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7 Magnetic, gravimetric, and seismic sensors

7 Magnetic, gravimetric, and seismic sensors

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R.A. Viscarra Rossel et al.

magnetization in the ground. Magnetization of naturally occurring

materials and rocks is determined by the quantity of magnetic minerals

and by the strength and direction of the permanent magnetization carried

by those minerals (Hansen et al., 2005). Typically, magnetics has been

used for the detection of geological bodies; however, there is increasing

use of the technique for near-surface applications. For example, for

mapping field drainage for hydrologic modeling (Rogers et al., 2005); to

better understand soil genesis and formation (Mathe and Leveque, 2003);

to detect anthropogenic pollution on topsoils; through their associations

with iron oxides (Schibler et al., 2002); and for rapid identification and

mapping of soil heavy metal contamination ( Jordanovaa et al., 2008).

2.7.2. Gravity

Gravity data can be collected using gravimeters (or gravitometers) and

provide information on the local gravitational field. There are two types

of gravimeter: relative and absolute. A relative gravimeter measures relative differences in the vertical component of the earth’s gravitational field

based on variations in the extension of an internal spring in the gravimeter.

The technique has typically been used to determine the subsurface configuration of structural basins, aquifer thickness, and geological composition.

An absolute gravimeter measures the acceleration of free fall of a control

mass. Absolute gravimetry can be used to measure mass water balances at

regional or local scales (Nabighian et al., 2005).

2.7.3. Seismology

Seismic reflection methods are sensitive to the speed of propagation of

various kinds of elastic waves. The elastic properties and mass density of the

medium in which the waves travel control the velocity of the waves and can

be used to infer properties of the earth’s subsurface. Reflection seismology

is used in exploration for hydrocarbons, coal, ores, minerals, and geothermal

energy. It is also used for basic research into the nature and origin of rocks

that make up the Earth’s crust (McCarthy and Thompson, 1988). It can

be used in near-surface applications for engineering, groundwater and environmental surveying (Harry et al., 2005). A method similar to reflection

seismology, which uses electromagnetic instead of elastic waves, is GPR.

2.8. Contact electrodes

This section refers to techniques for measuring electrical properties of

soils, such as their resistivity and dielectric, using direct injection of current into the soil using electrodes.

Proximal Soil Sensing for Measurements in Space and Time


2.8.1. Electrical resistivity

Electrical resistivity (ER) can be used to determine the resistivity distribution of the measured soil volume. Measurements of ER usually require

four electrodes: two to inject the current (current electrodes) and two

to measure the resulting potential difference (potential electrodes). The

ER of the soil is determined from this and measurements of the apparent

electrical conductivity (ECa) are possible because resistivity is the reciprocal

of conductivity.

The technique has long been used in geophysics, and various configurations of electrodes can be used to control the volume and depth of measurement. The soil properties that affect measurements of soil with EMI

instruments (see above) also affect resistivity measurements. Samoueălian

et al. (2005) provide a good review on the use of ER in soil science.

2.8.2. Induced polarization

Induced polarization (IP) measurements are essentially an extension of

the four-electrode resistivity technique. IP operates by first injecting

an electric current between a current electrode pair and the resulting

voltage induced in the soil is measured between a potential electrode

pair. However, IP captures both the charge loss (conduction) and the

charge storage (polarization) characteristics of the soil. IP instruments

have been used in hydrogeophysical applications, for example, to look at

hydraulic properties of soil in the vadose zone (Binley et al., 2005;

Boărner et al., 1996).

2.8.3. Electrochemical sensors

Electrochemical sensors have been developed to measure specific ions

in solution. The most common of these are electrodes to measure pH;

however, their uses for measuring various other ions are increasing in

environmental applications. Their durability, portability, fast response,

and ability to measure in unfiltered soil slurries are key advantages

allowing direct measurements of soil chemical properties. PSS using

electrochemical sensors is currently an active area of research with particular focus on the development of mobile soil pH, lime requirements,

and nutrient sensing (Adamchuk et al., 1999; Adsett and Zoerb, 1991;

Birrell and Hummel, 2001; Sibley et al., 2009; Viscarra Rossel and

McBratney, 1997; Viscarra Rossel et al., 2005). Kim et al. (2009a) provide a recent review.

