Abstract
Estimation of forest biomass with synthetic aperture radar (SAR) and interferometric SAR (InSAR) observables has been surveyed in 186 peer-reviewed papers to identify major research pathways in terms of data used and retrieval models. Research evaluated primarily (i) L-band observations of SAR backscatter; and, (ii) single-image or multi-polarized retrieval schemes. The use of multi-temporal or multi-frequency data improved the biomass estimates when compared to single-image retrieval. Low frequency SAR backscatter contributed the most to the biomass estimates. Single-pass InSAR height was reported to be a more reliable predictor of biomass, overcoming the loss of sensitivity of SAR backscatter and coherence in high biomass forest. A variety of empirical and semi-empirical regression models relating biomass to the SAR observables were proposed. Semi-empirical models were mostly used for large-scale mapping because of the simple formulation and the robustness of the model parameters estimates to forest structure and environmental conditions. Non-parametric models were appraised for their capability to ingest multiple observations and perform accurate retrievals having a large number of training samples available. Some studies argued that estimating compartment biomass (in stems, branches, foliage) with different types of SAR observations would lead to an improved estimate of total biomass. Although promising, scientific evidence for such an assumption is still weak. The increased availability of free and open SAR observations from currently orbiting and forthcoming spaceborne SAR missions will foster studies on forest biomass retrieval. Approaches attempting to maximize the information content on biomass of individual data streams shall be pursued.
Highlights
Above-ground biomass (AGB) refers to amount of organic matter that is stored in vegetation above the ground level
We present a review of investigations that were published until 2017 in peer-reviewed literature that were concerned with retrieval approaches of forest aboveground biomass from the backscattered intensity or interferometric synthetic aperture radar (SAR) observations
This paper summarized the results of a literature survey on forest biomass retrieval with SAR backscatter and interferometric SAR data with the scope of identifying pathways of research and suggesting future advances
Summary
Above-ground biomass (AGB) refers to amount of organic matter that is stored in vegetation above the ground level. A detailed forest inventory takes a substantial amount of time, entails significant costs, and does not permit a synoptic view of the distribution of biomass across a forest landscape In this sense, survey and biomass estimation techniques based on remote sensing data are more suitable for mapping and monitoring large areas. We present a review of investigations that were published until 2017 in peer-reviewed literature that were concerned with retrieval approaches of forest aboveground biomass from the backscattered intensity or interferometric synthetic aperture radar (SAR) observations. The paper ends with a set of conclusions on research pathways and suggested fields of future investigations (Section 7); the use of SAR observables is put in a broader context while considering approaches that are mentioned above but are not addressed in this survey
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