These are the results obtained from an empirical test looking at the communicative effectiveness between two types of two dimensional (2D) map formats (Choropleth maps, and Cartograms) of the Greater London area of the United Kingdom. Participants were interviewed and observed individually during the procedure. The results contain the recorded measurements of spatial accuracy, and the time taken for each participant to answers 3 test questions. A post-test qualitative reaction of each participants' preference between the two map types is recorded, along with their gender, age, visual impediments, and self-assessed map reading ability.

The map presented in this paper shows the effect of congestion on daily accessibility in the London metropolitan area on Wednesdays. Because of its dynamic nature, it is challenging to both calculate the effects of this phenomenon and to represent it clearly on simple maps. Although we can use many traditional techniques for this purpose, they are usually static, and they may lose some essential information on the effects studied. In this paper, we used two cartographic techniques rarely used in accessibility studies – cartograms and 3D maps, which we believe can achieve a more striking representation in static and animations of both the traffic-induced spatial distortion and the accessibility levels obtained. The results are presented in two animated maps and some snapshots of them – static maps. Both types of maps reinforce each other: Together, they can properly show the direct space–time link between congestion and accessibility, and can, therefore, give a more detailed overview of the consequences of this phenomenon.

Historical road networks in Europe: Shapefiles including the correct geometry and speed of the European road networks from 1960.

Methodological description and application in:

• Condeço-Melhorado, A. M., Christidis, P., Dijkstra, L. (2015). Travel speed changes along the European core road network for the period 1960–2030: An application of octilinear cartograms. Journal of Maps, (November), 1–4. doi:10.1080/17445647.2015.1088482

Three classes of roads (1,2,3), class 1 being highways. Six time periods: 2012, 2000, 1990, 1980, 1970 and 1955

Field NCLASS_xxx is the class of the road in each year (last xxx digits)

Travel time is the time (in minutes) to travel the distance (shape_length, in meters) at the speed of the class the road has in 2012.

A pseudo-geographic representation of New Zealand's Territorial Authority administrative areas that gives each area an equal visual weighting. This dataset helps map users visualise data for areas irrespective of their geographic size. In traditional geographic maps, small areas can be overshadowed by larger areas even if their values are equivalent.

Each hexagon represents a Territorial Authority or Auckland Local Board. All Territorial Authority Local Board (TALB) hexagons are the same size irrespective of the geographic size of the TALB. A TALB's hexagon is placed in a position which approximates its actual geographic location in relation to its neighbouring TALBs. In this cartogram the Auckland local boards have been separated from the rest of the country.

TALB is a combined classification of territorial authorities for New Zealand and local boards for Auckland Council. The TALB hexagon cartogram uses TALB2013_V1_00, the definitive set of territorial authority and local board boundaries for 2013 as defined by Stats NZ, as at 1 January 2013. This version contains 21 local boards in the Auckland Council.

This article describes a methodology for mapping the level of household car ownership for the island of Great Britain, using data from five population Censuses. The basic units of display are ‘Tracts’, which are aggregations of local municipality electoral wards that were in place for each of the three Censuses conducted in 1981, 1991 and 2001. In addition, this article documents the utility of these Tracts to represent a consistent geography across two additional Censuses, those of 1971 and 2011. This analysis enables a consistent and complete picture of changes in car ownership over a 40-year period to be visualised as both geographical maps and cartograms of Great Britain. The advantages and disadvantages of each type of representation are discussed. The paper finishes by providing evidence of a downward trend in car ownership in central London and increasing spatial homogeneity in car ownership through time.

Map of the pH. The data come from the soil analysis results of the 2200 sites of the Soil Quality Measurement Network, during the first sampling campaign.

