Fully Polarimetric L-Band Synthetic Aperture Radar for the Estimation of Tree Girth as a Representative of Stand Productivity in Rubber Plantations

Bambang H. Trisasongko, Dyah R. Panuju, Amy L. Griffin and David J. Paull
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Bambang H. Trisasongko: Department of Soil Science and Land Resources, Bogor Agricultural University, Jalan Meranti, Bogor 16680, Indonesia
Dyah R. Panuju: Department of Soil Science and Land Resources, Bogor Agricultural University, Jalan Meranti, Bogor 16680, Indonesia
Amy L. Griffin: School of Science, RMIT University, Melbourne 3001, Australia
David J. Paull: School of Science, UNSW Canberra, Campbell 2610, Australia

Geographies, 2022, vol. 2, issue 2, 1-13

Abstract: This article explores a potential exploitation of fully polarimetric radar data for the management of rubber plantations, specifically for predicting tree circumference as a crucial information need for sustainable plantation management. Conventional backscatter coefficients along with Eigen-based and model-based decomposition features served as the predictors in models of tree girth using ten regression approaches. The findings suggest that backscatter coefficients and Eigen-based decomposition features yielded lower accuracy than model-based decomposition features. Model-based decompositions, especially the Singh decomposition, provided the best accuracies when they were coupled with guided regularized random forests regression. This research demonstrates that L-band SAR data can provide an accurate estimation of rubber plantation tree girth, with an RMSE of about 8 cm.

Keywords: circumference; extreme gradient boosting; girth; polarimetric decomposition; rubber; regularized random forests (search for similar items in EconPapers)
JEL-codes: Q1 Q15 Q5 Q53 Q54 Q56 Q57 (search for similar items in EconPapers)
Date: 2022
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