Digital mapping and GIS-based spatial analyses of the Pur-Banera Group in Rajasthan, India, with special reference to the structural control on base-metal mineralization

Ghosh, Triparna; Chattopadhyay, Anupam; Verma, Gyan; Srivastava, Srijan; Sarkar, Arindam; Bhattacharjee, Dipanjan

doi:10.1016/j.jsg.2022.104762

Cited by 5 publications

(1 citation statement)

References 20 publications

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“…For example, combining geological maps with geophysical data can provide a better understanding of subsurface structures and lithological variations within basement rocks. GIS provides a suite of spatial analysis tools that aid in understanding and interpreting basement rock data [129,130] . These tools allow for the measurement, comparison, and modelling of geological parameters, such as thickness, depth, slope, and orientation.…”

Section: Remote Sensing Of Basement Lithologies Using Contextual Lith...mentioning

confidence: 99%

Regional Mapping of Basement Lithologies Using Geospatial Data in Semi-Arid Regions: Techniques, Advancements and Applications

Amusuk,

Hashim,

Beiranvand Pour

et al. 2024

adv. in geol. and geotech. eng. res.

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Lithological mapping in semi-arid regions has witnessed a phase of transformation due to advancement in remote sensing technology. This has permitted a more comprehensive understanding of surface lithological units. This review explores the evolution of remote sensing mapping techniques and their diverse uses at semi-arid regions, underscoring the significance of the mapping procedure and the prospects. Remote sensing technology has been advancing with moderate to high resolution spaceborne and airborne sensors, unmanned aerial vehicle (UAV) technology and LiDAR (light detection and ranging). These have significantly enhanced capacity, accuracy and the scope of lithological mapping procedures. Especially, the advancement of machine learning and Artificial Intelligent (AI) in automated remote sensing data analysis has ignited more precise ways of identifying and classification of lithological units. Using hybrid remote sensing/machine learning mapping techniques has extended the horizon of geological studies where mineral exploration, water resource management, land use planning, environmental assessments, and risk mitigation are particularly considered. The maps derived provide deeper insights into accurate delineation of mineral deposits, identification of potential sources of water, and aiding those making informed decision making for land development and resource management. The importance of hybrid remote sensing/ machine learning techniques lies with the profound contributions made through geological history, resource exploration, environmental preservation, and risk management directed to fragile ecosystems such as semi-arid environments. The future of the hybrid methodologies holds promise for further advancements in integrating various data sources, exploitation of their contextual properties, refining AI algorithms for faster and more accurate analysis, and methodologies that are specific to environments. These evolving technologies and diverse applications present a trajectory targeted at more comprehensive utilization of geological resources and improvement of environmental stewardship even to fragile regions.

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Section: Remote Sensing Of Basement Lithologies Using Contextual Lith...mentioning

confidence: 99%

Regional Mapping of Basement Lithologies Using Geospatial Data in Semi-Arid Regions: Techniques, Advancements and Applications

Amusuk,

Hashim,

Beiranvand Pour

et al. 2024

adv. in geol. and geotech. eng. res.

View full text Add to dashboard Cite

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Application of semi-automated methods for extraction of geological surface orientations: A case study from the outer Garhwal Himalaya

Panigrahi,

Srivastava,

Tiwari

et al. 2023

J Earth Syst Sci

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Enhancing local-scale groundwater quality predictions using advanced machine learning approaches

Yadav,

Raj,

Yadav

2024

Journal of Environmental Management

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Digital mapping and GIS-based spatial analyses of the Pur-Banera Group in Rajasthan, India, with special reference to the structural control on base-metal mineralization

Cited by 5 publications

References 20 publications

Regional Mapping of Basement Lithologies Using Geospatial Data in Semi-Arid Regions: Techniques, Advancements and Applications

Regional Mapping of Basement Lithologies Using Geospatial Data in Semi-Arid Regions: Techniques, Advancements and Applications

Application of semi-automated methods for extraction of geological surface orientations: A case study from the outer Garhwal Himalaya

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches

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