Dataset Name: OSNI Administrative BoundariesData Owner: Ordnance Survey NIContact: OSNI Mapping Helpdesk - mapping.helpdesk@finance-ni.gov.ukSource: Ordnance Survey NISource URL: Admin boundaries are also available on opendata ni https://www.nidirect.gov.uk/articles/osni-open-data-product-listUploaded: 27/09/22Update Frequency: InfrequentScale Threshold: N/AProjection : Irish GridFormat: Esri Feature Layer (Hosted on AGOL) Vector PolygonsNotes: This dataset contains 7 admin boundary layers covering Wards, PCs, Townlands, LGDs, DEAs and counties.

The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.The historical shoreline analysis was based on all available Ordnance Survey maps and aerial imagery information. Analysis looked at position and geometry over annual to decadal time periods, providing a dynamic picture of how the coastline has changed since the start of the early 1800s.Once all datasets were collated, data was interrogated using the ArcGIS package – Digital Shoreline Analysis System (DSAS). DSAS is a software package which enables a user to calculate rate-of-change statistics from multiple historical shoreline positions. Rate-of-change was collected at 25m intervals and displayed both statistically and spatially allowing for areas of retreat/accretion to be identified at any given stretch of coastline.The DSAS software will produce the following rate-of-change statistics:Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.

This layer of the map based index (GeoIndex) shows the availability of 1:50000 series geological maps. For England and Wales (and Northern Ireland), map sheets normally cover an area 30 km east-west and 20 km north-south; in Scotland the coverage is 20 km east-west and 30 km north-south. The 1:50 000 geological map grids are based on an early Ordnance Survey 1:63 360 (one inch to one mile) scale map grid and are not related to the current Ordnance Survey 1:50 000 map sheets. Maps are normally available in both flat and folded formats.

Dataset Name: NI Greenspace Off-Road Trails LayerData Owner: Outdoor NIContact: https://www.outdoorrecreationni.com/contact-us/Source URL: https://www.outdoorrecreationni.com/news/greenspaceni-map/Uploaded to SPACE Hub: 04/07/23Update Frequency: AnnualScale Threshold: N/AProjection : Irish GridFormat: Esri Feature Layer (Hosted) Vector PolygonNotes: The Department of Agriculture, Environment and Rural Affairs (DAERA) and the Department for Infrastructure (DfI) on behalf of the cross-government Strategic Outdoor Recreation Group (SORG) commissioned Outdoor Recreation Northern Ireland (ORNI) to create the Greenspace NI Map. ORNI have commissioned Geolytical to help with delivering a high value map of all off-road trails and publicly accessible greenspace.The Greenspace NI Map is designed so:i. The target of 'Annual increase of the population within a 5-minute walk of quality green/blue space' proposed for PfG and other strategies can be objectively measured;ii. It can be used by government departments and agencies, Councils, and eNGOs, for infrastructure planning, gap analysis, resource allocation, site suitability assessments and demographic analysis (e.g., health and deprivation etc);iii. The data will be published on SpatialNI, OpenDataNI, and on occasions, OutmoreNI.The Greenspace NI Map is comprised of 3 layers –• NI Greenspace Layer• NI Greenspace Access Points• NI Off-Road TrailsGreenspace Map – Off-Road Trails is a map layer that includes single-use and multi-use trails that have been collated, mapped and validated as part of the Greenspace Mapping Project. Some of these trails are also published to the interactive map viewer OutMoreNI. Separate layers will be published of Greenspaces, Greenspace Access Points and Bluespaces.What is a trail?A Trail is included in the Greenspace Map if:1. It is Off-Road (or described as off-road by the source)2. It has Public AccessHow has the Off-Road Trails Layer been created?This layer has been created by harmonising, combining, and enhancing data from our data providers - Ordnance Survey of NI, NIEA, Forest Service, Sustrans, Outdoor Recreation Northern Ireland, DAERA, Armagh City, Banbridge and Craigavon Borough Council, Belfast City Council, Causeway Coast and Glens Borough Council, Derry City and Strabane District Council, Fermanagh and Omagh District Council, Lisburn and Castlereagh City Council, Mid Ulster District Council, Woodland Trust, Ulster Wildlife.Once the data was imported, geometries were checked for accuracy and attributes were added including an off-road filter.Who's using the Greenspace NI Map?The Greenspace map can be used by anyone who has access to a Geographical Information programme such as ESRI ArcGIS. Knowledge of how to use such programmes is also essential. Some examples of users are:Public sector - Incorporated as a layer, the dataset can be 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.Innovators and researchers - NI's most comprehensive Open dataset of greenspaces can be used in a range of apps, products and innovations - providing the foundation to help create greener and healthier communities.FeedbackThink somewhere is missing from the data? Spot an inaccuracy in the attribution? Make us aware by emailing emma.taylor@outdoorrecreationi.comIf 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 2023 and has an annual update cycle.Usage and DisclaimerThe greenspace layer has been created with the most recent data available at time of publishing.Best efforts have been made in the production of the Greenspace NI Map to ensure the accuracy of the data, however as the data has come from a range of capture methodologies and scales, they ma not reflect actual positional accuracy on the ground. There may also be a time lag between the content of the map at the time of creation and changes made on the ground.These layers should not be used to determine exact boundaries of land ownership Where ‘source’ of data is outlined, it should be noted that this is the supplier of the data input, it does not define ownership of the area. However, in some cases the source may be the landowner also.Some assumptions and generalisations have been made to make the mapping process more feasible - polygons, points and lines have been aligned to Ordinance Survey NI maps. Exact details of each polygon, point or polyline have not undergone field validation so discrepancies may occur.Although the layer only includes land where the public have access, not every polygon or polyline has complete public access and some areas may have restricted access. ORNI and its providers of open and derived data will not be held responsible for any loss, damage or inconvenience of any nature caused as a result of any inaccuracy or error within the data.

