Using airborne radiometric
geophysical data, one can easily investigate a wide region in a short time and
with little cost to finally find areas that are rich in radioactive elements.
In this research, the uranium exploration data were first organized, filtered
and classified and then the frequency distribution tables and histograms were
drawn. After drawing the histograms, the statistical parameters for radioactive
elements were calculated. The separation of anomaly populations was done on the
basis of distribution around mean value, that is, the resulting mean, mean + 1SD,
mean + 2SD, and mean + 3SD were assumed to equal to background, threshold
value, the possible anomaly and the probable anomaly, respectively. In the end,
representative maps of anomalies and separation of anomaly populations from the
background were presented based on classical statistical calculations.
Cite this paper
Jafari, H. and Yazdi, A. (2014) Radioactive Anomalies in 1:50000 Dehbakri Sheet, South of Kerman Province, Iran. Open Journal of Geology
, 399-405. doi: 10.4236/ojg.2014.48031
 Hasani Pak, A.A. and Sharafoldin, M. (2001) The Analysis of Exploration Data (The Differentiation of Background Values from Anomaly, Engineering Probability and Statistics, Ore Reserve Estimation). Tehran University Press, Tehran.
 Dickson, B.L. (2004) Recent Advance in Aerial Gamma Ray Surveying. Journal of Environmental Radioactivity, 76, 225-236. http://dx.doi.org/10.1016/j.jenvrad.2004.03.028
 Hasani Pak, A.A. (1998) Geostatistics. Tehran University Press, Tehran.
 Sami, H. and Abd, N. (2001) Evaluation of Airborne Gamma Ray Spectrometric Data for the Missikat Uranium Deposit, Eastern Desert Egypt. Applied Radiation and Isotops, 54, 497-507.
 IAEA-TECDOC (2003) Guidelines for Radio Element Mapping Using Gamma Ray Spectrometry Data.