Mature Support Notice: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.To launch a web map containing this map layer, click here.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including Garmin, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale. Here's a ready-to-use web map that uses the National Geographic World Map as its basemap. Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, Garmin, HERE, INCREMENT P, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.Ocean Data: GEBCO, NOAA

[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

This dataset comprises 2 collections of maps. The facsmile collection contains all the marginalia information from the original map as well as the map itself, while the georectified collection contains just the map with an associated index for locating them. Each collection comprises approximately 101 000 monochrome images at 6-inch (1:10560) scale. Each image is supplied in .tiff format with appropriate ArcView and MapInfo world files, and shows the topography for all areas of England, Wales and Scotland as either quarter or, in some cases, full sheets. The images will cover the approximate epochs 1880's, 1900's, 1910's, 1920's and 1930's, but note that coverage is not countrywide for each epoch. The data was purchased by BGS from Sitescope, who obtained it from three sources - Royal Geographical Society, Trinity College Dublin and the Ordnance Survey. The data is for internal use by BGS staff on projects, and is available via a customised application created for the network GDI enabling users to search for and load the maps of their choice. The dataset will have many uses across all the geoscientific disciplines across which BGS operates, and should be viewed as a valuable addition to the BGS archive. There has been a considerable amount of work done during 2005, 2006 and 2007 to improve the accuracy of the OS Historic Map Collection. All maps should now be located to +- 50m or better. This is the best that can be achieved cost effectively. There are a number of reasons why the maps are inaccurate. Firstly, the original maps are paper and many are over 100 years old. They have not been stored in perfect condition. The paper has become distorted to varying degrees over time. The maps were therefore not accurate before scanning. Secondly, different generations of maps will have used different surveying methods and different spatial referencing systems. The same geographical object will not necessarily be in the same spatial location on subsequent editions. Thirdly, we are discussing maps, not plans. There will be cartographic generalisations which will affect the spatial representation and location of geographic objects. Finally, the georectification was not done in BGS but by the company from whom we purchased the maps. The company no longer exists. We do not know the methodology used for georectification.

This version of The Digital Chart of the World (DCW) is an Environmental Systems Research Institute, Inc. (ESRI) product originally developed for the US Defense Mapping Agency (DMA) using DMA data. This data was downloaded from the Penn State web site and then converted to Shapefile format using ArcMap. This dataset is derived from the Vector Map (VMap) Level 0 database; the third edition of the Digital Chart of the World. The second edition was a limited release item published 1995 09. The product is dual named to show its lineage to the original DCW, published in 1992, while positioning the revised product within a broader emerging-family of VMap products. VMap Level 0 is a comprehensive 1:1,000,000 scale vector basemap of the world. It consists of cartographic, attribute, and textual data stored on compact disc read only memory (CD-ROM). The primary source for the database is the National Imagery and Mapping Agency's (NIMA) Operational Navigation Chart (ONC) series. This is the largest scale unclassified map series in existence that provides consistent, continuous global coverage of essential basemap features. The database contains more than 1,900 megabytes of vector data and is organized into 10 thematic layers. The data includes major road and rail networks, major hydrological drainage systems, major utility networks (cross-country pipelines and communication lines), all major airports, elevation contours (1000 foot (ft), with 500ft and 250ft supplemental contours), coastlines, international boundaries and populated places.

The Historic Environment Opportunity Map for New Woodland dataset identifies areas in England that may be suitable for new woodland, based solely on available Historic Environment data. The dataset categorises land by different opportunity ratings to reflect the potential suitability of land for woodland creation while acknowledging areas of uncertainty due to data availability.

The purpose of this dataset is to guide landowners, planners, and decision-makers in considering woodland creation from a historic environment perspective. It should be noted that this dataset only considers the Historic Environment and therefore the opportunity ratings do not guarantee or preclude approval for woodland creation proposals.

As any forestry proposal could have the potential to affect the Historic Environment you should contact your local historic environment service. The local historic environment service can provide further data to support woodland creation proposals.

