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Conference paper - Peer-reviewed, 2023

Prediction of Hemi-Boreal Forest Biomass Change Using Alos-2 Palsar-2 L-Band SAR Backscatter

Huuva, Ivan; Persson, Henrik; Wallerman, Jörgen; Ulander, Lars M.H.; Fransson, Johan E. S.

Abstract

Pairs of fully polarimetric ALOS-2 PALSAR-2 L-band SAR images were used to model biomass on backscatter change over seven growth seasons in a hemi-boreal forest. The biomass change was related to backscatter change via consecutive field surveys of 263 field plots with a 10 m radius. To correct for differences in backscatter not related to biomass abundance, a HV-VV polarization ratio based correction, previously used on airborne L-band data, was applied to the data. The uncertainty of obtained predictions (lowest model mean RMSE 65.1 t/ha, lowest model mean bias 7.1 t/ha) was almost identical whether model fitting and prediction used data from the same scene pair, or different scene pairs. This could possibly attest to the feasibility of the backscatter correction for PALSAR-2 data, but no large backscatter offsets were observed for uncorrected data, and significant variance in predictions, due to the inherent noise in the data and the comparatively small area of evaluation plots, inhibit the analysis.

Keywords

SAR; backscatter; biomass change; ALOS-2 PALSAR-2; forestry

Published in

IEEE International Geoscience and Remote Sensing Symposium proceedings
2023, pages: 3326 - 3339
Title: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
eISBN: 979-8-3503-2010-7
Publisher: IEEE

Conference

IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 16-21 July 2023, Pasadena, CA, USA.