This data was collected by the Geological Survey Ireland, the Department of Culture, Heritage and the Gaeltacht, the Discovery Programme, the Heritage Council, Transport Infrastructure Ireland, New York University, the Office of Public Works and Westmeath County Council. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution varies depending on survey requirements. Resolutions for each organisation are as follows: GSI – 1m DCHG/DP/HC - 0.13m, 0.14m, 1m NY – 1m TII – 2m OPW – 2m WMCC - 0.25m Both a DTM and DSM are raster data. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. The grid cell size varies depending on the organisation that collected it. GSI data has a grid cell size of 1 meter by 1 meter. This means that each cell (pixel) represents an area of 1 meter squared.

In 2021, only three percent of the geographical coverage of mobile data services in Northern Ireland were complete not-spots, in other words, not covered by any operator. On the other hand were 79 percent of the land mass in Northern Ireland covered by all operators.

In 2022, the network providers Three had the highest mobile data network availability, covering 92 percent of the geographical area in Northern Ireland, along with Vodafone, also providing 92 percent coverage.

Irish Resident Investment Funds Issues and Redemptions by Geography. Published by Central Bank of Ireland. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Dataset provides a detailed quarterly geographical breakdown of the holders of equity in Irish Investment Funds and the net issues of the fund share/units of the funds....

A landslide is the movement of material down a slope. This includes rock, earth, mud and peat. Landslides in Ireland mainly occur on steep mountain slopes. Geologists map and record information on where and when landslides happen and on the material that has moved. They also map the area of a landslide in order to see how big the landslide was. To produce the location and extent data, landslides were mapped using digital imagery and mapping in the field. The area of the landslide was then drawn on a map.We collect new landslide event data and update the landslide event dataset every year. The are to the scale 1:5,000. This means they should be viewed at that scale. When printed at that scale 1cm on the map relates to a distance of 50m.They are vector datasets. Vector data portray the world using points, lines and polygons (area). The landslide extent perimeter data is shown as polygons which is the area of the landslide. Each polygon holds information about the landslide event, its date, its location, the type of landslide (topple, bogslide, flow), the type of material (peat, earth, rock) and the cause of the landslide (heavy rainfall).The landslide location data is shown as points. Each point holds information about the landslide event, its date, its location, the type of landslide (topple, bogslide, flow), the type of material (peat, earth, rock) and the cause of the landslide (heavy rainfall).A landslide susceptibility map shows areas where a landslide could occur, how likely it will occur and what causes them. The likelihood is measured from low to high. The map is created using a method called the Unique Condition Unit (UCU). A unique condition unit is an area with a set of ground types. It tells us what the soil type is, what the slope is (angle of the ground) and where water flows. When many landslides occur in a unit, the map will show high landslide susceptibility. The landslide susceptibility classification map is to the scale 1:50,000. This means it should be viewed at that scale. When printed at that scale 1cm on the map relates to a distance of 500m.It is a vector dataset. Vector data portray the world using points, lines, and polygons. A polygon represents an area. The landslide susceptibility data is shown as polygons. Each polygon gives information on the unit, its soil type, the slope of the ground, its description and the description of landslide susceptibility (High or low).

Download high-quality, up-to-date Ireland shapefile boundaries (SHP, projection system SRID 4326). Our Ireland Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

Description of Data Population estimates for the 3,780 Data Zones in Northern Ireland were published on 25th July 2024.

Time Period Estimates are provided for mid-2021 and mid-2022.

Notes: 1. Estimated populations are given as of 30th June for the year noted, rounded to the nearest person. 2. Rounding for estimates at this geographic level is independent. As such, figures may not add to higher geography totals.