2.8.4. Ion-selective electrodes

ISEs are potentiometric sensors that use ion-selective membranes to

measure the concentration of the target species. When submerged in the

solution to be analyzed, an electromotive force is generated at the sensing

surface proportional to the log of the ion activity. The electromotive force


R.A. Viscarra Rossel et al.

can then be measured using a suitable reference system (e.g., a reference

electrode). ISEs selective for many useful soil nutrients (nitrate, sodium,

potassium, calcium) are commercially available and phosphate-selective

electrodes for soil phosphorus are also being developed (Kim et al., 2007a).

2.8.5. Ion-sensitive field effect transistors

ISFETs combine ISE technology with that of the field effect transistor

(FET). The construction of the ISFET is as for the standard FET;

however, the gate is replaced with a separate electrode (in contact with

the analysis electrolyte) and the exposed insulating oxide (commonly

SiO2 but also Al2O3, Ta2O5) is also left in contact with the electrolyte

being analyzed. The charge developed on the oxide surface (due to

proton interaction) now controls the sourceÀdrain current of the FET,

which is then indicative of the electrolyte. Key advantages of pH ISFETs

over standard glass pH electrodes are small size, increased durability, fast

response, and the ability to mass produce using microelectronic manufacturing techniques. They have been used for proximal sensing of soil pH

(Viscarra Rossel and Walter, 2004) and lime requirement (Viscarra Rossel

et al., 2005).

ISFETs can be chemically modified by depositing membrane layers

on the oxide surface to produce CHEMFETs selective for other ionic

species. CHEMFETs selective for nitrate, calcium, and potassium have

been developed and evaluated for use in soil nutrient sensing (Artigas

et al., 2001; Birrell and Hummel, 2000, 2001).

2.8.6. Metal electrodes

Metal electrodes are also being explored for PSS applications to address a

need for increased physical durability. Antimony electrodes are being

researched as a durable alternative to glass electrodes in direct contact

soil pH measurement (Adamchuk et al., 2009; Viscarra Rossel and

McBratney, 1997). Kim et al. (2007a) explored the use of cobolt rod-based

ISEs for measuring soil phosphates.

2.9. Mechanical sensors

Another family of proximal soil sensors quantify soil properties by

measuring the mechanical interaction between the sensor and the soil.

Although there are no widely used commercial systems, a number of prototypes are being developed and include mechanical, acoustic, and fluid

permeability sensors.

2.9.1. Integrated draft

Soil strength, or mechanical resistance to failure, has been widely used to

estimate the degree of soil compaction. Soil compaction and soil strength

Proximal Soil Sensing for Measurements in Space and Time


can be measured using tine-based sensors (Hayhoe et al., 2002; Lapen

et al., 2002). A method to determine soil physical properties using specific

draft measurements was proposed by Van Bergeijk et al. (2001). In their

study, information gathered automatically during plowing was used to

predict the spatial distribution of topsoil clay content. Sirjacobs et al.

(2002) developed a soil strength sensor that was later evaluated by

Hanquet et al. (2004). It consisted of a single chisel shank pulled through

the soil at constant speed and a depth of 30 cm. In addition to the integrated (bulk) measure of draft, sensors have also been used to measure

vertical variation in soils to identify hardpan layers. These sensors measure

by moving the tool up and down while traveling across a field (Hall and

Raper, 2005; Manor and Clark, 2001; Pitla et al., 2009; Stafford and

Hendrick, 1988).

