Darmawan, Soni and Carolita, Ita and Hernawati, Rika and Dirgahayu, Dede (2014) The Potential Scattering Model for Oil Palm Phenology Based on Spaceborne X-, C-, and L-Band Polarimetric SAR Imaging. Journal of Sensors, 2014. pp. 1-14. ISSN 1687-7268

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Abstract

Information about oil palm phenology is required for oil palm plantation management, but using spaceborne polarimetric radar imagery remains challenging. However, spaceborne polarimetric radar on X-, C-, and L-band is promising on structure vegetation and cloud area. This study investigates the scattering model of oil palm phenology based on spaceborne X-, C-, and L-band polarimetric Synthetic Aperture Radar (SAR) imaging. The X-, C-, and L-band polarimetric SAR are derived from spaceborne of TerraSAR-X, Sentinel-1A, and ALOS PALSAR 2. Study area is located in oil palm plantations, Asahan District, North Sumatra, Indonesia. The methodology includes data collection, preprocessing, radiometric calibration, speckle filtering, terrain correction, extraction of scattering value, and development of scattering model of oil palm phenology. The results showed different scattering characteristics for the X-, C-, and L-band polarimetric SAR of oil palm for age and found the potential of the scattering model for oil palm phenology based on the X-band on HH polarization that showed a nonlinear model with R2 = 0:65. The C-band on VH and VV polarization showed a nonlinear model with R2 = 0:56 and R2 = 0:89. The Lband on HV and HH polarization showed a logarithmic model with R2 = 0:50 and R2 = 0:51. In this case, the most potential of the scattering model of oil palm phenology based onR2is using C-band on VV polarization. However, the scattering model based on X-, C-, and L-band is potentially to be used and applied to identify the phenology of oil palm in Indonesia, which is the main parameter in yield estimation. For the future phenology model needs to improve accuracy by integrating multisensors, including different wavelengths on optical and microwave sensors and more in situ data.

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