Google Earth has set new standards for visualizing geographical information systems (GIS) data. Great for viewing the worldâ€™s sightseeing spots, your house, or the nearest hotels and restaurants at your business, or, holiday destination. But thatâ€™s a bit limited. The full extent of rich scientific, and other, GIS datasets often cannot yet be easily converted for viewing in Google Earth, because of differences in formats. Speak to anyone at various geographical or scientific databases these days and you often hear the same question: â€œHow can we get our data into Google Earth?â€ New computing tools are now emerging, however, that are changing this situation.
Visualization of geographic and other spatial data has been revolutionized by Google Earth, launched by Google in June. Google Earth sets new standards in effortless and stunning 3-D visualization of spatial datasets, and its fast zoom-and-click Earth browsing capabilities have overnight made the many maps and globes that dot the websites of the worldâ€™s scientific and other agencies seem clunky, slow, and dated.
But visualization is just one aspect of geographical information systems (GIS). Itâ€™s the last, and arguably, one of the easier, steps in a long drawn-out process of collecting, processing, and analyzing data. Without all these stages beforehand, and the complex software needed to achieve them, one wouldnâ€™t have much meaningful data to visualize in the first place. What would be great would be to be able to quickly view and manipulate many large existing GIS spatial datasets, from disaster management to science, in Google Earth.
And thereâ€™s a problem; Google Earth, a mass-market product which deals only with visualization, was never intended as a replacement for GIS software, and lacks all the data analysis aspects. Google Earth also uses a lightweight XML language to represent data, called KML, which can be grasped in an evening.
But most of the vast amounts of GIS data on the planet are in formats that so far have not been straightforward to output in kml. The most popular GIS software is that developed by the industry, ESRI, the Redlands, California, company founded as the Environmental Systems Research Institute in 1969 — there are open source source alternatives, such as Quantum GIS which I’ll discuss in later posts. Its formats, including the humble ‘shapefile,’ have become the de facto standards for GIS data worldwide. A shapefile, for example, defines spatial information and data tables, and is composed of the following main filetypes:
â€¢ .shp â€“ the feature geometry.
â€¢ .shx – the index of feature geometry.
â€¢ .dbf â€“ database file of the attribute data of features.
â€¢ .sbn and .sbx – spatial index of features.
â€¢ .prj – coordinate system information.
Shapefiles are one of the most common formats used by scientists and other GIS users for working with spatial data. But so far it has not been easy to convert a shapefile to the kml needed for Google Earth to plot such data.
Thatâ€™s now changing. A swathe of new tools is now emerging, from the basic to the highly-functional, which allow shapefiles and other formats to be easily converted to kml, and so to be visualized in Google Earth. One of the most functional is Arc2Earth, scheduled for release in January, developed by Brian Flood, president of Spatial Data Logic systems. I’d the pleasure of evaluating a pre-release version of this, and used it to convert data from the Global Registry of Migratory Species database.
These tools mark progress, but of course require that you are have ArcGIS. More generic solutions to converting shapefiles to kml have been slower in forthcoming, although some scripts can do part of the job. The open source GIS players have, as far as I can see, also been slow to provide KML export to their products, but correct me if I’m wrong.
Meanwhile ESRI itself is scheduled to release in first quarter 2006 ArcGis Explorer, a free visualization tool, which is being billed by observers as a Google Earth killer, the screenshots, and comments from developers who have given it a tour, suggesting it does all that Google Earth does, but much, much, more — a Google Earth on steroids.
So the new year looks guaranteed to be a rich period for new GIS and visualization tools. One result, no doubt, will be that we will soon be seeing more large and extensive databases online in ways that are easier to view and manipulate.