Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/40784
Title: Relationships of S-Band Radar Backscatter and Forest Aboveground Biomass in Different Forest Types
Authors: Ningthoujam, Ramesh K.
Balzter, Heiko
Tansey, Kevin
Feldpausch, Ted R.
Mitchard, Edward T. A.
Wani, Akhlaq A.
Joshi, Pawan K.
First Published: 2-Nov-2017
Publisher: MDPI
Citation: Remote Sensing, 2017, 9 (11), 1116.
Abstract: 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.
DOI Link: 10.3390/rs9111116
ISSN: 2072-4292
eISSN: 2072-4292
Links: http://www.mdpi.com/2072-4292/9/11/1116
http://hdl.handle.net/2381/40784
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Geography

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