• DocumentCode
    3581544
  • Title

    Syaritar intelligent system for the detection of illegal logging in the river basin Jeneberang

  • Author

    Syarif, Syafruddin ; Hasanuddin, Zulfajri B. ; Tola, Muhammad ; Suryani

  • Author_Institution
    Fac. of Eng., Hasanuddin Univ., Makassar, Indonesia
  • fYear
    2014
  • Firstpage
    145
  • Lastpage
    149
  • Abstract
    The purpose of this study is to classify the use of intelligent Syaritar system, methods for the detection of illegal logging and changes in forest area in the water sed. The research of intelligent hybrid system methods simulate Syaritar to know and analyze the logging on a sample image of the area of protected forest in the Jeneberang basin river by using sample image pair years 2007 to 2009. On the methods off intelligent system is an digital image, then cropped and will be classified in order to obtain a picture of the two parts of the forest area and the area is not a forest. Futher input parameter in the form of finding the average value of R (Red), G (Green), and B (Blue) for each sample pair the image of the beginning and end. This parameter will be the input for a method of intelligent system.
  • Keywords
    forestry; geographic information systems; image classification; image segmentation; knowledge based systems; object detection; vegetation; Indonesia; Jeneberang basin river; Syaritar intelligent system; cropping; digital image; forest area change detection; illegal logging detection; image classification; intelligent hybrid system method; protected forest; river basin; watershed; Artificial intelligence; Hidden Markov models; Image color analysis; Image recognition; Irrigation; Pattern recognition; ArcGIS; DAS; Illegal logging; Landsat; NDVI; Syaritar; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Informatics (MICEEI), 2014 Makassar International Conference on
  • Print_ISBN
    978-1-4799-6725-4
  • Type

    conf

  • DOI
    10.1109/MICEEI.2014.7067328
  • Filename
    7067328