Methodology The population estimates for small geographical areas are created from an average of two statistical methods: the ratio change and cohort-component methods. The ratio change method applies the change in secondary (typically administrative) data sources to Census estimates. The 2022 small geographical area estimates use a single statistical dataset which has been created by amalgamating a series of different administrative data sources. This statistical dataset is a de-duplicated admin based estimate for the usually resident population of NI. The cohort-component method updates the Census estimates by ‘ageing on’ populations and applying information on births, deaths and migration. An average of both methods is taken and constrained to the published population figures. Further information is available at: NISRA 2022 Mid-year Population Estimates webpage

Geographic Referencing Population Estimates are based on a large number of secondary datasets. Where the full address was available, the Pointer Address database was used to allocate a unique property reference number (UPRN) and geo-spatial co-ordinates to each home address. These can then be used to map the address to particular geographies. Where it was not possible to assign a unique property reference number to an address using the Pointer database, or where the secondary dataset contained only postcode information, the Central Postcode Directory was used to map home address postcodes to higher geographies. A small proportion of records with unknown geography were apportioned based on the spatial characteristics of known records.

Further Information The next estimates of the population for Northern Ireland will be released later in 2024.

Contact: NISRA Customer Services 02890 255156 census@nisra.gov.uk Responsible Statistician: Jonathan Harvey

The 1885 UK parliamentary constituencies for Ireland were re-created in 2017 as part of a conference paper delivered at the Southern Irish Loyalism in Context conference at Maynooth University. The intial map only included the territory of the Irish Free State and was created by Martin Charlton and Jack Kavanagh. The remaining six counties of Ulster were completed by Eoin McLaughlin in 2018-19, the combined result is a GIS map of all the parliamentary constituecies across the island of Ireland for the period 1885-1918. The map is available in both ESRI Shapefile format and as a GeoPackage (GPKG). The methodology for creating the constituencies is outlined in detail below.

Methodology

A map showing the outlines of the 1855 – 1918 Constituency boundaries can be found on page 401 of Parliamentary Elections in Ireland, 1801-1922 (Dublin, 1978) by Brian Walker. This forms the basis for the creation of a set of digital boundaries which can then be used in a GIS. The general workflow involves allocating an 1885 Constituency identifier to each of the 309 Electoral Divisions present in the boundaries made available for the 2011 Census of Population data release by CSO. The ED boundaries are available in ‘shapefile’ format (a de facto standard for spatial data transfer). Once a Constituency identifier has been given to each ED, the GIS operation known as ‘dissolve’ is used to remove the boundaries between EDs in the same Constituency. To begin with Walker’s map was scanned at 1200 dots per inch in JPEG form. A scanned map cannot be linked to other spatial data without undergoing a process known as georeferencing. The CSO boundaries are available with spatial coordinates in the Irish National Grid system. The goal of georeferencing is to produce a rectified version of the map together with a world file. Rectification refers to the process of recomputing the pixel positions in the scanned map so that they are oriented with the ING coordinate system; the world file contains the extent in both the east-west and north-south directions of each pixel (in metres) and the coordinates of the most north-westerly pixel in the rectified image.

Georeferencing involves the identification of Ground Control Points – these are locations on the scanned map for which the spatial coordinates in ING are known. The Georeferencing option in ArcGIS 10.4 makes this a reasonably pain free task. For this map 36 GCPs were required for a local spline transformation. The Redistribution of Seats Act 1885 provides the legal basis for the constituencies to be used for future elections in England, Wales, Scotland and Ireland. Part III of the Seventh Schedule of the Act defines the Constituencies in terms of Baronies, Parishes (and part Parishes) and Townlands for Ireland. Part III of the Sixth Schedule provides definitions for the Boroughs of Belfast and Dublin.

The CSO boundary collection also includes a shapefile of Barony boundaries. This makes it possible code a barony in two ways: (i) allocated completely to a Division or (ii) split between two Divisions. For the first type, the code is just the division name, and for the second the code includes both (or more) division names. Allocation of these names to the data in the ED shapefile is accomplished by a spatial join operation. Recoding the areas in the split Baronies is done interactively using the GIS software’s editing option. EDs or groups of EDs can be selected on the screen, and the correct Division code updated in the attribute table. There are a handful of cases where an ED is split between divisions, so a simple ‘majority’ rule was used for the allocation. As the maps are to be used at mainly for displaying data at the national level, a misallocation is unlikely to be noticed. The final set of boundaries was created using the dissolve operation mentioned earlier. There were a dozen ED that had initially escaped being allocated a code, but these were quickly updated. Similarly, a few of the EDs in the split divisions had been overlooked; again updating was painless. This meant that the dissolve had to be run a few more times before all the errors have been corrected.

