Interpretation of Resistivity Anomalies
Interpretation of Gradiometry Anomalies
Geophysical surveys were performed at Everett Knoll located in Cuyahoga Valley National Park, in Cuyahoga Falls, Ohio. A group of six students( TEAM LIMA) from the University of Akron investigated Everett Knoll for an arch-geophysical sub-surface mapping class. The surveys were performed in order to determine whether or not the knoll is of archaeological significance. More specifically, is the knoll a Hopewell burial mound, or is it just a geologic feature. There is no question that the Hopewell culture did inhabit this area at one time, numerous artifacts associated with the Hopewell culture have been collected. Two different geophysical methods were applied for this investigation: Magnetic Gradiometry(FM-36) and Electrical Resistivity(RM-15). Information on these techniques can be viewed at http://www.cast.uark.edu/nadag/ The collected data was then processed for interpretation using the program GeoPlot. This website contains the collected data and interpretations of TEAM LIMA.
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Image 1: Raw gradiometry data. Image 2: Processed gradiometry data.
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Image 3: Raw resistivity data. Image 4: Processed resistivity data.
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Image 5: Resistivity anomalies
The results of the resistivity and gradiometry surveys reveal many regions of obvious noise where anthropogenic influence are known as well as many anomalies where the origin is less certain. Both survey methods covered each of the same 10 by 10 meter grids over Everett Knoll and the bordering field (Figure 7). Both methods clearly showed a difference in the background noise level, where the magnitude of the magnetic and resistivity reading are smaller in the field.
The resistivity image of the field is generally very uniform in comparison with the knoll, with two exceptions (Figure 8). The first of these is a region of low contrast and moderately higher resistivity located in the central eastern portion of grid C5 (anomaly R1), while the second is oriented diagonally across grid D4 in a NW-SE direction (anomaly R2) (Figures 9 and 10). Another region of moderately higher resistivity is imaged along the boundary between the knoll and the field (anomaly R4) while a region of lower resistivity parallels this boundary (anomaly R3). These anomalies are interpreted as the usual path of farming equipment and as the geological changes in ground cover in the transition between the knoll and the field.
Resistivity measurements on the knoll are generally of greater magnitude, with much greater contrast in background measurements. Along the western portion of the knoll, the resistivity readings are uncharacteristically high (Figures 8 and 9). This area is approximately all of the same elevation, which lies approximately at the knoll’s midpoint. The rectilinear features of the knoll include a highly resistant linear feature orientated diagonally NW across grid C3 (anomaly R5). This anomaly ends at a large tree at the south edge of the knoll where a small ridge borders the knoll. It appears that this would continue in grids D2 and D1 of the survey extended there and to be of geologic origin (Figures 9 and 10).
Regions of low resistivity on the knoll include two parallel patterns (anomalies R6 and R7) starting from grid B2 and C2 and both continuing NE to grids A1 and B1 where they cross at another low resistivity region (anomaly R8). North of the cross, the low resistivity region surrounds a higher resistivity region (anomaly R9). Another low resistivity region (R10) surrounds the pit located on grids B1 and C1. A more rectilinear anomaly lies in the center and extends to the north and east edges of grid B2 (anomaly R11). This L-shaped anomaly terminates at the low resistivity region of anomaly R6. A long linear feature of low resistance extends from the SE corner of grid C2 to the NW corner of C1 (anomaly R12) and a final low resistivity anomaly lies in the center of grid C2, which is surrounded by higher resistivity area (anomaly R13) (Figures 9 and 10).
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Image 6: Gradiometry anomalies.
The gradiometer data (figures 11 and 12), similar to the resistivity data, has very little contrast in the field. The obvious exceptions are two NW-SE trending linear paths of higher magnetic magnitude (anomalies G1 and G2) (figure 13). These anomalies parallel the edge of the knoll and are interpreted to be caused by farming equipment driving on the edge of the field (anomaly G1) and as the onset of the knoll (anomaly G2).
The gradiometry survey also has several linear and spot features scattered throughout the knoll. One of the linear features of higher magnetism is located in the SW corner of grid B2 and continues NNW to the NW corner of grid C1 (anomaly G3). This anomaly crosses another linear feature at the center of grid B2, which continues NE to the north-central edge of grid B1 (anomaly G4). A linear feature from the SW corner of grid B2, and extending diagonally to the NE corner of the same grid are five spots of higher magnetism (anomaly G5). Another feature extends north from the southern edge of grid B1 (anomaly G6). A region of very high gradiometer readings is located in the southern three-quarters of grid C2 (anomaly G7) (figure 13). These readings were partly recorded as dummy values because the reading were out of range for the gradiometer, and partly due to the processing where spikes outside three standard deviations were replaced with dummy values. The spot anomalies taken by the Gradiometer over the knoll was later all found to be due to modern metallic materials. These materials caused a spike in the data and often created regions of higher dipole magnetism around several grid squares, running much of the gradiometric image.
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Compare and interpret
The results of the resistivity and gradiometry surveys reveal regions where the interpretation is clear and regions of uncertain interpretation, regions of consistent results and seemingly inconsistent results. The agricultural field is an example of an area with clear and consistent interpretation. Both resistivity and gradiometry survey images indicate that the field is generally uniform in magnetic and resistivity readings with only few small anomalies of potential archaeological interest. These small anomalies of higher magnitude may be caused by the differences in field density due to plowing, or perhaps some artifacts. Ground truthing would be helpful here. Both survey results also image the transition zone between the knoll and the field, (R4, R5,G2) and the region where farming equipment more commonly drive (R3, G1) (Figure 14).
One of the gradiometric spots of higher readings (anomaly G7) correlated with resistivity region of low readings (anomaly R13). This anomaly correlates with the extreme anomaly of the gradiometry which was replaced by dummy values for processing and data collection reasons seems to be modern trash pits or sites of past excavation. The metal detector located a large concentration of metal in this depression indicating historic origins.
There are two linear anomalies which are imaged by both the resistivity and gradiometric data sets. The first of these is the linear low resistivity pattern of R12 and the high magnetic anomaly of G3. This anomaly is likely to be of historical origin as the orientation is perpendicular to Everett Road. The second is the low resistivity pattern of R7 and the high magnetic anomaly of G4. The linear pattern of these anomalies indicates that their origin is anthropogenic, yet the angle between them (about 60°) seems to indicate they are of different periods (figure 14).
Regions of seemingly inconsistent results are less common. One example of this is the diagonal magnetic anomaly (G5) in grid B2 that intersects an anomaly of low and high resistivity (anomaly R11). Another linear feature imaged on the magnetic but not on
the resistivity data sets, G6 is interpreted as a data collection or data processing error due to change in magnitude of the signal and to the fact that it fails to continue into grid B2.
A region of historical interest is the linear and perpendicular low resistivity patterns unimaged by the gradiometric survey (anomalies R6-11). Again this pattern indicates an anthropogenic origin. This can be interpreted as a possible location for an old school house or to features associated with the school, which was located on the knoll.
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TEAM LIMA consists of 2 Archaeologists, 2 Geophysicists, and 2 Geologists. All members of LIMA collected and interpreted data. The views shared by TEAM LIMA are exactly that... their views, maybe were right and you are probably wrong, 'res ipsa loquitur.
Archaeologist: Stuart Nealis, Charlotte Mader
Geophysicists: Mark Loken, Hussein Harbi
Geologists: Bob Rader, Brian Ingalls
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