University of Tasmania
Browse
152590 - Mapping above-ground biomass.pdf (4.91 MB)

Mapping above-ground biomass in tropical forests with ground-cancelled P-band SAR and limited reference data

Download (4.91 MB)
journal contribution
posted on 2023-05-21, 12:25 authored by Maciej Soja, Quegan, S, DAlessandro, MM, Banda, F, Scipal, K, Tebaldini, S, Ulander, LMH

This paper introduces the CASINO (CAnopy backscatter estimation, Subsampling, and Inhibited Nonlinear Optimisation) algorithm for above-ground biomass (AGB) estimation in tropical forests using P-band (435 MHz) synthetic aperture radar (SAR) data. The algorithm has been implemented in a prototype processor for European Space Agency's (ESA's) 7th Earth Explorer Mission BIOMASS, scheduled for launch in 2023. CASINO employs an interferometric ground cancellation technique to estimate canopy backscatter (CB) intensity. A power law model (PLM) is then used to model the dependence of CB on AGB for a large number of systematically distributed SAR data samples and a small number of calibration areas with a known AGB. The PLM parameters and AGB for the samples are estimated simultaneously within pre-defined intervals using nonlinear minimisation of a cost function. The performance of CASINO is assessed over six tropical forest sites on two continents: two in French Guiana, South America and four in Gabon, Africa, using SAR data acquired during airborne ESA campaigns and processed to simulate BIOMASS acquisitions. Multiple tests with only two randomly selected calibration areas with AGB > 100 t/ha are conducted to assess AGB estimation performance given limited reference data. At 2.25 ha scale and using a single flight heading, the root-mean-square difference (RMSD) is <= 27% for at least 50% of all tests in each test site and using as reference AGB maps derived from airborne laser scanning data. An improvement is observed when two flight headings are used in combination. The most consistent AGB estimation (lowest RMSD variation across different calibration sets) is observed for test sites with a large AGB interval and average AGB around 200-250 t/ha. The most challenging conditions are in areas with AGB < 200 t/ha and large topographic variations. A comparison with 142 1 ha plots distributed across all six test sites and with AGB estimated from in situ measurements gives an RMSD of 20% (66 t/ha).

History

Publication title

Remote Sensing of Environment

Volume

253

Article number

112153

Number

112153

Pagination

1-16

ISSN

0034-4257

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

Elsevier BV

Place of publication

Netherlands

Rights statement

© 2020 The Authors. Published by Elsevier Inc. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Repository Status

  • Open

Socio-economic Objectives

Forestry not elsewhere classified

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC