Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3819
Title: Satellite-based spectral mapping (ASTER and landsat data) of mineralogical signatures of beach sediments: a precursor insight
Authors: Rejith, R G
Sundararajan, M
Gnanappazham, L
Loveson, V J
Keywords: heavy minerals
SAM classification
landsat
ASTER
Thiruvananthapuram
Issue Date: 14-Apr-2020
Publisher: Informa UK Limited
Citation: Geocarto International;1-24
Abstract: Detailed investigation on texture and mineralogy of beach sediments helps to understand their nature of deposition and potential targets of strategic mineral deposits. The beach sediments from the coast of Thiruvananthapuram, the southernmost district of Kerala, India, have been studied to understand the variation in grain size by using the spectral indices as derived from the visible-NIR-TIR bands of Landsat and ASTER remote sensing data. Further, an attempt has been made to map the distribution of strategic minerals present in beach sands using standardized hyperspectral analysis techniques. The grain size shows a remarkable variation from medium sand to fine sand. The THM (Total Heavy Minerals) content was estimated to about 80.04% and 52.33% along the coast of Kovalam and Varkala, respectively. The ilmenite mineral predominantly exists in these areas, followed by monazite, sillimanite, rutile, zircon, garnet, leucoxene, and Kyanite. The hyperspectral analysis extracts two endmembers of ilmenite and light minerals from the Landsat and ASTER imagery, which could be successfully, mapped using the SAM classification algorithm. The satellite-derived map showing texture and mineralogy has been validated with the results of laboratory analysis and shows strong correlation almost in all locations. This study illustrates the potential use of satellite remote sensing techniques for the mapping of natural resources, especially mineral resources.
URI: https://doi.org/10.1080/10106049.2020.1750061
http://hdl.handle.net/123456789/3819
Appears in Collections:2020

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