK in the Marine Habitat Classification for Britain and Ireland and the European standard classification system, EUNIS. UKASH is composed of:

UKASH Library of Localised Maps: A standardised collection of individual, ground-truthed habitat maps from various sources. UKASH Mosaic of Localised Maps: A unified, non-overlapping map product that prioritises the most reliable maps from the UKASH Library of Localised Maps. UKSeaMap Predictive Map: A seamless, full-coverage predictive map of physical seabed habitats in the UK. UKASH Combined Map: The UKASH Mosaic of Localised Maps, with gaps filled by the UKSeaMap Predictive Map.

Further info: https://jncc.gov.uk/our-work/uk-atlas-of-seabed-habitats-ukash/#ukseamap

Land Cover Map 2021 (LCM2021) is a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2021. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2021. Land cover maps describe the physical material on the surface of the country. For example grassland, woodland, rivers & lakes or man-made structures such as roads and buildingsThis is a 10 m Classified Pixel dataset, classified to create a single mosaic of national cover. Provenance and quality:UKCEH’s automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2021 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy.View full metadata information and download the data at catalogue.ceh.ac.uk

A collection of 1:250 000 scale geophysical maps in the Universal Transverse Mercator (UTM) projection, covering the United Kingdom and continental shelf areas between 1975 – 1990. Mapping is divided into squares which cover 1 degree by 1 degree of latitude / longitude. A geophysical map is a graphical representation of data collected through various geophysical methods to investigate the subsurface characteristics of the Earth. Geophysics is the study of the physical properties and processes of the Earth using measurements of physical quantities such as gravity, magnetic fields, seismic waves, electrical resistivity, and others. The collection includes aeromagnetic anomaly maps (1975 – 1990), Bouguer gravity anomaly maps (1975 – 1989) and a small number of free air anomaly maps (1981 – 1989). These maps are hard-copy paper records stored in the National Geoscience Data Centre (NGDC) and are delivered as digital scans through the BGS website.

It is still unknown which factors of physical activity behaviour (PAB) may be effective and how they may influence PAB in UK children. The objective of the current study was to generate a conceptual analysis of the factors of PAB in UK children (5-12 years) using the input of researchers in the field of physical activity (PA experts; PAE) and researchers in other fields (non-PA experts; non-PAE). The concept mapping approach was used to identify potential (new) factors of PAB in children, assess their importance based on rating of potential modifiability and effect, and generate a concept map depicting the associations between them. In the first (brainstorming) stage (n=32 experts) yielded 93 factors, including 14 (new) not identified in previous reviews. In the second (rating and sorting) stage (n=26 experts), 32 factors were rated as important and four-cluster concept map was generated including themes related to Society/community, Home/social setting, Personal/social setting, and Psychological/emotional factors. Two additional concept maps were generated for PAE and non-PAE. From expert opinion, we identified new factors of PAB that warrant further research and we highlight the need to consider the interaction between intrapersonal and external factors when designing interventions to promote PA in UK children.The data has been downloaded from Ariadne (minds21.org) and includes the raw data and the analysed data (clustering and rating data). Participant information has been removed from the data files and replaced with participant numbers.

UKSeaMap 2018V2 is a broad-scale physical habitat map for UK waters. It is a by-product of the 2013-2016 activities of the EMODnet Seabed Habitats 2013–2016 consortium. This dataset contains two products: a roughly 100 m* resolution broad-scale predictive seabed habitat map in geodatabase format, and a set of confidence maps in GeoTIFF format. The data has been clipped to cover the current extent of the UK continental shelf.

*3 arc second = 93 m latitudinally by between 44 m (north) and 53 m (south) longitudinally

Classification system:

• EUNIS habitat classification system, with additional deep sea zones
• MSFD Benthic Broad Habitat Types
• The Marine Habitat Classification for Britain and Ireland (https://mhc.jncc.gov.uk/)

Input data layers:

• Seabed substrate type
• Depth to the seabed
• Amount of light reaching the seabed
• Wave disturbance at the seabed
• Kinetic energy at the seabed caused by tidal currents and waves

The dataset and the validation are fully described in a Nature Scientific Data Descriptor https://www.nature.com/articles/s41597-019-0265-5

If you want to use this dataset in an interactive environment, then use this link https://mybinder.org/v2/gh/GeographerAtLarge/TravelTime/HEAD

The following text is a summary of the information in the above Data Descriptor.