2.9.2. Mechanical resistance

Soil penetrability is a measure of the effort required to force an object

through the soil. Penetration resistance of soil is relatively easy to measure

and is governed by several soil properties, including shear strength, compressibility, and friction between the soil and the metal. Numerous tip-based

penetrometers have been developed (Fig. 9), including the standardized

vertically operating cone penetrometer (ASABE, 2009), the single-tip

horizontal soil impedance sensor (Alihamsyah et al., 1990), the multiple-tip

horizontal soil impedance sensor (Chukwu and Bowers, 2005; Chung and

Sudduth, 2006; Chung et al., 2006, 2008), and the vertically oscillating shank

with a horizontal single-wedge sensor (Hall and Raper, 2005). While the

vertically operated sensor provides the conventional means for measuring

soil strength, horizontally operated tip-based sensors have been used for

mobile, on-the-go sensing.

In addition to multiple-tip soil impedance sensors, several attempts

have been made to use tine-based sensors to perform mobile measurements of the entire profile. There are two approaches: (i) using an array

of strain gauges mounted on a rigid tine (Adamchuk et al., 2001a, 2001b;

Glancey et al., 1989) and (ii) multiple active cutting edges supported by

independent load cells (Andrade-Sanchez et al., 2007, 2008; Khalilian

et al., 2002). Hemmat and Adamchuk (2008) reviewed proximal soil

sensor prototypes to measure compaction.

2.9.3. Fluid permeability

Many soil processes depend on the effects of soil structure indirectly

through hydraulic conductivity, air porosity, bulk density, and other relevant properties. Therefore, measuring the pressure required to inject a

constant flow of air into the soil, as an indication of the relative soil pore

space and the continuity of the pores, can provide a measure for soil compaction (Clement and Stombaugh, 2000). Air was forced into the soil


R.A. Viscarra Rossel et al.

Figure 9

A five-probe soil penetrometer system.

at a depth of 30 cm using a subsoiler shank and the measured pressure

resistance was related to the air permeability of the subsoil. The sensor

could detect changes in soil structure/compaction, moisture content,

and soil type. Later, Koostra and Stombaugh (2003) redesigned the first

version of the air permeability sensor to minimize the soil disturbance

induced by the wide point of its shank.

2.9.4. Acoustic sensors

The interaction between an implement and the soil creates noise. Thus,

Liu et al. (1993) tested an acoustic method for determining soil texture.

A shank with a rough surface and hollow cavity was equipped with a

microphone that recorded the sound produced through the interaction

of soil and shank. The frequency of the resulting sound was used to

distinguish different types of soil. In a system developed by Tekeste et al.

(2002), sound waves were used to detect compaction layers. A small

microphone installed inside a horizontal cone attached to a tine was

pulled through the soil. The amplitude of sound in a selected frequency

range was compared to the cone index obtained at different depths in the

soil profile. The instrument could successfully detect a prepared hardpan

at a particular depth; however, in both studies, the authors needed it was

necessary to account for background noise.

2.10. Telemetry—Wireless sensing

Wireless sensor networks can be used for continuous and real-time

monitoring of soil properties such as soil water and nutrients for irrigation.

Commercial systems for monitoring soil water using wireless telemetry

are currently available, for example, capacitance probes linked to mobile

Proximal Soil Sensing for Measurements in Space and Time


telephone systems or radio networks are being used in irrigated agriculture

(Vellidis et al., 2008).

Wireless sensor technologies are increasingly being used to monitor the

condition of the environment (Zerger et al., 2010). With wireless systems,

it is possible to obtain information about soil matric potential, water content, temperature, and other properties from remote locations in real time

(Kim et al., 2009b; Vellidis et al., 2008). This improves the accuracy and

convenience of monitoring soil water content. Irrigation systems manager

can then use the data collected to optimize the use of resources in response

to dynamic changes in soil condition and reduce the risk of water stress

in crops (Han et al., 2009; Lamm and Aiken, 2008; Miranda et al., 2005).

Ramanathan et al. (2006) describe a series of wireless networking case

studies for monitoring soil CO2, temperature, and moisture. These systems also incorporate ISEs selective for ammonium, calcium, carbonate,

chloride, pH, reductionÀoxidation, and nitrate. Lemos et al. (2004)

describe a system that uses potassium ISEs along a PVC tube at various

depths with real-time data relayed wirelessly to a base station. The main

problems with wireless sensing using ISEs are durability, large sensor drift,

and difficulties with in situ calibration.

