Estimation of Boreal Forest Properties From TanDEM-X Data Using Inversion of the Interferometric Water Cloud Model
Artikel i vetenskaplig tidskrift, 2017

In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acquisitions made between June 2011 and August 2014 over a boreal forest in Krycklan, northern Sweden, using a new method based on nonlinear least-squares optimization. A high-resolution digital terrain model is used as ground reference during interferometric synthetic-aperture radar (InSAR) processing and 26 stands with areas 1.5-22 ha and unaltered during the study period are studied. The dependence of biomass estimation performance, ground and vegetation backscatter coefficients (sigma(0)(gr) and sigma(0)(veg)), canopy attenuation (alpha), and zero-biomass coherence (gamma 0) on selected system and environmental parameters is studied. High correlation between the estimated biomass and reference biomass derived from in situ measurements is observed for all 87 acquisitions (r between 0.81 and 0.93), while the root-mean-square difference is between 18% and 32% for all 43 acquisitions made in snow-free conditions and with heights-of-ambiguity (HOAs) between 36 and 150 m. Significant biomass estimation bias is observed for HOAs above 150 m and for some acquisitions over snow-covered forest. It is also observed that sigma(0)(gr) and sigma(0)(veg) are the largest for temperatures below 0 degrees C and with significant snow cover. For temperatures above 0 degrees C, sigma(0)(gr) appears independent of temperature, while sigma(0)(veg) shows a tendency to increase with temperature. Moreover, gamma 0 decreases from just below 1 for HOAs around 40 m to around 0.8 for HOAs above 150 m.

interferometric

interferometric model inversion

boreal forest

Above-ground biomass (AGB)

Radar

Biomass

SAR Interferometry

Författare

Maciej Soja

Mikrovågs- och optisk fjärranalys

Jan Askne

Mikrovågs- och optisk fjärranalys

Lars Ulander

Mikrovågs- och optisk fjärranalys

IEEE Geoscience and Remote Sensing Letters

1545-598X (ISSN)

Vol. 14 997-1001 7935363

Ämneskategorier

Fjärranalysteknik

Elektroteknik och elektronik

DOI

10.1109/LGRS.2017.2691355