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Model-based biomass estimation of a hemi-boreal forest from multitemporal TanDEM-X acquisitions

Askne, J.I.H. and Fransson, Johan and Santoro, M. and Soja, M.J. and Ulander, L.M.H. (2013). Model-based biomass estimation of a hemi-boreal forest from multitemporal TanDEM-X acquisitions. Remote sensing. 5:11, 5574-5597
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Official URL: http://dx.doi.org/10.3390/rs5115574

Abstract

Above-ground forest biomass is a significant variable in the terrestrial carbon budget, but is still estimated with relatively large uncertainty. Remote sensing methods can improve the characterization of the spatial distribution and estimation accuracy of biomass; in this respect, it is important to examine the potential offered by new sensors. To assess the contribution of the TanDEM-X mission, eighteen interferometric Synthetic Aperture Radar (SAR) image pairs acquired over the hemi-boreal test site of Remningstorp in Sweden were investigated. Three models were used for interpretation of TanDEM-X signatures and above-ground biomass retrieval: Interferometric Water Cloud Model (IWCM), Random Volume over Ground (RVoG) model, and a simple model based on penetration depth (PD). All use an allometric expression to relate above-ground biomass to forest height measured by TanDEM-X. The retrieval was assessed on 201 forest stands with a minimum size of 1 ha, and ranging from 6 to 267 Mg/ha (mean biomass of 105 Mg/ha) equally divided into a model training dataset and a validation test dataset. Biomass retrieved using the IWCM resulted in a Root Mean Square Error (RMSE) between 17% and 33%, depending on acquisition date and image acquisition geometry (angle of incidence, interferometric baseline, and orbit type). The RMSE in the case of the RVoG and the PD models were slightly higher. A multitemporal estimate of the above-ground biomass using all eighteen acquisitions resulted in an RMSE of 16% with R 2 = 0.93. These results prove the capability of TanDEM-X interferometric data to estimate forest aboveground biomass in the boreal zone.

Authors/Creators:Askne, J.I.H. and Fransson, Johan and Santoro, M. and Soja, M.J. and Ulander, L.M.H.
Title:Model-based biomass estimation of a hemi-boreal forest from multitemporal TanDEM-X acquisitions
Series/Journal:Remote sensing (2072-4292)
Year of publishing :2013
Volume:5
Number:11
Page range:5574-5597
Number of Pages:24
Publisher:MDPI - Open Access Publishing
ISSN:2072-4292
Language:English
Publication Type:Journal article
Refereed:Yes
Article category:Scientific peer reviewed
Version:Published version
Full Text Status:Public
Agris subject categories.:K Forestry > K01 Forestry - General aspects
X Agricola extesions > X60 Technology
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Environmental Sciences (social aspects to be 507)
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
Agrovoc terms:Forestry, Boreal forests, Biomass, Models, Allometry
Keywords:TanDEM-X, InSAR, forestry, boreal, biomass estimation, model-based, allometry
URN:NBN:urn:nbn:se:slu:epsilon-e-1854
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-1854
Additional ID:
Type of IDID
Web of Science (WoS)000328626900010
DOI10.3390/rs5115574
ID Code:11048
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:11 Apr 2014 10:57
Metadata Last Modified:05 Feb 2016 18:27

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