An alternative wireless technique that provides greater spatial coverage

and reduced cost is ad hoc wireless networking or “mesh” networking. It is

suited to situations where small rates and volumes of data exchange are

required. It is based on the deployment of a large number of sensor “nodes”

that are battery or solar powered and equipped with low power and low

cost radio systems. Various configurations are possible in a network (with

each node measuring one or more soil properties) and nodes can be used

for relaying information to extend their range through self-configuring

ad hoc networks. An example of such a system is the farm-based wireless

sensor network developed by Sikka et al. (2006), which is part of a wider

network and contains 12 soil moisture nodes using up to five gypsum

blocks to measure soil moisture through the profile (to 1 m depth).

2.11. Geographic positioning and elevation

In addition to locating sensor measurements on the landscape, the

availability of differential global positioning systems (DGPS) and real-time

kinematic (RTK) GPS systems make it possible to collect low cost, accurate digital elevation data. This data can then be used to create a digital

elevation model (DEM) and provides information on surface geometry

(e.g., slope, aspect, various curvatures, and wetness indices), which is

an important descriptor of soil. Local variations in terrain control the

movement of sediments, water, and solutes in the landscape. Soil formation is strongly influenced by these processes and the DEM and related

attributes can be used to help characterize the spatial distribution of


R.A. Viscarra Rossel et al.

soil properties (Moore et al., 1993). A DEM also provides the landscape

framework for interpreting results from other sensors (e.g., EM, γ-ray

survey, and GPR) (Gish et al., 2005). Global positioning and the collection of elevation data are imperative for PSS, particularly for mobile and

multisensor systems.

2.12. Multisensor systems

As every soil-sensing technology has strengths and weaknesses and no

single sensor can measure all soil properties, the selection of a complementary set of sensors to measure the required suite of soil properties is important. Integrating multiple proximal soil sensors in a single multisensor

platform can provide a number of operational benefits over single-sensor

systems, such as:

robust operational performance

increased confidence as independent measurements are made on the

same soil

extended attribute coverage

increased dimensionality of the measurement space (e.g., different

sensors measuring various portions of the EM spectrum).

There are few reports of multisensor systems directed at PSS in the literature. For example, Christy et al. (2004) reported the use of a mobile sensor

platform that simultaneously measures soil pH and ECa. An NIR sensor

has also been recently added to this multisensor platform (Christy, 2008).

Taylor et al. (2006) reported the development of a multisensor platform

consisting of two EMI instruments, ER and pH sensors, a γ-radiometer,

and a DGPS (Fig. 10A). Adamchuk and Christenson (2007) described a system that simultaneously measured soil mechanical resistance, optical reflectance, and capacitance (Fig. 10B). Yurui et al. (2008) reported the

development of a multisensor technique for measuring soil physical properties (soil water, mechanical strength, and electrical conductivity).

Other sophisticated integrated sensor systems have been developed

for various applications. For example, the United States Army’s site characterization and analysis penetrometer system (SCAPS) is mounted on a

20-ton truck. Down-hole determinations are made to 50 m using realtime video; γ-ray spectrometers to detect radioactive waste; sensors to

measure water content, pore water pressure, liquid and gas samplers;

laser-induced fluorescence sensors to detect hydrocarbons; mass spectrometers to detect volatile organic compounds; LIBS to measure various

metals; and XRF for measuring heavy metals. Eight SCAPS trucks are

operated by three federal agencies in the United States and millions of dollars have been saved in site investigation and cleanup costs (USAEC, 2000).


Proximal Soil Sensing for Measurements in Space and Time



Figure 10 Multisensor platforms. (A) A multisensor platform with EMI, passive

γ, electrical resistivity, and pH sensors and (B) one with mechanical, electrical,

and optical sensors.

