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 R2 = 0.93. These results prove the capability of TanDEM-X interferometric data to estimate forest aboveground biomass in the boreal zone.
Highlights
Forest above-ground dry biomass (AGB, referred to as biomass) is an important variable for the global carbon budget, due to the uptake of carbon dioxide in the process of photosynthesis, and because forests store huge amounts of carbon, which are eventually released into the atmosphere following a disturbance [1]
The study on above-ground dry biomass retrieval with TanDEM-X interferometry follows a number of investigations on remote sensing data and retrieval techniques at the Remningstorp test site
Interferometric Synthetic Aperture Radar (SAR) datasets acquired at C-band with one-day temporal separation were evaluated to retrieve forest stem volume in [13] achieving Root Mean Square Error (RMSE) of 27%
Summary
Forest above-ground dry biomass (AGB, referred to as biomass) is an important variable for the global carbon budget, due to the uptake of carbon dioxide in the process of photosynthesis, and because forests store huge amounts of carbon, which are eventually released into the atmosphere following a disturbance [1]. Accurate and timely mapping of forest AGB is crucial to support carbon cycle modeling. Traditional methods based on forest inventories and aerial photography, and more recently, LiDAR campaigns, give accurate estimates of AGB; such methods are expensive and become inefficient whenever frequent and large-scale mapping is needed. There is a need for development of alternative methods for frequent and large-scale biomass mapping [2]. One of the more promising techniques for above-ground dry biomass mapping is Synthetic. Aperture Radar (SAR), cf [3]. Radar is independent of weather and external illumination. Interferometric SAR, InSAR, offers the possibility to exploit two further observables besides the radar backscatter, namely the coherence and the interferometric phase
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