AndreaBozzo/ceres-open-data-index huggingface dataset:
WWNP Floodplain Woodland Potential

WWNP Floodplain Woodland Planting Potential is our best estimate of locations where tree planting on the floodplain may be possible, and effective to attenuate flooding. The dataset is designed to support signposting of areas of floodplain not already wooded. The dataset is based upon fluvial Flood Zone 2 of the Flood Map for Planning. A set of open access constraints data was used to erase areas which contained existing woodland, watercourses, peat, roads, rail and urban locations. The information provided is largely based on modelled data and open constraints data, and is therefore indicative rather than specific. Locations identified may have more recent building or land use than available data indicates. It is important to note that land ownership and change to flood risk have not been considered, and it may be necessary to model the impacts of significant planting. The Environment Agency’s Flood Map for Planning (2016) - Flood Zone 2 (0.1% AEP) was used to delineate areas close to the watercourse in the floodplain which may be suitable for tree planting. The ‘Woodland Constraints’ data was then applied, masking existing woodland, watercourses, peat, roads, rail and urban areas.
WWNP Wider Catchment Woodland Potential

WWNP Wider Catchment Woodland Potential is our best estimate of locations where there are slowly permeable soils, where scrub and tree planting may be most effective to increase infiltration and hydrological losses. The dataset is designed to support signposting of areas not already wooded. The dataset is based upon the 1:50k BGS geology survey, and relies upon identifying drift and bedrock geologies that are characteristic of slowly permeable soils. A set of open access constraints data was used to erase areas which contained existing woodland, watercourses, peat, roads, rail and urban locations. The information provided is largely based on a 100m gridded version of the BGS 1:50k superficial and bedrock data, along with open constraints data, and is indicative rather than specific. Locations identified may have more recent building or land use than available data indicates. It is important to note that land ownership and change to flood risk have not been considered, and it may be necessary to model the impacts of significant planting. The ‘Superficial Deposits’ and ‘Bedrock Geology’ themes from the BGS Geology 50k map data were used to identify areas of slowly permeable soils where tree planting may increase infiltration and hydrological losses. The ‘Woodland Constraints’ data was then applied, masking existing woodland, watercourses, peat, roads, rail and urban areas.
WWNP Floodplain Reconnection Potential

WWNP Floodplain Reconnection Potential is our best estimate of locations where it may be possible to establish reconnection between a watercourse and its natural floodplain, especially during high flows. The dataset is designed to support signposting of areas where there is currently poor connectivity such that flood waters are constrained to the channel and flood waves may therefore propagate downstream rapidly. The dataset is based upon the Risk of Flooding from Rivers and Sea probability maps, and identifies areas of low and very low probability that are close to a watercourse, but which do not contain residential property or key services. The areas may contain non-residential property so it is important to consider this and recent buildings or defences when considering floodplain reconnection. Locations identified may have more recent building or land use than available data indicates. It is important to note that land ownership and change to flood risk have not been considered, and it may be necessary to model the impacts of significant reconnection. Areas of low or very low probability of fluvial flooding were identified from the Risk of Flooding from Rivers and Sea dataset. The Detailed River Network (2013) was used to derive the proximity of the watercourses to the floodplain, but not displayed due to data licensing restrictions. The National Receptor Dataset (2014) property points were used to screen out areas with residential property and key services. This dataset is not open data, so is also not displayed in the mapping work
WWNP Runoff Attenuation Features 1in30 AEP

Runoff Attenuation Features Potential is our best estimate of locations of high flow accumulation across the land surface or in smaller channels, where it may be possible to temporarily store water and attenuate flooding during high flows. The dataset is designed to support signposting of areas where to target enhanced storage. It is based upon the Risk of Flooding from Surface Water datasets and identifies areas of high flow accumulations for the 3.3% Annual Exceedance Probability surface water maps. The areas of ponding or accumulation are between 100 and 5000 metres squared, and have been tagged where they fall on an area of slope steeper than 6% as gully blocking opportunities. All the potential areas have been constrained so that they are not in urban areas or on roads, rails or canals. The data does not does not provide information on design, which may need to consider issues such as drain-down between flood events. It is important to note that land ownership and change to flood risk have not been considered. Locations identified may have more recent building or land use than available. A GIS tool developed by JBA, called JRAFF (JBA Runoff Attenuation Feature Finder) was used to analyse potential for Runoff Attenuation Features. This identifies areas of high flow accumulation from the Risk of Flooding from Surface Water Depth 3.3 percent annual chance map that could be targeted as opportunities for enhanced temporary storage. OS Terrain 50 (2016) was used to determine gully blocking potential, based on a threshold of > 6 degrees (10%). A constraint layer was applied based on CORINE Land Cover Urban layer (2012), OS Open Map Local – Roads, Rail and Building layers (2016) and OS Open Rivers – Canal layer (2016).
WWNP Runoff Attenuation Features 1in100 AEP

Runoff Attenuation Features Potential is our best estimate of locations of high flow accumulation across the land surface or in smaller channels, where it may be possible to temporarily store water and attenuate flooding during high flows. The dataset is designed to support signposting of areas where to target enhanced storage. It is based upon the Risk of Flooding from Surface Water datasets and identifies areas of high flow accumulations for the 1% Annual Exceedance Probability surface water maps. The areas of ponding or accumulation are between 100 and 5000 metres squared, and have been tagged where they fall on an area of slope steeper than 6% as gully blocking opportunities. All the potential areas have been constrained so that they are not in urban areas or on roads, rails or canals. The data does not does not provide information on design, which may need to consider issues such as drain-down between flood events. It is important to note that land ownership and change to flood risk have not been considered. Locations identified may have more recent building or land use than available. A GIS tool developed by JBA, called JRAFF (JBA Runoff Attenuation Feature Finder) was used to analyse potential for Runoff Attenuation Features. This identifies areas of high flow accumulation from the Risk of Flooding from Surface Water Depth 1 percent annual chance map that could be targeted as opportunities for enhanced temporary storage. OS Terrain 50 (2016) was used to determine gully blocking potential, based on a threshold of > 6 degrees (10%). A constraint layer was applied based on CORINE Land Cover Urban layer (2012), OS Open Map Local – Roads, Rail and Building layers (2016) and OS Open Rivers – Canal layer (2016).
WWNP Woodland Constraints

This dataset comprises a range of land cover types where the woodland potential layers have been masked, owing to existing woodland, watercourses, peat, roads, rail and urban areas. Other constraints data, such as protected habitats and high grade agricultural land, should also be considered. Locations identified may have more recent land use change than available at the time of publication. The Woodland Constraints data is based on an amalgamation of the following datasets: OS Open Map Local – Roads, Rail and Woodland layers (2016); Forestry Commission Woodland Inventory (2015); OS Open Water – Lines, Areas and Rivers (2016); CORINE Land Cover Urban and Peat layers (2012).
OS Open Greenspace

Please note that this dataset is no longer maintained by Ordnance Survey. To access the latest OS Open Greenspace data please go to [https://osdatahub.os.uk/]. OS Open Greenspace depicts the location and extent of spaces such as parks and sports facilities that are likely to be accessible to the public. Where appropriate, it also includes access points to show how people get into these sites. Its primary purpose is to enable members of the public to find and access green spaces near them for exercise and recreation. Find out more about the uses and case studies surrounding Greenspace on the dedicated [OS Open Greenspace] webpage, and technical information about the greenspaces it contains and how to use them in our detailed [specification]. Who's using OS Open Greenspace? Innovators - Britain’s most comprehensive Open dataset of greenspaces underpins a range of apps, products and innovations - providing the foundation to help create greener and healthier communities. Public sector (Public Health England) - Incorporated as a layer into [SHAPE], the dataset has been used alongside asset location data (GPs, pharmacies, schools) and indicator data (population and deprivation), to help inform and support the strategic planning of services and physical assets across the health economy. Emergency services - A vital tool in helping our emergency services, OS Open Greenspace includes site use and access points, making it quicker to get to emergency situations. Feedback Think somewhere is missing from the data? Spot an inaccuracy in the attribution? Make us aware using the Error Reporting Tool on the [OS DataHub]! If you have any further questions about the product, or would like to get in contact with a member of our support team, please reach out via our [website]. Currency and update frequency The currency of the product is April 2022 and has a six-monthly update cycle (April and October).
Natural Capital projects January 2025

