Soil Dielectric Permittivity Research Articles

Effect of soil compaction on the measurements of complex dielectric permittivity spectrum with an open-ended antenna probe and the coaxial cell system

The paper proposes the use of dielectric spectroscopy to measure changes in dielectric permittivity for soil subjected to compression. Density-dependent dielectric permittivity characteristics of soils for the entire range of obtained density, and thus for a significant parameter of soil properties corresponding with ideal conditions for plant growth as well as those inhibiting their growth were presented. Measurements were carried out for three soil types with different moisture content using an open-ended antenna probe (OE-A), operating in the frequency range of 20 MHz–1.2 GHz and a coaxial cell system in frequency range of 20 MHz–3 GHz. Experimental results showed that an increase in bulk density and volumetric water content of soil affects the complex dielectric permittivity spectrum – a model for this relationship was proposed. Soil dielectric permittivity as a parameter reflecting soil moisture and density can be useful in assessing soil quality.

ANALYSIS OF LANDMINE DETECTION METHODS AND THE IMPORTANCE OF STUDYING SOIL PROPERTIES FOR THEIR EFFECTIVE APPLICATION

The review attempts to analyze the problem of mine detection and outline the prospects for using soil properties that are useful in detecting explosive objects and creating new algorithms for processing relevant data. The article analyzes five main areas in which modern landmine detection technologies are divided. Their main advantages and disadvantages are identified. Using the example of metal detectors and ground-penetrating radar technology, the necessity of a detailed study of the main physical properties of soils is justified, which will enable more efficient use of appropriate technologies for detecting landmines. Keywords: methods of mine detection, sensors, physical properties of soil, magnetic susceptibility of soil, electrical conductivity of soil, dielectric permittivity of soil, soil moisture

Detection of hydrocarbon spills by means of a coaxial impedance dielectric sensor

Leakages from storage tanks or pipes frequently produce pollution of soils and groundwater reservoirs by hydrocarbons. Common practices for monitoring and characterising site contamination involve soil drilling, sampling and chemical analysis, complemented with geophysical surveys. This study evaluates the presence of paraffin oil inside soil pores by means of dielectric permittivity measurements, using a coaxial impedance device in laboratory-scale models. The real dielectric permittivity of unsaturated sand is measured before, during and after a contamination process. Monitoring small variations in real dielectric permittivity allows detection of the partial replacement of air (κ′ = 1) by paraffin oil (κ′ ≈ 2) in soil pores. These variations in soil dielectric properties enable pollution levels to be assessed, knowing in advance the κ′ of the soil at the initial stage and measuring the influence of oil and water content on κ′. The technique proposed can also be used for monitoring the lateral extension of a contaminant plume and can be successfully applied at the laboratory scale for oil leakage detection by periodically monitoring changes in the soil dielectric permittivity.

Experimental Study on the Variation of Soil Dielectric Permittivity under the Influence of Soil Compaction and Water Content

The dielectric permittivity of common soils is mainly controlled by water content and porosity, while the latter is closely related to the characteristics of compaction. By studying the changes in dielectric permittivity of soil samples with different soil water content and compaction levels, the influence of the controlling factors on the relationship model between soil water content and dielectric permittivity can be evaluated. In this paper, network analyzer was used to measure the dielectric permittivity of 7 groups of soil samples with gravimetric water content ranging from 8.09% to 14.52% and dry density ranging from 1.61 g/cm3 to 1.96 g/cm3. The results show that the dielectric permittivity increases with the increase of water content and dry density, and the effect of water content on permittivity is more significant for soils with higher dry density. Furthermore, when the water content is less than or equal to the optimal water content, Topp formula and the complex refractive index model (CRIM) can better predict the soil dry density. When the water content approaches the saturated state of soil, there is a deviation between the predicted value and the actual value. At last, the modified Topp formula and the complex refractive index model (CRIM) can accurately predict soil compactness. This provides an important basis for rapid detection of water content and compactness of highway subgrade soil by ground penetrating radar.