The dataset is a suite of global travel-time accessibility indicators for the year 2015, at approximately one-kilometre spatial resolution for the entire globe. The indicators show an estimated (and validated), land-based travel time to the nearest city and nearest port for a range of city and port sizes.

The datasets are in GeoTIFF format and are suitable for use in Geographic Information Systems and statistical packages for mapping access to cities and ports and for spatial and statistical analysis of the inequalities in access by different segments of the population.

These maps represent a unique global representation of physical access to essential services offered by cities and ports.

The datasets travel_time_to_cities_x.tif (where x has values from 1 to 12) The value of each pixel is the estimated travel time in minutes to the nearest urban area in 2015. There are 12 data layers based on different sets of urban areas, defined by their population in year 2015 (see PDF report).

travel_time_to_ports_x (x ranges from 1 to 5)

The value of each pixel is the estimated travel time to the nearest port in 2015. There are 5 data layers based on different port sizes.

Format Raster Dataset, GeoTIFF, LZW compressed Unit Minutes

Data type Byte (16 bit Unsigned Integer)

No data value 65535

Flags None

Spatial resolution 30 arc seconds

Spatial extent

Upper left -180, 85

Lower left -180, -60 Upper right 180, 85 Lower right 180, -60 Spatial Reference System (SRS) EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)

Temporal resolution 2015

Temporal extent Updates may follow for future years, but these are dependent on the availability of updated inputs on travel times and city locations and populations.

Methodology Travel time to the nearest city or port was estimated using an accumulated cost function (accCost) in the gdistance R package (van Etten, 2018). This function requires two input datasets: (i) a set of locations to estimate travel time to and (ii) a transition matrix that represents the cost or time to travel across a surface.

The set of locations were based on populated urban areas in the 2016 version of the Joint Research Centre’s Global Human Settlement Layers (GHSL) datasets (Pesaresi and Freire, 2016) that represent low density (LDC) urban clusters and high density (HDC) urban areas (https://ghsl.jrc.ec.europa.eu/datasets.php). These urban areas were represented by points, spaced at 1km distance around the perimeter of each urban area.

Marine ports were extracted from the 26th edition of the World Port Index (NGA, 2017) which contains the location and physical characteristics of approximately 3,700 major ports and terminals. Ports are represented as single points

The transition matrix was based on the friction surface (https://map.ox.ac.uk/research-project/accessibility_to_cities) from the 2015 global accessibility map (Weiss et al, 2018).

Code The R code used to generate the 12 travel time maps is included in the zip file that can be downloaded with these data layers. The processing zones are also available.

Validation The underlying friction surface was validated by comparing travel times between 47,893 pairs of locations against journey times from a Google API. Our estimated journey times were generally shorter than those from the Google API. Across the tiles, the median journey time from our estimates was 88 minutes within an interquartile range of 48 to 143 minutes while the median journey time estimated by the Google API was 106 minutes within an interquartile range of 61 to 167 minutes. Across all tiles, the differences were skewed to the left and our travel time estimates were shorter than those reported by the Google API in 72% of the tiles. The median difference was −13.7 minutes within an interquartile range of −35.5 to 2.0 minutes while the absolute difference was 30 minutes or less for 60% of the tiles and 60 minutes or less for 80% of the tiles. The median percentage difference was −16.9% within an interquartile range of −30.6% to 2.7% while the absolute percentage difference was 20% or less in 43% of the tiles and 40% or less in 80% of the tiles.

This process and results are included in the validation zip file.

Usage Notes The accessibility layers can be visualised and analysed in many Geographic Information Systems or remote sensing software such as QGIS, GRASS, ENVI, ERDAS or ArcMap, and also by statistical and modelling packages such as R or MATLAB. They can also be used in cloud-based tools for geospatial analysis such as Google Earth Engine.

