Spectral signatures and spectral mixture modeling as a tool for targeting aluminous laterite and bauxite ore deposits, Koraput, India Results and discussion: From the composite image of bands 743 (figure 2) it is clear that all the laterite and bauxite cappings on the hilltops are displayed in red to magenta colour. But there are some rock exposures and rocky pavement in the valleys, which are also displayed, in magenta colour. They are either laterite floats on the hill slopes or khondalite and charnockite exposures in the area. Vegetation is displayed in green colour as band 4 giving highest reflectance in NIR bands is assigned green filter. Dry red soil is displayed in pink to bluish pink colour, may be because of the contribution from band 3 (projected in blue filter) is more. In general iron oxide gives high reflectance in band 3, which corresponds to the iron reflection peak, and red soil in this region is the weathered product of khondalites and charnockites, which are rich in iron. On the otherhand spectral processing results are displayed in the form of separate images corresponding to each group of pixels (endmembers). MTMF method applied on Landsat TM images gave three score (abundance) images for three different classes (endmembers) such as Laterite/bauxite, vegetation and red soil respectively (figure 5a, 5b and 5c). The laterite/bauxite score image showed the target areas of laterite and bauxite very nicely (figure 5a). All the laterite and bauxite cappings in the study area are represented by bright pixels in this image, which was confirmed during the fieldwork. Vegetation score image showed the areas dominated by vegetation cover (figure 5b). Bare redsoil areas are nicely detected in the score image of redsoil (figure 5c). A colour composite of these three output images was made for better interpretability (figure 6). In this colour composite image laterite and bauxite deposits are shown in red colour, vegetation dominated areas are shown in green colour and redsoil in blue colour. The areas not categorized in these three classes are shown as dark pixels in the colour composite image. This is because the MTMF method does not require all the endmembers to be known in an image for classification. Laterite/ bauxite score image showed number of hills having signatures of laterite and bauxite cappings including the Panchpatmali and Kodingamali hills where presently mining is being carried out. Other hills such as Hatimali, Kakirimali, Gusramali and numerous other small hills also showed the signature of presence of laterite and bauxite deposits.
Rock samples from one of the non-mining locations (Kakirimali hills) were collected during the fieldwork and analysed chemically. The chemical analysis result for five samples collected from Kakirimali hills showed the presence of high-grade bauxite in this hill (table 3). 
Summary and conclusions: Spectral signatures, being unique to each material, can be used for differentiating various materials present in an image depending on its spatial extent and contrast. It was found from the study that laterite and bauxite cappings could be very well identified in the satellite images with the help of spectral processing techniques. This is because of their unique spectral signature and high contrast with the surrounding region. Analysis of spectral signatures of laterite/bauxite, vegetation and redsoil (figure 4) showed that in TM band 7 vegetation gives low reflectance and laterite/ bauxite gives high reflectance where as in band 4 it is vice versa. Hence vegetation can be very well separated from laterite and bauxite deposits. Redsoil has reflectance pattern similar to that of laterite and bauxite, which makes it sometimes difficult to distinguish between these two materials. But aluminous laterite and bauxite cappings occur only on the flat-topped barren hills with sharp escarpment at the periphery, which makes it easier to distinguish them from red soil areas. Spectral processing and classification results have helped in identifying number of new aluminous laterite and bauxite ore deposits in the study area. Therefore it is concluded that this technique can be extrapolated to similar areas for identification of aluminous laterite and bauxite ore deposits. 
Acknowledgement: The author is grateful to Dr. R.R. Navalgund, Director, National Remote Sensing Agency, Hyderabad, India for his kind help. Author is also thankful to Dr. P. S. Roy, Dean, Indian Institute of Remote Sensing, Dehradun for all his support to carry out this research. Prof. V. K. Jha, Head Geosciences Division, IIRS, is also greatly acknowledged for his scientific suggestions and recommendations. References:
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