For the Northern Ireland districts, a slightly different methodology was deployed which involved linking parishes and townlands along side baronies, using open data sources from the OSM Townlands.ie project and OpenData NI.

Constrained estimates, total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.

More information can be found in the Release Statement

The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

This is a restricted dataset and this download is available to NIMA users only.

OSNI 250k contains a tabulated list of 330 main cities, towns and villages of Northern Ireland appearing on the 1:250,000 map. Irish grid references are incorporated in the table to allow the spatial location of the settlements to be plotted. The data has been captured by extracting all textual levels for the main cities, towns and villages of Northern Ireland appearing on the 1:250,000 map. OSNI 50k Gazetteer contains a list of all main text appearing on OSNI 1:50 000 scale Discoverer Map Series. Includes names of cities, towns, villages, water features, mountains, hills and forests of Northern Ireland. Irish Grid references are incorporated.

Users outside of the Spatial NI Portal please use Resource Locator 2.

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Northern Ireland. It describes Northern Ireland's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. 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/10.5285/35f15502-d340-4ab5-a586-abd42f238b6e

Comprehensive dataset of 1 Faculty of geography and histories in Longford, Ireland as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Cartographic text needed for named place at scale 1:250.000 that cannot be put into attributes. Named locations specially required are regions e.g. Mountain range, Valley, Peak, Gorge, Bay, Sea, Fjord, Inlet/cape, Sandbank, Beach, Headland/Peninsula, Sea water and forest name. For data transfer and better data interoperability, each geographical name is represented by a line feature and by a text feature. GNAMEL is a copy of GNAMET with a different geometric representation.

Description of Data Notes: The estimates are produced using a variety of data sources and statistical models. Therefore small estimates should not be taken to refer to particular individuals. The migration element of the components of change have been largely derived from a data source which is known to be deficient in recording young adult males and outflows from Northern Ireland. Therefore the estimates are subject to adjustment to account for this and, while deemed acceptable for their use, will not provide definitive numbers of the population in the reported groups/areas. Further information is available in the Limitations section of the statistical bulletin: NISRA 2023 Mid-year Population Estimates webpage Time Period Estimates are provided for mid-1971 to mid-2023. Methodology The cohort-component method was used to create the population estimates for 2023. This method updates the Census estimates by 'ageing on' populations and applying information on births, deaths and migration. Further information is available at: NISRA 2023 Mid-year Population Estimates webpage Geographic Referencing Population Estimates are based on a large number of secondary datasets. Where the full address was available, the Pointer Address database was used to allocate a unique property reference number (UPRN) and geo-spatial co-ordinates to each home address. These can then be used to map the address to particular geographies. Where it was not possible to assign a unique property reference number to an address using the Pointer database, or where the secondary dataset contained only postcode information, the Central Postcode Directory was used to map home address postcodes to higher geographies. A small proportion of records with unknown geography were apportioned based on the spatial characteristics of known records. Further Information NISRA Mid-year Population Estimates webpage Contact: NISRA Customer Services 02890 255156 census@nisra.gov.uk Responsible Statistician: Shauna Dunlop

