Open AccessPotential of PALSAR SCANSAR data for oil palm plantation in growth monitoring and mapping
Author(s) -
Ita Carolita,
Mohammad Syamsu Rosid,
Ahmad Asrul Ibrahim,
Dede Dirgahayu,
Heru Noviar,
Jatna Supriatna
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/739/1/012091
Subject(s) - synthetic aperture radar , environmental science , remote sensing , backscatter (email) , satellite imagery , radar , palm , satellite , palm oil , biomass (ecology) , geography , geology , computer science , agroforestry , engineering , oceanography , telecommunications , physics , quantum mechanics , aerospace engineering , wireless
The main objective of this study is to analyze the potential use of L-band radar data with 100 meter spatial resolution for age estimation of oil palm. Age of oil palm are very important parameter to be investigated, because age and condition of oil palm are the main factors for yield forecasting, biomass estimation, replanting plan, fertilization plan, etc. As sensitive to roughness and moisture, the variations of oil palm backscatter that received by SAR satellite caused by the differences of oil palm age. This condition give possibility to investigate the relation between backscatter and age. Four radar images were acquired using the Scanning synthetic aperture radar/Advanced Land Observing Satellite (ScanSAR/ALOS)-2 sensor over the oil palm plantation in Tandun Riau, July 2016, 2017, 2018 and 2019. The information about ages from very young up to mature were gathered from oil palm plantation of PTP N V in Tandun.. The growth model equation was built to describes the development of backscatter of oil palm from young age to mature age. Method to get growth model is regression analysis. The growth model that has been obtained is logarithmic equation with R 2 around 0,90 for HH SAR polarization. Growth model then can be used for age estimation and produce oil palm map based on it’s age that can be used for yield estimation, as well as for oil palm’s condition monitoring including it’s health.