Geophysical Survey Methods
The methods most often
employed by Archaeo-Physics are electrical resistance, magnetic
field gradient, and ground penetrating radar (GPR) survey.
These methods have proven to be the most useful tools for
archaeological prospection in most situations. We also have
a variety of other methods which we may employ under special
circumstances, including: EM conductivity survey; "total
field" magnetometry; soil compaction survey; and laboratory
testing of field samples.
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A GPS-controlled magnetometer
survey |
These methods provide excellent resolution
of many types of archaeological features, and are capable
high sample density surveys of very large areas and of operating
under a wide range of conditions. When two or more methods
are used in combination the different instruments provide
complimentary data sets, which can give greater insight
into feature composition than could be gained from a single
method.
A brief introduction
to our principal methods is presented here as an introduction
to archaeologists. An in-depth study of these and other methods
as applied to archaeology can be found in Clark
(1996).
The general procedure followed to perform most
surveys is to divide the survey area into a series of square or
rectangular survey "grids." Each grid is surveyed by
taking readings at regular intervals along regularly spaced transects.
Ropes marked at regular intervals are used to control transect
spacing and position along each transect. Successive transects
are surveyed in a zigzag pattern until the grid is completed.
The value and position of each data point is automatically recorded
in digital format, and is later downloaded to a portable computer.
For some large-scale reconnaissance surveys, spatial control may
be provided by an integral GPS. Occasionally,
these instruments are also used to record selected individual
transects or for less formally "scanning" areas of interest
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Electrical resistance survey using ropes
for spatial control |
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Electrical Resistance Survey
Electrical resistance surveys
introduce an electrical current into the soil and measure the ease
(or difficulty) with which this current flows within the soil. Variance
in measured resistance values across a site can be interpreted as
variance in the relative resistivity of materials composing the
matrix in the vicinity of each reading. Resistance surveys respond
to a combination of soil moisture, soluble ion concentration and
physical soil type. Moist soils have lower resistivity than dry
soils. Fine soils (clay) have lower resistivity than coarse soils
(sands or gravels), and high salinity soils have low resistivity.
At a more fundamental level, the resistivity is governed by the
number and mobility of free charge carriers available in the soil.
The principal sources of these free charge carriers are soluble
ions. Thus, the simultaneous availability of soil moisture and
soluble salts determines the free charge carrier concentration
in the soil. The mobility of these carriers is also an important
parameter in soil resistivity. The mobility of the soluble ions
is governed by soil moisture content, soil grain size, temperature,
soil compaction, as well as the surface chemistry of the soil
grains. These variables govern soil resistivity at the low frequency
used in these surveys. At higher frequencies soil resistivity
becomes a more complex issue.
Twin electrode surveys respond to the soil
resistivity in the immediate vicinity of the sampling probes.
The depth of the response is roughly proportional to a semi-spherical
volume with a radius equal to the spacing of the current and potential
probes. The actual radius of "response" is a complex
function of feature contrast, feature size, feature geometry,
and depth below the surface. In general, a greater probe spacing
will result in increased depth of penetration, at the expense
of resolution of small, low-contrast features.
Archaeologically useful surveys
result when the resistivity contrast between the archaeological
record and the surrounding soil matrix is great enough to be detected.
The recorded data are an average made up of contributions from the
surrounding soil matrix and the archaeological record. Therefore,
it is clear that for detection, the contribution from the archaeological
components to the measured average must be greater than the statistical
uncertainty in the survey data. Appropriate survey design (instrument
selection, instrument configuration, data sample density, and field
methods) is necessary for a successful survey.
Site geology is seldom uniform
and the spatial variability of resistance data associated with the
geology will also be present in the survey data. Geology can usually
be distinguished in the resistance data by its scale and geometry.
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Portable computers are used
in the field for data download and aquisition, quality
control, and real-time monitoring of survey results
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Electrical Resistance Data Processing
Resistance survey data are processed with Geoplot
software, which is provided by the manufacturer of the survey
instruments. The data quality is usually excellent and very little
"clean up" processing is required. Extreme outliers
are typically removed and the data are clipped to the appropriate
range by examining the data statistics and histogram characteristics.
The data are also interpolated (up or down) to a 4-x-4 data sample
per meter density for viewing and export to graphic software.
A convolutional highpass filter is often used
to suppress large-scale geologic variation and to enhance small
low-contrast anomalies. It is implemented by calculating the local
mean in a moving window and subtracting the mean from the original
map data. The size of the moving window is adjustable. It is typically
set in the range of 5 - 10 meter radius. The result is a new map
in which the average "background" resistance of the
site has been subtracted. The mean value of the new map is zero.