The nine layers represent travel times to human settlements of different population ranges. Two or more layers can be combined into one layer by recording the minimum pixel value across the layers. For example, a map of travel time to the nearest settlement of 5,000 to 50,000 people could be generated by taking the minimum of the three layers that represent the travel time to settlements with populations between 5,000 and 10,000, 10,000 and 20,000 and, 20,000 and 50,000 people.

The accessibility layers also permit user-defined hierarchies that go beyond computing the minimum pixel value across layers. A user-defined complete hierarchy can be generated when the union of all categories adds up to the global population, and the intersection of any two categories is empty. Everything else is up to the user in terms of logical consistency with the problem at hand.

The accessibility layers are relative measures of the ease of access from a given location to the nearest target. While the validation demonstrates that they do correspond to typical journey times, they cannot be taken to represent actual travel times. Errors in the friction surface will be accumulated as part of the accumulative cost function and it is likely that locations that are further away from targets will have greater a divergence from a plausible travel time than those that are closer to the targets. Care should be taken when referring to travel time to the larger cities when the locations of interest are extremely remote, although they will still be plausible representations of relative accessibility. Furthermore, a key assumption of the model is that all journeys will use the fastest mode of transport and take the shortest path.

SafeGraph Places provides baseline information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation. Easily ingest this data to power your map products today.

The objective of the priority habitat map in England is to:• help organisations protect the most natural remaining examples of rivers from further impacts on natural processes, and • highlight any aspects of habitat integrity (hydrological, chemical, physical, biological) that could most usefully be improved. The priority river habitat map that has been produced is an English interpretation of the UK definition of priority river habitat, focusing on naturalness as the principal criterion in recognition of the vital importance of natural processes in delivering sustainable riverine habitats and supporting characteristic biodiversity.Full metadata can be viewed on data.gov.uk.

Various data recorded by Historic England relating to aerial investigation and mapping projects. N.B. This is a dynamic dataset that is constantly evolving, not only with the addition of newly completed projects, but also with the reassessment of some earlier projects. See https://historicengland.org.uk/research/methods/airborne-remote-sensing/aerial-investigation/ for further details of Historic England's work with aerial sources.It's currently not possible to provide download access to the earlier hand drawn projects, which are only available as raster files, but these can be viewed via the Aerial Archaeology Mapping Explorer. We aim to create vector monument polygons for these features as the next phase of the project.More information and help with these the layers Detailed MappingThis layer shows the detailed mapping of archaeological features derived from aerial imagery; this includes photographic imagery from many decades taken specifically for archaeological purposes, as well as other photography taken for other reasons and airborne lidar. The data are symbolised initially based on their physical form i.e. cut/negative (e.g. pit, ditch etc) or built/positive (e.g. mound, bank etc) .

    Field name
    Field alias
    Description
    Mandatory Y/N


    LAYER
    LAYER
    The layer used for mapping
    Y


    PROJECT
    PROJECT
    Project name
    Y

    PERIOD
    PERIOD
    The presumed date/period assigned to the feature (terminology from FISH thesaurus)
    Y


    MONUMENT_TYPE
    MONUMENT_TYPE
    The presumed type/function assigned to the feature (terminology from FISH thesaurus)
    Y


    EVIDENCE_1
    EVIDENCE_1
    The primary evidence for the feature e.g. cropmark, earthwork etc (terminology from FISH thesaurus)
    Y


  SOURCE_1
    SOURCE_1
    The primary source for the feature e.g. aerial photo reference, documentary source etc
    Y


  EVIDENCE_2
    EVIDENCE_2
    Where available the latest evidence for the feature e.g. cropmark, earthwork etc (terminology from FISH thesaurus) N.B. This was the latest evidence seen and does not necessarily represent the current status of the feature.
    N


  SOURCE_2
    SOURCE_2
    Where available the latest source for the feature N.B. This was the latest evidence seen and does not necessarily represent the current status of the feature.
    N


    HE_UID
    HE_UID
    Composite of Unique identifier(s) used by Historic England
    Y

    HER_NO
    HER_NO
    Composite of Unique identifier(s) used by Historic Environment Records
    N