NHLE is the official, up to date register of all nationally protected historic buildings and sites in England.

SHINE is a single, nationally consistent dataset of non-designated historic and archaeological features from across England that could benefit from land management schemes.

The opportunity ratings are as defined:

· Favourable - Areas deemed suitable for new woodland on consideration of available Historic Environment data.

· Neutral - Areas deemed neither favourable nor unfavourable for new woodland on consideration of available Historic Environment data. Proposals in these areas will require additional consideration of the Historic Environment on a case-by-case basis.

· Unclassified - Areas, where SHINE data has been supplied, with no assigned opportunity rating. This illustrates a current absence of recorded data from a Historic Environment perspective. However, as SHINE data is included in the dataset for this area, a degree of confidence may be inferred when considering the absence of historic environment features.

· Unclassified (No SHINE supplied) - Areas, where SHINE data has not been supplied, with no assigned opportunity rating. This illustrates a current absence of recorded data from a Historic Environment perspective.

· Unsuitable - Areas deemed unsuitable for new woodland on consideration of available Historic Environment data.

Unclassified areas may be suitable or unsuitable for new woodland. To better understand these areas, contact the local historic environment service in accordance with the UKFS and Historic Environment Guidance for Forestry in England - GOV.UK

The datasets included in each opportunity rating are as follows:

Favourable

· Lost Historic Woodlands (ArchAI/Forestry Commission) – An A.I. dataset that identifies areas of woodland depicted on early 20th Century Ordnance Survey mapping which have since been lost.

Neutral

· Historic Parklands (Zulu Ecosystems) – an A.I. dataset that identifies areas of parkland depicted on early 20th Century Ordnance Survey mapping.

· World Heritage Site Core data (Historic England) – Core areas of World Heritage Sites, as designated by UNESCO.

· World Heritage Site Buffer (Historic England) – Buffer zones surrounding World Heritage Sites, as designated by UNESCO.

· Ridge and Furrow (Low) (ArchAI) – an A.I. dataset that identifies areas of less well-preserved historic ridge and furrow derived from LiDAR data.

Unclassified

· HER Boundaries (SHINE supplied) – Geographic areas covered by local historic environment services, where SHINE data has been supplied to the Forestry Commission.

· HER Boundaries (No SHINE supplied) - Geographic areas covered by local historic environment services where SHINE data has not been supplied to the Forestry Commission.

Unsuitable

· Historic Landscape Characterisation (HLC) (local historic environment services) – regional datasets that provide information on the historic character of the landscape.

· Scheduled Monuments (Historic England) – Protected archaeological sites of national importance.

· Scheduled Monuments Buffer – A 20 metre buffer surrounding Scheduled Monuments in-line with UKFS.

· Selected Heritage Inventory for Natural England (SHINE)(local historic environment services) – National dataset of non-designated heritage assets.

· Registered Parks and Gardens (Historic England) – Parks and Gardens designated as being of national significance.

· Registered Battlefields (Historic England) – Battlefields designated as being of national significance.

· Ridge and Furrow (High) (ArchAI) – an A.I. dataset that identifies areas of well-preserved historic ridge and furrow derived from LiDAR data.

The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets supplied by the Regional Centers, as sparse grids, i.e. only grid cells that contain data were populated, were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA.

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

Dataset info

The dataset contains Local Authority Boundaries for Great Britain (England, Scotland and Wales) as of December 2021. A total of 363 Local Authority objects are included. Created for future use in folium choropleth maps when combined with other datasets that contain the matching Local Authority Codes. Additionally, subsets were created for convenience holding the boundaries of local authorities in England and Wales together, and in each individual country, i.e., England, Scotland and Wales on their own.

