scholarly journals Fast Derivation of Soil Surface Roughness Parameters Using Multi-band SAR Imagery and the Integral Equation Model

2010 ◽  
Author(s):  
Benjamin Seppke ◽  
Leonie Dreschler-Fischer ◽  
Jo-Ann Heiming ◽  
Felix Wengenroth
Keyword(s):  
Integral Equation ◽  
Surface Roughness ◽  
Soil Surface ◽  
Equation Model ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Soil Surface Roughness ◽  
Sar Imagery ◽  
Multi Band

scholarly journals Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

2010 ◽  
Vol 7 (4) ◽  
pp. 4995-5031 ◽  
Author(s):  
H. Lievens ◽  
N. E. C. Verhoest ◽  
E. De Keyser ◽  
H. Vernieuwe ◽  
P. Matgen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
State Of The Art ◽  
Incidence Angle ◽  
Soil Surface ◽  
Equation Model ◽  
Roughness Parameters ◽  
Effective Roughness ◽  
Soil Surface Roughness ◽  
L Band ◽  
Microwave Backscatter

Abstract. Soil moisture retrieval from Synthetic Aperture Radar (SAR) using state-of-the-art backscatter models is not yet fully operational at present, mainly due to difficulties involved in the parameterisation of soil surface roughness. Recently, increasing interest has been drawn to the use of calibrated or effective roughness parameters, as they circumvent issues known to the parameterisation of field-measured roughness. This paper analyses effective roughness parameters derived from C- and L-band SAR observations over a large number of agricultural seedbed sites in Europe and furthermore shows that parameters may largely differ between SAR acquisitions, as they are related to the observed backscatter coefficients and variations in the local incidence angle. Therefore, a statistical model is developed that allows the estimation of effective roughness parameters from microwave backscatter observations. Subsequently, these parameters can be propagated through the Integral Equation Model (IEM) for soil moisture retrieval. It is shown that fairly accurate soil moisture results are obtained both at C- and L-band, with an RMSE ranging between 4 vol% and 6.5 vol%.

scholarly journals Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

2011 ◽  
Vol 15 (1) ◽  
pp. 151-162 ◽  
Author(s):  
H. Lievens ◽  
N. E. C. Verhoest ◽  
E. De Keyser ◽  
H. Vernieuwe ◽  
P. Matgen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Incidence Angle ◽  
Soil Surface ◽  
Equation Model ◽  
Roughness Parameters ◽  
Effective Roughness ◽  
Soil Surface Roughness ◽  
L Band ◽  
Microwave Backscatter ◽  
Param Eters

Abstract. Soil moisture retrieval from Synthetic Aperture Radar (SAR) using state-of-the-art back\\-scatter models is not fully operational at present, mainly due to difficulties involved in the parameterisation of soil surface roughness. Recently, increasing interest has been drawn to the use of calibrated or effective roughness parameters, as they circumvent issues known to the parameterisation of field-measured roughness. This paper analyses effective roughness parameters derived from C- and L-band SAR observations over a large number of agricultural seedbed sites in Europe. It shows that param\\-eters may largely differ between SAR acquisitions, as they are related to the observed backscatter coefficients and variations in the local incidence angle. Therefore, a statistical model is developed that allows for estimating effective roughness parameters from microwave backscatter observations. Subsequently, these parameters can be propagated through the Integral Equation Model (IEM) for soil moisture retrieval. It is shown that fairly accurate soil moisture results are obtained both at C- and L-band, with an RMSE ranging between 4 vol% and 6.5 vol%.

scholarly journals Effect of tillage, slope, and rainfall on soil surface microtopography quantified by geostatistical and fractal indices during sheet erosion

2020 ◽  
Vol 12 (1) ◽  
pp. 232-241
Author(s):  
Na Ta ◽  
Chutian Zhang ◽  
Hongru Ding ◽  
Qingfeng Zhang
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Soil Surface ◽  
Rainfall Events ◽  
Tillage Practices ◽  
Surface Microtopography ◽  
Artificial Rainfall ◽  
Soil Surface Roughness ◽  
The Difference ◽  
Sheet Erosion

AbstractTillage and slope will influence soil surface roughness that changes during rainfall events. This study tests this effect under controlled conditions quantified by geostatistical and fractal indices. When four commonly adopted tillage practices, namely, artificial backhoe (AB), artificial digging (AD), contour tillage (CT), and linear slope (CK), were prepared on soil surfaces at 2 × 1 × 0.5 m soil pans at 5°, 10°, or 20° slope gradients, artificial rainfall with an intensity of 60 or 90 mm h−1 was applied to it. Measurements of the difference in elevation points of the surface profiles were taken before rainfall and after rainfall events for sheet erosion. Tillage practices had a relationship with fractal indices that the surface treated with CT exhibited the biggest fractal dimension D value, followed by the surfaces AD, AB, and CK. Surfaces under a stronger rainfall tended to have a greater D value. Tillage treatments affected anisotropy differently and the surface CT had the strongest effect on anisotropy, followed by the surfaces AD, AB, and CK. A steeper surface would have less effect on anisotropy. Since the surface CT had the strongest effect on spatial variability or the weakest spatial autocorrelation, it had the smallest effect on runoff and sediment yield. Therefore, tillage CT could make a better tillage practice of conserving water and soil. Simultaneously, changes in semivariogram and fractal parameters for surface roughness were examined and evaluated. Fractal parameter – crossover length l – is more sensitive than fractal dimension D to rainfall action to describe vertical differences in soil surface roughness evolution.

scholarly journals Estimation of Soil Surface Roughness Using Stereo Vision Approach

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4386
Author(s):  
Afshin Azizi ◽  
Yousef Abbaspour-Gilandeh ◽  
Tarahom Mesri-Gundoshmian ◽  
Aitazaz A. Farooque ◽  
Hassan Afzaal
Keyword(s):  
Surface Roughness ◽  
Stereo Vision ◽  
Agricultural Soils ◽  
Depth Map ◽  
Soil Surface ◽  
Regression Equations ◽  
Height Profile ◽  
Peak Fitting ◽  
Soil Surface Roughness ◽  
Tillage Operations

Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness formed on the agricultural soils. Additionally, soil till quality was investigated by analyzing the height of plow layers. An image dataset was provided in the real conditions of the field. For determining the soil surface roughness, the elevation of clods obtained from tillage operations was computed using a depth map. This map was obtained by extracting and matching corresponding keypoints as super pixels of images. Regression equations and coefficients of determination between the measured and estimated values indicate that the proposed method has a strong potential for the estimation of soil shallow roughness as an important physical parameter in tillage operations. In addition, peak fitting of tilled layers was applied to the height profile to evaluate the till quality. The results of this suggest that the peak fitting is an effective method of judging tillage quality in the fields.

Effect of species and grinding disc distance on the surface roughness parameters of medium density fiberboard

2016 ◽  
Vol 75 (3) ◽  
pp. 335-346 ◽  
Author(s):  
Lidia Gurau ◽  
Nadir Ayrilmis ◽  
Jan Thore Benthien ◽  
Martin Ohlmeyer ◽  
Manja Kitek Kuzman ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Medium Density Fiberboard ◽  
Medium Density ◽  
Roughness Parameters ◽  
Surface Roughness Parameters
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