On the Accuracy of Averaging Radar Backscattering Coefficients for Bare Soils Using the Finite-Element Method

Khankhoje, Uday K.; Burgin, Mariko; Moghaddam, Mahta

doi:10.1109/lgrs.2013.2293392

Cited by 4 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We also assume that a given pixel has homogeneous soil moisture and texture composition along each slice of the profile; we note that this is not a fundamental assumption. Spatial heterogeneity in soil characterization can be implemented when computing radar backscattering as given in [15].…”

Section: Introductionmentioning

confidence: 99%

Generalized Terrain Topography in Radar Scattering Models

Burgin

Khankhoje

Duan

et al. 2016

IEEE Trans. Geosci. Remote Sensing

Self Cite

View full text Add to dashboard Cite

Modeling of terrain topography is crucial for vegetated areas given that even small slopes impact and alter the radar wave interactions between the ground and the overlying vegetation. Current missions either exclude pixels with large topographic slopes or disregard the terrain topography entirely, potentially accumulating substantial modeling errors and therefore impacting the retrieval performance over such sloped pixels. The underlying terrain topography needs to be considered and modeled to obtain a truly general and accurate radar scattering model. In this paper, a flexible and modular model is developed: the vegetation is considered by a multilayered multispecies vegetation model capable of representing a wide range of vegetation cover types ranging from bare soil to dense forests. The ground is incorporated with the stabilized extended boundary condition method, allowing the representation of an N -layered soil structure with rough interfaces. Terrain topography is characterized by a 2-D slope with two tilt angles (α, β). Simulation results for an evergreen forest show the impact of a 2-D slope for a range of tilt angles: a 10 • tilt in the plane of incidence translates to a change of up to 15 dB in HH, 10 dB in VV, and 1.5 dB in HV for the total radar backscatter. Terrain topography is shown to be crucial for accurate forward modeling, especially over forested areas.

show abstract

Section: Introductionmentioning

confidence: 99%

Generalized Terrain Topography in Radar Scattering Models

Burgin

Khankhoje

Duan

et al. 2016

IEEE Trans. Geosci. Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…From the aforementioned considerations, it is natural to assume that fields are the larger agricultural extents in which land properties can be regarded as homogeneous. Therefore, a fieldbased retrieval scheme will guarantee the minimal possible soil heterogeneity compatible with the required radiometric uncertainties [3]. For this reason, SAR-based soil moisture estimates are best defined on a field basis.…”

Section: Introductionmentioning

confidence: 99%

Rationale Behind an Optimal Field Experiment to Assess the Suitability of Soil Moisture Retrieval Algorithms for SAR Data

Barber¹,

Grings²,

Bruscantini³

et al. 2015

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

Validation of soil moisture products derived from synthetic aperture radar (SAR) remotely sensed observations involves a comparison against ground-truth data. This validation step helps one to state the performance of competing retrieval algorithms. Nevertheless, the design of a field experiment in the context of SAR retrieval is not straightforward. Ground-based measurements are affected by instrument errors due to both the physical limitations of the measurement technique and the uncertainties related to the spatial variability of the soil moisture. To properly assess the performance of the retrieved estimates, both of the mentioned sources of uncertainties should be considered in the ground-based sampling and in the subsequent error assessment analysis. This letter addresses the rationale behind an optimal field experiment designed to assess the suitability of soil moisture retrieval algorithms.

show abstract

GPU-accelerated Calculation of Acoustic Echo Characteristics of Underwater Targets

Wang

et al. 2020

2020 Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)

View full text Add to dashboard Cite

On the Accuracy of Averaging Radar Backscattering Coefficients for Bare Soils Using the Finite-Element Method

Cited by 4 publications

References 11 publications

Generalized Terrain Topography in Radar Scattering Models

Generalized Terrain Topography in Radar Scattering Models

Rationale Behind an Optimal Field Experiment to Assess the Suitability of Soil Moisture Retrieval Algorithms for SAR Data

GPU-accelerated Calculation of Acoustic Echo Characteristics of Underwater Targets

Contact Info

Product

Resources

About