ASTER Mineral Classification for Regolith Mapping in Tick Hill Mount Isa, Northwest Queensland

Abstract

-This paper analyzed the mineral maps of AlOH bearing minerals and iron oxide using ASTER imagery in Tick Hill, Mount Isa, northwestern part of Queensland, as a guide for mapping the regolith unit within the area. Tick Hill is part of the Proterozoic Eastern and Western Fold Belt Province (Mount Isa Inlier Complex) covered by Mesozoic and Paleozoic lithologies and dominated by medium to coarse hornblende-biotite granite and gneiss; both of which intruded during 1760 -1720 Ma. Highly weathered landforms cover the whole area. The Mesozoic sediments have experienced deep weathering, and currently present in the form of mesas. The weathering profiles are dominated by kaolinite, smectite, and pedogenic carbonates with some secondary silicification. Part of the landform is covered by colluvium varying in thickness from less than 1 m up to 12 m in certain places. Digital image processing has been done to ASTER imagery, i.e: calibrating, mosaicing, and band ratioing and false colour RGB. Within these methods, iron oxide, kaolinite, AlOH, and MgOH group mineral maps have successfully been created through the ASTER imagery. Later, these mineral maps were applied to interpret the surface regolith mapping unit. In addition, field samples have been taken in regolith covered areas to validate the ASTER mineral information.

Characterization of Regolith Types and its Impact on Gold Anomaly in Highly Weathered Terrains Using Multiple Dataset

“…Aster L1T image was also pre-processed on ERDAS IMAGINE and later imported onto Arc GIS. The Aster image was free of clouds however, its sensor properties provided spectral coverage in fourteen bands with three subsystems (VNIR, SWIR, and TIR) (Agustin, 2017). Since all the bands had different spatial resolutions it was necessary to re-classify the VNIR and SWIR images into 30m resolution to aid the creation of RGB (Tapley, 2002;Agustin, 2017).…”

“…This was considered as the first step of the classification process and used remotely sensed data such as Aster, GDEM and radiometric. The classification of the terrain using the remote sensing data relied on well-established spatial, genetic and environmental correlation techniques between landforms, mineralogy and regolith as suggested by McQueen and Craig (1995); Laffan and Lees (2004); Arhin (2013); Agustin (2017). Pain et al (1991) defined Regolith landform units (RLU) as areas within which similar landform and regolith characteristics can be isolated at the scale of mapping.…”

“…Band ratio techniques were also applied to the ASTER image. The band ratio of (b4/b3) was able to highlight Iron rich and ferric oxides areas (Agustin, 2017). These were however extracted as a single unit to represent the ferruginous regime.…”