2.13. Core scanning and down-borehole technologies

Core scanning and borehole sensors can be used to measure soil profiles,

for example, to measure soil carbon stocks, determine subsoil constraints

to root growth (e.g., subsurface acidity), or to characterize the soilÀwater

regime. Some of the PSS technologies described above provide bulk

measurements to a specific depth. For example, EMI sensors provide a

depth-weighted ECa reading to a depth proportional to their coil spacing

(Sudduth et al., 2010). However, there is still a need to develop core

scanning and down-borehole technologies that can characterize the entire

soil profile layer by layer to at least 1.5 m.

Undisturbed soil cores can be readily collected with small drill rigs

using either push-tubes or core samplers. There is an excellent opportunity to apply many of the methods considered above to an automated

scanning system for soil cores. Commercial units have been developed

for sediment and rock cores (Geotek, 2001) that include active γ-ray

attenuation for measuring water content and bulk density, ER, magnetic

susceptibility, and digital photography (Fig. 11). Research prototypes

that allow core scanning for ECa (Myers et al., 2010) and for visÀNIR

reflectance (Kusumo et al., 2011) have also been reported. Use of such

rapid core measurement systems would allow soil surveys to be undertaken in a far more efficient manner and would be a natural complement

to vehicle-mounted sensor systems.

Down-borehole sensor systems also provide a means for characterizing

soil profiles. Measurements of electrical conductivity in particular can be

made at a well-defined depth and the sensor can integrate over a realistic

volume of soil to reduce the effects of short-range variation (Myers et al.,

2010). Cone penetrometers or other specialized probes can also be modified to contain sensors or fiber optic probes for visÀNIR spectroscopy

(Ben-Dor et al., 2008; Hummel et al., 2004; Kweon et al., 2009), XRF

(Elam et al., 1998) and LIBS (Mosier-Boss et al., 2002).


R.A. Viscarra Rossel et al.

Figure 11

A core scanning multisensor system.

3. Proximal Sensors Used to Measure

Soil Properties

Many soil properties can be measured with different proximal soil

sensors. This section describes and gives examples of alternative techniques that are available for measuring soil properties.

3.1. Soil water and related properties

Several sensor systems for measuring water content have been developed.

Soil water content has been measured using active γ-ray attenuation (Pires

et al., 2005), visÀNIR (Sudduth and Hummel, 1993; Whiting et al., 2004)

and mid-IR spectroscopy ( Janik et al., 2007a), tine-mounted microwave

sensors (Whalley, 1991), TDR and FDR, capacitance (Paltineanu and

Starr, 1997), GPR (Huisman et al., 2003), and EMI and ER (Sudduth

et al., 2005). Although total soil water content as measured by these sensors

is useful, measurements of plant-available water capacity (PAWC) are more

important for agriculture. PAWC is determined in the field by measuring

differences between volumetric water content at the drained upper and

lower limits after complete extraction of water by the plants. Whalley et al.

(1992) evaluated multisensor capacitance probes in the nontraffic interrows

of agricultural fields to monitor soil water dynamics over the growing season. Wireless sensor networks (Vellidis et al., 2008) can also be used for

Proximal Soil Sensing for Measurements in Space and Time


this. EMI surveys measured at different times may be used to approximate

PAWC ( Jiang et al., 2007; Wong et al., 2006), but local calibration and

careful interpretation are imperative. Rapid measurements of bulk density

are needed to convert water content measurements to a volumetric basis

(see below).

3.2. Nutrients and elements

Soil nutrients are important for healthy plant growth. The macronutrients

(nitrogen, potassium and phosphorus) are required in large quantities and

are therefore managed and replaced as fertilizer on a crop-by-crop basis.

They represent a significant input cost of food production both financially

and environmentally: excessive nitrogen fertilizer can subsequently leach

soil nitrates into waterways and have direct consequences on human and

environmental health and water quality.

There are various options for proximal sensing of plant nutrients and

elements in soil (Kim et al., 2009a); however, their measurement is not

straightforward because these properties show large variability in both

space and time. This is particularly true for nitrateÀnitrogen, which has

been measured using mid-IR spectroscopy ( Jahn et al., 2006), LIBS

(Harmon et al., 2005), and electrochemical techniques using ISEs and

ISFETs (Adsett and Zoerb, 1991; Artigas et al., 2001; Birrell and

Hummel, 2001; Davenport and Jabro, 2001; Kim et al., 2006;

Sethuramasamyraja et al., 2008; Sibley et al., 2009).