The Geospatial Analytics Market size was valued at USD 79.06 USD billion in 2023 and is projected to reach USD 202.74 USD billion by 2032, exhibiting a CAGR of 14.4 % during the forecast period. The growing adoption of location-based technologies and the increasing need for data-driven decision-making in various industries are key factors driving market growth. Geospatial analytics captures, produces and displays GIS (geographic information system)-maps and pictures that may be weather maps, GPS or satellite photos. The geospatial analysis as a tool works with state of art technology in every formats namely; the GPS, sensors that locates, social media, mobile devices, multi of the satellite imagery to produce data visualizations that are facilitating trend-finding in complex relations between people and places as well are the situations' understanding. Visualizations are depicted through the use of maps, graphs, figures, and cartograms that illustrate the entire historical picture as well as a current changing trend. This is why the forecast becomes more confident and the situation is anticipated better. Recent developments include: February 2024: Placer.ai and Esri, a Geographic Information System (GIS) technology provider, partnered to empower customers with enhanced analytics capabilities, integrating consumer behavior analysis. Additionally, the agreement will foster collaborations to unlock further features by synergizing our respective product offerings., December 2023: CKS and Esri India Technologies Pvt Ltd teamed up to introduce the 'MMGEIS' program, focusing on students from 8th grade to undergraduates, to position India as a global leader in geospatial technology through skill development and innovation., December 2023: In collaboration with Bayanat, the UAE Space Agency revealed the initiation of the operational phase of the Geospatial Analytics Platform during its participation in organizing the Space at COP28 initiatives., November 2023: USAID unveiled its inaugural Geospatial Strategy, designed to harness geospatial data and technology for more targeted international program delivery. The strategy foresees a future where geographic methods enhance the effectiveness of USAID's efforts by pinpointing development needs, monitoring program implementation, and evaluating outcomes based on location., May 2023: TomTom International BV, a geolocation technology specialist, expanded its partnership with Alteryx, Inc. Through this partnership, Alteryx will use TomTom’s Maps APIs and location data to integrate spatial data into Alteryx’s products and location insights packages, such as Alteryx Designer., May 2023: Oracle Corporation announced the launch of Oracle Spatial Studio 23.1, available in the Oracle Cloud Infrastructure (OCI) marketplace and for on-premises deployment. Users can browse, explore, and analyze geographic data stored in and managed by Oracle using a no-code mapping tool., May 2023: CAPE Analytics, a property intelligence company, announced an enhanced insurance offering by leveraging Google geospatial data. Google’s geospatial data can help CAPE create appropriate solutions for insurance carriers., February 2023: HERE Global B.V. announced a collaboration with Cognizant, an information technology, services, and consulting company, to offer digital customer experience using location data. In this partnership, Cognizant will utilize the HERE location platform’s real-time traffic data, weather, and road attribute data to develop spatial intelligent solutions for its customers., July 2022: Athenium Analytics, a climate risk analytics company, launched a comprehensive tornado data set on the Esri ArcGIS Marketplace. This offering, which included the last 25 years of tornado insights from Athenium Analytics, would extend its Bronze partner relationship with Esri. . Key drivers for this market are: Advancements in Technologies to Fuel Market Growth. Potential restraints include: Lack of Standardization Coupled with Shortage of Skilled Workforce to Limit Market Growth. Notable trends are: Rise of Web-based GIS Platforms Will Transform Market.

Map of the contents in total lime. The data come from the soil analysis results of the 2200 sites of the Soil Quality Measurement Network, during the first sampling campaign.

Animated cartogram representing the party with the most votes for all Austrian municipalities and Viennese districts. The cartogram oscillates between a geographically correct representation and a distorted representation in which the size of each municipality corresponds to the number of eligible voters.

This map shows the ecological status (i.e. status or potential) of macrophytes in European lakes (i.e. lakes and reservoirs) potentially impacted by eutrophication. The ecological status class of a country's waterbodies (or stations) is assessed by each country according to their national classification system, following the Water Framework Directive. The assessment may be based by one or more samples measured during the year of reporting. The purpose of this map is to show ecological status of individual biological quality elements (BQEs) and the major impact types. In comparison, the map layer "Ecological status or potential of water bodies" in the WFD Surface Water Viewer (http://www.eea.europa.eu/themes/water/interactive/soe-wfd/wfd-surface), displays ecological status or potential based on all BQEs combined, represented by the BQE with the worst class (the "one-out-all-out" principle). Moreover, the maps based on SoE-WISE biological data will be updated yearly, whereas the WFD database will be updated every 6th year. The data on the ecological status (i.e. status or potential) of macrophytes in lakes is displayed in the following 2 layers:• macrophytes in lakes by country • macrophytes in lakes by stationLayer: Macrophytes in lakes by country displays the ecological status of macrophytes in lakes as classified cartograms , showing the distribution of status classes per country as one bar chart for each country. This can be used to compare the situation in your country with that in other countries. Layer: Macrophytes in lakes by station displays the location of the Eionet-Water lakes stations where macrophytes were monitored. Station points are coloured according to the class of ecological status of macrophytes (as shown in the legend on the left-hand side of the map).The map shows the data provided in 2013 ( = sampled in 2012) or the latest reported year.