Highpass filtering of resistance data offers
a number of benefits to the mapping and interpretation of resistance
data. In addition to enhancing the visibility of small low-contrast
features, it also creates a resistance map with zero mean. This
zero mean map can be thought of as a resistance map containing
features which are greater than the local average (the positive
values) and features which are less than the local average resistance
(the negative values). The zero data regions correspond to areas
of no resistance deviation from "background" or local
mean.
With this insight, it is convenient to interpret
positive data as features with "greater than average resistance."
For example, stone architecture or pits filled with sand or gravel
might appear as high-resistance anomalies. In like manner it is
convenient to interpret negative data as features with "less
than average resistance." Pits and trenches containing organically
enriched fill, clays, and high salinity soils might appear as
low-resistance anomalies.
Magnetic Field Gradient Survey
For the purpose of this type of survey and
in the absence of archaeological and geological contributions,
the earth's magnetic field near the surface of the earth is uniform
and the gradient of this field is zero. When there is an archaeological
or geological magnetic field, it adds to the earth's magnetic
field and the magnetic field gradient is no longer zero.
Magnetic field gradient surveys
measure this deviation from uniformity and report it as positive
data when the deviation is in the direction of the earth's magnetic
field and as negative data when the deviation is in the direction
opposite the earth's magnetic field. In these surveys, the more
"magnetic" the archaeological record the greater the magnetic
field distortion and the greater the feature contrast in the survey
map.
The archaeological record has
two basic properties or mechanisms by which it distorts the earth's
magnetic field. These are called the remanent magnetization (a permanent
magnetic effect) and the magnetic susceptibility (a bulk magnetic
property similar to density). Both mechanisms are dependent on the
presence of iron (e.g., iron oxides in soils, sherds, and hearths)
and both mechanisms alter the magnetic field at the surface of the
site. They are thus mapped as distortions of the earth's magnetic
field.
Remanent magnetization is the
familiar "permanent magnet" effect and is associated with
iron and steel objects (including rust) as well as with ceramics,
hearths, fire pits, fire-altered soils and stone. In these materials,
the remanent magnetization originates from heating the iron oxides
found in most soils above a critical temperature (565 to 675 degrees
C), called the Curie temperature. When the soil cools, the temperature-induced
changes in the iron oxide crystals are "frozen" and become
permanent. It is this change in the magnetic state of the soil (ceramic,
hearth, etc.) which creates a remanent magnetic field. This thermally
created magnetic field adds vectorially to the earth's magnetic
field to cause a local distortion. Thus, most cultural objects and
processes associated with heating are potential archaeo-magnetic
survey objects of interest.
The magnetic susceptibility
alters the earth's magnetic field directly in a manner roughly analogous
to the way porosity alters the flow of water through a solid. That
is, where the magnetic susceptibility is large (high porosity),
the magnetic field is increased and where the magnetic susceptibility
is low (low porosity), the magnetic field is decreased. Many cultural
objects and processes (thermal, chemical, biological and biochemical,
physical and mechanical) locally increase the magnetic susceptibility
of the soil. The mechanism for this increase is also associated
with changes in the iron oxide crystal structures within the soils.
Local changes in site magnetic susceptibility alter the earth's
magnetic field and it is this distortion which is mapped. In magnetic
surveys, remanent magnetization (permanent magnet) effects are usually
somewhat greater than susceptibility effects.
Many magnetic highs are a combination
of induced field and remanent magnetization. The observed magnetic
field strength is the result of the total magnetization of an object.
The total magnetization is a vector sum of the induced magnetization
and the remanent magnetization (Sharma 1997).
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Spatial control is critical!
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Magnetic Field Gradient Data Processing
All magnetic field gradient
data are processed with Geoplot software, which is provided by the
manufacturer of the survey instruments. Typically the data are "cleaned
up" using a "Zero Mean Traverse" algorithm which
removes scan to scan instrument and operator bias defects. A gaussian
lowpass filter is used to remove high-frequency spatial detail,
or smooth the data. The data are also interpolated (up or down)
to a 4-x-4 data sample per meter density for viewing and export
to graphic software.
As with highpass filtered resistance
data, magnetic field gradient data are also a zero mean bipolar
data set. Magnetic field gradient maps can be thought of as containing
features which increase the field gradient by locally adding to
the earth's field and features which decrease the field gradient
by locally subtracting from the earth's magnetic field. The zero
data regions correspond to areas of uniform or undisturbed magnetic
field.