Sensor-free Soil Moisture Sensing Using LoRa Signals

Soil moisture sensing is one of the most important components in smart agriculture. It plays a critical role in increasing crop yields and reducing water waste. However, existing commercial soil moisture sensors are either expensive or inaccurate, limiting their real-world deployment. In this paper, we utilize wide-area LoRa signals to sense soil moisture without a need of dedicated soil moisture sensors. Different from traditional usage of LoRa in smart agriculture which is only for sensor data transmission, we leverage LoRa signal itself as a powerful sensing tool. The key insight is that the dielectric permittivity of soil which is closely related to soil moisture can be obtained from phase readings of LoRa signals. Therefore, antennas of a LoRa node can be placed in the soil to capture signal phase readings for soil moisture measurements. Though promising, it is non-trivial to extract accurate phase information due to unsynchronization of LoRa transmitter and receiver. In this work, we propose to include a low-cost switch to equip the LoRa node with two antennas to address the issue. We develop a delicate chirp ratio approach to cancel out the phase offset caused by transceiver unsynchronization to extract accurate phase information. The proposed system design has multiple unique advantages including high accuracy, robustness against motion interference and large sensing range for large-scale deployment in smart agriculture. Experiments with commodity LoRa nodes show that our system can accurately estimate soil moisture at an average error of 3.1%, achieving a performance comparable to high-end commodity soil moisture sensors. Field studies show that the proposed system can accurately sense soil moisture even when the LoRa gateway is 100 m away from the LoRa node, enabling wide-area soil moisture sensing for the first time.

Effectiveness of Electrostatic Shielding in High-Frequency Electromagnetic Induction Soil Sensing.

High-frequency electromagnetic induction (HFEMI) sensors, operating in the frequency range from 300 kHz to 30 MHz, have been proposed for the measurement of soil electrical conductivity and dielectric permittivity that are related to the physical and chemical properties of soil. Because of the high-frequency operation, the capacitive coupling between the sensor transmitter and receiver coils is comparable to inductive coupling, creating the need for electrostatic shielding. The remnant capacitive coupling after the implementation of shielding can lead to significant difficulties in the sensor signal interpretation, because both coupling mechanisms are highly dependent on the geometry of the HFEMI sensor and applied shield. In this paper, we introduce the discussion on the relationship between the sensor geometry, shielding and the coupling mechanisms for HFEMI soil sensing. We theoretically and experimentally evaluate a typical HFEMI sensor and its shielding in the frequency range of up to 20 MHz and propose a method for evaluating the effectiveness of a shield configuration. In the case study, we experimentally analyze the HFEMI sensor above a saline solution for two shield configurations. The results agree well with the results of a finite element method analysis.

Dielectric models for moisture determination of soils with variable organic matter content

An accurate calibration function relating soil dielectric permittivity to its volumetric water content is essential for reliable measurements of soil moisture with the use of dielectric sensors. In the operational frequency range of popular capacitance and impedance sensors, various soil properties may influence the relation between the soil moisture and dielectric permittivity, which may worsen the measurement accuracy of a sensor. The aim of this paper is to investigate the relations among the organic matter content, dry bulk density, volumetric water content and dielectric permittivity in the 10–500 MHz frequency range, which covers the frequency range of operation of common soil moisture dielectric sensors operating in the frequency domain. Samples of soil material of belonging to sand, sandy loam and silt loam texture classes with varied organic matter content were measured with the use of a coaxial-like open-ended seven-rod probe connected to a vector-network-analyzer. A new simplified dielectric model is presented in order to accurately describe the obtained spectra. Next, several models connecting the real part of dielectric permittivity and volumetric water content, taking account of the impact of bulk density, were examined. It was found that two linear segmented models fitted to the obtained data better in the case of soil materials of sandy loam and silt loam textures. The best segmented model exhibited RMSE of about 0.023 m3 m−3 in comparison to about 0.04 m3 m−3 in the case of a simple linear model without density correction.

