Potential of thermal emissivity for mapping of greenstone rocks and associated granitoids of Hutti Maski Schist belt, Karnataka
Keywords: Alpha Residual, Decorrelation stretching, Emissivity, Emissivity normalisation, granite, granodiorite, Reference Channel, Minimum Noise Fraction, Thermal data
Abstract. In the present study, different temperature-emissivity separation algorithms were used to derive emissivity images based on processing of ASTER( Advanced spaceborne thermal emission and reflection radiometer) thermal bands. These emissivity images have been compared with each other in terms of geological information for mapping of major rock types in Hutti Maski schist Belt and its associated granitoids. Thermal emissivity images are analyzed conjugately with thermal radiance image, radiant temperature image and albedo image of ASTER bands to understand the potential of thermal emissivity in delineating different rock types of Archaean Greenstone belt. The emissivity images derived using different emissivity extraction algorithms are characterised with poor data dimensionality and signal to noise ratio. Therefore, Inverse MNF false-colour composites(FCC) are derived using bands having better signal to noise(SNR)ratio to enhance the contrast in emissivity. It has been observed that inverse-MNF of emissivity image; which is derived using emissivity-normalisation method is suitable for delineating silica variations in granite and granodioritic gneiss in comparison to other inverse- MNF-emissivity composites derived using other emissivity extraction algorithms(reference channel and alpha residual method). Based on the analysis of ASTER derived emissivity spectra of each rocks, band ratios are derived(band 14/12,band 10/12) and these ratios are used to delineate the rock types based on index based FCC image. This FCC image can be used to delineate granitoids with different silica content. The geological information derived based on processing of ASTER thermal images are further compared with the image analysis products derived using ASTER visible-near-infrared(VNIR) and shortwave infrared(SWIR) bands. It has been observed that delineation of different mafic rocks or greenstone rocks(i.e. separation between chlorite schist and metabasalt) are better in SWIR composites and these composites also provide comparable results with thermal bands in terms of delineation of different types of granitoids.