[HTML][HTML] Accounting for surface roughness scattering in the characterization of forest litter with ground-penetrating radar

F Andr�, F Jonard, M Jonard, H Vereecken, S Lambot�- Remote Sensing, 2019 - mdpi.com
Remote Sensing, 2019mdpi.com
Accurate characterization of forest litter is of high interest for land surface modeling and for
interpreting remote sensing observations over forested areas. Due to the large spatial
heterogeneity of forest litter, scattering from litter layers has to be considered when sensed
using microwave techniques. Here, we apply a full-waveform radar model combined with a
surface roughness model to ultrawideband ground-penetrating radar (GPR) data acquired
above forest litter during controlled and in situ experiments. For both experiments, the�…
Accurate characterization of forest litter is of high interest for land surface modeling and for interpreting remote sensing observations over forested areas. Due to the large spatial heterogeneity of forest litter, scattering from litter layers has to be considered when sensed using microwave techniques. Here, we apply a full-waveform radar model combined with a surface roughness model to ultrawideband ground-penetrating radar (GPR) data acquired above forest litter during controlled and in situ experiments. For both experiments, the proposed modeling approach successfully described the radar data, with improvements compared to a previous study in which roughness was not directly accounted for. Inversion of the GPR data also provided reliable estimates of the relative dielectric permittivity of the recently fallen litter (OL layer) and of the fragmented litter in partial decomposition (OF layer) with, respectively, averaged values of 1.35 and 3.8 for the controlled experiment and of 3.9 and 7.5 for the in situ experiment. These results show the promising potentialities of GPR for efficient and non-invasive characterization of forest organic layers.
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