EMODnet Vessel Density Map were created by Cogea in 2019 in the framework of EMODnet Human Activities, an initiative funded by the EU Commission. The maps are based on AIS data purchased by CLS and show shipping density in 1km*1km cells of a grid covering all EU waters (and some neighbouring areas). Density is expressed as hours per square kilometre per month. A set of AIS data had to be purchased from CLS, a commercial provider. The data consists of messages sent by automatic tracking system installed on board ships and received by terrestrial and satellite receivers alike. The dataset covers the whole 2017 for an area covering all EU waters. A partial pre-processing of the data was carried out by CLS: (i) The only AIS messages delivered were the ones relevant for assessing shipping activities (AIS messages 1, 2, 3, 18 and 19). (ii) The AIS DATA were down-sampled to 3 minutes (iii) Duplicate signals were removed. (iv) Wrong MMSI signals were removed. (v) Special characters and diacritics were removed. (vi) Signals with erroneous speed over ground (SOG) were removed (negative values or more than 80 knots). (vii) Signals with erroneous course over ground (COG) were removed (negative values or more than 360 degrees). (viii) A Kalman filter was applied to remove satellite noise. The Kalman filter was based on a correlated random walk fine-tuned for ship behaviour. The consistency of a new observation with the modeled position is checked compared to key performance indicators such as innovation, likelihood and speed. (ix) A footprint filter was applied to check for satellite AIS data consistency. All positions which were not compliant with the ship-satellite co-visibility were flagged as invalid.The AIS data were converted from their original format (NMEA) to CSV, and split into 12 files, each corresponding to a month of 2017. Overall the pre-processed dataset included about 1.9 billion records. Upon trying and importing the data into a database, it emerged that some messages still contained invalid characters. By running a series of commands from a Linux shell, all invalid characters were removed. The data were then imported into a PostgreSQL relational database. By querying the database it emerged that some MMSI numbers are associated to more than a ship type during the year. To cope with this issue, we thus created an unique MMSI/shyp type register where we attributed to an MMSI the most recurring ship type. The admissible ship types reported in the AIS messages were grouped into macro categories: 0 Other, 1 Fishing, 2 Service, 3 Dredging or underwater ops, 4 Sailing, 5 Pleasure Craft, 6 High speed craft, 7 Tug and towing, 8 Passenger, 9 Cargo, 10 Tanker, 11 Military and Law Enforcement, 12 Unknown and All ship types. The subsequent step consisted of creating points representing ship positions from the AIS messages. This was done through a custom-made script for ArcGIS developed by Lovell Johns. Another custom-made script reconstructed ship routes (lines) from the points, by using the MMSI number as a unique identifier of a ship. The script created a line for every two consecutive positions of a ship. In addition, for each line the script calculated its length (in km) and its duration (in hours) and appended them both as attributes to the line. If the distance between two consecutive positions of a ship was longer than 30 km or if the time interval was longer than 6 hours, no line was created. Both datasets (points and lines) were projected into the ETRS89/ETRS-LAEA coordinate reference system, used for statistical mapping at all scales, where true area representation is required (EPSG: 3035).The lines obtained through the ArcGIS script were then intersected with a custom-made 1km*1km grid polygon (21 million cells) based on the EEA's grid and covering the whole area of interest (all EU sea basins). Because each line had length and duration as attributes, it was possible to calculate how much time each ship spent in a given cell over a month by intersecting line records with grid cell records in another dedicated PostgreSQL database. Using the PostGIS Intersect tool, for each cell of the grid, we then summed the time value of each 'segment' in it, thus obtaining the density value associated to that cell, stored in calculated PostGIS raster tables. Density is thus expressed in hours per square kilometre per month. The final step consisted of creating raster files (TIFF file format) with QuantumGIS from the PostgreSQL vessel density tables. Annual average rasters by ship type were also created. The dataset was clipped according to the National Marine Planning Framework (NMPF) assessment area. None

