United Kingdom Exports of maps, hydrographic or similar charts (printed) to United States was US$19.82 Million during 2024, according to the United Nations COMTRADE database on international trade. United Kingdom Exports of maps, hydrographic or similar charts (printed) to United States - data, historical chart and statistics - was last updated on July of 2025.

PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.

United States Exports of maps, hydrographic or similar charts (printed) to United Kingdom was US$551.04 Thousand during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of maps, hydrographic or similar charts (printed) to United Kingdom - data, historical chart and statistics - was last updated on June of 2025.

The map shows annual mean concentrations of Particulate Matter (PM2.5) in Europe based on daily averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting)Thresholds used in the maps for annual values [µg/m3]:≤ 10: (10 μg/m3, as set out in the WHO air quality guideline for PM2.5)> 10 ≤ 20: (20 μg/m3, limit value as set out in the Air Quality Directive, 2008/50/EC)> 20 ≤ 25: (25 μg/m3, target value as set out in the Air Quality Directive, 2008/50/EC)> 25 ≤ 30> 30Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA collaborating countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.

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

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

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

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

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

The map shows annual mean concentrations of Particulate Matter (PM2.5) in Europe based on daily averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting)Thresholds used in the maps for annual values [µg/m3]:≤ 10: (10 μg/m3, as set out in the WHO air quality guideline for PM2.5)> 10 ≤ 20: (20 μg/m3, limit value as set out in the Air Quality Directive, 2008/50/EC)> 20 ≤ 25: (25 μg/m3, target value as set out in the Air Quality Directive, 2008/50/EC)> 25 ≤ 30> 30Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA collaborating countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for countries in the United Kingdom.Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for regions in the United Kingdom.Government offices for the regions (GOR) were established across England in 1994. Reflecting a number of government departments, their aim was to work in partnership with local people and organisations in order to maximise prosperity and the quality of life within their area. In 1996 the GORs became the primary classification for the presentation of regional statistics. GORs were built up of complete counties/unitary authorities, so although they were subject to change, they always reflected administrative boundaries as at the end of the previous year. Scotland, Wales and Northern Ireland were not subdivided into GORs but are listed with them as regions in UK-wide statistical comparisons. After the Comprehensive Spending Review, it was confirmed that the GORs would close on 31 March 2011, shifting focus away from regions to local areas. However, there is still a requirement to maintain a region-level geography for statistical purposes. Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.Add administrative hierarchy.

In the century between Napoleon's defeat and the outbreak of the First World War (known as the "Pax Britannica"), the British Empire grew to become the largest and most powerful empire in the world. At its peak in the 1910s and 1920s, it encompassed almost one quarter of both the world's population and its land surface, and was known as "the empire on which the sun never sets". The empire's influence could be felt across the globe, as Britain could use its position to affect trade and economies in all areas of the world, including many regions that were not part of the formal empire (for example, Britain was able to affect trading policy in China for over a century, due to its control of Hong Kong and the neighboring colonies of India and Burma). Some historians argue that because of its economic, military, political and cultural influence, nineteenth century Britain was the closest thing to a hegemonic superpower that the world ever had, and possibly ever will have. "Rule Britannia" Due to the technological and logistical restrictions of the past, we will never know the exact borders of the British Empire each year, nor the full extent of its power. However, by using historical sources in conjunction with modern political borders, we can gain new perspectives and insights on just how large and influential the British Empire actually was. If we transpose a map of all former British colonies, dominions, mandates, protectorates and territories, as well as secure territories of the East India Trading Company (EIC) (who acted as the precursor to the British Empire) onto a current map of the world, we can see that Britain had a significant presence in at least 94 present-day countries (approximately 48 percent). This included large territories such as Australia, the Indian subcontinent, most of North America and roughly one third of the African continent, as well as a strategic network of small enclaves (such as Gibraltar and Hong Kong) and islands around the globe that helped Britain to maintain and protect its trade routes. The sun sets... Although the data in this graph does not show the annual population or size of the British Empire, it does give some context to how Britain has impacted and controlled the development of the world over the past four centuries. From 1600 until 1920, Britain's Empire expanded from a small colony in Newfoundland, a failing conquest in Ireland, and early ventures by the EIC in India, to Britain having some level of formal control in almost half of all present-day countries. The English language is an official language in all inhabited continents, its political and bureaucratic systems are used all over the globe, and empirical expansion helped Christianity to become the most practiced major religion worldwide. In the second half of the twentieth century, imperial and colonial empires were eventually replaced by global enterprises. The United States and Soviet Union emerged from the Second World War as the new global superpowers, and the independence movements in longstanding colonies, particularly Britain, France and Portugal, gradually succeeded. The British Empire finally ended in 1997 when it seceded control of Hong Kong to China, after more than 150 years in charge. Today, the United Kingdom consists of four constituent countries, and it is responsible for three crown dependencies and fourteen overseas territories, although the legacy of the British Empire can still be seen, and it's impact will be felt for centuries to come.

