Effects of Spatial Sampling Interval on Roughness Parameters and Microwave Backscatter over Agricultural Soil Surfaces

Abstract

Abstract:The spatial sampling interval, as related to the ability to digitize a soil profile with a certain number of features per unit length, depends on the profiling technique itself. From a variety of profiling techniques, roughness parameters are estimated at different sampling intervals. Since soil profiles have continuous spectral components, it is clear that roughness parameters are influenced by the sampling interval of the measurement device employed. In this work, we contributed to answer which sampling interval the profiles needed to be measured at to accurately account for the microwave response of agricultural surfaces. For this purpose, a 2-D laser profiler was built and used to measure surface soil roughness at field scale over agricultural sites in Argentina. Sampling intervals ranged from large (50 mm) to small ones (1 mm), with several intermediate values.Large-and intermediate-sampling-interval profiles were synthetically derived from nominal, 1 mm ones. With these data, the effect of sampling-interval-dependent roughness parameters on backscatter response was assessed using the theoretical backscatter model IEM2M. Simulations demonstrated that variations of roughness parameters depended on the working wavelength and was less important at L-band than at C-or X-band. In any case, an underestimation of the backscattering coefficient of about 1-4 dB was observed at larger sampling intervals. As a general rule a sampling interval of 15 mm can be recommended for L-band and 5 mm for C-band.

Influence of Surface Roughness Measurement Scale on Radar Backscattering in Different Agricultural Soils

“…Regarding the influence of small-scale components, the results demonstrate that eliminating these small-scale roughness components from the profiles caused a strong variation in the values of horizontal parameters, while vertical ones were more insensitive. This is in agreement with Barber et al [30] who observed that when the sampling interval increased, s decreased slightly and l increased causing the separability between different roughness classes to decrease. The results also confirm that l values did not stabilize with long profiles, but showed rather an increase in their variability [19], [26].…”

“…Barber et al [30] evaluated the influence of sampling interval on the SSR statistics over agricultural soils and observed that class differences were reduced as the measurement interval increased. They also recommended intervals of 15 and 5 mm for L-and C-bands, respectively.…”

Surface Roughness Estimation in the Orog Nuur Basin (Southern Mongolia) Using Sentinel-1 SAR Time Series and Ground-Based Photogrammetry

“…The dense point cloud was then rotated to the true X, Y, and Z directions using markers that were manually placed on images showing the measuring tapes and assuming Z = 0 for all points (i.e., models then display the surface elevation relative to the plain defined by the two measuring tapes). In the third step, the DEM and the ortho-mosaic were processed with a pixel spacing of 0.2 cm, of 0.1 cm respectively, meeting the sampling interval for C-Band data (0.5 cm) recommended by [44]. Table 2 reports the accuracies of the processed ground-based DEMs in X, Y, and Z direction.…”

Soil Dielectric Constant Estimation Using GNSS Reflectometry Andthe Interference Pattern Technique

“…Usualmente, el método SPM también es usado el límite de su rango de validez, s ∼ 0,05λ , produciendo resultados satisfactorios [9,10,13,14]. En el caso de suelo desnudo y para el rango de microondas en banda L (λ = 25 cm), la condición de validez se cumple si la altura rms de la superficie cumple s < 1,25 cm, lo que es una hipótesis razonable para suelos de agricultura sin vegetación, en donde s ∼ 1 cm [5,6,15].…”

“…En el marco de este esquema, cuando un satélite de la red GPS ilumina una superficie, se genera una señal dispersada que depende, principalmente, de dos aspectos: i) la geometría de la superficie; ii) las características dieléctricas de la misma. Teniendo en cuenta que siempre se trabaja con superficies reales, los perfiles de las mismas no se describen a través de funciones analíticas sino mediante parámetros estadísticos [5]. Cuando se monitorea superficies sin vegetación (suelos desnudos) las características geométricas se definen a través de la altura rms de la superficie (s) y de la función de autocorrelación entre dos puntos de la misma (ρ(x, x )); comúnmente, esta función es una Gaussiana con media cero y una longitud típica, que es la longitud de correlación (l).…”