Abstract. Oil palm tree discrimination is an important step for tree counting. In order for proper planning and management of the plantation, it is important to identify and classify oil palm tree species distinctively from other tree species and weeds. As oil palm trees are green leafy plants, it is difficult to differentiate between oil palm trees and weeds through color classification alone. Tree height can be determined through proper photogrammetric method. However, it is time consuming. SAR data processing is becoming a promising technology in the field of geospatial. Backscatter coefficient value is influenced by the roughness of surface, type of target and moisture content of target. The aim of this research is to utilize L-band ALOS PALSAR-2 dataset and open source C-band Sentinel-1 SAR datasets to discriminate oil palm trees from weeds as there is significant height difference between them. This research determines the backscatter coefficient value range of oil palm trees and weeds, it investigates the suitability of utilizing C-band and L-band SAR data on oil palm tree discrimination. Several existing oil palm field parameters are tested based on the backscatter value of SAR image. The results and discussion of backscatter value ranges between oil palm tree species and weed species will be further discussed in the paper.
The main objective of this paper is to show the potential use of L-Band SAR polarimetry. We used SAR images to estimate the above ground biomass (AGB) of an oil palm plantation. The approach used in this study was to analyze the relationship between the radar backscatter and AGB data by a specific allometric equation in variation of age. The four polarization of PALSAR was adapted in this study and converted to sigma nought for respective ages. Laplacian filter with window size 3×3, 5×5 and 7×7 was used on the PALSAR polarimetry images. Laplacian filter was used to show the best improvement to the relation of radar backscattering and AGB of oil palm trees. As a conclusion, improved radar backscattering of oil palm trees can be useful to estimate AGB of oil palm trees.
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