Electromagnetic Simulation for Estimation of Forest Vertical Structure Using Polsar Data

Abstract

A novel method for the estimation of a forest vertical structure using Polarimetric Synthetic Aperture Radar (PolSAR) data only without the need to interferometry data is proposed in the present paper. Electromagnetic (EM) simulation is used to develop the proposed method, where the SAR pulse is simulated as a plane wave incident in the direction of the side looking angle of the SAR. For this purpose, the forest canopy layer is modeled as clouds of randomly oriented thin straight dipoles which are randomly distributed within an inclined prism volume, whereas the forest soil surface is modeled as a random rough surface. The proposed method aims to estimate the average height of the canopy layer above the soil surface, the canopy layer thickness, and the roughness of the forest ground surface. The proposed method is based on the Radar Vegetation Index (RVI) and the normalized Radar Cross Section (RCS) calculated from the PolSAR data and their relevance to the parameters of the forest vertical structure. Some examples are presented to demonstrate the capability of the proposed method using some PolSAR images obtained through EM simulation of the scattering from forest regions and by applying the theorem of SAR target composition with the Multiple Component Scattering Model (MCSM). The phase differences between the components of scattering obtained from the solution of the SAR target decomposition problem are used in the estimation process. The accuracy of the proposed method is assessed by calculating the percentage error of the estimated vertical structure and ground roughness for each resolution cell of the simulated forest region. It is shown that the percentage errors of the estimated parameters are very low, which reflects the accuracy and efficiency of the proposed method.

Estimation of Soil Electric Properties and Water Content Through PolSAR Target Decomposition

“…Despite many advantages that can be derived from the knowledge of soil moisture distribution, the measurement of soil moisture has a few limitations. However, the measurement of soil moisture not only depends on target characteristics such as surface roughness, vegetation cover, dielectric constant, and topography but also depends on various combinations of the radar sensor parameters including frequency, polarization, and angle of incidence (θ ) with respect to nadir [9]. The measurements depend on the separation of the effects of water content and other factors such as surface roughness or soil texture which affect the backscattered signal.…”

“…Unfortunately, most of the studies deal with the relationships obtained between the backscattering coefficient and soil moisture for a given set of radar configuration parameters. In [9], the soil moisture is estimated approximately from the microwave backscattering coefficients for the case of bare soil. In [10], soil surface parameters are retrieved from fully polarimetric SAR data.…”

Radar Pulse Compression with Optimized Weighting Window for SAR Receivers

“…Synthetic aperture radar (SAR) can be considered as the most effective land imaging system for earth remote sensing irrespective of the daytime and environmental conditions [1][2][3][4]. High imaging resolution and high performance of land target detection are essential requirements for efficient SAR systems [5].…”