Model-Based Biomass Estimation of a Hemi-Boreal Forest from Multitemporal TanDEM-X Acquisitions

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% OPEN ACCESS Remote Sens. 2013, 5 5575 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.

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

“…To avoid potentially masking out forest regions with low coherence (typically not a problem, but higher/denser forest generally decreases the coherence), both the coherence and the phase height might be used in conjunction, or one could simply use an external water mask. The interferometric coherence also has a strong relevance for AGB estimations, when other non-empirical approaches are used, such as the random volume over ground (RVoG), two-level model (TLM) or the interferometric water cloud model (IWCM), all of which have been proven to have good results [23][24][25]62,63]. The single coverage of Sweden required a compensation of the antenna gain loss against the scene sides, to stabilize the otherwise strong dependence on across-track location.…”

A review of remote sensing applications for oil palm studies

“…The biomass can be related to remotely sensed data like optical bands reflectance, vegetation indices, texture analysis, radar backscatter signals, polarimetric response, or height data derived from LiDAR, InSAR, and so on (Foody et al 2001;Englhart, Keuck, and Siegert 2011;Cartus, Santoro, and Kellndorfer 2012;Askne et al 2013). Because a forest landscape is structurally different from an oil palm plantation and to narrow the scope limited to the purpose of this review, we only discuss the techniques carried out in an oil palm scenario in this paper.…”

Research Pathways of Forest Above-Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations

“…Long winter-frozen conditions guaranteed the maximum contrast of coherence between low and high biomass. On the other hand, single-pass coherence as from the TanDEM-X mission, is only affected by volume decorrelation so that the sensitivity to biomass depends on the length of the spatial baseline [32].…”