Dataset Name: NISRA Health DataData Owner: NISRAContact: census@nisra.co.ukSource URL: https://build.nisra.gov.uk/Uploaded to SPACE Hub: 03/07/23Update Frequency: Per censusScale Threshold: some data has 10k threshold appliedProjection : Irish GridFormat: Esri Feature Layer (Hosted) Vector PolygonAbstractThe census collected information on the usually resident population of Northern Ireland on Census Day (21 March 2021).Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on Census Day.Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc.The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.Disclosure control methodsStatistical disclosure control (SDC) refers to a range of methods that aim to protect individuals, households, businesses, and their attributes from being identified in published information.NISRA has taken steps to ensure that the confidentiality of respondents is fully protected.All published results from the census have been subject to statistical processes to ensure that individuals cannot be identified. These processes may result in very marginal differences between tables for the same statistic.For Census 2021, NISRA is applying two strategies - targeted record swapping (TRS) and cell key perturbation (CKP), to ensure individuals are protected from identification while minimising the impact on the quality of results.Disclosure control methodologyFor more information, please refer to:Statistical disclosure control methodologyMethodologyThe census questionnaire including the questions asked and the administrative procedures involved in collecting the census data underwent substantial testing. Coding of the data was subject to quality checks.The quality of the results was improved by the use of edit and imputation procedures for missing or incorrect data, and the data were adjusted for over and under-enumeration.The outputs reflect the complete usually-resident population of Northern Ireland.Methodology overviewFurther information on the methodology used in Census 2021 is available in the:Census 2021 methodology overviewQuality issuesThe census results underwent an extensive quality assurance process, which included checks against administrative data sources and information on particular groups such as students and HM Forces personnel.Edit procedures were applied to obviously incorrect responses (such as someone aged 180) and were designed to correct the mistake by making the least possible change to the data.Imputation procedures were applied to missing data on a returned questionnaire, and drew on responses to the question from people with similar characteristics.Quality assurance reportFurther information on the quality assurance processes used in Census 2021 is available in the:Census 2021 quality assurance reportStatement about data qualityFor more information on data quality, including response rate and item response rate, please refer to the:Census 2021 statement about data qualityGeographic referencingIrish National GridNational Statistics publicationCensus statistics are produced by the Northern Ireland Statistics and Research Agency free from political influence and have been assessed as National Statistics by the Office for Statistics Regulation.Office for Statistics RegulationMore information is available on the following web site:Office for Statistics RegulationProducing census statisticsCensus 2021 statistics meet the highest standards of trust, quality and value and are produced using standards set out in the statutory Code of Practice for Statistics.Code of Practice for StatisticsMore information is available in the:Code of Practice for StatisticsDate of publicationJune 2023Further informationCensus 2021 results webpage

Private households by size by Small Area. (Census 2022 Theme 5 Table 2 )Census 2022 table 5.2 is private households by size. Details include private households by size, number of households and number of persons. Census 2022 theme 5 is Private Households. Census Small Areas are the lowest level of geography for the dissemination of Census data and typically contain between 50 and 200 dwellings. They are generally comprised of complete neighbourhoods or townlands and they nest within CSO Electoral Divisions. Census 2022 Small Areas have been redrawn to ensure they remain consistent with the principle of data protection and are relatively comparable in size. This redraw was necessary following changes in population size and distribution between 2016 and 2022 and was done by the CSO with support from Tailte Éireann. Small Areas were first published for Census 2011 following work undertaken by the National Institute of Regional and Spatial Analysis (NIRSA) on behalf of Tailte Éireann and in consultation with the CSO. Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. CSO Small Areas 2022

Constrained estimates, total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.

More information can be found in the Release Statement

The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

Catholic Parish Registers Geodata. Published by National Library of Ireland. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).This repository contains geo-data concerning the National Library of Ireland’s collection of Catholic parish register microfilms. The data is used in the mapping features of https://registers.nli.ie/. The registers contain records of baptisms and marriages from the majority of Catholic parishes in Ireland and Northern Ireland up to 1880....

Abstract copyright UK Data Service and data collection copyright owner.

The Northern Ireland Grid-Square Product comprises population counts for a regular grid of 1km and 100m cells for 1971, 1981, 1991 and 2001. It is a unique data resource, which has previously been under-utilised because it has been held in an inaccessible format, where data have had to be extracted by the manual entry of each cell's co-ordinates. The data are valuable because they permit the analysis of change through time using geographical units that are consistent between censuses. The Linking Northern Ireland Census of Population Data project sought to make these data more widely available by extracting all counts for all years and subsequently reformatting the data to make them more amenable for general analysis with commonly used software. Linkages between variables through time have been documented, and basic look-up tables linking the 1km and 100m cell counts to Census 2001 output geographies have been provided. All variable counts for all years are given. The data make it possible to trace local patterns of social, demographic and economic change in Northern Ireland through time, using a consistent geography between 1971 and 2001.

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The data comprise variables covering economic and labour markets, housing conditions, migration, religion and other topics, and population counts. Users should note that the data files are for use with ArcInfo software.