A framework for ontology-supported intelligent geospatial feature discovery services

Liping Di, Peng Yue, Peisheng Zhao, Wenli Yang, Weiguo Han

Research output: Contribution to journalConference articlepeer-review

Abstract

Geospatial feature discovery from remote sensing imageries is widely used in national defense and security communities. Existing methods in the geospatial image mining and feature extraction focus on the manual or automated processing of images to detect individual elementary features, such as building and highway. Such elementary features don't tell much semantic information about the features. Compound geospatial features such as Weapons of Mass Destruction (WMD) proliferation facilities are spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling ponds, and transportation railways). The identity and much semantic information of a compound geospatial feature can be derived from the spatial relationship among the elementary elements. In this paper, we propose a flexible service framework for discovering compound geospatial features using an ontology-supported approach. The ontology for facilities helps find compound features that contain the specified spatial relationships among constituent features. The framework uses Web services for elementary feature extraction or access of existing elementary features, identifies facilities based on semantic descriptions of elementary feature constituents and their spatial relationships, and composes workflow-based service chains for automatic feature discovery.

Original languageEnglish
Pages (from-to)31-35
Number of pages5
JournalCEUR Workshop Proceedings
Volume808
StatePublished - 2011
Externally publishedYes
Event6th International Conference on Semantic Technologies for Intelligence, Defense, and Security, STIDS 2011 - Fairfax, VA, United States
Duration: Nov 16 2011Nov 17 2011

Keywords

  • Feature discovery
  • Geospatial services
  • Image mining
  • Ontology
  • Semantic web
  • Workflow

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