Application of a dagger probe for soil dielectric permittivity measurement by TDR

The most basic parameter of soil is volumetric water content (VWC). This parameter is typically determined indirectly, based on other parameters. Currently, a widely used method for indirect VWC determination is a method which is based on soil dielectric permittivity (DP) measurement, using the well-known Topp formula. The paper presents a novel probe for soil VWC and electrical conductivity (EC) measurement employing the above method. The new probe is going to be adopted on a mobile plant-watering machines used in precise agriculture e.g. for plants watering, thus it features a robust mechanical design and allows for instantaneous readout of VWC and EC values. The design of the probe mimics a dagger with three flat conductors forming a short-circuited coplanar waveguide with the space between the conductors filled with a mineral cold-curing resin. The resin filling the space between the bars improves the mechanical stiffness of the probe and ensures constant electrical parameters, which increases the measurement accuracy. In the first step, Ansys HFSS software was used to perform electromagnetic (EM), numerical simulations for the proposed solution, in order to determine the optimal electrical parameters of the probe. Next, a probe prototype was made to carry out laboratory tests. The measurements were performed with the use of a vector network analyzer (VNA) in the frequency range (3.74 MHz − 3 GHz). The measured complex reflection coefficients were transformed into the time domain with the use of the inverse Discrete Fourier Transform (IDFT). Based on the time distance between the reflections of an electric pulse traveling along the probe's sensing element, bulk dielectric permittivity of soil surrounding the probe can be calculated. A linear relation between the square root of DP and the pulse propagation time was obtained. Also, the probe was calibrated for bulk electrical conductivity measurements.

Detection of ionic contaminants in unsaturated soils using time domain reflectometry penetrometer

Previous investigations using time domain reflectometry (TDR) to detect ionic contaminants has mainly focused on saturated coarse-grained soils and conventional probes (e.g., coaxial, two- or three-rod probe). To explore the applicability of using the TDR penetrometer for the site investigation of ionically contaminated land, a theoretical framework was proposed to estimate the pore water electrical conductivity of both saturated and unsaturated silts based on measured soil dielectric permittivity and bulk electrical conductivity. The theoretical framework consists of three equations, the empirical equation relating soil dielectric permittivity and volumetric water content, the soil dielectric mixing model, and the modified Archie’s law considering the surface conductivity. To verify the theoretical framework, chamber tests using the TDR penetrometer were performed to detect CuSO4 contaminants in silt columns. Results show that the theoretical framework provides an increasingly better calculation of the pore water electrical conductivity of saturated and unsaturated silt with increasing the concentration of CuSO4 solution. This is because that the modified Archie’s law with a constant surface conductivity in the theoretical framework can well capture the relationship between soil bulk electrical conductivity and pore water electrical conductivity at high solution concentrations (i.e., 0.015 and 0.030 mol/L CuSO4 solutions), but not at low solution concentrations (i.e., tap water). The theoretical framework and chamber tests are expected to provide scientific guidance for extending the capacity of TDR penetrometer to the site investigation of ionically contaminated land.

The Arctic soils dielectric characteristics

The state of the underlying surface has a noticeable effect on the process of emission and propagation of radio waves. The state of the underlying surface is dependent on the value of the complex dielectric permittivity. Usually, the underlying surface is understood as soil or ground medium. The Dobson model is recommended by the International Telecommunication Union (ITU) for calculating the dielectric permittivity of moist soils over a wide frequency range. However, this model was developed based on experimental data obtained at frequencies above 1 GHz for soils of the temperate climatic zone. This paper presents the results of measuring the complex dielectric permittivity of the Arctic region soils sample at the frequency range from 1 MHz to 8 GHz. Also, we compared the dielectric permittivity data measured in laboratory conditions and calculated by the Dobson model. It was found that the Arctic soil dielectric permittivity data measured under laboratory conditions and calculated using the Dobson model differ markedly from each other, which indicates the impossibility of using the Dobson model for calculating soil dielectric permittivity of the Arctic region. The data obtained in the laboratories case may be used to estimate the directional characteristics of near-surface emissivity systems, as well as of the ground wave propagation prediction in the Arctic region.