    DHEUID_1
    DHEUID_1
    Primary Unique identifier used by Historic England
    Y

    DHEUID_2
    DHEUID_2
    Secondary Unique identifier used by Historic England. Used where a feature may relate to more than one Historic England record
    N

    DHEUID_3 ~ 5
    DHEUID_3 ~ 5
    Additional Unique identifier used by Historic England. Used where a feature may relate to more than one Historic England record
    N


    HE_URL1
    HE_URL1
    URL link to the relevant Historic England record in Heritage Gateway
    Y

    HE_URL2
    HE_URL2
    URL link to the relevant Historic England record in Heritage Gateway
    N

    HE_URL3 ~ 5
    HE_URL3 ~ 5
    URL link to the relevant Historic England record in Heritage Gateway
    N


    DHERNO_1
    DHERNO_1
    Primary unique identifier used by the relevant Historic Environment Record (HER)
    Y


    DHERNO_2
    DHERNO_2
    Secondary unique identifier used by the relevant Historic Environment Record. Used where a feature may relate to more than one HER record
    N


    DHERNO_3 ~ 5
    DHERNO_3 ~ 5
    Tertiary unique identifier used by the relevant Historic Environment Record. Used where a feature may relate to more than one HER record
    N

    DHERPREF_1
    DHERPREF_1
    Primary alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID
    Y

    DHERPREF_2
    DHERPREF_2
    Secondary alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID Used where a feature may relate to more than one HER record
    N

    DHERPREF_3 ~ 5
    DHERPREF_3 ~ 5
    Additional alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID Used where a feature may relate to more than one HER record
    N


    HER_LINK_1
    HER_LINK_1
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    Y


    HER_LINK_2
    HER_LINK_2
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    N


    HER_LINK_3 ~ 5
    HER_LINK_3 ~ 5
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    N

The data are symbolised initially based on their physical form i.e. cut/negative (e.g. pit, ditch etc) or built/positive (e.g. mound, bank etc)

    Layer name
    Colour (Hex)
    Description

Bank #A50026 Used to outline banks, platforms, mounds and spoil heaps.

Ditch #313695 Used to outline cut features such as ditches, ponds, pits or hollow ways.

    Extent of Feature
    #FDAE61 (Dashes)
    Used to depict the extent of large area features such as airfields, military camps, or major extraction.


    Ridge and Furrow Alignment
    #74ADD1
    Line or arrow(s) (hand drawn not a symbol) depicting the direction of the rigs in a block of ridge and furrow.


    Ridge and Furrow Area
    #74ADD1 (Dots)
    Used to outline a block of ridge and furrow .


    Slope
    #4575B4
     The top of the “T” indicates the top of slope and the body indicates the length and direction of the slope. Used to depict scarps, edges of platforms and other large earthworks.

    Structure
    #F46D43
     Used to outline structures including stone, concrete, metal and timber constructions e.g., buildings, Nissen huts, tents, radio masts, camouflaged airfields, wrecks, fish traps, etc.

You can find instructions on how to create a QGIS style file (.qml) to recreate our mapping symbology in QGIS via our Open Data Downloads page under Aerial Investigation Mapping data.Monument ExtentsThis layer shows the general extent of the monuments, created from multiple sources, primarily aerial imagery, but referring to other sources such as earthwork surveys, documentary evidence and any information available from the relevant Historic Environment Record etc. This differs from the 'Detailed Mapping' layer, which shows the individual features as they appear on the ground.

    Field name
    Field alias
    Description
    Mandatory Y/N


    LAYER
    LAYER
    The layer used for mapping
    Y

    HE_UID
    HE_UID
    Composite of Unique identifier(s) used by Historic England
    Y

    HER_NO
    HER_NO
    Composite of Unique identifier(s) used by Historic Environement Records
    N


    HE_UID1
    HE_UID1
    Primary Unique identifier used by Historic England
    Y

    HE_UID2
    HE_UID2
    Secondary Unique identifier used by Historic England. Used where a feature may relate to more than one Historic England record
    N

    HE_UID3 ~ 5
    HE-UID3 ~ 5
    Additional Unique identifier used by Historic England. Used where a feature may relate to more than one Historic England record
    N


