Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient
Journal article, 2015

A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance Delta h and with area-weighted backscatter ratio mu. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a high-resolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance Delta h can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (sigma) < 10%, or 1.8 m). Moreover, the uncorrected area fill factor eta(0) = 1/(1 + mu) can be used as an estimate of the vegetation ratio, which is a canopy density estimate defined as the fraction of lidar returns coming from the canopy to all lidar returns (for regular plots: r > 0.59 and sigma approximate to 10%, or 0.07).

synthetic aperture radar (SAR)

interferometric model


two-level model (TLM)

forest height

Canopy density



Maciej Soja

Chalmers, Earth and Space Sciences, Radar Remote Sensing

H. Persson

Swedish University of Agricultural Sciences (SLU)

Lars Ulander

Chalmers, Earth and Space Sciences, Radar Remote Sensing

IEEE Geoscience and Remote Sensing Letters

1545-598X (ISSN)

Vol. 12 3 646-650 2354551

Driving Forces

Sustainable development

Subject Categories

Remote Sensing



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