Performance evaluation and calibration of capacitance sensor for estimating the salinity of reclaimed land

Generally, soil moisture and salinity in reclaimed land are monitored using soil dielectric sensors such as time domain reflectometry, frequency domain reflectometry, and capacitance. The soil dielectric sensor measures apparent dielectric permittivity. However, apparent dielectric permittivity is affected by soil moisture, salinity, and texture. In this study, performance evaluation and calibration of a dielectric sensor (5TE; METER Group, Inc., Pullman, WA, USA) for monitoring soil salinity were performed. Laboratory calibration tests were completed, incorporating various levels of dry density, water content, and salinity. The soil salinity was determined by the electrical conductivity (EC)1:5 method. The volumetric water content as measured by the sensor was affected by dry density and water content. Generally, it linearly increased as dry density and water content increased. However, when dry density or water content was high, the measured value of the sensor increased nonlinearly. The bulk EC measured by sensor had no specific correlation with EC1:5. The EC1:5 measurement had a linear relationship with the gradient of θ and θs. Therefore, it can be estimated with a simple linear equation using θ from the soil test and θs from the capacitance sensor. The R2 value of the EC1:5 estimation equation was 0.98. The proposed equation requires θ from the gravimetric sample and θs from the sensor. Therefore, in the case of monitoring salinity using a sensor, it is recommended to measure the water content with a tensiometer. Keywords: salinity, capacitance sensor, volumetric water content, reclaimed land soil, saline soil DOI: 10.25165/j.ijabe.20201301.3905 Citation: Kim D, Son Y, Park J, Kim T, Jeon J. Performance evaluation and calibration of capacitance sensor for estimating the salinity of reclaimed land. Int J Agric & Biol Eng, 2020; 13(1): 206–210.

Performance evaluation and calibration of capacitance sensor for estimating the salinity of reclaimed land

Generally, soil moisture and salinity in reclaimed land are monitored using soil dielectric sensors such as time domain reflectometry, frequency domain reflectometry, and capacitance. The soil dielectric sensor measures apparent dielectric permittivity. However, apparent dielectric permittivity is affected by soil moisture, salinity, and texture. In this study, performance evaluation and calibration of a dielectric sensor (5TE; METER Group, Inc., Pullman, WA, USA) for monitoring soil salinity were performed. Laboratory calibration tests were completed, incorporating various levels of dry density, water content, and salinity. The soil salinity was determined by the electrical conductivity (EC)1:5 method. The volumetric water content as measured by the sensor was affected by dry density and water content. Generally, it linearly increased as dry density and water content increased. However, when dry density or water content was high, the measured value of the sensor increased nonlinearly. The bulk EC measured by sensor had no specific correlation with EC1:5. The EC1:5 measurement had a linear relationship with the gradient of θ and θs. Therefore, it can be estimated with a simple linear equation using θ from the soil test and θs from the capacitance sensor. The R2 value of the EC1:5 estimation equation was 0.98. The proposed equation requires θ from the gravimetric sample and θs from the sensor. Therefore, in the case of monitoring salinity using a sensor, it is recommended to measure the water content with a tensiometer. Keywords: salinity, capacitance sensor, volumetric water content, reclaimed land soil, saline soil DOI: 10.25165/j.ijabe.20201301.3905 Citation: Kim D, Son Y, Park J, Kim T, Jeon J. Performance evaluation and calibration of capacitance sensor for estimating the salinity of reclaimed land. Int J Agric & Biol Eng, 2020; 13(1): 206–210.

