Using remote sensing and GIS techniques in Iron Ore exploration in Rubanda district.

Abstract

Iron exploration in Rubanda has not been very effective due to use of ground-based methods which are time consuming and costly for a wide area. Therefore, in this study integration of Remote sensing and GIS tools offer less costly techniques of detecting Iron and its Iron Ores. The iron ore deposits in southwestern Uganda are among the best in the world in terms of grade(Abraham et al., 2020). As a result, Muko ore is better suited to processing than Tororo ore. The country's iron and steel manufacturing industry has yet to develop to the point where it can meet the demand for these products. Prospective quantification puts the deposits at 30-50 million tonnes of raw-ore reserves. To date the deposits lay unexploited, with small holder black smith activities taking place in the area(Judah & Muwanguzi, 2010). The Band ratio band 1/band 2 is sensitive to ferrous-iron absorption and Ratio band 5/band 3 used for expressing the steep slope caused by the combined effect of ferrous-iron absorption in the VNIR wavelength region. Hence, the band 1/band 2 and band 5/band 3 ratios were useful to distinguish these similar features, a ratio of ASTER band l over band 2 enhanced the small contribution of iron oxide minerals. Band Ratio band2/band 1 of VNIR of ASTER data maximizes iron (III) since iron (III) is highly reflected in band 2 and absorbed in band 1. Hence making iron (III) to have brighter pixels of higher values. Rubanda is dominated by Hematite as the iron ore and other three iron ores that is Magnetite, pyrite and Limonite.