Animated cartogram representing the party with the most votes for all Austrian municipalities and Viennese districts. The cartogram oscillates between a geographically correct representation and a distorted representation in which the size of each municipality corresponds to the number of eligible voters.

Map of the contents in Potassium total

A free mapping tool that allows you to create a thematic map of London without any specialist GIS skills or software - all you need is Microsoft Excel. Templates are available for London’s Boroughs and Wards. Full instructions are contained within the spreadsheets.

Borough maps

• Map for quantitative data
• Map for categorical data
• Cartogram that uses squares to represent London Boroughs

Ward maps

Pre-2014 boundaries

• Greater London
• Individual Boroughs: Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Camden, Croydon, Ealing, Enfield, Greenwich, Hackney, Hammersmith and Fulham, Haringey, Harrow, Havering, Hillingdon, Hounslow, Islington, Kensington and Chelsea, Kingston upon Thames, Lambeth, Lewisham, Merton, Newham, Redbridge, Richmond upon Thames, Southwark, Sutton, <a href="https://

This map shows the ecological status (i.e. status or potential) of phytoplankton in European lakes (i.e. lakes and reservoirs) potentially impacted by eutrophication. The ecological status class of a country's waterbodies (or stations) is assessed by each country according to their national classification system, following the Water Framework Directive. The assessment may be based by one or more samples measured during the year of reporting.. The purpose of this map is to show ecological status of individual biological quality elements (BQEs) and the major impact types. In comparison, the map layer "Ecological status or potential of water bodies" in the WFD Surface Water Viewer (http://www.eea.europa.eu/themes/water/interactive/soe-wfd/wfd-surface), displays ecological status or potential based on all BQEs combined, represented by the BQE with the worst class (the "one-out-all-out" principle). Moreover, the maps based on SoE-WISE biological data will be updated yearly, whereas the WFD database will be updated every 6th year. The data on the ecological status (i.e. status or potential) of phytoplankton in lakes is displayed in the following 2 layers:• Phytoplankton in lakes by country • Phytoplankton in lakes by stationLayer: Phytoplankton in lakes by country displays the ecological status of phytoplankton in lakes as classified cartograms , showing the distribution of status classes per country as one bar- chart for each country. This can be used to compare the situation in your country with that in other countries. Layer: Phytoplankton in lakes by station displays the location of the Eionet-Water river stations where phytoplankton was monitored. Station points are coloured according to the class of ecological status of phytoplankton (as shown in the legend on the left-hand side of the map). The map shows the data provided in 2013 ( = sampled in 2012) or the latest reported year.

Map of the assimilable phosphorus contents

A final aggregated vulnerability index was obtained by combining all the partial indices belonging to each of the five vectors with V4 scores multiplied by −1 since Vector 4 indicators are of “resilience” rather than of “vulnerability”. Figures 6a and 6b show respectively map and cartogram of the geographical distribution obtained for this vector. As can be seen, except for most of Ireland, the Atlantic European coast ap- pears in redish colours corresponding to higher values of vulnerability.

This map shows the ecological status (i.e. status or potential) of phytobenthos in European rivers (i.e. rivers and canals) potentially impacted by eutrophication. The ecological status class of a country's waterbodies (or stations) is assessed by each country according to their national classification system, following the Water Framework Directive. The assessment may be based by one or more samples measured during the year of reporting. The purpose of this map is to show ecological status of individual biological quality elements (BQEs) and the major impact types. In comparison, the map layer "Ecological status or potential of water bodies" in the WFD Surface Water Viewer (http://www.eea.europa.eu/themes/water/interactive/soe-wfd/wfd-surface), displays ecological status or potential based on all BQEs combined, represented by the BQE with the worst class (the "one-out-all-out" principle). Moreover, the maps based on SoE-WISE biological data will be updated yearly, whereas the WFD database will be updated every 6th year. The data on the ecological status (i.e. status or potential) of phytobenthos in rivers is displayed in the following 2 layers:• Phytobenthos in rivers by country • Phytobenthos in rivers by stationLayer: Phytobenthos in rivers by country displays the ecological status of phytobenthos in rivers as classified cartograms , showing the distribution of status classes per country as one bar- chart for each country. This can be used to compare the situation in your country with that in other countries. Layer: Phytobenthos in rivers by station displays the location of the Eionet-Water river stations where phytobenthos were monitored. Station points are coloured according to the class of ecological status of phytobenthos (as shown in the legend on the left-hand side of the map). The map shows the data provided in 2013 ( = sampled in 2012) or the latest reported year.