Soil Water Content Estimation Using High-Frequency Ground Penetrating Radar

The rapid high-precision and nondestructive determination of shallow soil water content (SWC) is of vital importance to precision agriculture and water resource management. However, the low-frequency ground penetrating radar (GPR) technology currently in use is insufficient for precisely determining the shallow SWC. Therefore, it is essential to develop and use a high-precision detection technology to determine SWC. In this paper, a laboratory study was conducted to evaluate the use of a high-frequency GPR antenna to determine the SWC of loamy sand, clay, and silty loam. We collected soil samples (0–20 cm) of six soil types of loamy sand, clay, and silty loam and used a high-frequency (2-GHz) GPR antenna to determine the SWC. In addition, we obtained GPR data and images as well as characteristic parameters of the electromagnetic spectrum and analyzed the quantitative relationship with SWC. The GPR reflection two-way travel times and the known depths of reflectors were used to calculate the average soil dielectric permittivities above the reflectors and establish a spatial relationship between the soil dielectric permittivity ( ε ) and SWC ( θ ), which was used to estimate the depth-averaged SWC. The results show that the SWC, which affects the attenuation of wave energy and the wave velocity of the GPR signal, is a dominant factor affecting the soil dielectric permittivity. In addition, the conductivity, magnetic soil, soil texture, soil organic matter, and soil temperature have substantial effects on the soil dielectric permittivity, which consequentially affects the prediction of SWC. The correlation coefficients R2 of the “ θ ~ ε ” cubic curve models, which were used to fit the relationships between the soil dielectric permittivity ( ε ) and SWC ( θ ), were greater than 0.89, and the root-mean-square errors were less than 2.9%, which demonstrate that high-frequency GPR technology can be applied to determine shallow SWC under variable hydrological conditions.

Determination of the Porosity Distribution during an Erosion Test Using a Coaxial Line Cell.

The detection of porosity changes within a soil matrix caused by internal erosion is beneficial for a better understanding of the mechanisms that induce and maintain the erosion process. In this paper, an electromagnetic approach using Spatial Time Domain Reflectometry (STDR) and a transmission line model is proposed for this purpose. An original experimental setup consisting of a coaxial cell which acts as an electromagnetic waveguide was developed. It is connected to a transmitter/receiver device both measuring the transmitted and corresponding reflected electromagnetic pulses at the cell entrance. A gradient optimization method based on a computational model for simulating the wave propagation in a transmission line is applied in order to reconstruct the spatial distribution of the soil dielectric permittivity along the cell based on the measured signals and an inversion algorithm. The spatial distribution of the soil porosity is deduced from the dielectric permittivity profile by physically based mixing rules. Experiments were carried out with glass bead mixtures of known dielectric permittivity profiles and subsequently known spatial porosity distributions to validate and to optimize both, the proposed computational model and the inversion algorithm. Erosion experiments were carried out and porosity profiles determined with satisfying spatial resolution were obtained. The RMSE between measured and physically determined porosities varied among less than 3% to 6%. The measurement rate is sufficient to be able to capture the transient process of erosion in the experiments presented here.