Measurement of soil phosphorus is difficult. Most indices estimate

readily available (or labile) phosphates that occur in soil solution. These

occur as freshly precipitated forms or as anions that can be readily

removed from positively charged sites on clay and organic surfaces.

However, most of the phosphorus in soil is very slowly available (or less

labile). Apart from electrochemical methods, proximal soil sensors for

measuring soil phosphorus are indirect and return variable results,

although good correlations using visÀNIR spectroscopy have been

reported in the literature (Bogrekci and Lee, 2005). Janik et al. (1998) also

reported good results for phosphorus sorption using mid-IR spectroscopy,

but not for available phosphorus. Kim et al. (2007a, 2007b) evaluated the

ability of ion-selective membranes and cobalt-rod electrodes to quantify

available phosphorus and reported relatively good success with cobalt


Potassium can be measured using passive γ-radiometry (Wong and

Harper, 1999) and electrochemically (Kim et al., 2006; Sethuramasamyraja

et al., 2008). Measurements of potassium using visÀNIR and mid-IR

spectroscopy have also been reported but with variable results. Other major

nutrients such as calcium and magnesium, however, appear to correlate

well with both visÀNIR and mid-IR spectra (Lee et al., 2009; Viscarra


R.A. Viscarra Rossel et al.

Rossel and McBratney, 2008). Minor nutrients and elements can be

measured directly using XRF (Kalnicky and Singhvi, 2001) and LIBS

(Hussain et al., 2007) and electrochemically using ISEs or ISFETs (Artigas

et al., 2001; Davenport and Jabro, 2001). Heavy metal contamination in

soils can be measured using XRF, visÀNIR and mid-IR spectroscopy

(Bray et al., 2009), and LIBS (Hilbk-Kortenbruck et al., 2001). Salinity and

sodicity can be measured electrochemically with ISEs or ISFETs (Artigas

et al., 2001; Davenport and Jabro, 2001) as well as with EMI and ER

(Corwin et al., 2003).

3.3. Cation exchange capacity

CEC determines the nutrient supply in soils, with cation nutrients in

higher CEC soils generally more available to plants. CEC increases

with increasing pH, clay, and organic matter in the soil. It also varies with

the type of clay, with smectites having the highest CEC, followed by

illites and kaolinites. CEC can be inferred using visÀNIR and mid-IR

spectra (Sudduth and Hummel, 1993; Viscarra Rossel et al., 2006b).

Reports of good correlations using EMI and ER instruments do exist

(Sudduth et al., 2005). Since CEC is affected by soil texture, mineralogy,

and organic matter content, it may be more accurately measured by

combining measurements from different proximal sensors.

3.4. Carbon

Carbon plays a key role in improving soil physical properties, increasing

CEC and water-holding capacity, and improving soil structure. Soil carbon

is thus considered important in assessing soil quality (Andrews et al., 2004).

Furthermore, the ability of soils to sequester carbon is of increasing interest

as a potential way to mitigate greenhouse gases in the atmosphere. Soil

carbon can be measured using charge-coupled devices (Viscarra Rossel

et al., 2008), visÀNIR and mid-IR (Viscarra Rossel et al., 2006b), LIBS

(Cremers et al., 2001), and INS (Wielopolski et al., 2008). Carbon fractions

can also be measured using visÀNIR (Cozzolino and Moron, 2006), but

measurements appear to be more accurate using mid-IR spectroscopy

( Janik et al., 2007b).

3.5. pH

As a measure of acidity, the level of soil pH is important in many processes,

including availability of plant nutrients and efficacy of herbicides. Soil pH,

buffering capacity, and lime requirement can be measured using ISE or

ISFET systems (Adamchuk et al., 1999; Viscarra Rossel and McBratney,

1997; Viscarra Rossel and Walter, 2004; Viscarra Rossel et al., 2005).

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