Abstract: Introduced in 2005, Google Maps offers 18 maps of the world at different scales, varying from approximately 1:85 million to 1:4,800 at the equator at a screen resolution of 100 dpi. Each map has been tiled into individual raster squares that are downloaded separately, often from different servers. A typical Google Map might download map tiles from seven or eight different IP addresses, each associated with a different server that could be located in different Google data centers. Subdividing the map into tiles improves the perceived map download time and allows the map to be easily panned. Google Maps also makes use of the Asynchronous JavaScript and XML (AJAX) server/client technology that maintains a constant connection to the map server, a major improvement in server/client performance. Maps and imagery in Google Maps have been projected with the Mercator projection. The limitations of this projection have been well-documented, and its distorted depiction of the world has been a major cause for concern. For example, Greenland is represented as being larger than Africa when, in fact, Africa is 14 times larger than Greenland. Scale varies continuously from the equator to the polar areas. Changes in scale in the Google Maps display can be observed by examining the scale bar when moving north or south from the equator. The change in map scale is particularly noticeable at the extreme latitudes. The distortion caused by the Mercator projection is not noticeable with larger scale maps. In 2006, Google introduced an Application Programming Interface (API) that includes a series of functions that may be invoked by the user. These functions control the appearance of the map, including the scale, position, and any added information in the form of points, lines, or areas. The API makes it possible to incorporate Google Maps on Web sites, and to overlay information from other sources – a process referred to as a “map mashup.” One application of the Google Maps API is the construction of choropleth maps by super-imposing shadings. Current examples include maps of London by the UCL Centre for Advanced Spatial Analysis (CASA) and election result maps by county or state (see Web Resources). The UCL CASA provides Google Map Creator, a freeware application for thematic mapping with Google Maps (see Web Resources). One advantage of choropleth mapping with Google is that the underlying map can remain visible, providing some geographic context to the representation of the data. Normally, thematic maps lack the necessary background map to properly interpret the locational component. While it can be argued that stripping background information may result in the better formation of spatial patterns by the map user, providing more locational information may be viewed as a necessary component for all thematic maps. The purpose here is to demonstrate how choropleth maps can be made with Google Maps.

Abstract: In the beginning of the 19th century, thematic cartography was enriched with subjects related to the human world. In particular, the enthusiasm for statistics put on the foreground several topics drawn from what we would call today “social sciences”: demography, political economics, and moral statistics. In this context, most of the methods of quantitative mapping were invented within a short period, between 1826 and 1850. This article deals with the first and the most popular among these methods, the shaded map, which is credited to the Frenchman Charles Dupin. We explore the circumstances in which it was imagined, and its modes of diffusion in European cartography. Dupin’s shaded map became quickly famous and was imitated by scholars in the field of vital and moral statistics, then of medicine and anthropology. We suggest that these thematic maps were not neutral illustrations, but were primarily conceived as arguments in scientific or ideological debates, and that their sign system played a major role in their persuasive effect.

Abstract: This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for E Social Science programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which makes it possible to view a range of health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern.

Abstract: In this paper we propose a solution to several key limitations of current web based mapping systems: slow rendering speeds and the restriction of online map viewing to a small number of areal units as well as a limited number of users. Our approach is implemented as a Scalable Tile Map Service that distributes dynamic choropleth maps in real-time through a new caching methodology. This new Map Service lays the foundation for advances in web based applications reliant on dynamic map rendering such as emergency management systems and interactive exploratory spatial data analysis. We present the results of an empirical illustration in which this new methodology is used to facilitate collaborative decision making by visualizing spatial outcomes of simulation results on the fly.

Abstract: This paper explores in detail a new and effective metaphor for visualising choropleth map uncertainty. The “level-of-detail” metaphor has been shown here to communicate attribute uncertainty, but also spatial uncertainty as a secondary expression. The metaphor is delivered to the map viewer via the regular tessellated output of the Hexagonal or Rhombus (HoR) quadtree spatial data structure, as a semi-transparent map layer that lies on top of the choropleth (termed the trustree when used in this manner). For testing, multiple images were created with differing resolution levels of output from the trustree and superimposed on a New Zealand 2001 census choropleth map of Dunedin City. An Internet survey was designed and run, to reveal the visual metaphors that the trustree communicates uncertainty through. The choice of metaphor offered was (1) a level of detail (or resolution) metaphor, where less detail (i.e. coarser resolution cells) represents more uncertainty (i.e. uncertainty is sketchy), or (2) a metaphor of clutter, where the data structure output can be sufficiently dense so as to cover spatial information, in effect hiding uncertain areas (i.e. uncertainty is a barrier). In this case the finer resolution cells indicate more uncertainty. Also, the survey aimed to determine a usable trustree tessellation resolution level to express uncertainty information. The results showed the trustree tessellation was more effective when representing a metaphor of detail and that attribute and spatial uncertainty can be effectively expressed, depending on the tessellation level used.

Abstract: A primary function of Environmental Public Health Tracking is the communication of spatial trends of diseases. Traditional (choropleth) approaches to disease mapping}?> have difficulty conveying intuitive understandings of the spatial continuity of disease risk, rate calculations in rural areas, and degrees of statistical significance. A spatial loess function can be utilized to depict continuous variations in preterm birth risk for the state of California on the basis of a 3-year birth cohort. Results from this function were graphically depicted and incorporated into a Web mapping service to maximize public accessibility. The function was evaluated as a tool for communication by considering its intuitive interpretation and comparing information derived from the function with that, which would be derived from a choropleth map using the same data. In general, the loess function was able to generate risk information for a variety of both urban and rural settings. Although richer in detail, this information was mostly consistent with that which would come from choropleth maps. Occasionally, information from the loess function stood in contradiction to the choropleth mapping procedure; however; we enumerate these occasions and discuss ways to maximize the consistency of the loess function with intuitive understandings of disease risk.

Abstract: The use of geobrowsers has increased considerably over the last few years. Thematic mapping has a long history in cartography, but the new geobrowsers (like Google Maps and Earth) tend not to focus on this aspect of geographical information representation. This paper examines how Keyhole Markup Language (KML) can be used for thematic mapping. KML is not targeted towards thematic mapping, but it is possible to use KML elements in ways that were probably not intended. Current possibilities for making proportional symbol maps, chart maps, choropleth maps and animated maps with KML will be presented. These experiments show that KML and geobrowsers offer great potential for thematic mapping, but that there are significant issues that need to be resolved.

Abstract: This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for e Social Science (NCeSS) programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which presents a repository of choropleth maps across a range of domains including health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern.

Abstract: Please click here to download the map associated with this article. The objective of the accompanying map is to show the relation between world poverty, environmental vulnerability and population at risk for natural hazards. Sub-national infant mortality rates are used as proxy for poverty and mapped as a bivariate choropleth map together with national levels of environmental vulnerability. Past density and distribution of natural hazards were mapped on to a textonequarter degree grid and presented as an inset map. An inset map with global population densities is also provided. All maps are in Lambert cylindrical equal-area projection. The main map scale is 1:100 000 000. According to the result from the bivariate mapping of poverty and environmental vulnerability, the world can be stratified into three groups. 1) Regions with low poverty rates and relatively high degree of environmental vulnerability (e.g. Scandinavia, North America). 2) Regions with high levels of poverty and a relatively low d...