Fantasy island

A widely reported story, courtesy of the BBC, appeared last week describing the unusual case of Sandy Island, a south Pacific island between Australia and New Caledonia.  Although the island appeared on Google Maps and Google Earth, a research team from Australia were unable to locate it when they went to investigate. Expecting to find a ‘sizeable’ strip of land, the researchers found instead 1,400 m of deep blue sea. In their defence Google commented that they did consult a number of authoritative data sources for their maps, and the island did appear to be a genuine feature.

It seems the island never really existed and was most likely the product of an error that had gone unnoticed and had been perpetuated over the years.  This story touched on a number of issues we discussed in The GIS Guide to Public Domain Data including the use of assertive versus authoritative data sources. What does authoritative really mean and how far should we go to get the definitive answer?  Should we no longer rely solely on the traditional sources of geographic data when it seems even they can’t be guaranteed, and always get a second opinion? Prof. Michael Goodchild (Univ. of California, Santa Barbara) discusses a hybrid solution in a paper entitled ‘Assertion and Authority: The Science of User Generated Geographic Content’  and sees the merits in taking advantage of the expertise and knowledge accumulated by the traditional data providers (national mapping agencies, survey companies and so on) but also taking advantage of independent verification from volunteer groups, research teams and other interested individuals and organisations.

Future developments in data capture and verification will probably mean cases like this should be rare. However given the rate of change in both the physical and man-made environment and the ever-present possibility of mis-interpretation, the  ‘definitive map’ will probably remain an elusive goal.

California Launches New Geodata Portal

One of the themes we discuss in the book The GIS Guide to Public Domain Data is the increasing number of geodata portals that host maps and services from government agencies, from local to global.  While some say that the increased Internet search capabilities are rendering some of these portals obsolete, they remain a very helpful way for data users to access geospatial information.  Web-based data portals began appearing during the 1990s and continue to be created today, as evidenced by the recent announcement of a new data portal for California.  California, though its Cal-Atlas clearinghouse, has been providing geospatial information to the community for many years.  Indeed, it has always been one of the best examples of a state data clearinghouse that is rich in content.

The recent announcement revealed that California launched a new geospatial data portal, http://portal.gis.ca.gov/geoportal/catalog/main/home.page.  I have been experimenting with this new portal and it does contain several new features that I believe data users will appreciate, including the “footprint” on a map indicating the extent of coverage for each layer.  A map viewer also exists, but I was unsuccessful finding many appropriate layers via this method.  The announcement hints that more agencies contribute to the new portal, thus increasing potential content.  I hope that is the case, because for me and many other data users, while better interfaces are certainly welcomed, the most important thing is always the amount of content hosted on the site.  Furthermore, data portals and their searching and browsing capabilities are only as effective as the richness of the metadata that are associated with them.  Like any data portal, this one takes some getting used to, but given the number of agencies using and hosting geospatial data in California, this is a good one to keep an eye on to see what develops.

New California State Data Portal

Global inventory of glaciers

Earlier this year a global inventory of glacier outlines, the “Randolph Glacier Inventory” (RGI), was released. The inventory, a result of international cooperation, provides a comprehensive set of glacier outlines and is based on new and existing published glacier outlines. It provides a supplement to the Global Land Ice Measurements from Space initiative (GLIMS) Glacier Database and, subject to registration and some constraints, is available for download (either the complete inventory or by region).

The inventory identifies 19 different polar regions, categorised into first and second order regions. Data are provided as shapefiles in geographic coordinates (longitude/latitude, in degrees) and are referenced to the WGS84 datum. The shapefiles contain the outlines of glaciers and glacier complexes, a collection of contiguous glaciers that meet at glacier divide, and are organized by first-order region, with one shapefile containing all glaciers for each region.

To provide easy access to the GLIMS Glacier Database, the GLIMS Web Mapping Service (WMS) has also been developed. Several layers in the WMS can be viewed and queried, including  Glacier Outlines, Regional Center Locations, and The World Glacier Inventory.

Maps as representations of reality: The deciduous-coniferous tree “line”

One of the themes running through our book The GIS Guide to Public Domain Data is that maps are representations of reality.  While almost everyone reading this statement is likely to agree with it, in the fast-paced world that GIS analysis and creating maps has become, it is easy to lose sight of this fact when staring at tables, maps, and imagery.  In a recent video, I discuss just one place where care needs to be made in making decisions based on spatial data.  In the video, observe my surroundings as I stand near the traditional “line” that divides the deciduous forest to the south from the coniferous forest to the north in North America. Is the “line” really a line at all, or is it better described as a gradual change from deciduous to coniferous as one travels north?  Is that vector line then better symbolized as a “zone”, or is vegetation better mapped as a raster data set, with each cell representing the percentage of deciduous and coniferous trees?

How many other data sets do we tend to see as having firm boundaries, when the boundaries are not really firm at all in reality?  How does that affect the decisions we make with them?  Even the boundary between wetlands and open water were originally interpreted based on land cover data or a satellite or aerial image.   As we state in the book, even contour lines were often interpreted originally from aerial stereo pairs.  And each data set was collected at a specific scale, with certain equipment and software, at a specific date, and within certain margins of error that the organization established.  Maps are representations of reality.  They are incredibly useful representations to be sure, but care needs to be taken when using this or any abstracted data.