Simple Features

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Simple Features (officially Simple Feature Access) is both an Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO) standard ISO 19125 that specifies a common storage and access model of mostly two-dimensional geographical data (point, line, polygon, multi-point, multi-line, etc.)

The ISO 19125 standard comes in two parts. Part one, ISO 19125-1 (SFA-CA for "common architecture"), defines a model for two-dimensional simple features, with linear interpolation between vertices. The data model defined in SFA-CA is a hierarchy of classes. This part also defines representation using Well-Known Text (and Binary). Part 2 of the standard, ISO 19125-2 (SFA-SQL), defines an implementation using SQL.[1] The OpenGIS standard(s) cover implementations in CORBA and OLE/COM as well, although these have lagged behind the SQL one and are not standardized by ISO.

The ISO/IEC 13249-3 SQL/MM Spatial extends the Simple Features data model mainly with circular interpolations (e.g. circular arcs) and adds other features like coordinate transformations and methods for validating geometries as well as Geography Markup Language support.[1]

Standard documents

Part 1 details

The geometries are also associated with spatial reference systems. The standard also specifies attributes, methods and assertions with the geometries. In general, a 2D geometry is simple if it contains no self-intersection. The specification defines DE-9IM spatial predicates and several spatial operators that can be used to generate new geometries from existing geometries.


Part 2 of Simple Feature Access is implemented to varying degrees in:

The GDAL library (sometimes described as a Spatial ETL because it can convert between various proprietary storage models) implements the Simple Features data model in its OGR component.[12] The Java-based deegree framework implements SFA (part 1) and various other OGC standards.[13]

GeoSPARQL is an OGC standard that is intended to allow geospatially-linked data representation and querying based on RDF and SPARQL by defining an ontology for geospatial reasoning supporting a small Simple Features (as well as DE-9IM and RCC8) RDFS/OWL vocabulary for GML and WKT literals.[14]


As of 2012, various NoSQL databases have very limited support for "anything more complex than a bounding box or proximity search".[3]

See also


  1. 1.0 1.1 Wolfgang Kresse; David M. Danko (2011). Springer Handbook of Geographic Information. Springer. pp. 81–83. ISBN 978-3-540-72678-4. 
  2. MySQL 5.1 documentation on Spatial extensions
  3. 3.0 3.1 Frank Hardisty (Fall 2012). "Penn State Geography 583: Geospatial System Analysis and Design. Databases.". 
  4. MySQL 5.6 documentation on Spatial extensions
  5. "GeoSpatial - MonetDB". 4 March 2014. 
  6. 6.0 6.1 6.2 Wolfgang Kresse; David M. Danko (2011). Springer Handbook of Geographic Information. Springer. pp. 105–106. ISBN 978-3-540-72678-4. 
  7. SpatiaLite Simple Features implementation for SQLite
  8. Ravikanth V. Kothuri; Euro Beinat; Albert Godfrind (2004). Pro Oracle Spatial. Apress. p. 65. ISBN 978-1-59059-383-7. 
  9. Alastair Aitchison (2012). Pro Spatial with SQL Server 2012. Apress. pp. 21–23. ISBN 978-1-4302-3491-3. 
  10. SAP Sybase IQ support for spatial data
  11. SAP HANA Spatial Reference: Supported Import and Export Formats for Spatial Data
  13. Shashi Shekhar; Hui Xiong (2007). Encyclopedia of GIS. Springer. pp. 235–236. ISBN 978-0-387-30858-6. 
  14. Battle, Robert; Kolas, Dave (2012). "Enabling the Geospatial Semantic Web with Parliament and GeoSPARQL" (PDF). Semantic Web (IOS Press) 3 (4): 355–370. doi:10.3233/SW-2012-0065. Retrieved 21 November 2012. 

External links