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Relationships of S-Band Radar Backscatter and Forest Aboveground Biomass in Different Forest Types

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posted on 2018-01-09, 15:18 authored by Ramesh K. Ningthoujam, Heiko Balzter, Kevin Tansey, Ted R. Feldpausch, Edward T. A. Mitchard, Akhlaq A. Wani, Pawan K. Joshi
Synthetic Aperture Radar (SAR) signals respond to the interactions of microwaves with vegetation canopy scatterers that collectively characterise forest structure. The sensitivity of S-band (7.5–15 cm) backscatter to the different forest types (broadleaved, needleleaved) with varying aboveground biomass (AGB) across temperate (mixed, needleleaved) and tropical (broadleaved, woody savanna, secondary) forests is less well understood. In this study, Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model simulations showed strong volume scattering returns from S-band SAR for broadleaved canopies caused by ground/trunk interactions. A general relationship between AirSAR S-band measurements and MIMICS-I simulated radar backscatter with forest AGB up to nearly 100 t/ha in broadleaved forest in the UK was found. Simulated S-band backscatter-biomass relationships suggest increasing backscatter sensitivity to forest biomass with a saturation level close to 100 t/ha and errors between 37 t/ha and 44 t/ha for HV and VV polarisations for tropical ecosystems. In the near future, satellite SAR-derived forest biomass from P-band BIOMASS mission and L-band ALOS-2 PALSAR-2 in combination with S-band UK NovaSAR-S and the joint NASA-ISRO NISAR sensors will provide better quantification of large-scale forest AGB at varying sensitivity levels across primary and secondary forests and woody savannas.


The authors acknowledge Leland Pierce from the Radiation Lab, The University of Michigan (United States of America) for providing the MIMICS-I code. MIMICS simulation was performed using ALICE High Performance Computing Facility at the University of Leicester. The AirSAR 2014 data was procured from Airbus Defence and Space, Satellite Applications Catapult and Natural Environment Research Council Airborne Research & Survey Facility. We thank João R. Santos (INPE, Brazil) for providing their published field data table. We also thanked Yadvinder Malhi (SOGE, University of Oxford), Jon Lloyd (Life Sciences, Imperial College University), Simon L. Lewis (Geography, University College London and University of Leeds), Bonaventure Sonké (Biology, University of Yaoundé), Keith Morrison (University of Reading), France Gerard, Charles George (Centre for Ecology and Hydrology), Geoff Burbidge, Sam Doody, Van Beijma Sybrand (Airbus Defence and Space), Nick Veck (Satellite Applications Catapult), Gary M. Llewellyn (Natural Environment Research Council Airborne Research & Survey Facility), Thomas Blythe (Forestry Commission, Bristol and Savernake), Sarah C.M. Johnson, Pedro Rodriguez-Veiga, Bernard Spies, James E.M. Wheeler, Chloe Barnes, Valentin Louis, Tom Potter, Marc Padilla, Alexander Edwards-Smith and Jaime Polo Bermejo for their invaluable contributions. The Environmental Change Network plot database for Wytham Woods being shared by Lorna Sherrin from Centre for Ecology & Hydrology (CEH) is also appreciated. Heiko Balzter was supported by the Royal Society Wolfson Research Merit Award, 2011/R3 and the NERC National Centre for Earth Observation. Pawan K. Joshi is thankful to DST-PURSE of Jawaharlal Nehru University for research support. We would like to thank all three reviewers and academic editors for their comments, which has helped us to improve the quality of our manuscript.



Remote Sensing, 2017, 9 (11), 1116.

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/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment/GIS and Remote Sensing


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