🇬🇧 영국 English The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.The historical shoreline analysis was based on all available Ordnance Survey maps and aerial imagery information. Analysis looked at position and geometry over annual to decadal time periods, providing a dynamic picture of how the coastline has changed since the start of the early 1800s.Once all datasets were collated, data was interrogated using the ArcGIS package – Digital Shoreline Analysis System (DSAS). DSAS is a software package which enables a user to calculate rate-of-change statistics from multiple historical shoreline positions. Rate-of-change was collected at 25m intervals and displayed both statistically and spatially allowing for areas of retreat/accretion to be identified at any given stretch of coastline.The DSAS software will produce the following rate-of-change statistics:Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.

This layer of the map based index (GeoIndex) shows the availability of 1:50000 series paper geological maps. For England and Wales (and Northern Ireland), map sheets normally cover an area 30 km east-west and 20 km north-south; in Scotland the coverage is 20 km east-west and 30 km north-south. The 1:50 000 geological map grids are based on an early Ordnance Survey 1:63 360 (one inch to one mile) scale map grid and are not related to the current Ordnance Survey 1:50 000 map sheets. Maps are normally available in both flat and folded formats.

The Geological Survey of Northern Ireland (GSNI) and the British Geological Survey (BGS) completed a regional geochemical survey of Northern Ireland's soils, sediments and waters between 2004 and 2006.

Soil sampling of all of Northern Ireland was completed under the Tellus survey between 2004 and 2006. Soil samples were collected on a systematic basis from rural areas in most of the region, excluding only the major urban centres of Belfast and Bangor. Soils were also collected at a higher sampling density from the urban areas of Belfast, Bangor, Carrickfergus, Carryduff, Castlereagh, Greenisland, Holywood, Lisburn, Newtownabbey and Londonderry, although these urban results are not reported here.

In rural areas, samples were collected from alternate 1 km Irish national- grid squares. Site selection within each square was random, subject to the avoidance wherever possible of roads, tracks, railways, human habitation and other disturbed ground. At each site two composite samples of five auger flights were collected, each composite sample comprising approximately 750 g of unsieved material. Samples were collected using a hand auger with a 20 by 5 cm flight from a standard depth interval of 5–20 cm for designated ‘A’ samples, referred to subsequently as ‘surface soils’, and at 35–50 cm for designated ‘S’ samples (nominally the B horizon), referred to subsequently as ‘deep soils’. Some 6,862 regional soil sites were sampled (see supplementary map - soil locations) and analysed, resulting in an average regional sampling density of 1 site per 2 km2. Observations of soil colour, depth, clast lithology and abundance were recorded at site. The samples were classified into five textural groups (sand, sand-silt, silt, silt-clay and clay).

The methods used for urban soils were similar except that (1) the sample density was higher, at four sites per square kilometre; (2) the sample sites corresponded closely to a predefined grid and did not avoid areas of human influence. In addition, extra samples requiring special treatment were taken for the determination of selected organic constituents (Smyth, 2009: especially Appendix 1).

At each soil sample site, information on the location, site and catchment geology, contamination, land use, and other features required for data interpretation were entered onto field cards. The sample location was also plotted on a field copy of the 1:50 000 Ordnance Survey of Northern Ireland (OSNI) map.

Observations from field cards were entered into a digital Access2000™ database after undergoing a field quality control process (Lister et al, 2005). This involved checking that the correct codes had been recorded on field cards and that GPS coordinates recorded on the card matched those in the GPS unit for each site. Thus both a traditional paper archive of observations was maintained as well as the construction of a computerised database.

Soils were initially air-dried at the field-base prior to transport to the sample store where they were dried in a temperature controlled oven at 30°C for 2–3 days. At the end of each field campaign samples were checked against field sheets prior to packing for transport to the BGS laboratory for sample preparation. On arrival at the laboratory samples were checked against shipping lists prior to assigning laboratory batch numbers in the BGS UKAS Quality Assurance System. The A and S soils were prepared in the same manner in a trace-level sample preparation laboratory.

Samples were disaggregated prior to sieving to a <2 mm fraction using nylon mesh. Replicate samples were prepared by riffle splitting each of the duplicate samples. Soil pH and LOI was determined for every A surface soil sample. A representative 30 g (± 2 g) sub-sample was obtained by cone and quartering. This sub-sample was then milled in an agate ball mill at 300 rpm for 30 minutes.

Different analytical procedures were employed for the surface and deep soils. Pressed pellet production and XRF analysis were completed by laboratory on surface soils only. Sub-samples of milled soil were weighed and placed into tamper-evident plastic sample tubes. The XRF pressed pellet was prepared by adding an aliquot (3 g ±0.05 g) of two blended synthetic waxes comprising 90 % EMU 120 FD wax and 10 % Ceridust (both waxes are styrene based co-polymers) to 12 g (± 0.05 g) of milled material. This mixture was milled for 4 minutes at 300 rpm. On completion of the binder milling the prepared powders were placed into tamper evident plastic sample tubes for temporary storage prior to pellet preparation. Pellets (40 mm) were pressed using a calibrated Herzog semi-automatic pellet press at 25 kN.

Prior to analysis, concealed certified reference materials and secondary reference materials were inserted into the sample batches. XRF analysis of the A samples was undertaken at the BGS; ICP analysis of A and S samples at SGS Laboratories, Toronto; and fire-assay of S samples at SGS Laboratories, Toronto.

For the Tellus samples, Energy Dispersive Polarised X-Ray Fluorescence (ED(P)- XRF) spectrometers were used to analyse those elements for which the WD-XRF spectrometers were insufficiently sensitive. Certified Reference Material (CRM) standards were used to calibrate the instruments. The PANalytical software was used for spectral deconvolution and to fit calibration curves, applying matrix correction by internal ratio Compton correction method. The calibrations were validated by analysis of a wide range of RMs. The detectors were calibrated weekly. All backgrounds and peaks were corrected for instrument drift using two external ratio monitors, when required. Quality control was maintained by regular analysis of two glass monitor samples containing 47 elements at nominally 30 mg/ kg and 300 mg/kg. Results were presented as run charts for statistical analysis using statistical process control software (SPC).

The lower limits of detection are theoretical values for the concentration equivalent to three standard deviations (99.7 % confidence interval) above the background count rate for the analyte in an iron-rich alumino-silicate matrix. For silicate matrices the practical detection limits for most elements approach the theoretical values due to high instrumental stability. LLDs were calculated from a matrix blank and the ‘synthetic’ Pro-Trace standards.

Individual results are not reliable below the quoted lower limits, but reliable estimates of the average or typical values over an area may be obtained at lower levels of concentration; meaningful distribution patterns may thus be recognised for some elements at levels lower than the LLD.

The data are described in Young, Mike; Donald, Alex, eds. 2013 A guide to the Tellus data. Belfast, UK, Geological Survey of Northern Ireland, 233pp. available for free download from: http://nora.nerc.ac.uk/509171/

The Tellus survey was funded by the Department of Enterprise, Trade and Investment (DETI), now the Department for the Economy (DfE) in Northern Ireland and the INTERREG IVA programme of the European Union (EU) Regional Development Fund.

🇬🇧 영국 English The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.The historical shoreline analysis was based on all available Ordnance Survey maps and aerial imagery information. Analysis looked at position and geometry over annual to decadal time periods, providing a dynamic picture of how the coastline has changed since the start of the early 1800s.Once all datasets were collated, data was interrogated using the ArcGIS package – Digital Shoreline Analysis System (DSAS). DSAS is a software package which enables a user to calculate rate-of-change statistics from multiple historical shoreline positions. Rate-of-change was collected at 25m intervals and displayed both statistically and spatially allowing for areas of retreat/accretion to be identified at any given stretch of coastline.The DSAS software will produce the following rate-of-change statistics:Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.