    HE_URL1
    HE_URL1
    URL link to the relevant Historic England record in Heritage Gateway
    Y

    HE_URL2
    HE_URL2
    URL link to the relevant Historic England record in Heritage Gateway
    N

    HE_URL3 ~ 5
    HE_URL3 ~ 5
    URL link to the relevant Historic England record in Heritage Gateway
    N


    HERNO_1
    HERNO_1
    Primary unique identifier used by the relevant Historic Environment Record (HER)
    Y


    HERNO_2
    HERNO_2
    Secondary unique identifier used by the relevant Historic Environment Record. Used where a feature may relate to more than one HER record
    N


    HERNO_3 ~ 25
    HERNO_3 ~ 25
    Tertiary unique identifier used by the relevant Historic Environment Record. Used where a feature may relate to more than one HER record
    N

    HERPREF_1
    HERPREF_1
    Primary alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID
    Y

    HERPREF_2
    HERPREF_2
    Secondary alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID Used where a feature may relate to more than one HER record
    N

    HERPREF_3 ~ 25
    HERPREF_3 ~ 25
    Additional alternative unique identifier used by the relevant Historic Environment Record. Some HERs use the same number for both the HER No. and the reference to link to the record; others use different numbers and give them different names e.g MonUID Used where a feature may relate to more than one HER record
    N


    HER_LINK_1
    HER_LINK_1
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    Y


    HER_LINK_2
    HER_LINK_2
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    N


    HER_LINK_3 ~ 25
    HER_LINK_3 ~ 25
    URL link to the relevant Historic Environment Record (HER) record in Heritage Gateway
    N


    PROJECT
    project
    Project name
    Y

Project AreaThis layer shows the extent of the

Three files consisting of a txt file dataset of gamma radiation count observations, with SLAM estimated position, and a 2D SLAM map of the Lancaster University Neutron Laboratory (LUNL).The LUNL_radiation_data.txt consists of comma separated values, with a header row indicating the data types. Timestamp is with respect to Unix Epoch time (as is standard in ROS). Spatial coordinates of the robot x, y, z are in metres. As the robot is a ground level 2D robot, the SLAM estimate restricts the Z height to be roughly constant. Only x and y data are necessary. The counts data are in counts per second, indicating the number of events collected over a ~1 second time window by a CeBr3 scintillator detector and mixed field analyser.The map file (.pgm) is a trinary (three value) map generated by SLAM via ROS (Robot Operating System). The three values related to occupied (obstacles and physical features, such as walls), unoccupied (free-space), and unknown.The map metadata file (.yaml) provides values to convert pixel position of the map file into coordinates (in metres).Data was originally collected 05/12/2019 (in ROS bag format), which was interrogated to provide the data in the .txt file.This dataset is then post-processed to provide interpolated maps of gamma radiation, based on the point observations and maps in these files.

In some cases, a full-coverage map displaying the best available data everywhere at the expense of consistency is required. The production of such a product showing EUNIS level 3 habitats requires integrating EUNIS level 3 seabed habitat data from fine and broad-scale habitat maps. The product aims to create a complete map that presents the best available information on the distribution of EUNIS level 3 habitats at any locations in UK waters. This data product is required for, among other things, assessments of progress towards networks of marine protected areas (MPAs) and marine spatial planning in the UK. The aim was to produce a single map layer displaying the best quality EUNIS level 3 data for any given location. Furthermore, the process for producing the layer needed to be: • Repeatable; • Transparent; • Easy to explain and understand; • Objective; • Fully documented; • Appropriate for EUNIS level 3 habitats; and, • Appropriate for the UK intertidal and subtidal areas Any location would show only a single value describing the habitat at EUNIS level 3, i.e. no overlapping polygons leading to multiple possible values at a location. The data at any location should be the best available to describe the EUNIS level 3 habitat type (i.e. the most likely to be correct). EUNIS level 3 habitats (Appendix 1) describe physical habitats classified using biologically meaningful parameters, substrate type, and additionally for rock: energy and biological zone. Therefore, a method was created to choose data based on their ability to describe these physical variables.

