High resolution multispectral satellite data interpretation and limited ground checking: A proxy for geological mapping and uranium exploration in Mahakoshal Fold Belt of Son valley area, Madhya Pradesh

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• 作者：A. K. Dwivedi ; Abhinav Kumar…
• 刊名：Journal of the Geological Society of India
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：88
• 期：2
• 页码：159-172
• 全文大小：8,064 KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Geology
  Geosciences
  Geography
  Mineralogy
  
• 出版者：Springer India, co-published with Geological Society of India
• ISSN：0974-6889
• 卷排序：88

文摘

This research aims at integrating remote sensing data and field studies to prospect for uranium mineralisation in the Palaeoproterozoic Mahakoshal Group of rocks in the Son valley area, Central India. In present work, a revised geological map of Mahakoshal Fold Belt (MFB) bounded by Son-Narmada north fault (SNNF) and Son-Narmada south fault (SNSF) along Chorhut-Sidhi-Chitrangi sector falling in Sidhi, Rewa and Shahdol districts of Madhya Pradesh has been prepared based on interpretation of digitally enhanced satellite images. The satellite image interpretation is supported by limited field works, radioelemental measurements (eU, eTh and % K) of in-situ rocks by four channel Portable Gamma Ray Spectrometer (PGRS) and existing published geological maps of Geological Survey of India. In search for mineral potential areas, accurate and up-to-date geological maps are essential as it represent the most basic information for carrying out further exploration activities. However, available geological maps of MFB and sedimentary formations ofVindhayan Supergroup along SNNF and Chhotanagpur Granite Gneissic Complex (CGGC) and Gondwana Supergroup along SNSF available in public domain are discontinuous and multi-scaled.Optical bands of Landsat Enhanced Thematic Mapper Plus (ETM+) and Indian Remote Sensing (IRS) PAN of the study area were used in mapping lithological units, structural features and small intrusive bodies. Principal Component Analysis (PCA), Image Fusion, Linear Contrast Stretch, Histogram Equalisation and False Color Composite (FCC) of various band combination and ratio maps were performed in the digital image processing of geo-rectified satellite imageries. In analyzing and interpreting high resolution multi-spectral images, certain standard norms were employed to acquire information about litho-structural features such as topographic, geomorphic and tectonic facets. The main criteria are colour and tones, geomorphology, drainage patterns and vegetation anomalies. The processed Landsat ETM+ images were interpreted and classified to delineate detailed lithological units and structural features in order to update existing geological maps.To validate the prepared litho-structural map, ground survey was carried out along critical geological sections for checking the geological features like rocks, folds, faults, fractures and foliations. While comparing with the ground geological data to that obtained from the satellite imagery, it is observed that remote sensing interpreted litho-structural map is in a class with the ground observations. Various data sets such as unconformable geological contacts, fault breccias zone, lineaments and gamma ray spectrometric data (eU, eTh and % K) based on PGRS study were integrated and modelled using Geographical Information System (GIS) for identifying important prospective horizons for uranium mineralisation in the MFB of Son valley area. It is concluded that the revised large scale geological map is of practical use for not only for mapping of litho-structural architecture, but also in identifying potential areas for ‘vein–type’ uranium mineralisation along the structurally deformed zones of the SNNF, Asmi-Jiawan fault (AJF) and SNSF; and ‘unconformity- type’ of uranium mineralisation in the outliers of Jungel Group. The revised map and radiometric data acquired are useful in formulating exploration strategy for the ongoing uranium exploration in this areaKeywordsRemote SensingGISUranium ExplorationMahakoshal Fold BeltSon ValleyMadhya Pradesh