Methodology

The original dataset was downloaded from ONS. Since the dataset was too large for most use cases (129.4MB) due to the level of detail, it was simplified with https://mapshaper.org/ using the default method (Visvalingam / weighted area) with 'prevent shape removal' enabled. The simplification was set to 1.4%, followed by intersection repair and export back to geojson. The shape coordinates were originally in British National Grid (BNG) format, which had to be converted to WGS84 (latitude and longitude) format. Finally, the coordinates were rounded to 6 decimal places, resulting in a file containing 2.2MB of uncompressed data with a sensible level of detail. The individual country data were extracted, based on the LAD21CD property, to create the additional files.

Licence

https://www.ons.gov.uk/methodology/geography/licences

Digital boundary products and reference maps are supplied under the Open Government Licence. You must use the following copyright statements when you reproduce or use this material:

• Source: Office for National Statistics licensed under the Open Government Licence v.3.0
• Contains OS data © Crown copyright and database right 2023

This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometre or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. This map was produced through a collaboration between MAP (University of Oxford), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands.The underlying datasets used to produce the map include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a "friction surface"; a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. Least-cost-path algorithms (running in Google Earth Engine and, for high-latitude areas, in R) were used in conjunction with this friction surface to calculate the time of travel from all locations to the nearest (in time) city. The cities dataset used is the high-density-cover product created by the Global Human Settlement Project. Each pixel in the resultant accessibility map thus represents the modelled shortest time from that location to a city. Authors: D.J. Weiss, A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. A global map of travel time to cities to assess inequalities in accessibility in 2015. (2018). Nature. doi:10.1038/nature25181

Processing notes: Data were processed from numerous sources including OpenStreetMap, Google Maps, Land Cover mapping, and others, to generate a global friction surface of average land-based travel speed. This accessibility surface was then derived from that friction surface via a least-cost-path algorithm finding at each location the closest point from global databases of population centres and densely-populated areas. Please see the associated publication for full details of the processing.

Source: https://map.ox.ac.uk/research-project/accessibility_to_cities/

This data set contains Global maps of five ecosystem services using 6 different among-model ensemble approaches: the provisioning services of water supply, biomass for fuelwood and forage production, the regulating service Carbon Storage for CO2 retention and the cultural non-material service Recreation. For water, the data comes as one shapefile with polygons per watershed, each polygon containing seven ensemble estimates. The other services – recreation, carbon storage, biomass for fuelwood and forage production – come as seven tiff- maps at a 1-km2 resolution with associated world files for each tiff-map contains 43,200 x 18,600 pixels for one ensemble approach, with LZW compressed file sizes between 400MB and 950MB. For all maps, 600dpi jpg depictions are added to the supporting information with uniform colour scaling set for the median ensemble per service. Ensemble output maps were calculated with different approaches following the supporting documentation and associated publication. Uncertainty estimates for these services are included as variation among contributing model outputs and among the employed ensemble approaches. The work was completed under the ‘EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models’ project (NE/T00391X/1) funded by the UKRI Landscape Decisions programme, with additional funding from ES/R009279/1 (MobilES) & ES/T007877/1 (RUST).

Intellectual property of A Song of Ice and Fire, this map and all locations copyright George RR Martin (www.georgerrmartin.com).

Map of Westeros (original version) created originally by Tear of the Cartographer's Guild (http://www.cartographersguild.com/showthread.php?t=6683), updated and extended by theMountainGoat (http://www.sermountaingoat.co.uk/map/index.php) in 2012: Updates to Westeros, addition of Essos, Sothoryos, Ibben and the Summer Isles based in part upon the speculative world map drawn by Werthead (www.thewertzone.blogspot.com). Some locations positioned according to the maps drawn by Other-in-Law.

These GIS-map-files are based on this work and are created by cadaei in QGIS 2.8.

The scale is of course not exact, as it is not clear what projection the original map used and on what kind of planet the map is located. I placed the continents roughly on the place of the coordinates of Africa to minimize the distortion near the poles. The scale is slightly too small (the Wall is only 240 miles long), so don't use the map for distance measuring. It's thought to provide the vector-geometry and labels of the world of a Song of Ice and Fire.