The population of the United Kingdom in 2023 was estimated to be approximately 68.3 million in 2023, with almost 9.48 million people living in South East England. London had the next highest population, at over 8.9 million people, followed by the North West England at 7.6 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.16 million, and 1.92 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 622,000, while in Wales, it was the Cardiff Unitary Authority at around 372,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of around 348,000.

The market for professional map services is projected to grow at a CAGR of 7.1% from 2025 to 2033, reaching a value of $1,175 million by 2033. The growth of the market is attributed to the increasing use of maps in various applications, such as navigation, location-based services, and asset tracking. Consulting and advisory services segment is expected to grow at the highest rate during the forecast period. Deployment and integration services segment is estimated to have the largest market share during the forecast period. Application wise, utilities segment is expected to grow at the highest rate during the forecast period. Geographically, the North America region is expected to dominate the professional map services market over the forecast period, followed by Europe and Asia-Pacific. The United States is the largest market for professional map services in North America, followed by Canada and Mexico. The United Kingdom is the largest market for professional map services in Europe, followed by Germany and France. China is the largest market for professional map services in Asia-Pacific, followed by India and Japan. The growth of the professional map services market in these regions is attributed to the increasing adoption of location-based services and the growing demand for accurate and reliable maps.

In 2023, London had a gross domestic product of over 569 billion British pounds, by far the most of any region of the United Kingdom. The region of South East England which surrounds London had the second-highest GDP in this year, at over 360 billion pounds. North West England, which includes the major cities of Manchester and Liverpool, had the third-largest GDP among UK regions, at almost 250 billion pounds. Levelling Up the UK London’s economic dominance of the UK can clearly be seen when compared to the other regions of the country. In terms of GDP per capita, the gap between London and the rest of the country is striking, standing at over 63,600 pounds per person in the UK capital, compared with just over 37,100 pounds in the rest of the country. To address the economic imbalance, successive UK governments have tried to implement "levelling-up policies", which aim to boost investment and productivity in neglected areas of the country. The success of these programs going forward may depend on their scale, as it will likely take high levels of investment to reverse economic neglect regions have faced in the recent past. Overall UK GDP The gross domestic product for the whole of the United Kingdom amounted to 2.56 trillion British pounds in 2024. During this year, GDP grew by 0.9 percent, following a growth rate of 0.4 percent in 2023. Due to the overall population of the UK growing faster than the economy, however, GDP per capita in the UK fell in both 2023 and 2024. Nevertheless, the UK remains one of the world’s biggest economies, with just five countries (the United States, China, Japan, Germany, and India) having larger economies. It is it likely that several other countries will overtake the UK economy in the coming years, with Indonesia, Brazil, Russia, and Mexico all expected to have larger economies than Britain by 2050.

Map shows monitoring bathing water locations in 2013 and quality of bathing water from 2003 till 2013. For the scale 1:5,000,001 and less detailed, data are aggregated by country. In such cases, stacked bars show percentage of bathing water quality for coastal and inland waters together. Number of bathing waters within certain category is seen in pop up window which can be activated with a click on one of the countries. For the scale range 1:5,000,000 to 1:700,001, individual bathing water sites (points) are visible instead of classified stacked charts and are coloured according to achivied bathing water quality. Symbol size depends on the map scale (in more detailed map scales symbols are bigger). For the scales 1:700,000 and more detailed, symbol of bather in a square appears instead of points. All symbols (charts, circles and squares with bather) are coloured according to achieved quality status. Historical data is seen in pop-up windows which can be opened with a click on individual bathing water monitoring site.Assessment is done according to assessment rules of the Directive 76/160/EEC (classification into categories CG, CI, NC...) and of the Directive 2006/7/EC (classification into categories Excellent, Good, Sufficient...).The EEA has checked all bathing waters for a pre-season sample and monthly samples thereafter for the 2013 season. When these requirements are met, the bathing water is categorised as 'frequency of sampling satisfied'. If these criteria are not met (bathing waters are either closed or insufficiently sampled), the bathing water is categorised as 'frequency of sampling not satisfied'. Bathing waters are classified as 'excellent', 'good', 'sufficient' or 'poor' if they have at least 4 (if the bathing season is less than 8 weeks long, then 3) samples distributed throughout the 2013 season, and 16 (if the bathing season is less than 8 weeks long, then 12) samples available for the assessment period.Some bathing waters cannot be classified according to their quality. They are instead classified as 'closed' (temporarily or throughout the bathing season), 'new' (quality classification not yet possible), 'changes' (quality classification not yet possible after changes that affect or could have affected bathing water quality) or they do not have enough samples in the 2013 season or throughout the assessment period.

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.

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

Explore a full description of the map.This map layer shows the 24 time zones commonly used in the Greenwich Mean Time model. The hours added or subtracted from the time in Greenwich are marked on the map. For example, if it is 1:00 p.m. in London, England, United Kingdom, it is 6:30 pm in New Delhi, Delhi, India (+5.50), and 5:00 a.m. in Los Angeles, California, United States (-8.00). CreditsEsri, from National Geographic MapMakerTerms of Use This work is licensed under the Esri Master License Agreement.View Summary | View Terms of Use

This layer is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information