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Application of hyperspectral remote sensing and artificial neural network in the mineral exploration and discrimination of Saranda forest and its surroundings regions
  • Hemant Kumar
Hemant Kumar
USM Malaysia

Corresponding Author:[email protected]

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Abstract

This study was acquited on the mining area located under the Saranda area of West Singhbhum district in Jharkhand and part of the state of Odisha. Here, GST data is used at the 30 m resolution of Hyperion, a hyperspectral remote sensing satellite. In this study, different types of image processing exemplar are used to empower and extract the Hematite and Manganese ore mining class. The present method was created to improve the mining class with a spectral signature associated with the features class. In the present study, an index, that is, a mineral index created to distinguish the mineral ore as seen on Earth in open mining areas. A decree analysis is to clarify the eubstance of this index.In this way, the multifarious process & generated mineral-index applied to wedded frequency, strength to enhance the mineral class & comparative evaluation done over the data sets.The diverse supervised classification has been done to identify the mineral class under the GUA Mining range of Hyperion data. Also, the NDVI used to excerption the open cast mining class after the virtual removal of vegetation class on the scale of (1-NDVI).Further THOR, ICA, ANN used here to single out the minerals, & also by this way the new index probed.