Abstract

The use of satellite imagery for plantation management is helpful in monitoring the development of various parties including oil palm plantations. In a panchromatic IKONOS satellite imagery, oil palm plantations have unique characteristics that can be interpreted visually. This study tried to classify oil palm plantations from satellite imagery using texture characteristics with their spatial and frequency parameters. Spatial parameters are determined by calculating the first order features, while the second order texture variables are determined based on Gray Level Co-occurrence Matrix (GLCM), local feature, and Radially Average Power Spectrum Value (RAPSV). The classification accuracy of of this study reached 86%. An addition of average value of the power spectrum has increased the accuracy up to 28% compared to the usage of first order only.

Original languageEnglish
Title of host publicationProceedings of 2015 International Conference on Information and Communication Technology and Systems, ICTS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-94
Number of pages6
ISBN (Electronic)9781509000951
DOIs
Publication statusPublished - 12 Jan 2016
EventInternational Conference on Information and Communication Technology and Systems, ICTS 2015 - Surabaya, Indonesia
Duration: 16 Sept 2015 → …

Publication series

NameProceedings of 2015 International Conference on Information and Communication Technology and Systems, ICTS 2015

Conference

ConferenceInternational Conference on Information and Communication Technology and Systems, ICTS 2015
Country/TerritoryIndonesia
CitySurabaya
Period16/09/15 → …

Keywords

  • Feature identification
  • IKONOS panchromatic
  • oil palm plantations
  • radially average power spectrum value (RAPSV)
  • texture

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