Thus, all positive data can be interpreted
as features with increased magnetic field due to increased susceptibility
or remanent magnetization oriented in the same direction as the
earth's magnetic field (e.g., hearths, fire-altered soils, bricks,
sherds, and iron). All negative data can be interpreted as features
with decreased magnetic field due to decreased susceptibility
or remanent magnetization oriented in the direction opposite the
earth's magnetic field (e.g. bricks, sherds, and iron).
Ground Penetrating Radar Survey
The GPR functions by sending high-frequency
electromagnetic waves into the ground from a transmitter antenna.
Some of these waves are reflected back to the surface as they
encounter changes in the dielectric permittivity of the matrix
through which they are traveling and are detected by a receiver
antenna. The amplitude and two-way travel time of these reflections
is recorded on a portable computer. This information is then used
to construct a two-dimensional plot of horizontal distance versus
travel time. Data collected in the field are stored on a portable
computer for later analysis. A more complete and technical discussion
of the method can be found elsewhere (Annan and
Cosway 1992; Conyers and Goodman 1997).
The effectiveness of GPR is controlled by the
local soil conditions. GPR is most effective in locating buried
objects in a homogenous soil matrix with a high electrical resistivity.
GPR is least effective in a heterogeneous environment with high
electrical conductivity. A heterogeneous environment contributes
to signal scattering and can result in insufficient depth of penetration
and a "noisy" reflection (poor signal-to-noise ratio).
A conductive environment can seriously inhibit depth of penetration
due to conductive losses. Conductive loss is the result of the
electromagnetic wave creating a conductive current in the soil
medium. This conductive current loses energy in the form of heat
and can also set up what is often referred to as "eddy currents."
Eddy currents are secondary electromagnetic waves created by the
conductive currents in the soil. These waves can obscure reflections
of interest with strong horizontal banding, a phenomenon known
as "ringing."
Although GPR survey can be performed in a number
of ways, the method we generally employ involves dragging the
transmitter and receiver antennas together over the ground at
a fixed rate, called fixed offset reflection mode. The transmitter
emits pulses at regular intervals along a transect which are picked
up by the receiver. A laptop computer controls data collection
and displays the data as a two dimensional profile.
The GPR is able to detect subsurface features
whose electrical properties contrast with those of the surrounding
soil. The GPR can detect archaeological features in several ways.
It may detect disturbed soil, breaks in the natural stratigraphy
or soil profile, or reflections from buried archaeological features.
Ground Penetrating Radar Data Processing
The analysis of GPR data is carried out by
processing the data using different gains and filtering techniques.
Gain is a value by which raw data are multiplied to enhance low-amplitude
reflections. Signal amplitude commonly decreases exponentially
at increasing travel times (greater depth below surface). This
was compensated for by designing a custom time gain that increased
the signal strength to a constant average value. Filtering is
the use of mathematical processing algorithms to "clean"
noise from the data and/or enhance certain characteristics of
the data. Among the filtering techniques which can be applied
are: Bandpass frequency (noise reduction), temporal median (noise
reduction), spatial lowpass (noise reduction and continuity of
horizontal events), spatial highpass (background removal), and
deWOW (removal of very low-frequency inductive phenomena).
GPR data is most often plotted as single transects,
which appear as vertical profiles. A technique known as time slicing
makes it possible to construct planview maps of an area which
has been surveyed with multiple adjacent transects. This not only
makes interpretation of the data in the horizontal plane much
more intuitive, but also allows us to isolate specific depths
(or more properly, the two-way travel times of reflected waves)
for examination. Recent developments in GPR data processing and
imaging software has enabled plan view presentation GPR data as
average enveloped amplitude time slices and as statistical activity
analysis within a time window. Average amplitude time slicing
methods and case studies are presented in some detail by Conyers
and Goodman (1997). Statistical activity analysis of GPR data
was shown to be an effective alternative method of plan view presentation
by Barker et al. (1998).
References:
Annan A.P. and Cosway S.W. 1998 Ground
Penetrating Radar Survey Design. Paper Prepared for the Annual
Meeting of SAGEEP. April 26-29, Chicago, Illinois.
Barker P., Fletcher M., Bradley J. 1998.
Reflections on the past: Progress in the application of GPR in
Archaeology. Proceedings of the Seventh International Conference
on Ground-Penetrating Radar. May 27-30, 1998, Lawrence, Kansas,
USA
Clark, Anthony J. 1996 Seeing Beneath the
Soil. Prospecting Methods in Archaeology. B.T. Batsford Ltd.,
London, United Kingdom
Conyers, Lawrence B. And Dean Goodman 1997
Ground Penetrating Radar: An Introduction for Archaeologists.
Walnut Creek, CA.: Altamira Press.
Sharma, Prem V. 1997 Environmental and
Engineering Geophysics. Cambridge University Press, Cambridge,
Unted Kingdom.
