Delineation of mineral potential zone using U-statistic method in processing satellite remote sensing images

Delineating and mapping alteration zones in porphyry copper exploration is of special importance. In this study, satellite image processing techniques were employed to highlight alteration zones in the Zafarghand exploration area. The Zafarghand area is located in the southeastern part of Ardestan and the northwestern part of Isfahan. It is situated within the geological structural zones of central Iran and the intermediate magmatic arc of Urmia-Dokhtar. Various alteration haloes are present in this area, including phyllic, potassic, propylitic, argillic, and slightly siliceous alterations. In this study, the detection of related alterations was carried out using ASTER sensor imagery. Accordingly, considering the raster nature and digital form of satellite images, the digital number values of each pixel from the image matrices were considered as samples in a systematic network. Finally, the U spatial statistic algorithm was implemented as a moving window algorithm for determining anomaly samples in the set of digital number (DN) values of ASTER satellite image pixels. The results of this technique show that the application of the U-statistic method, considering its structural nature and neighboring samples in decision-making, has been successful and has proven to be very effective in determining the alteration zones in the Zafarghand area. It could be observed the delineated propylitic alteration by the U-statistic method is closely associated with the defined zone of propylitic alteration, which is also consistent with the field and microscopic observation of the porphyry Cu mineralization in this alteration zone. It is also observed that the determined phyllic alteration by this image processing is spatially conformable with the sericitic alteration presented in the alteration map (based on field observations and geochemical sampling).