• DocumentCode
    2783801
  • Title

    A study on decision tree classification method of land use/land cover -Taking tree counties in Hebei Province as an example

  • Author

    Ping Wang ; Ji-xian Zhang ; Wei-jie Jia ; Zong-jian Lin

  • Author_Institution
    Shandong Univ. of Sci. & Technol., Qingdao
  • fYear
    2008
  • fDate
    June 30 2008-July 2 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.
  • Keywords
    decision trees; geophysical techniques; image classification; vegetation mapping; CART system; China; Hebei Province; LULC information; SPOT data; TM data; decision tree classification; fault-tolerance feature; ground spectral feature information; land cover classification; land use classification; Biological system modeling; Classification tree analysis; Data mining; Decision trees; Fault tolerance; Geoscience; Humans; Information analysis; Spatial databases; Spectral analysis; LULC; decision model; decision tree; sub-district;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Earth Observation and Remote Sensing Applications, 2008. EORSA 2008. International Workshop on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2393-4
  • Electronic_ISBN
    978-1-4244-2394-1
  • Type

    conf

  • DOI
    10.1109/EORSA.2008.4620331
  • Filename
    4620331