Locations have a field 'confirmed' which is '1' for confirmed locations and '0' for locations with speculative location.

The Areas outside the polygons of the file officialMapAreas.shp are the parts of the map which are not official and based on assumptions (see http://www.sermountaingoat.co.uk/map/index.php for more info about how theMountainGoat created these areas) and can be outdated.

Credits

Original Data

Foto von mauRÍCIO SANTOS auf Unsplash

Data from the British Geological Survey's GeoIndex Map products theme are made available for viewing here. GeoIndex is a website that allows users to search for information about BGS data collections covering the UK and other areas world wide. Access is free, the interface is easy to use, and it has been developed to enable users to check coverage of different types of data and find out some background information about the data. More detailed information can be obtained by further enquiry via the web site: www.bgs.ac.uk/geoindex.

ESYS plc and the Department of Geomatic Engineering at University College London (UCL) have been funded by the British National Space Centre (BNSC) to develop a web GIS service to serve geographic data derived from remote sensing datasets. Funding was provided as part of the BNSC International Co-operation Programme 2 (ICP-2).

Particular aims of the project were to:

1. use Open Geospatial Consortium (OGC, recently renamed from the OpenGIS Consortium) technologies for map and data serving;

2. serve datasets for Europe and Africa, particularly Landsat TM and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data;

3. provide a website giving access to the served data;

4. provide software scripts, etc., and a document reporting the data processing and software set-up methods developed during the project.

ICEDS was inspired in particular by the Committee on Earth Observing Satellites (CEOS) CEOS Landsat and SRTM Project (CLASP) proposal. An express intention of ICEDS (aim 4 in the list above) was therefore that the solution developed by ESYS and UCL should be redistributable, for example, to other CEOS members. This was taken to mean not only software scripts but also the methods developed by the project team to prepare the data and set up the server. In order to be compatible with aim 4, it was also felt that the use of Open Source, or at least 'free-of-cost' software for the Web GIS serving was an essential component. After an initial survey of the Web GIS packages available at the time , the ICEDS team decided to use the Deegree package, a free software initiative founded by the GIS and Remote Sensing unit of the Department of Geography, University of Bonn , and lat/lon . However the Red Spider web mapping software suite was also provided by IONIC Software - this is a commercial web mapping package but was provided pro bono by IONIC for this project and has been used in parallel to investigate the possibilities and limitations opened up by using a commercial package.

http://iceds.ge.ucl.ac.uk/

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community.

This dataset contains a map of a ecosystem.

This map depicts the 825 terrestrial ecoregions of the globe. Ecoregions are relatively large units of land contain ing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. This comprehensive, global map provides a useful framework for conducting biogeographical or macroecological research, for identifying areas of outstanding biodiversity and conse rvation priority, for assessing the representation and gaps in conservation efforts worldwide, and for communicating the global distribution of natural communities on earth.

CREATOR: Moxon, Joseph, 1627-1691IMPRINT: [London] DATE CREATED: [1711] TYPE OF RESOURCE: Cartographic GENRE: Map Digital maps Early maps Separate map EXTENT: 21.9 x 43.4 cm, 32.3 x 46.1 cm including border. MAP DATA: [ca. 1: 60,000,000] ; (W 180° --E 180°/N 85° --S 85°) STATE 1: As above, without Pennsylvania noted. STATE 2: With Pennsylvania marked and labeled as 57. New Spain is noted on the mainland as 61. List of numbered locations includes: Europa, 1-25 and xxx; Asia, 26-44 and xx; Africa, 45-55 and x; and America, 56-78. Issued in: The Book of common prayer / Printed by Charles Bill, and the Executrix of Thomas Newcombe. -- London, 1711. REFERENCES: Shirley 457 (Plate 339); Clancy BXIII, 106. STATEMENT OF RESPONSIBILITY: By J. Moxon, Hydrographer to the Kings most Excellent Majesty. PUBLICATIONS: Issued in: Sacred Geographie, or, Scriptural Mapps... . London, 1671. NOTE: California with a flat northern coast and with a large area jutting off the top left-hand side of the island. The island is named but has no place names. Dedication: To the most Reverend Father in God Gilbert Lord Arch Bishop of Canterbury. His Grace Primate of all England and Metropolitan This Map is humbly Dedicated by Joseph Moxon. (Note: Gilbert Sheldon was the Archbishop of Canterbury from 1663 to 1677.) Map surrounded by scenes from the Bible. Eden is prominently note on the Euphrates. Noah’s son Japhet is named on the North American continent, that part of the earth having been given to him. Includes a key to the numbered locations. Printed for binding into Bibles along with five other maps of Biblical interest. COLLECTION: The Glen McLaughlin Map Collection of California as an Island SUBJECT: World > Maps California as an island > Maps POST PUBLICATION MAP NUMBER: 1032 POST PUBLICATION MAP NUMBER WITH LATEST STATE INFORMATION: 1032-02https://exhibits.stanford.edu/california-as-an-island/catalog/ws505mf2722

