Mapping of Ferric (Fe3+) and Ferrous (Fe2+) Iron Oxides Distribution Using Aster and Landsat 8 Oli Data in Negash Lateritic Iron Deposit Northern Ethiopia.
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Date
2021-09-10
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Addis Ababa University
Abstract
Iron play important role in the industrial and engineering development of a country and there is a
rapid demand for iron in Ethiopia. However, the search for valuable and means of primary mineral
resource exploration remains challenging and costly. Therefore, this study aims to map iron oxide
minerals using Landsat-8 Operational Land Imager (OLI) and Advanced Spaceborne Thermal
Emission and Reflection Radiometer satellite imagery in Negash Lateritic iron deposit, Northern
Ethiopia. Different image processing techniques such as band ratio, selective principal component
analysis, linear spectral unmixing and mixture tuned matched filter were used to produce iron
oxide maps. Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and N-dimensional
visualizer were also applied to extract endmembers in Automated spectral hourglass wizard. First,
Normalized Difference Vegetation Indices (NDVI) were calculated and values greater than 0.4
and 0.3 for ASTER and Landsat 8 OLI were used to mask vegetation and, reduce the effects of
vegetation on the processed image, respectively. Band ratio of band-2/band-1 and band-5/band-3
+ band-1/band-2 of ASTER, band-4/band-3 and band-6/band-4 of Landsat 8 OLI was used to map
ferric (3+) and ferrous (2+) respectively. In addition to this, the enhanced image thresholding (from
ratio, selective PCA and unmixing) through a varying percentage of confidence level and scatter
plot (from MTMF) were used to map anomalous (potential) areas. Ferric iron oxide band ratio of
ASTER mapped maximum area of 62.1 km2
followed by a laterite band ratio of ASTER covering
57.8 km2. The result shows a high correlation between results obtained using selective PCA with
r = 0.59, and r = 0.3 moderate correlation between ferric iron, a poor correlation for ferrous iron
with r = 0.22. The correlation result shows that iron oxides mapped from the selective principal
component analysis have a better correlation with one another. The result was validated using
existing iron oxide polygons and results obtained from selective PCA show a strong match with
the existing iron oxide polygons. The sub-pixel mapping techniques show poor accuracy in
mapping goethite and hematite relative to the pixel level. Results obtained from ASTER images
show a better match with the existing iron oxide polygons. The comparison shows ASTER mapped
better than Landsat 8 OLI for band ratio selective PCA, unmixing and MTMF. In poor countries
like Ethiopia applying these techniques is a good option to map and use as preliminary exploration
tools.
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Keywords
Endmembers Extraction, Selective PCA, Band Ratio, LSU, MTMF