A layer identifying DEFRA funded natural capital initiatives with some detail about those programmes/projects. Updated in February 2025 to show the delivery stage. This layer has been published for use in [Local Investment In Natural Capital Progamme (arcgis.com)] Due to data protection, the points on the map do not identify the exact location of land within each programme but gives you a flavour of other work going on in the area.
Monthly Precipitation Projections 2050-2079

What does the data show? This data shows monthly averages of precipitation (mm/day) for 2050-2079 from the UKCP18 regional climate projections. The data is for the high emissions scenario (RCP8.5). Limitations of the data We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data. What are the naming conventions and how do I explore the data? This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower'. E.g. 'pr July Median' is the median value for July. To understand how to explore the data, see this page: [https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578] Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January Median’ values. What do the ‘median’, ‘upper’, and ‘lower’ values mean? Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the monthly averages of precipitation for 2050-2079 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. * The ‘lower’ fields are the second lowest ranked ensemble member. * The ‘upper’ fields are the second highest ranked ensemble member. * The ‘median’ field is the central value of the ensemble. This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty. Data source pr_rcp85_land-rcm_uk_12km_12_mon-30y_200912-207911.nc (median) pr_rcp85_land-rcm_uk_12km_05_mon-30y_200912-207911.nc (lower) pr_rcp85_land-rcm_uk_12km_04_mon-30y_200912-207911.nc (upper) UKCP18 v20190731 (downloaded 04/11/2021) Useful links * Further information on the [UK Climate Projections] (UKCP). * Further information on [understanding climate data] within the Met Office Climate Data Portal
Monthly Temperature Projections 2050-2079

What does the data show? This data shows monthly averages of surface temperature (°C) for 2050-2079 from the UKCP18 regional climate projections. The data is for the high emissions scenario (RCP8.5). Limitations of the data We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data. What are the naming conventions and how do I explore the data? This data contains a field for the average over the period. They are named 'tas' (temperature at surface), the month, and 'upper' 'median' or 'lower'. E.g. 'tas July Median' is the median value for July. To understand how to explore the data, see this page: [https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578] Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tas January Median’ values. What do the ‘median’, ‘upper’, and ‘lower’ values mean? Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the monthly averages of temperature for 2050-2079 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. * The ‘lower’ fields are the second lowest ranked ensemble member. * The ‘upper’ fields are the second highest ranked ensemble member. * The ‘median’ field is the central value of the ensemble. This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty. Data source tas_rcp85_land-rcm_uk_12km_12_mon-30y_200912-207911.nc (median) tas_rcp85_land-rcm_uk_12km_05_mon-30y_200912-207911.nc (lower) tas_rcp85_land-rcm_uk_12km_04_mon-30y_200912-207911.nc (upper) UKCP18 v20190731 (downloaded 04/11/2021) Useful links * Further information on the [UK Climate Projections] (UKCP). * Further information on [understanding climate data] within the Met Office Climate Data Portal
National Forest Inventory England 2023

The National Forest Inventory (NFI) woodland map covers all forest and woodland area over 0.5 hectare with a minimum of 20% canopy cover, or the potential to achieve it, and a minimum width of 20 metres. This includes areas of new planting, clearfell, windblow and restock. The woodland map excludes all 'tarmac' roads and active railways, and forest roads, rivers and powerlines where the gap in the woodland is greater than 20 meters wide. All woodland (both urban and rural), regardless of ownership, is 0.5 hectare or greater in extent, with the exception of Assumed woodland or Low density areas that can be 0.1 hectare or greater in extent. Also, in the case of woodland areas that cross the countries borders, the minimum size restriction does not apply if the overall area complies with the minimum size. Woodland less than 0.5 hectare in extent, with the expectation of the areas above, will not be described within the dataset but will be included in a separate sample survey of small woodland and tree features. The woodland map is updated on an annual basis and the changes in the woodland boundaries use the Ordnance Survey MasterMap® (OSMM) as a reference where appropriated. The changes in the canopy cover have been identified on: * Sentinel 2 imagery taken during spring/summer 2023 or colour aerial orthophotographic imagery available at the time of the assessment; * New planting information for the financial year 2022/2023, from grant schemes and the sub-compartment database covering the estate of Forestry England, Forestry and Land Scotland and Natural Resources Wales; * Transition areas where the difference between the last assessment date (source) and the latest date (source) currently available was greater than 17 years. Woodland areas, greater than 0.5 hectares, are classified as an interpreted forest type (IFT) from aerial photography and satellite imagery. Non-woodland areas, open areas greater than 0.5 hectare completely surrounded by woodland are described according to open area types. IFT categories are Conifer, Broadleaved, Mixed mainly conifer, Mixed mainly broadleaved, Coppice, Coppice with standards, Shrub, Young trees, Felled, Ground prep, Cloud \ shadow, Uncertain, Low density, Assumed woodland, Failed, Windblow. IOA categories are Open water, Grassland, Agricultural land, Urban, Road, River, Powerline, Quarry, Bare area, Windfarm, Other vegetation. For further information regarding the interpreted forest types (IFT) and the interpreted open areas (IOA) please see NFI description of attributes available on [www.forestresearch.gov.uk]
Current Bathing Water Status (England)

