Comparison of Supervised Classification Methods for Efficiently Locating Possible Mineral Deposits using Multispectral Remote Sensing data

Coastal landforms characterized by an accumulation of a wide range of sediment types and by many varied coastal environments. Sediment deposits around the central Tamilnadu coast contain significant amounts of heavy minerals and may attain concentrations of economicimportance. The research work emphasize to locating possible heavy mineral deposits from multispectral imagery using supervised classificationmethods. We focused on soil prototype for locating possible minerals due to presence of placer deposits and absence of rock formations in ourstudy area. The textural features were employed aiming at obtaining a highly separable class sets. Many supervised classification techniques areutilized in surface mineral investigation. Among them, several supervised techniques are analysed and the algorithm that best suit for theapplication is determined