Monitoring tree moisture using an estimation algorithm applied to SAR datafrom BOREAS

During several field campaigns in spring and summer of 1994, the NASA/JPL a irborne synthetic aperture radar (AIRSAR) collected data over the southern and northern study sites of BOREAS. Among the areas over which radar data w ere collected was the young jack pine (YJP) tower site in the south, which is generally characterized as having short (2-4 m) but closely spaced trees with a dense crown layer. In this work, the AIRSAR data over this YJP stan d from six different dates were used, and the dielectric constant and hence the moisture content of its branch layer components were estimated. The ap proach was to first derive a parametric scattering model from a numerical d iscrete-component forest model, which is possible if the predominant scatte ring mechanism can be identified. Here, a classification algorithm was used for this purpose, concentrating on areas where the volume scattering mecha nism from the branch layer dominates. The unknown parameters were taken to be the real and imaginary parts of the dielectric constant, from which the moisture content can he derived, Once the parametric model was derived, a n onlinear estimation algorithm was employed to retrieve the model parameters from SAR data. This algorithm is iterative, and takes the statistical prop erties of the data and unknown parameters into account, The inversion proce ss was first verified using synthetic data. It was observed that the algori thm is robust with respect to the a priori estimate, The estimation algorit hm was then applied to AIRSAR data of BOREAS. The results show how the envi ronmental conditions affected the moisture state of this forest stand over a period of six months, It is observed that canopy moisture increased durin g the thaw season (early April through late April), was stable starting fro m the end of the thaw season throughout most of the growing season (late Ap ril through late July), after which a period of dry-down was observed at th e end of the growing season (September). The results were compared in detai l to the available ground-truth for canopy moisture content, which were mea sured during the months of June through August. It was found that the estim ated values had an absolute error level of 15% (g/g) gravimmetric moisture content compared to the ground measurements. Several sources of error were identified and discussed.