Remote Sensing Of The Mine Environment

A guide for students and professionals, this introductory course book covers the basic principles of remote sensing and its applications in mine environment monitoring. Building from a reader’s basic knowledge of mine monitoring, it teaches how to implement remote sensing techniques and how to interpret the acquired data for different purposes. Following a general introduction to remote sensing principles and image analysis, mine subsidence monitoring, slope stability monitoring, reclamation planning and implementation, and post-closure mine and land use analysis are explained and illustrated. With the help of case studies, the techniques and tools presented are demonstrated. With an increasing importance of sustainable mining, this accurate text is intended for the education of university students in mining, civil, geological and environmental engineering. Researchers and professionals in these disciplines may find it beneficial as well to guide their professional monitoring investigations.

This book discussed on the basic principles of remote sensing and its applications in mine environment monitoring. Building from a reader's basic knowledge of mine monitoring, it teaches how to implement remote sensing techniques and how to interpret the acquired data for different purposes. Following a general introduction to remote sensing principles and image analysis, mine subsidence monitoring, slope stability monitoring, reclamation planning and implementation, and post-closure mine and land use analysis are explained and illustrated. With the help of case studies, the techniques and tools presented are demonstrated.

This book examines the theory and methods of remote sensing intelligent interpretation based on deep learning. Based on geological and environmental effects on mines, this book constructs a set of systematic mine remote sensing datasets focusing on the multi-level task with the system of “target detection→scene classification→semantic segmentation." Taking China’s Hubei Province as an example, this book focuses on the following four aspects: 1. Development of a multiscale remote sensing dataset of the mining area, including mine target remote sensing dataset, mine (including non-mine areas) remote sensing scene dataset, and semantic segmentation remote sensing dataset of mining land cover. The three datasets are the basis of intelligent interpretation based on deep learning. 2. Research on mine target remote sensing detection method based on deep learning. 3. Research on remote sensing scene classification method of mine and non-mine areas based on deep learning. 4. Research on the fine-scale classification method of mining land cover based on semantic segmentation. The book is a valuable reference both for scholars, practitioners and as well as graduate students who are interested in mining environment research.

In recent decades, remote sensing technology has been incorporated in numerous mineral exploration projects in metallogenic provinces around the world. Multispectral and hyperspectral sensors play a significant role in affording unique data for mineral exploration and environmental hazard monitoring. This book covers the advances of remote sensing data processing algorithms in mineral exploration, and the technology can be used in monitoring and decision-making in relation to environmental mining hazard. This book presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling, offering excellent information to professional earth scientists, researchers, mineral exploration communities and mining companies.

In recent decades, remote sensing technology has been incorporated in numerous mineral exploration projects in metallogenic provinces around the world. Multispectral and hyperspectral sensors play a significant role in affording unique data for mineral exploration and environmental hazard monitoring. This book covers the advances of remote sensing data processing algorithms in mineral exploration, and the technology can be used in monitoring and decision-making in relation to environmental mining hazard. This book presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling, offering excellent information to professional earth scientists, researchers, mineral exploration communities and mining companies.

Aims to present remote sensing as it applies to environmental monitoring. It features mineral and petroleum remote-sensing. There is a focus on multispectral applications and digital photogrammetry. Ratio codes and brightness codes are included in an appendix. This has reduced the spectra of minerals to simple, one-digit-per-band codes, helping the user select the best bands or ratios to highlight a mineral. Imaging gases, especially methane, have been included. With the book, students can perform elevation extraction from digitized stereo pairs. Case studies appear throughout the text, allowing students to see how remote-sensing is used in petroleum and mining companies.

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.