Google Earth Science and KML

The unattributed claim that 80% of all information has a geographical component (Hart and Dolbear 2007) can only encourage the emergence of a geospatial web. The development of geo-browsers and 3D Earth viewers in recent years is evidence of how our inherent spatial awareness can be harnessed to provide improved modes of information retrieval and communication. The value of a geospatially-enabled Web to the geoscience community is immense. Geologists operate in a scientific realm that requires an appreciation of the 3D geometry of the Earth, as well as the temporal component associated with geological processes. The ability to access a spectrum of geological information for specific locations at a range of scales and perspectives represents a potential paradigm shift in accessing geological information. Geo-browsers such as Google Earth serve as excellent Earth observation applications and resources, providing free access to satellite imagery and 3D topographic data of the entire planet. Similar to GIS applications, 3D Earth viewers have become a standard feature on the desktops of geologists throughout the globe. Mike Goodchild of the University of California, Santa Barbara remarked, "Just as the PC democratized computing, so systems like Google Earth will democratize GIS" (Butler 2006a).

The use of Google Earth for scientific visualization has been widely documented in recent literature (Biever 2005; Lubick 2005; Brodersen 2006; Dunne and Sutton 2006; Gramling 2007). Lisle (2006) provides a comprehensive insight into the use of Google Earth as a geological visualization tool. Dunne and Sutton (2006) demonstrate how large-scale multi-beam imagery datasets can be integrated into Google Earth using a combination of KML and OpenGIS WMS (Web Map Service) technologies. Beck (2006), Allen (2007) and Patterson (2007) examine the application of Google Earth for student instruction and geoscience education. The potential of Google Earth for geoscientific visualization is notable from the emergence of dedicated geological conference sessions dedicated to the use of Google Earth and other 3D earth viewers. The use of Google Earth for scientific visualization outside of the Earth science domain is widely appreciated and equally well documented (see Boulos 2005; Duindam 2006; Stanger 2006; Butler 2006b).

A principal advantage of using Google Earth for geoscientific visualization is the ability to add customized geospatial content to the application using KML. KML is an Extensible Markup Language (XML) dialect (World Wide Web Consortium 2008). KML files can be created ‘internally’ using the Google Earth application, or ‘externally’ using any standard XML or text editor. KML files containing text, imagery and 3D models can be compressed to KMZ (zipped KML) files. 3D modelling software applications such as SketchUp™ and GIS software with KML export functionalities provide additional methods in generating content for Google Earth. This compression functionality allows multiple file-formats (e.g. KML, PNG, DAE) to be merged into one KMZ file, allowing for efficient distribution of KML content via email, Intranet, or served on the World Wide Web. In addition, KML files can be viewed in Google Maps™ in 2D.

Generation of the Geochemical Maps

The use of GIS for the geostatistical interpolation of radioelement data is well documented throughout scientific literature (Kemski et al. 2001; Rybach et al. 2002; Lech et al. 2003; Tourliere et al. 2003; Lima et al. 2005; Ruffell et al. 2006). The production of a smooth geostatistical map derived from irregularly spaced survey data involves the interpolation of the original data onto a mesh of values at regularly spaced intervals (IAEA 2003). Lech et al. (2003) employed an IDW interpolation gridding method to investigate variations in uranium abundances in granites. Rybach et al. (2002) examined the spatial distribution of radiation exposure of the population in Switzerland using GIS, based on data sources that included terrestrial gamma-ray spectrometry. Lima et al. (2005) compiled a series of radioactivity and U, Th and K geochemical maps and demonstrated a close relationship between the individual lithologies and radioelement concentrations. Other studies of radioelement concentrations in Ireland include the work of Hadley et al. (2000), who used gamma-ray spectrometry to study structural relations in the Dalradian rocks of Donegal, northwest Ireland.

Owing to the irregular spacing of the spectrometric data, an IDW interpolation technique was deemed a suitable interpolation method for this study. IDW interpolation estimates grid cell values by averaging the values of sample data points in the vicinity of each cell. The closer a point is to the centre of the cell being estimated, the more influence, or weight, it has in the averaging process. IDW interpolation is suited for geochemical mapping because it fits the source data accurately and preserves local anomalies in the interpolation grid (Robinson and Ayotte 2006). IDW interpolation, based on the method developed by Shepard (1968), is a widely used interpolation technique used by earth scientists (Ware et al. 1991). The resultant IDW grids were generated at a cell size of 50 m.

The raw survey data (Appendix 2, Madden, 1987) was digitized using optical character recognition (OCR) software, and georeferenced using MapInfo GIS software. The original dataset was tied to the Irish National Grid (ING) and all data processing was carried out in the ING coordinate system. The dataset comprises of measurements pertaining to radiogenic heat production throughout the batholith. Heat production values (A) were calculated using an equation adapted from that of Drury and Lewis (1983), using the relationship A = (0.0963 cU + 0.0264 cTh + 0.0358 cK)ρ; where ρ is rock density in Mgm-3, c denotes radioelement concentration in Wkg-1 and A = heat production in μW/m3.

