Improved estimation of soil clay content by the fusion of remote hyperspectral and proximal geophysical sensing

Ciampalini, Andrea; André, Frédéric; Garfagnoli, Francesca; Grandjean, Gilles; Lambot, Sébastien; Chiarantini, Leandro; Moretti, Sandro

doi:10.1016/j.jappgeo.2015.03.009

Cited by 30 publications

(17 citation statements)

References 51 publications

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“…Gravimetric measurements (especially time‐lapse) can be useful to constrain estimates of hydraulic states and fluxes (Blainey et al, ). The hyperspectral method uses the light reflected by the soil, which in turn is determined by its composition (texture, organic matter, and salinity) and could be useful to improve estimates of related properties (e.g., clay content) over large areas (Ciampalini et al, ).…”

Section: Geophysical Methods In Soil Sciencementioning

confidence: 99%

A Review of Geophysical Methods for Soil Structure Characterization

Romero-Ruiz

Linde

Keller

et al. 2018

Reviews of Geophysics

126

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The growing interest in the maintenance of favorable soil structure is largely motivated by its central role in plant growth, soil ecological functioning, and impacts on surface water and energy fluxes. Soil structure pertains to the spatial arrangement of voids and solid constituents, their aggregation, and mechanical state. As a fragile product of soil biological activity that includes invisible ingredients (mechanical and ecological states), soil structure is difficult to define rigorously, and measurements of relevant metrics often rely on core samples or on episodic point measurements. The presence of soil structure has not yet been explicitly incorporated in climate and Earth systems models, partially due to incomplete methodological means to characterize it at relevant scales and to parameterize it in spatially extensive models. We seek to review the potential of harnessing geophysical methods to fill the scale gap in characterization of soil structure directly (via impact of soil pores, transport, and mechanical properties on geophysical signals) or indirectly by measurement of surrogate variables (wetness and rates of drainage). We review basic aspects of soil structure and challenges of characterization across spatial and temporal scales and how geophysical methods could be used for the task. Additionally, we propose the use of geophysical models, inversion techniques, and combination of geophysical methods for extracting soil structure information at previously unexplored spatial and temporal scales.

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Section: Geophysical Methods In Soil Sciencementioning

confidence: 99%

A Review of Geophysical Methods for Soil Structure Characterization

Romero-Ruiz

Linde

Keller

et al. 2018

Reviews of Geophysics

126

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“…Campos et al (2016) used this technique to analyze groundwater depth and the influence of geological structure on water flow. Several studies have been developed to analyze soil compaction, map shallow soils, and prevent damage during its implementation (Ciampalini et al, 2015;Campos et al, 2016). In addition, this equipment has been used to monitor moisture content and water infiltration in irrigated fields (Rossi et al, 2015;Tran et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Use of Ground Penetrating Radar to Study Spatial Variability and Soil Stratigraphy

Campos

Vidal‐Torrado²,

Modolo

2019

Eng. Agríc.

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Ground Penetrating Radar (GPR) is a geophysical method that uses electromagnetic waves to study subsurface structure in different fields such as geology, agriculture and civil engineering. The wave penetration in the soil is strongly controlled by the electrical conductivity of soil components such as clay, organic matter, and water. In this study, tests were conducted in a floodplain in the Elizabeth Creek watershed (New Jersey-USA). We established one transect where measurements were completed using two techniques, common mid point (CMP) and constant offset profile (COP), both with 100-MHz frequency antennas. Measurements were also completed using 250 and 500 MHz shielded antennas. GPR showed good accuracy to study soil spatial variability and stratigraphy. Antennas of a higher frequency had less vertical investigation capacity and greater accuracy. In this study, it was not possible to clearly differentiate signals from organic matter and clay; this was the main limitation of the GPR system.

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“…However, the relationships between soil properties and environmental factors are uncertain in large regions and inconspicuous in small or field-scale regions [16,17]. Consequently, environmental factors cannot offer accurate auxiliary information for the spatial unbiasedness of soil properties, especially in field or local regions [18].…”

Section: Introductionmentioning

confidence: 99%

“…Laboratorial or field VNIR reflectance spectroscopy is a valuable technique used to predict SOC [17,22]. Hyperspectral sensors placed on fixed-wing aircraft or helicopters can perform spatially continuous mapping with high spatial resolution, and spectral reflectance can capture the valuable information of topsoil [18]. Many studies have indicated the potential of airborne or satellite hyperspectral images in the prediction of topsoil SOC or other properties [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

“…Many studies have indicated the potential of airborne or satellite hyperspectral images in the prediction of topsoil SOC or other properties [23][24][25][26]. Ciampalini, et al [18] used the prototypal multisensor hyperspectral system produced by Galileo Avionica, which consists of two electro-optical heads in VNIR and short-wavelength infrared (SWIR) spectral range (from 400 nm to 24,500 nm, over 700 bands) to obtain the hyperspectral images. Their study showed the ability of airborne hyperspectral data from relatively inexpensive and efficient sensing methods for producing reliable and high-resolution maps of clay content.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Sensitivity of Sampling Density in Digital Mapping of Soil Organic Carbon and Its Application in Soil Sampling

et al. 2018

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The rapid monitoring and accurate estimation of dynamic changes in soil organic carbon (SOC) can make great efforts in understanding the global carbon cycle. Traditional field survey is the main approach to obtain soil data and measure SOC content. However, the limited number of soil samples and the sampling cost hinder the quality of digital soil mapping. This research aims to explore the sensitive of sampling density in digital soil mapping, and then design a suitable soil sampling plan based on a series of sampling indices. Headwall hyperspectral images (400-1700 nm) were used to estimate the SOC map by partial least squares regression (PLSR) and PLSR kriging (PLSRK). Three traditional soil sampling methods (random, grid, and Latin hypercube sampling) with 10 classes of sampling densities (6.26, 2.79, 1.57, 1.01, 0.69, 0.53, 0.39, 0.30, 0.26, and 0.20 ha −1) were designed. The R 2 , root mean square error (RMSE) and ratio of standard deviation to RMSE (RPD) were used to evaluate the prediction accuracy in digital soil mapping by ordinary kriging. Three new indices, namely, the ratio of sampling efficiency to performance (RSEP), the density of soil samples index and the comprehensive evaluation index of prediction accuracy, were used to select a suitable soil sampling plan. Results showed that (1) the prediction accuracy of PLSRK (RPD = 2.00) was higher by approximately 11.73% than that of PLSR (RPD = 1.79), and the hyperspectral images provided an actual referential SOC map for the study of soil sampling; (2) the grid sampling plan performed better than the random and Latin hypercube sampling methods, and the quality of SOC map improves with the increase of the sampling density, and (3) the computer simulation and field verification indicated that RSEP is one feasible index in designing a suitable soil sampling plan.

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Improved estimation of soil clay content by the fusion of remote hyperspectral and proximal geophysical sensing

Cited by 30 publications

References 51 publications

A Review of Geophysical Methods for Soil Structure Characterization

A Review of Geophysical Methods for Soil Structure Characterization

Use of Ground Penetrating Radar to Study Spatial Variability and Soil Stratigraphy

Exploring the Sensitivity of Sampling Density in Digital Mapping of Soil Organic Carbon and Its Application in Soil Sampling

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