Data mining applied in land use control in city-country combinative area

Shuliang Wang, Xinzhou Wang

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper studies the concepts of city-country combinative area (CCCA), and how to apply data cleaning, and data mining in land use control in CCCA. A new data cleaning method named as Vectorizing Character-string and Matching Number (VCMN) is advanced, which can integrates multi-origin data. It is suggested that the control points be acquired with GPS-supported aerial triangulation, CCCA images be dealt with digital photogrammetry system before image databases come into being. Then all related land databases can be rebuilt up a data warehouse after data cleaning. In the network, online data mining is carried out in the light of constraint conditions. Finally, some Wuhan City CCCA knowledge is discovered with rough set.

Original languageEnglish
Pages (from-to)1677-1683
Number of pages7
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume33
Publication statusPublished - 2000
Externally publishedYes
Event19th International Congress for Photogrammetry and Remote Sensing, ISPRS 2000 - Amsterdam, Netherlands
Duration: 16 Jul 200023 Jul 2000

Keywords

  • City-country combinative area
  • Data cleaning
  • Data mining
  • Land use control
  • Photogrammetry
  • Rough set
  • Vectorizing character-string and matching number

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