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Open AccessJournal ArticleDOI

Backscattering Analysis for Snow Remote Sensing Model with Higher Order of Surface-Volume Scattering

Syabeela Syahali, +1 more
- 01 Jan 2016 - 
- Vol. 48, pp 25-36
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TLDR
In this article, the effect of including multiple surface scattering and additional surface-volume scattering up to second order in the backscattering coefficient calculation of snow layer is studied for co-polarized and crosspolarised returns.
Abstract
The study of earth terrain in Antarctica is important as this region has a direct impact on global environment and weather condition. There have been many research works in developing remote sensing technologies, as it can be used as an earth observation technique to monitor the polar region [11, 15]. In previous studies, remote sensing forward model has been developed to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. This paper is an extended work from previous studies [16–19], where an improved theoretical model to study polar region was developed. Multiple-surface scattering, based on an existing integral equation model (IEM) that calculates surface scattering and additional second-order surface-volume scattering, were added in the model from prior research works [7] for improvement in the backscattering calculation. We present herein the application of this model on a snow layer above ground which is modeled as a volume of ice particles that are closely packed and bounded by irregular boundaries above a homogenous half space. The effect of including multiple surface scattering and additional surface-volume scattering up to second order in the backscattering coefficient calculation of snow layer is studied for co-polarized and cross-polarized returns. Comparisons with satellite data are also done for validation. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the snow layer and should not be ignored in polar research.

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Citations
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Journal ArticleDOI

Multifrequency Microwave Backscatter From a Highly Saline Snow Cover on Smooth First-Year Sea Ice: First-Order Theoretical Modeling

TL;DR: The paper represents an evolution in a theoretical understanding on how an active microwave approach using multiple frequencies can be further utilized toward the development of snow thickness and/or snow water equivalent algorithm on smooth FYI.

Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing

TL;DR: In this article, images from satellite based Synthetic Aperture Radar (SAR) are acquired to provide ground information about various types of earth terrain sensed (such as vegetation, farm, urban area, sea ice and snow covered land, etc).
Journal ArticleDOI

Backscattering Analysis Utilizing Relaxed Hierarchical Equivalent Source Algorithm (RHESA) for Scatterers in Vegetation Medium

TL;DR: In this paper , the backscattering cross section of cylindrical and elliptical disk-shaped scatterers was investigated using a new numerical solution method called the relaxed hierarchical equivalent source algorithm (RHESA).
Proceedings ArticleDOI

Understanding the Correlation in Scattering Mechanisms Between H-Alpha Decomposition and Theoretical Modelling

TL;DR: In this article, the authors used theoretical model simulation to study the wave interaction with different terrain cover as well as the expected backscatter results for SAR images, and a study of the correlation of these theoretical results based on basic scattering mechanisms is conducted with the associated scattering mechanisms indicated in the $H$ -Alpha Decomposition which is a method commonly used in SAR image classification.
Proceedings Article

Radar backscatter from a dense discrete random medium : Remote sensing for a sustainable future

TL;DR: In this paper, a dense medium phase matrix based on the concept of random lattice perturbation is employed in the radiative transfer theory to calculate the co-and cross-polarized backscatter from a layer of randomly distributed spherical scatterers.
References
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Book

Microwave Scattering and Emission Models and their Applications

TL;DR: First-order radiative transfer solution passive sensing formulation of the surface scattering problem surface model and special cases ranges validity of the IEM model matrix doubling formulations for scattering and emission scattering and emissions models for snow and sea ice comparisons of model predictions with backscattering and emission measurements from snow and ice.
Journal ArticleDOI

Attenuation constant of a coherent field in a dense distribution of particles

TL;DR: In this article, the authors present an optical experimental study to show that, when the particle density is greater than about 0.1, the attenuation constant departs markedly from the formula based on an uncorrected scatter assumption.
Journal ArticleDOI

A reappraisal of the validity of the IEM model for backscattering from rough surfaces

TL;DR: The results of comparisons with both the numerical simulations and measurements for the backscattering case indicate that the IEM is improved, becoming more accurate and practical to use.
Journal ArticleDOI

Dense medium radiative transfer theory: comparison with experiment and application to microwave remote sensing and polarimetry

TL;DR: In this paper, the authors used the dense medium radiative transfer theory to study the multiple scattering of electromagnetic waves in a slab containing densely distributed spherical particles overlying a homogeneous half-space.
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