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

Organic soils play a key role in global warming because they store large amount of soil carbon which might be degraded with changing soil temperatures or soil water contents. There is thus a strong need to monitor these soils and, in particular, their hydrological characteristics using, for instance, space-borne L-band brightness temperature observations. However, there are still open issues with respect to soil moisture retrieval techniques over organic soils. In view of this, organic soil blocks with their vegetation cover were collected from a heathland in the Skjern River catchment in western Denmark and then transported to a remote sensing field laboratory in Germany where their structure was reconstituted. The controlled conditions at this field laboratory made it possible to perform tower-based L-band radiometer measurements of the soils over a period of two months. Brightness temperature data were inverted using a radiative transfer (RT) model for estimating the time variations in the soil dielectric permittivity and the vegetation optical depth. In addition, the effective vegetation scattering albedo parameter of the RT model was retrieved based on a two-step inversion approach. The remote estimations of the dielectric permittivity were compared to in situ measurements. The results indicated that the radiometer-derived dielectric permittivities were significantly correlated with the in situ measurements, but their values were systematically lower compared to the in situ ones. This could be explained by the difference between the operating frequency of the L-band radiometer (1.4 GHz) and that of the in situ sensors (70 MHz). The effective vegetation scattering albedo parameter was found to be polarization dependent. While the scattering effect within the vegetation could be neglected at horizontal polarization, it was found to be important at vertical polarization. The vegetation optical depth estimated values over time oscillated between 0.10 and 0.19 with a mean value of 0.13. This study provides further insights into the characterization of the L-band brightness temperature signatures of organic soil surface layers and, in particular, into the parametrization of the RT model for these specific soils. Therefore, the results of this study are expected to improve the performance of space-borne remote sensing soil moisture products over areas dominated by organic soils.

Design of Ground Penetrating Radar Antenna for Detecting Soil Contamination at L-band Frequencies

Maintenance of oil pipelines is an issue of great concern for oil companies. Soil contamination is caused by oil leaks from underground pipelines. Ground penetrating radar (GPR) is a rapid and relatively inexpensive technique used for locating and characterizing soil contaminated sites without producing fractures and causing further migration of contaminants. One of the most critical hardware components for the performance of GPR is the antenna system. The present paper reports on the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect soil contamination. A prototype model of the GPR system setup is developed to simulate the electromagnetic fields in different soil types. The dielectric permittivity of soil, needed in order to carry out simulations during the design process, is measured and analytically represented by Debye relaxation model. The contrast in the dielectric permittivity between contaminated and uncontaminated soils is the most important parameter to be considered for detecting the presence of contamination. The application of GPR is proved to be well-versed in the investigation of soil contamination.Â

Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra

AbstractCoincident monitoring of the spatiotemporal distribution of and interactions between land, soil, and permafrost properties is important for advancing our understanding of ecosystem dynamics. In this study, a novel monitoring strategy was developed to quantify complex Arctic ecosystem responses to the seasonal freeze‐thaw‐growing season conditions. The strategy exploited autonomous measurements obtained through electrical resistivity tomography to monitor soil properties, pole‐mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness, and soil dielectric permittivity. The spatially and temporally dense monitoring data sets revealed several insights about tundra system behavior at a site located near Barrow, AK. In the active layer, the soil electrical conductivity (a proxy for soil water content) indicated an increasing positive correlation with the green chromatic coordinate (a proxy for vegetation vigor) over the growing season, with the strongest correlation (R = 0.89) near the typical peak of the growing season. Soil conductivity and green chromatic coordinate also showed significant positive correlations with thaw depth, which is influenced by soil and surface properties. In the permafrost, soil electrical conductivity revealed annual variations in solute concentration and unfrozen water content, even at temperatures well below 0°C in saline permafrost. These conditions may contribute to an acceleration of long‐term thaw in Coastal permafrost regions. Demonstration of this first aboveground and belowground geophysical monitoring approach within an Arctic ecosystem illustrates its significant potential to remotely “visualize” permafrost, soil, and vegetation ecosystem codynamics in high resolution over field relevant scales.

