• DocumentCode
    1680855
  • Title

    Multiscale tree analysis from satellite images

  • Author

    Ozcan, Abdullah H. ; Sayar, Yetkin ; Hisar, Dilara ; Unsalan, Cem

  • fYear
    2015
  • Firstpage
    265
  • Lastpage
    269
  • Abstract
    As satellite images cover wide areas and obtaining them has become easier, using these images in agriculture has become an important research area. Especially, satellite images can be used in seasonal crop estimation. In this study, we focused on crop estimation from trees. The boundary of a tree is proportional to its age which gives information on the approximate crop that can be obtained from it. Obtaining the number of trees in a region, with the size of each tree, gives the approximate amount of crop that can be harvested from that region. In this study, we propose a method based on multiple filtering, watershed segmentation, and Otsu thresholding to detect trees and their boundaries. To test the proposed method, we picked three satellite images containing 6928 trees. These trees have diameters between 2 to 30 pixels. We compared the proposed method with two other methods in the literature. We summarized the obtained results in this study.
  • Keywords
    agriculture; geophysical image processing; image segmentation; vegetation; Otsu thresholding; agriculture; multiple filtering; multiscale tree analysis; satellite images; seasonal crop estimation; tree boundary; tree detection; watershed segmentation; Agriculture; Image segmentation; Remote sensing; Satellites; Shape; Spatial resolution; Vegetation; Tree detection; local maximum filtering; multiple filtering; thresholding; tree boundary detection; watershed segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Advances in Space Technologies (RAST), 2015 7th International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-7760-7
  • Type

    conf

  • DOI
    10.1109/RAST.2015.7208353
  • Filename
    7208353