Priority habitats form part of the UK’s commitment to the International Convention on Biodiversity. Each country who signed up to to the Convention is required to define a range of habitats (and individual species) where action is a priority to protect and restore biodiversity, and then to take the necessary action. The UK’s list of priority habitats includes both river and lake habitats. Existing nationally generated maps of river/stream and lake restoration priorities are now being refined with stakeholders to become a mechanism for highlighting local priorities for different sorts of restoration of natural habitat function – hydrological, physical, chemical and biological. Any site that falls under the UK river and lake priority habitat definitions (which essentially means any river, stream or lake), and therefore warrants specific consideration, can be highlighted as a priority for restoration action, if the action restores natural function. Restoration of natural habitat function of rivers and streams can involve many different practical measures – 21 measures are explicitly itemised within the river and stream restoration priorities layer. These arePhysical RestorationEstablish riparian zone of natural vegetationEstablish at least patchy cover of native riparian treesAllow natural delivery and retention of woody materialRestore natural mire-stream transition zoneRestore natural lateral movement of the channelRemove in-channel structuresRestore natural channel bed levelsRemove flood embankmentsRe-establish alluvial woodlandRestore natural floodplain wetland mosaicHydrological RestorationRestore natural springflows to headwater streamsRestore natural flow regimeRemove land drainageChemical RestorationTarget critical pollution source areas of the catchmentEstablish naturally functioning habitat mosaics on critical areasEstablish effective soil/nutrient conservation regimes on critical areasBiological RestorationStrategic area-based control of non-native speciesReduce intensity of/halt fish stockingHalt fishery-driven removal of non-target native fish speciesReduce/halt in-channel and marginal weed cuttingEliminate heavy grazing of riparian vegetationThis dataset is in the early stages of development and will grow as more partners and stakeholders add their local knowledge. See the Priority Habitat data portal for more information on priority river (including streams) and lake habitats in England, how you can get involved in their protection and restoration, and in particular how you can provide information on the sites you visit to help prioritise conservation action. Other parts of the UK have their own approaches to conserving priority habitats as part of their separate biodiversity strategies.You can also view this data via the Data Display app on the Priority Habitat Data Portal which allows you to easily visualise the different measures being recommended at each site.

"One of the two datasets that make up the Priority River Habitat Map. Consists of rivers and streams that exhibit a high degree of naturalness. The naturalness classification used to map priority river habitat is based on recent work to review the river SSSI series. It evaluates four main components of habitat integrity: hydrological, physical, physico-chemical (water quality) and biological. An additional classification of the naturalness of headwaters (defined as streams with a catchment area of <10km2 to coincide with WFD typology boundaries) uses land cover data as a surrogate for direct information on river habitat condition (information which is generally lacking on headwaters). Streams and rivers operating under natural processes, free from anthropogenic impact and with a characteristic and dynamic mosaic of small-scale habitats that supports characteristic species assemblages (including priority species), are the best and most sustainable expression of river ecosystems. Key elements are: a natural flow regime; natural nutrient and sediment delivery regimes; minimal physical modifications to the channel, banks and riparian zone; natural longitudinal and lateral hydrological and biological connectivity; an absence of non-native species; low intensity fishery activities. These conditions provide the best defence against climate change, maximising the ability of riverine ecosystems to adapt to changing conditions. They also provide the most valuable and effective transitional links with other priority habitats, including lakes, mires and coastal habitats. In English rivers and streams, high levels of naturalness are rare. "

This spreadsheet contains the UK wide data submitted to the EU Commmission as part of the Standard Data Form information completed for all Special Areas for Conservation (under the Habitats Directive). It is an archived data series form August 2009 to July 2015). Note that Gibraltar information is not included in this spreadsheet. Please note that this information was superceded in December 2015 by a spreadsheet that contains information for both SACs and also SPAs - in other words for the whole Natura 2000 network. This dataset is entitled "Natura 2000 all site details"

