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Hi Ben & Jon & all, interesting to notice that your community requires coverage types beyond what's listed in ISO 19123. This nicely coincides with the general feeling that ISO 19123 (== OGC Abstract Spec Topic 6) deserves an update - we might bring in your types on that occasion. The best way for this probably would be if someone wrote a change request to add a section about this your new coverage type. The WCS group certainly is more than open to have a close look at such a description. -Peter Ben Domenico wrote:
Hi Jon, Feature/coverage is a distinction I've struggled with for some time. George has pointed to one of the documents that I have found most helpful in terms of a general conceptual definition of a coverage --the ISO 19123 document which is also an OGC spec as George points out.http://portal.opengeospatial.org/files/?artifact_id=19820 It defines things from a mathematical point of view in terms of what I used to think of as the independent variables (domain) and dependent variables (range). One area where ISO 19123 is a bit weak from the metoceans perspective is that it has a limited view of "continuous" coverages. Where metoceans models the continuous function space in terms of the equations of fluid dynamics, ISO 19123 does so in terms of strictly geometric equations. Nevertheless the defining concepts are very valuable and the discrete coverage concepts map well into our metoceans data collections. Others may disagree with me on this, but the other documents I find helpful in understanding these feature/coverage concepts are those ofOGC Observations and Measurements.http://www.opengeospatial.org/standards/om In particular they define "features of interest," examples of which might be the Indian Ocean or the atmosphere above London. This sort of feature fits will into metoceans community which models such entities in terms of functions governed by the equations of fluid dynamics. Moreover, many of our observational data collections and forecast model outputs are really just samplings of the value of those functions at discrete points in space and time. O & M uses the concept of "sampling features" for that sort of dataset. For me the sampling feature is very helpful for developing an understanding from the user point of view. The sampling features are generally categorized by dimensionality: point (a station observation), curve (a vertical sounding), surface (satellite image), solid (forecast model output). One other useful element of the O & M framework is that it explicitly deals with collections of data. For example a collection of measurements and sounding profiles from observing stations can itself be considered a sampling feature. And such a collection is a sampling feature that fits into the coverage category just as the satellite image and forecast model output do. So such collections are considered coverages even though the spatiotemporal points are not regularly spaced. In the case of observing stations, the locations have to be specified in a table rather than by an algorithm. In the case of observations from ground-based radars, the locations are defined by a table of stations and an algorithm describing the scanning geometry. Many of our metoceans datasets are just such collections. But the key point is that, in the world of ISO 19123 and OGC O & M, these data collections are indeed coverages. Enough for now, but these documents are relatively easy to read and are very helpful at the conceptual level. -- Ben
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