Rigorous solutions for electromagnetic scattering from rough surfaces

Saillard, Marc; Sentenac, Anne

doi:10.1080/13616670109409779

Cited by 88 publications

(74 citation statements)

References 70 publications

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“…All higher order correlations can be expressed in terms of the (second order) autocorrelation function, which simplifies modelling the surface scattering process. A simple and often used form for the www.intechopen.com autocorrelation is the Gaussian function but other forms have also been studied (Saillard & Sentenac, 2001). …”

Section: Random Surface Componentmentioning

confidence: 99%

Power of Laser Target Signal from Rough Earth Surface in Hazy Atmosphere

Белов¹,

Городничев²,

Alekhin³

2017

HoBMSTU.SIE

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Section: Random Surface Componentmentioning

confidence: 99%

Power of Laser Target Signal from Rough Earth Surface in Hazy Atmosphere

Белов¹,

Городничев²,

Alekhin³

2017

HoBMSTU.SIE

View full text Add to dashboard Cite

“…All higher order correlations can be expressed in terms of the (second order) autocorrelation function, which simplifies modelling the surface scattering process. A simple and often used form for the autocorrelation is the Gaussian function but other forms have also been studied (Saillard & Sentenac, 2001). …”

Section: Random Surface Componentmentioning

confidence: 99%

Models for Scattering from Rough Surfaces

Ticconi¹,

Pulvirenti²,

Pierdicca³

2011

Electromagnetic Waves

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“…The second class of electromagnetic models relies on numerical methods for solving Maxwell's equations and boundary conditions [6][7][8]. These models are so called exact if no physical approximation is made.…”

Section: Data Sar -Electromagnetic Models and Soil Modelling: Positiomentioning

confidence: 99%

“…The electromagnetic modeling is a valuable tool for radar data inversion to intend to characterize the roughness and / or the humidity of agricultural soils. The electromagnetic models based on the Maxwell's equations and the boundary conditions can be classified into two categories: analytical models [5] and numerical models [6][7][8][9].…”

Section: Data Sar -Electromagnetic Models and Soil Modelling: Positiomentioning

confidence: 99%

Statistical Characterization of Bare Soil Surface Microrelief

Vannier¹,

Taconet²,

Dusséaux³

et al. 2014

Advanced Geoscience Remote Sensing

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Because the soil surface occurs at the boundary between the atmosphere and the pedosphere, it plays an important role for geomorphologic processes. Roughness of soil surface is a key parameter to understand soil properties and physical processes related to substrate movement, water infiltration or runoff, and soil erosion. It has been noted by many authors that most of the soil surface and water interaction processes have characteristic lengths in millimeter scales. Soil irregularities at small scale, such as aggregates, clods and interrill depressions, influence water outflow and infiltration rate. They undergo rapid changes caused by farming imple‐ ments, followed by a slow evolution due to rainfall events. Another objective of soil surface roughness study is investigating the effects of different tillage implements on soil physical properties (friability, compaction, fragmentation and water content) to obtain an optimal crop emergence. Seedbed preparation focuses on the creation of fine aggregates and the size distribution of aggregates and clods produced by tillage operations is frequently measured. Active microwave remote sensing allows potential monitoring of soil surface roughness or moisture retrieving at field scale using space-based Synthetic Aperture Radars (SAR) with high spatial resolution (metric or decametric). The scattering of microwaves depends on several surface characteristics as well as on imagery configuration. The SAR signal is very sensitive to soil surface irregularities and structures (clod arrangement, furrows) and moisture content in the first few centimeters of soil (depending on the radar wavelength). In order to link the remote sensing observations to scattering physical models as well as for modelling purpose, key features of the soil microtopography should be characterized. However, this characteri‐ zation is not fully understood and some dispersion of roughness parameters can be observed in the same field according to the methodology used. It seems also, that when describing surface roughness as a whole, some information related to structured elements of the micro‐ topography is lost

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Rigorous solutions for electromagnetic scattering from rough surfaces

Cited by 88 publications

References 70 publications

Power of Laser Target Signal from Rough Earth Surface in Hazy Atmosphere

Power of Laser Target Signal from Rough Earth Surface in Hazy Atmosphere

Models for Scattering from Rough Surfaces

Statistical Characterization of Bare Soil Surface Microrelief

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