This data results from the NRSC's ongoing 1:25000 UK Aerial Photography Programme; a project designed to maintain an up to date aerial coverage of the United Kingdom, covering the complete area at least every 5 years.

The Orthoview product has been generated from vertical aerial photographs. The photographs have been orthorectified (to correct for distortion towards their edges) then mosaiced to provide a seamless dataset for the UK at a 0.5 metre resolution. This allows imagery for any area of interest to be generated without issues associated with scenes falling across multiple photographs.

In addition to its prime application in photogrammetric mapping (from updating and contouring existing maps to preparing large scale engineering plans), the data is used for environmental studies, general planning, land use and land capability, soils, pollution, forestry, mining and quarrying, housing and leisure development, agriculture, geology, water, transport and civil engineering, boundary disputes, public enquiries, etc.

The data is stored in digital form and can be supplied on either Exabyte, CD-ROM or CCT. Various hard copy forms can also be generated, including posters and photographic positives/negatives. Price lists and further information are available from the National Remote Sensing Centre (NRSC).

Note: All photography is flown to RICS Specification for Aerial Photography Issue III, see references.

This dataset shows the global distribution of coral reefs in tropical and subtropical regions. It is the most comprehensive global dataset of warm-water coral reefs to date, acting as a foundation baseline map for future, more detailed, work. This dataset was compiled from a number of sources by UNEP World Conservation Monitoring Centre (UNEP-WCMC) and the WorldFish Centre, in collaboration with WRI (World Resources Institute) and TNC (The Nature Conservancy). Data sources include the Millennium Coral Reef Mapping Project (IMaRS-USF and IRD 2005, IMaRS-USF 2005) and the World Atlas of Coral Reefs (Spalding et al. 2001).

Citation: UNEP-WCMC, WorldFish Centre, WRI, TNC (2018). Global distribution of warm-water coral reefs, compiled from multiple sources including the Millennium Coral Reef Mapping Project. Version 4.0. Includes contributions from IMaRS-USF and IRD (2005), IMaRS-USF (2005) and Spalding et al. (2001). Cambridge (UK): UN Environment World Conservation Monitoring Centre. URL: http://data.unep-wcmc.org/datasets/1

Citations for the separate entities: IMaRS-USF (Institute for Marine Remote Sensing-University of South Florida) (2005). Millennium Coral Reef Mapping Project. Unvalidated maps. These maps are unendorsed by IRD, but were further interpreted by UNEP World Conservation Monitoring Centre. Cambridge (UK): UNEP World Conservation Monitoring Centre

IMaRS-USF, IRD (Institut de Recherche pour le Developpement) (2005). Millennium Coral Reef Mapping Project. Validated maps. Cambridge (UK): UNEP World Conservation Monitoring Centre

Spalding MD, Ravilious C, Green EP (2001). World Atlas of Coral Reefs. Berkeley (California, USA): The University of California Press. 436 pp.

The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

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.

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.