Structural variables estimation in pine plantacion using CosmoSkyMed polarimetric ratios

Los datos satelitales son de gran utilidad en aplicaciones forestales. La cobertura nubosa afecta la adquisición de imágenes ópticas, pero no a los radares. Aunque la banda X no posee un gran poder de penetración en la vegetación, ameritan su evaluación. En este trabajo se evalúa la relación entre la retrodispersión medidas en imágenes CosmoSkyMed y variables estructurales en plantaciones de Pinus taeda L. en Misiones mediante modelos de regresión múltiple. El área basal fue la variable estructural donde se observó mejor ajuste del modelo (r2=0,82) seguida por el diámetro cuadrático medio (r2=0,59). No se halló un ajuste significativo utilizando la densidad del rodal. Los modelos ajustados son de carácter exploratorio dado las escasas observaciones de campo pero indican buenas posibilidades para predecir el área basal. El agregado de la edad como variable predictora podría mejorar el ajuste de los modelos pero con los datos disponibles no se justifica incluirlos.Optical and radar satellite data are very useful in forest application. Cloud cover affects the acquisition of optical data, but not affects the radar. Despite X-band do not enable deep penetration into vegetation, it deserves the evaluation. In this work, the relationship between the backscatter of CosmoSkyMed data and structural variables in Pinus taeda L. plantations, in Misiones, were evaluated by multiple regression models. Basal area exhibit-ed the best fit for models (r2=0,82) followed by quadratic mean diameter (r2=0,59). No significant fit was found for stand density. Due to scarce field observations the models must be taken as exploratory but seems to be suitable for basal area estimation. The introduction of the stand age as a predictor could increase the models fit but with the small ana-lyzed data set it does not seem to be necessary to include it.Laboratorio de Investigación de Sistemas Ecológicos y Ambientale

Multiple-grid adaptive integral method for general multi-region problems

textEfficient electromagnetic solvers based on surface integral equations (SIEs) are developed for the analysis of scattering from large-scale and complex composite structures that consist of piecewise homogeneous magnetodielectric and perfect electrically/magnetically conducting (PEC/PMC) regions. First, a multiple-grid extension of the adaptive integral method (AIM) is presented for multi-region problems. The proposed method accelerates the iterative method-of-moments solution of the pertinent SIEs by employing multiple auxiliary Cartesian grids: If the structure of interest is composed of K homogeneous regions, it introduces K different auxiliary grids. It uses the k^{th} auxiliary grid first to determine near-zones for the basis functions and then to execute AIM projection/anterpolation, propagation, interpolation, and near-zone pre-correction stages in the k^{th} region. Thus, the AIM stages are executed a total of K times using different grids and different groups of basis functions. The proposed multiple-grid AIM scheme requires a total of O(N^{nz,near}+sum({N_k}^Clog{N_k}^C)) operations per iteration, where N^{nz,near} denotes the total number of near-zone interactions in all regions and {N_k}^C denotes the number of nodes of the k^{th} Cartesian grid. Numerical results validate the method’s accuracy and reduced complexity for large-scale canonical structures with large numbers of regions (up to 10^6 degrees of freedom and 10^3 regions). Then, a Green function modification approach and a scheme of Hankel- to Teoplitz-matrix conversions are efficiently incorporated to the multiple-grid AIM method to account for a PEC/PMC plane. Theoretical analysis and numerical examples show that, compared to a brute-force imaging scheme, the Green function modification approach reduces the simulation time and memory requirement by a factor of (almost) two or larger if the structure of interest is terminated on or resides above the plane, respectively. In addition, the SIEs are extended to cover structures composed of metamaterial regions, PEC regions, and PEC-material junctions. Moreover, recently introduced well-conditioned SIEs are adopted to achieve faster iterative solver convergence. Comprehensive numerical tests are performed to evaluate the accuracy, computational complexity, and convergence of the novel formulation which is shown to significantly reduce the number of iterations and the overall computational work. Lastly, the efficiency and capabilities of the proposed solvers are demonstrated by solving complex scattering problems, specifically those pertinent to analysis of wave propagation in natural forested environments, the design of metamaterials, and the application of metamaterials to radar cross section reduction.Electrical and Computer Engineerin

L-Band Multi-Polarization Radar Scatterometry over Global Forests: Modelling, Analysis, and Applications

Spaceborne L-band radars have the ability to penetrate vegetation canopies over forested areas, suggesting a potential for regular and frequent global monitoring of both the vegetation state and the subcanopy soil moisture. However, L-band radar’s sensitivity to both vegetation and ground also complicates the relationship between the radar observations and the ecological and geophysical parameters. Accurate yet parsimonious forward models of the radar backscatter are valuable to building an understanding of these relationships. In the first part of this thesis, a model of L-band multi-polarization radar backscatter from forests, intended for use at regional to global spatial scales, is presented. Novel developments in the model include the consideration of multiple scattering within the dense vegetation canopy, and the application of a general model of plant allometry to mitigate the need for much intensive field data for training or over-tuning towards specific sites and tree species. Aided by our model, in the remainder and majority of the thesis, a detailed analysis and interpretation of L-band backscatter over global forests is performed, using data from the Aquarius and SMAP missions. Quantitative differences in backscatter predicted by our model due to freeze/thaw states, branch orientation, and flooding are partially verified against the data, and fitted values of aboveground-biomass and microwave vegetation optical depths are comparable to independent estimates in the literature. Polarization information is used to help distinguish vegetation and ground effects on spatial and temporal variations. We show that neither vegetation nor ground effects alone can explain spatial variations within the same land cover class. For temporal variations during unfrozen periods, soil moisture is found to often be an important factor at timescales of a week to several months, although vegetation changes remain a non-negligible factor. We report the observation of significant differences in backscatter depending on beam azimuthal angle, possibly due to plant phototropism. We also investigated diurnal variations, which have the potential to reveal signals related to plant transpiration. SMAP data from May-July 2015 showed that globally, co-polarized backscatter was generally higher at 6PM compared to 6AM over boreal forests, which is not what one might expect based on previous studies. Based on our modelling, increased canopy extinction at 6AM is a possible cause, but this is unproven and its true underlying physical cause undetermined. Finally, by making simplifying approximations on our forward model, we propose and explore algorithms for soil moisture retrieval under forest canopies using L-band scatterometry, with preliminary evaluations suggesting improved performance over existing algorithms.</p