The information provided here, follows the officially agreed site information format for Natura 2000 sites, as set out in the Official Journal of the European Union recording the Commission Implementing Decision of 11 July 2011 (2011/484/EU). The content matches exactly the data submitted to the European Commission. Further technical documentation may be found here http://bd.eionet.europa.eu/activities/Natura_2000/reference_portal More general information on Special Areas of Conservation (SACs) in the United Kingdom is available from the SAC home page on the JNCC website. http://jncc.defra.gov.uk/default.aspx?page=23. This webpage also provides links to Standard Data Forms for all SACs in the UK.

this sheet is organised in a series of tabs - corresponding to different sections of the standard data form. All sheets are filterable by Country codes - (E, S, W, NI and OF for offshore). Cross border sites take the first letter of each country code eg EW for England Wales, SO for Scotland/Offshore. The tabs are: *Site details - one row per site, containing basic site details. *SAC interest features - habitats and species listed on the standard data form. *Maps - a facility to produce simple dot maps of sites *SAC Habitat classes *SAC Physical site characteristics (pre 2013 versions of this spreadshet only - from 2013 these details are integrated into a column on the site details table). *SAC component SSSIs (up until 2013 - dropped from subsequent versions because of a lack of updated information).

This dataset includes geomorphological features that were mapped within the Lagunas de las Huaringas, northern Peru using a combination of digital elevation models (DEMs) and remotely sensed optical imagery using well establish geomorphological mapping technique's. Also within is the subsequent glacier reconstructions that were informed by the geomorphological mapping, along with their reconstructed equilibrium line altitudes (ELAs) and glacial surface contours. For added context to the surrounding mapped features and reconstructed glaciers, basemap data is also included with 200 m elevational contours, height points and streams/rivers. A break down of what is included can be found below:Geomorphological features:

Alluvial fan

Alluvial plain

Bedrock step

Boulders

Cirque

Glacial lineations

Hill slope failures

Hummocky terrain

Moraines

Moraine deposits

Palaeo hill slope failures

Pronounced moraine crests

Rivers/streams

Smoothed bedrock

Steep bedrock slopes

Waterbodies

Glacier reconstructions:

Reconstructed glacier outlines with metrics

Reconstructed glacier ELAs

Reconstructed glacier profile contours

Basemap data:

Streams/rivers

200 m contours

Study regions

Height points

1965 Coastal Land Use Data. Created from physical survey carried out by University of Reading. Project details: https://www.nationaltrust.org.uk/documents/mapping-our-shores-fifty-years-of-land-use-change-at-the-coast.pdf

SSKIB (Scottish Soils Knowledge and Information Base) is a summary dataset comprising mean, median, maximum, minimum and standard deviations of a range of soil chemical and physical attributes for a typical (modal) soil profile for all soil series delineated on the 1:250,000 Scottish National Soil Map.

The dataset was developed over a number of years (from around 2004) for internal use and was released to the public to accompany the 1:250 000 scale National Soil Map of Scotland on 1st April 2011. It is based on soil analytical data from soil profiles collected since 1934, with the bulk of the data collected from the late 1960s to late 1980s.

There is a related table with soil hydrological and physical properties (bulk density, moisture retention and hydraulic conductivity derived by pedotransfer function) which is not yet publically available, but which is potentially available to researchers. Please contact the data distributor for further details.

Development of SSKIB began as a Scottish Government (RESAS) funded research programme around 2004 primarily for internal use with the then Macaulay Land Use Research Institute for broad scale modelling of changes in soil chemistry. Its use was extended to assess potential changes in soil carbon contents (ECOSSE model) and finally developed to deliver soils information via the web (http://sifss.hutton.ac.uk/) over PC, Android and IOS operating systems. It was released for general use in 2011 to provide soil chemical data to accompany the 1:250 000 scale soil map and underwent a few minor revisions until this release in 2018. Funding to maintain the dataset comes from the Rural & Environment Science & Analytical Services Division of the Scottish Government Underpinning Capacity fund.

The dataset should be cited as 'Soil Survey of Scotland Staff. 2018. Scottish Soils Knowledge and Information Base (SSKIB). Version 1.1. 10.5281/zenodo.5566700'

Spearman’s rank correlation coefficients between each PPG feature and annotated PPG features from the UK Biobank.