Variations in the geochemistry within the individual granite bodies were investigated by applying geological boundary limits to the gridding process. A separate IDW interpolation process was carried out on each of the individual granite units of the Galway Batholith (Figure 2). Using a default MapInfo grid generation option, the boundary of each granite unit was used to clip each grid for that associated granite body. Processing each lithological unit independently prevented adjacent lithologies with distinctly different chemistries from influencing the final interpolation process. This method is reliant on there being an adequate density of survey points within each geological unit. The same IDW gridding parameters were used for all granite units, with the exception of the Lough Fadda Granite (Table 1). A smaller search radius was necessary for the Lough Fadda Granite, owing to the significantly smaller outcrop area of this granite body relative to all other granite units. The density of survey stations (Figure 3) is variable over the study area and this factor must be taken into consideration when interpreting the maps. Regions of low sample density generally correspond to areas of little or no exposure (mainly heathland and wetland). Areas lying outside of the search range of a survey station appear grey in the interpolated maps.

Table 1. IDW interpolation parameters used for radioelement maps.

  Cell size Search Radius Exponent
Lough Fadda Granite 0.05km 0.8km 2
All other granite units 0.05km 2.0km 2

The resultant maps provide an indication of the geochemistry for each specific lithological unit. The final geochemical raster grids were projected in the WGS84 reference system, in accordance with the coordinate system used in Google Earth, and formatted as a PNG image file, enabling transparency for regions outside of the study area.

A super-overlay is used to load the geochemical maps at different resolutions, depending on the zoom level. Owing to the distribution of the survey stations, a cell size of 50m is used. A zoom-level limit was placed on the geochemical KML files so as to avoid over-pixilation and loss of detail. When the viewer zooms in too closely, the map is no longer displayed. This is a standard feature in Google Maps.

Visualization of Geochemical Maps in Google Earth

Four maps were generated from the spectrometry assay data ("Google Earth" file). The geochemical maps are displayed in Google Earth using the <GroundOverlay> KML element. The set of maps are listed as features in the Places panel in the Google Earth sidebar. Users can switch between the various maps using radio button controls. The radio button function is configured in KML using the <ListStyle> tag. The <radioFolder> option, used within the <listItemType> tag allows only one item within a specific folder' to be activated at a time. The transparency of each map can be altered, allowing the maps to be interrogated in respect of the batholith geological bedrock map provided as an image overlay. When activated, the associated legend for each map is displayed on the left side of the 3D viewer using the <ScreenOverlay> KML tag.

Building the 4D Emplacement Models

The 4D schematic model of the emplacement of the Connemara granites employs the Google Earth time-slider control, available in Google Earth version 4 or greater. Spatial surface coverage of the granite bodies was extracted from Geological Survey of Ireland 1:100000 scale Sheet 10 (Long and McConnell 1995) and Sheet 14 (Pracht et al. 2005). A KML file for each granite body was generated using ArcGIS™ and Shape2Earth™ software, using the <PolyStyle> KML element. Each KML file was extruded by a value of 500 m and projected in WGS84 projection system, conformable with the projection system used in Google Earth. Extrusion of the polygons provides a discernible footprint of each granite body. The ages of emplacement are represented by units of years before the Common Era (BCE). BCE is the default abbreviation used in Google Earth. In an attempt to adhere to standard geological time notation, we configure the temporal models such that one Google Earth year represents one million years (e.g. 430 BCE ≈ 430 Ma). A KML file was generated for each of the 3D granite models. These KML files can be considered as the child files that are accessed from the parent KML file using the <Link> element, with each <Link> element nested within a KML <Folder> tag. As the parent of the <Link> element is the <NetworkLink> tag, the <href> (hypertext reference) is a KML file. The <href> can be a locally specified file or an remote URL (Google 2007). The example below shows the syntax used to activate the CMG model in the parent KML file.

                        <name>Costelloe Murvey Granite</name>
                                <Snippet maxLines="0"></Snippet>

The granite emplacement events are configured in each KML file using the <TimeSpan> tag, with the KML elements <begin> and <end> used to define the dates of emplacement for each of the various Connemara granite units.


To allow the animation to run for a brief introductory time period before the first granite body is emplaced, a <TimeSpan> tag is used within a <ScreenOverlay> tag. This feature enables the animation to commence at 488 Ma, whereby a legend is displayed in the viewer, prior to the emplacement of the Oughterard Granite at 463 Ma, and the subsequent emplacement events thereafter.