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Airborne Geophysical data in Practice: Processing and Noise Reduction Methods Using R Tools
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The aim of this book is to present a clear and accessible guide to processing a range of remote sensing datasets for geological mapping, with a particular emphasis on cleaning, denoising, and enhancing airborne geophysical data. These datasets play a crucial role in Earth science applications, including lithological prediction, mineral exploration, structural analysis, and environmental studies. Throughout the chapters, R programming tools are used extensively for statistical analysis, data manipulation, visualization, and the development of descriptive machine-learning models, demonstrating how R can support efficient, reproducible workflows in geophysical data processing.
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The aim of this book is to present a clear and accessible guide to processing a range of remote sensing datasets for geological mapping, with a particular emphasis on cleaning, denoising, and enhancing airborne geophysical data. These datasets play a crucial role in Earth science applications, including lithological prediction, mineral exploration, structural analysis, and environmental studies. Throughout the chapters, R programming tools are used extensively for statistical analysis, data manipulation, visualization, and the development of descriptive machine-learning models, demonstrating how R can support efficient, reproducible workflows in geophysical data processing.
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