Coverage data

A coverage is the digital representation of some spatio-temporal phenomenon. ISO 19123 provides the definition:

Coverages play an important role in geographic information systems, geospatial content and services, GIS data processing, and data sharing.

A coverage is represented by its "domain" (the universe of extent) and a number of range of values representing the coverage's value at each defined location. For example, a satellite image derived from remote sensing might record varying degrees of light pollution. Aerial photography, land cover data, and digital elevation models all provide coverage data. Generally, a coverage can be multi-dimensional, such as 1-D sensor timeseries, 2-D satellite images, 3-D x/y/t image time series or x/y/z geo tomograms, or 4-D x/y/z/t climate and ocean data.

However, coverages are more general than just regularly gridded imagery. The corresponding standards (see below) address regular and irregular grids, point clouds, and general meshes.

An interoperable service definition for navigating, accessing, processing, and aggregation of coverages is provided by the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) suite and Web Coverage Processing Service (WCPS), a spatio-temporal coverage query language.

Standards

Coverages represent digital geospatial information representing space/time-varying phenomena. OGC Abstract Topic 6[1] - which is identical to ISO 19123 - defines an abstract model of coverages. Many implementations are conceivable which all conform to this abstract model while not being interoperable. This abstract coverage model is concretized to the level of interoperability by the OGC standard GML 3.2.1 Application Schema - Coverages[2] (often referred to as GMLCOV) which in turn is based on the Geography Markup Language (GML) 3.2,[3] an XML grammar written in XML Schema for the description of application schemas as well as the transport and storage of geographic information.

The European legal framework for a unified Spatial Data Infrastructure, INSPIRE, in its Annex II and III relies on the OGC definitions of coverages as well, but modifies them in places in a way making them less compatible and interoperable with the OGC standard. For example, components of the coverage concept are selectively recombined into new, different definitions of a coverage.

Coverage model

Formally, in GMLCOV AbstractCoverage is a subtype of AbstractFeature (indicating its close relation). An abstract coverage consists of the following components:

This abstract coverage is refined into several concrete coverage types, which can be instantiated, for example:

Among the special cases which can be modelled by coverages are

Relationship to Features

A coverage is a special kind of geographic feature, with the distinguishing characteristics that other features have one particular value associated (such as a road number, which remains constant over all the road's extent) whereas a coverage typically conveys different values at different locations within its domain. ISO 19109 (2nd Ed.) explains the relationship between features and coverages as follows (clause 7.2.2):

Both viewpoints are required since they each express a fundamental meta-model of the world: as a space populated by things, or as a space within which properties vary. Furthermore, requirements relating to both viewpoints may occur in a single application, typically matching a data-flow: from observation through interpretation, and then elaboration and simulation.[4]

Coverage encoding

Different coverage encodings
Different coverage encodings

The format-independent logical structure of coverages can be mapped to GML (such as for sensor time series) or to any of a series of data formats, such as GeoTIFF, NetCDF, HDF-EOS, or NITF.

As some of these encoding formats are not capable of incorporating all metadata making up a coverage, the coverage model foresees a multipart MIME encoding (see Figure) where the first component encodes the coverage description (domain extent, range type, metadata, etc.) and the second part consists of the range set "payload" using some encoding format.

Services

In Web services following the open OGC standards, coverages can be used by various service types:

Industry Terminology: GIS format

Early GIS systems were often characterised as either 'raster' or 'vector' systems, depending on the underlying approach to handling geometry. Raster GIS could be interpreted as using a regular discrete coverage model, while Vector GIS are more feature-oriented. The term "coverage" was most notably applied to the legacy Arc/INFO format developed by ESRI. At that time this was a novel concept, extending CAD formats into more spatially aware data that featured linked attributes. This usage was consistent with the coverage concept discussed here, in the sense that an Arc/Info coverage provided a one-to-one mapping from space to the thematic value or classification for each layer or coverage. However, Arc/Info coverages had a particular topological approach to ensure completeness and uniqueness, processed using the BUILD and CLEAN commands are 2D planar datasets that maintain topological information, thus a polygon "knows" which segments of its perimeter it shares with adjacent polygons. Due to the lack of processing power in computing at the time of its development, the Coverage model employs indexed binary files to store spatial and attribute data separately as opposed to utilizing a RDBMS.[5]

This has changed with the advent of raster database technology like rasdaman which makes efficient ad hoc filtering and processing feasible.[6][7]

References

  1. ↑ Topic 6 - Schema for coverage geometry and functions, OGC 07-011
  2. ↑ OGC GML Application Schema - Coverages, OGC 09-146r2
  3. ↑ OpenGIS Geography Markup Language (GML) Encoding Standard, OGC 07-036
  4. ↑ A Woolf; S J D Cox; C Portele (2010). "Data Harmonization - GEOSS AIP-3 Contribution" (PDF). doi:10.13140/RG.2.1.1840.4569. Retrieved 2016-01-27.
  5. ↑ Zeiler, Michael. Modeling Our World, The ESRI Guide to Geodatabase Design. ESRI Press, 1999. ISBN 1-879102-62-5
  6. ↑ Baumann, P.; Jucovschi, C.; Stancu-Mara, S.: Efficient Map Portrayal Using a General-Purpose Query Language (A Case Study). DEXA 2009, August 31 - September 04, 2009, Vienna, Austria, Springer Berlin/Heidelberg, LNCS 5690, pp. 153-163
  7. ↑ Jucovschi, C., Baumann, P., Stancu-Mara, S.: Speeding up Array Query Processing by Just-In-Time Compilation. IEEE Intl Workshop on Spatial and Spatiotemporal Data Mining (SSTDM-08), Pisa, Italy, 15 December 2008, pp. 408 - 413
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