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Journal ArticleDOI

An empirical model and an inversion technique for radar scattering from bare soil surfaces

TLDR
An inversion technique was developed for predicting the rms height of the surface and its moisture content from multipolarized radar observations, which was found to yield very good agreement with the backscattering measurements of the present study.
Abstract
Polarimetric radar measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10 degrees to 70 degrees . Using a laser profiler and dielectric probes, a complete and accurate set of ground truth data was collected for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. Based on knowledge of the scattering behavior in limiting cases and the experimental observations, an empirical model was developed for sigma degrees /sub hh/, sigma degrees /sub vv/, and sigma degrees /sub hv/ in terms of ks (where k=2 pi / lambda is the wave number and s is the rms height) and the relative dielectric constant of the soil surface. The model, which was found to yield very good agreement with the backscattering measurements of the present study as well as with measurements reported in other investigations, was used to develop an inversion technique for predicting the rms height of the surface and its moisture content from multipolarized radar observations. >

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Citations
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Journal ArticleDOI

Measuring soil moisture with imaging radars

TL;DR: An empirical algorithm for the retrieval of soil moisture content and surface root mean square (RMS) height from remotely sensed radar data was developed using scatterometer data and inversion results indicate that significant amounts of vegetation cause the algorithm to underestimate soil moisture and overestimate RMS height.
Journal ArticleDOI

Inversion of surface parameters from polarimetric SAR

TL;DR: It demonstrates how three polarimetric parameters, namely the scattering entropy, the scattering anisotropy, and the alpha angle may be used in order to decouple surface roughness from moisture content estimation offering the possibility of a straightforward inversion of these two surface parameters.
Journal ArticleDOI

Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data

TL;DR: Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground.
Journal ArticleDOI

Operational readiness of microwave remote sensing of soil moisture for hydrologic applications

TL;DR: In this article, the authors reviewed recent progress made with retrieving surface soil moisture from three types of microwave sensors -radiometers, Synthetic Aperture Radars (SARs), and scatterometers.
Journal ArticleDOI

An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations

TL;DR: The WARP5 algorithm results in a more robust and spatially uniform soil moisture product, thanks to its new processing elements, including a method for the correction of azimuthal anisotropy of backscatter, a comprehensive noise model, and new techniques for calculation of the model parameters.
References
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Book

The scattering of electromagnetic waves from rough surfaces

TL;DR: The scattering of electromagnetic waves from rough surfaces PDF is available at the online library of the University of Southern California as mentioned in this paper, where a complete collection of electromagnetic wave from rough surface books can be found.
Journal ArticleDOI

Microwave Dielectric Behavior of Wet Soil-Part 1: Empirical Models and Experimental Observations

TL;DR: In this article, the authors evaluate the microwave dielectric behavior of soil-water mixtures as a function of water content, temperature, and soil textural composition, and present two mixing models to account for the observed behavior: 1) a semi-empirical refractive mixing model that accurately describes the data and requires only volumetric moisture and soil texture as inputs, and 2) a theoretical four-component mixing model explicitly accounts for the presence of bound water.
Journal ArticleDOI

Backscattering from a Gaussian-distributed perfectly conducting rough surface

TL;DR: In this article, an analytical approach to the problem of scattering by composite random surfaces is presented, where the surface is assumed to be Gaussian so that the surface height can be split (in the mean-square sense) into large and small scale components relative to the electromagnetic wavelength, and a first-order perturbation approach developed by Burrows is used wherein the scattering solution for the large-scale structure is perturbed by the small-scale diffraction effects.
Journal ArticleDOI

A convenient technique for polarimetric calibration of single-antenna radar systems

TL;DR: In this paper, a calibration target such as a conducting sphere or a trihedral corner reflector is used to calibrate the radar system, both in amplitude and phase, for all linear polarization configurations.
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