A TDR Array Probe for Monitoring Near‐Surface Soil Moisture Distribution

Core Ideas A TDR array has been developed for soil moisture profiling. The sensor provides eight incremental measurements at centimeter‐depth resolution. Permittivity, evaporation rate, and soil moisture profile were determined. Near‐surface soil conditions (i.e., moisture and temperature) moderate mass and energy exchange at the soil–atmosphere interface. While remote sensing offers an effective means for mapping near‐surface moisture content across large areas, in situ measurements, targeting those specific remotely sensed soil depths, are poorly understood and high‐resolution near‐surface measurement capabilities are lacking. Time domain reflectometry (TDR) is a well‐established, accurate measurement method for soil dielectric permittivity and moisture content. A TDR array was designed to provide centimeter‐resolution measurements of near‐surface soil moisture. The array consists of nine stainless steel TDR rods spaced 1 cm apart, acting as waveguide pairs to form eight two‐rod TDR probes in series. A critical aspect of the design was matching the spacing of the coaxial cable–TDR rod transition to avoid unwanted reflections in the waveforms. The accuracy of the TDR array permittivity measurement (±1 permittivity unit) was similar to that of conventional TDR as verified in dielectric liquids. Electric field numerical simulations showed minimal influence of adjacent rods during a given rod‐pair measurement. The evaporation rate determined by the TDR array compared well with mass balance data in a laboratory test. Near‐surface soil moisture profile dynamics were monitored at centimeter‐depth resolution using the TDR array in a field experiment where volumetric moisture content estimates (0–8 cm) were within 2% of conventional three‐rod TDR probes averaging across 0 to 8 cm and from 1‐ to 3‐cm depths.

Soil moisture estimation in Chambal irrigation command using C-band HH polarization multi-incidence angle Radarsat-1 SAR and IRS LISS III data

Soil moisture is one of the key variables in agricultural water management, particularly in scheduling of irrigation in the major irrigation commands. Several studies have been carried out for modelling of soil moisture using synthetic aperture radar (SAR) which is sensitive to soil dielectric permittivity. However, two critical factors viz. random surface roughness and vegetation cover introduces complexities in the precise estimation of soil moisture. The estimation is further constrained when using single configuration SAR. In the present study, microwave and optical synergy were used wherein soil moisture in the Chambal Irrigation Command, India during 2002-03 winter season, was modelled in two steps. In the first step the surface roughness was modelled taking advantage of multi-incidence angle image acquisition by Radarsat-1 within a short temporal interval with the assumption that the soil moisture has not significantly changed. An output called ‘Roughness Normalized Backscatter Coefficient’ (RNBS) was generated which was used subsequently to correct the vegetation effect. In the second step RNBS was plotted against the normalized difference vegetation index (NDVI) generated from IRS-LISS III sensor as a function of volumetric soil moisture. Based upon the relation between RNBS and NDVI, several polynomial models at different moisture levels were generated and applied to the RNBS image to generate different regimes of soil moisture. The modelled soil moisture was validated based upon the independent samples collected from the field. The proposed methodology is found to be applicable under fallow and sparsely vegetated conditions where the NDVI is less than 0.4.

Ground penetrating radar for underground sensing in agriculture: a review

AbstractBelowground properties strongly affect agricultural productivity. Traditional methods for quantifying belowground properties are destructive, labor-intensive and pointbased. Ground penetrating radar can provide non-invasive, areal, and repeatable underground measurements. This article reviews the application of ground penetrating radar for soil and root measurements and discusses potential approaches to overcome challenges facing ground penetrating radar-based sensing in agriculture, especially for soil physical characteristics and crop root measurements. Though advanced data-analysis has been developed for ground penetrating radar-based sensing of soil moisture and soil clay content in civil engineering and geosciences, it has not been used widely in agricultural research. Also, past studies using ground penetrating radar in root research have been focused mainly on coarse root measurement. Currently, it is difficult to measure individual crop roots directly using ground penetrating radar, but it is possible to sense root cohorts within a soil volume grid as a functional constituent modifying bulk soil dielectric permittivity. Alternatively, ground penetrating radarbased sensing of soil water content, soil nutrition and texture can be utilized to inversely estimate root development by coupling soil water flow modeling with the seasonality of plant root growth patterns. Further benefits of ground penetrating radar applications in agriculture rely on the knowledge, discovery, and integration among differing disciplines adapted to research in agricultural management.