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Title: MAGNETOMETRY, SELF-POTENTIAL, AND SEISMIC - ADDITIONAL GEOPHYSICAL METHODS HAVING POTENTIALLY SIGNIFICANT FUTURE UTILIZATION IN AGRICULTURE

Author
item Allred, Barry
item ROGERS, MICHAEL - ITHACA COLLEGE

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 1/1/2008
Publication Date: 6/10/2008
Citation: Allred, B.J., Rogers, M. 2008. Magnetometry, self-potential, and seismic - additional geophysical methods having potentially significant future utilization in agriculture. In: Allred, B.J., Daniels, J.J., Ehsani, M.R., editors. Handbook of Agricultural Geophysics. Boca Raton, FL: CRC Press. p. 147-161.

Interpretive Summary:

Technical Abstract: Geophysical methods can provide important information in agricultural settings, and the use of these techniques are becoming more and more widespread. Magnetrometry, self-potential, and seismic are three geophysical methods, all of which have the potential for substantial future use in agriculture, but at present are being employed sparingly or not at all for agricultural purposes. Magnetometry is a passive remote sensing method that records the magnitude of the Earth’s local magnetic field at a sensor location. Self-potential, from an operational standpoint, is probably the simplest geophysical method, essentially requiring only the measurement of a naturally occurring electric potential difference (voltage) between two locations on the ground surface. The electric potential difference measured is associated with non-artificial electric current transmitted through the ground. Seismic methods employ explosive, impact, vibratory, and acoustic energy sources to introduce elastic (or seismic) waves into the ground. These seismic waves are basically elastic vibrations that propagate through soil and rock materials. The seismic waves are timed as they travel through the subsurface from the source to the sensors, which are called geophones. This chapter describes all three of these geophysical methods with regard to basic theory, equipment employed, field procedures, data analysis, and potential uses in agriculture.