Boreal Forest Properties from TanDEM-X Data Using Interferometric Water Cloud Model and Implications for a Bistatic C-Band Mission
Artikel i vetenskaplig tidskrift, 2021

Data from TanDEM-X in single-pass and bistatic interferometric mode together with the interferometric water cloud model (IWCM) can provide estimates of forest height and stem volume (or the related above-ground biomass) of boreal forests with high accuracy. We summarize results from two boreal test sites using two approaches, i.e., 1) based on model calibration using reference insitu stands, and 2) based on minimization of a cost function. Both approaches are based on inversion of IWCM, which models the complex coherence and backscattering coefficient of a homogeneous forest layer, which includes gaps where free-space wave propagation is assumed. A digital terrain model of the ground is also needed. IWCM is used to estimate forest height or stem volume, since the two variables are assumed to be related through an allometric equation. A relationship between the fractional area of gaps, the area-fill, and stem volume is also required to enable model inversion. The accuracy of the stem volume estimate in the two sites varies between 16% and 21% for height of ambiguity <100 m. The results clearly show the importance of using summer-time acquisitions. Based on the TanDEM-X results at X-band, C-band data from the ERS-1/ERS-2 tandem mission are revisited to investigate the potential of a future bistatic C-band interferometric mission. Out of nine ERS-1/ERS-2 pairs, only one pair was found to be acquired at summer temperatures, without precipitation and with high coherence. A simulated bistatic phase height is shown to give approximately the same sensitivity to stem volume as TanDEM-X.

C-band

Biomass

boreal forest

bistatic SAR interferometry

X-band

Författare

Jan Askne

Chalmers, Rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys

Lars Ulander

Geovetenskap och fjärranalys

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

1939-1404 (ISSN) 2151-1535 (eISSN)

Vol. 14 8627-8637 9513532

Ämneskategorier

Meteorologi och atmosfärforskning

Geofysik

Oceanografi, hydrologi, vattenresurser

DOI

10.1109/JSTARS.2021.3104631

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Senast uppdaterat

2022-05-19