English bathing waters designated under the EU Bathing Water Directive and monitored for water quality by the Environment Agency. Symbolised with 2023 water quality status. Attributes include responsible water company, URL to open the full bathing water profile on the Environment Agency's [Bathing Water Explorer] and whether the bathing water quality is impacted by heavy rain. Additionally, de-designated bathing waters have been added. Download generated using the EA's Linked Data API: [https://environment.data.gov.uk/doc/bathing-water.csv?&_pageSize=1000] Published to AGOL from ArcGIS Pro
ONS Population Estimate Summary

Office for National Statistics’ national and subnational total mid-year population estimates for England and Wales for a selection of administrative and census areas by sex for 2012 to 2020. The data is source is from [ONS Population Estimates]. Find out more about this dataset [here]. This data is issued at [(BGC) Generalised (20m)] boundary type for: * Country, * Region, * Upper Tier Local Authority (2021), * Lower Tier Local Authority (2021), * Middle Super Output Area (2011), and * Lower Super Output Area (2011). If you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at dataenquiries@esriuk.com. The Office for National Statistics (ONS) produces annual estimates of the resident population of England and Wales at 30 June every year. The most authoritative population estimates come from the census, which takes place every 10 years in the UK. Population estimates from a census are updated each year to produce mid-year population estimates (MYEs), which are broken down by local authority, sex and age. More detailed information on the methods used to generate the mid-year population estimates can be found [here]. For further information on the usefulness of the data and guidance on small area geographies please see [here]. The currency of this data is 2021. Methodology The total and 5-year breakdown population counts are reproduced directly from the source data. The age range estimates have been calculated from the published estimates by single year of age. The percentages are calculated using the gender specific (total, female or male) total population count as a denominator except in the case of the male and female total population where the total population is used to give female and male proportions. This dataset will be updated annually, in two releases. Creator: Office for National Statistics. Aggregated age groupings and percentages calculated by Esri UK. ______________________________________________________________________________________ The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system. [Read more] about the NDS.
EWCO - NfC Social

Spatial data supporting the England Woodland Creation Offer (EWCO) ‘Close to settlements’ Additional Contribution. This contribution is available where woodland creation will provide social and environmental benefits by being close to people. This Additional Contribution will be awarded on the following basis: 1. Spatial targeting: Proposed woodland meeting the design requirements touches the ‘EWCO - NfC Social’ layer, 2. Species mix and 3. Stocking density/ The land under this dataset meets at least one of the following criteria: Be within the 40% most deprived areas in England that are also within 4km of built-up areas with a population of 10,000 or more. OR Be within 1km of built-up areas with a population of 2,000 or more. Data input sources: Measure of ‘deprived’ = Index of Multiple Deprivation (IMD) 2019 joined to Lower Layer Super Output Areas (LSOAs) census geographies - 2011. Built up area = Office for National Statistics (ONS) Built-up Areas (BUAs) census geographies - December 2011. Population = ONS Key statistics - Usual resident population - KS101EW - Census 2011. Attributes: ‘Status’ – features assigned as ‘Meets social criteria’.