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Automatic Extraction of Complex Objects from Land Cover Maps

  • Eliseo ClementiniEmail author
  • Enrico Ippoliti
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

The ESA Support to Topology (STO) project addressed the problem of extracting so-called complex objects, intended as particular land use elements (urban fabric, industrial units…) from land cover maps, by means of topological relations among the different land cover objects. We developed an approach to give a semantic characterization to complex objects. Based on that, we developed a functional strategy to identify complex objects in an image and to build a visual representation compatible with the scale and resolution of the original map. The spatial operators, not only topological but directional and metric as well, were either taken from already existing systems or specifically implemented for the study. The developed approach and prototype web-GIS system, named Topology Software System (TSS), have been validated through several use cases, run by specialized end-users, in order to verify that the expected operations could be performed.

Keywords

Land Cover Geographical Information System Spatial Relation Complex Object Topological Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The author would like to thank the European Space Agency (ESA) for granting the Support To Topology (STO) project (http://wiki.services.eoportal.org/tiki-index.php?page=STO+Project), the SISTEMA GmbH, Vienna, Austria, for developing the prototype of the Topology Software System (TSS), the Environmental Protection Agency of Austria (UBA), Department for Biodiversity and Nature Conservation, Vienna, for providing LISA images and test cases, the GISAT, Prague, Czech Republic, for providing Urban Atlas images and test cases.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Department of Industrial and Information Engineering and EconomicsUniversity of L’AquilaL’AquilaItaly

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