Magnetic measurements in electrical prospecting by resistivity methods

The electrical resistivity and induced polarization (IP) methods are widely used in geological mapping, prospecting and exploration of mineral deposits, engineering geology, hydrogeology, archaeology, and geotechnical and environmental applications. Historically, these methods have formed the basis of the electrical prospecting technique. In these methods, a DC or low-frequency AC electrical current is introduced into the earth through a grounded transmitter line. The measured quantity is the electric field. However, if the earth’s resistivity or chargeability changes horizontally, this change gives rise to an anomalous magnetic field, which is studied by the magnetometric resistivity (MMR) and magnetic induced polarization (MIP) methods, respectively. Along with advantages, some shortcomings are inherent in the MMR and MIP techniques. Apparently, the main drawback of these methods is that the magnetic fields of both the transmitter line wire and ground electrodes on the surface are several orders of magnitude greater than the anomalous magnetic field response. This introduces a significant “noise” to magnetic-resistivity data. We investigate the potential of using a circular electric dipole (CED) in magnetometric resistivity techniques. It has been found that the application of a CED, instead of a conventional transmitter line, dramatically enhances the signal-to-noise ratio.     

A computer-aided framework for subsurface identification of white shark pigment patterns

Subsurface video footage can be used as a successful identification tool for various marine organisms; however, processing of such information has proven challenging. This study tests the use of automated software to assist with photo-identification of the great white shark Carcharodon carcharias in the region of Gansbaai, on the south coast of South Africa. A subsurface photo catalogue was created from underwater video footage. Single individuals were identified by using pigmentation patterns. From this catalogue, two images of the head for each individual were inserted into automated contour-recognition software (Interactive Individual Identification System Beta Contour 3.0). One image was used to search the database, the other served as a reference image. Identification was made by means of a contour, assigned using the software to the irregular border of grey and white on the shark's head. In total, 90 different contours were processed. The output provided ranks, where the first match would be a direct identification of the individual. The method proved to be accurate, in particular for high-quality images where 88.24% and 94.12%, respectively, were identified by two independent analysts as first match, and with all individuals identified within the top 10 matches. The inclusion of metadata improved accuracy and precision, allowing identification of even low-quality images.