Multispectral And Hyperspectral Remote Sensing Data For Mineral Exploration And Environmental Monitoring Of Mined Areas
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Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas by Amin Beiranvand Pour,Basem Zoheir,Biswajeet Pradhan,Mazlan Hashim Pdf
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.
Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas by Amin Beiranvand Pour,Basem Zoheir,Biswajeet Pradhan,Mazlan Hashim Pdf
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.
Geospatial Analysis Applied to Mineral Exploration by Amin Beiranvand Pour,Mohammad Parsa,Ahmed M Eldosouky Pdf
Geospatial Analysis Applied to Mineral Exploration: Remote Sensing, GIS, Geochemical, and Geophysical Applications to Mineral Resources presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling for Earth scientists, researchers, mineral exploration communities and mining companies. This book will help readers solve high complexity issues in remote sensing data processing, geochemical data analysis, geophysical data analysis, and appropriate applications of GIS techniques for data fusion designed for mineral exploration purposes. It contains updated knowledge of remote sensing imagery, geochemistry, geophysics and geospatial techniques that can assist in delineating the signatures and patterns linked to deep-seated, covered, blind or buried mineral deposits. Covers advances in remote sensing data processing algorithms and geochemical data analysis Includes sections on geophysical data analysis and machine learning algorithms for mineral exploration Introduces the suite of geo-spatial tools currently available for mineral exploration Presents case studies to provide real-world examples of the theories covered
Remote Sensing Intelligent Interpretation for Mine Geological Environment by Weitao Chen,Xianju Li,Lizhe Wang Pdf
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.
Fundamentals of Geological and Environmental Remote Sensing by Robert K. Vincent Pdf
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.
Remote Sensing and Geographic Information Systems by Christopher Legg Pdf
Incorporating recent advances made in remote sensing technology, this text draws attention to ways in which remote sensing may minimize the environmental impact of exploration and improve cost-effectiveness. Topics include image processing, geographic information systems, current and future sensing
Encyclopedia of Mathematical Geosciences by B. S. Daya Sagar,Qiuming Cheng,Jennifer McKinley,Frits Agterberg Pdf
The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work. It provides concise explanation on each term that is related to Mathematical Geosciences. Over 300 international scientists, each expert in their specialties, have written around 350 separate articles on different topics of mathematical geosciences including contributions on Artificial Intelligence, Big Data, Compositional Data Analysis, Geomathematics, Geostatistics, Geographical Information Science, Mathematical Morphology, Mathematical Petrology, Multifractals, Multiple Point Statistics, Spatial Data Science, Spatial Statistics, and Stochastic Process Modeling. Each topic incorporates cross-referencing to related articles, and also has its own reference list to lead the reader to essential articles within the published literature. The entries are arranged alphabetically, for easy access, and the subject and author indices are comprehensive and extensive.
Remote Sensing for Environmental Monitoring by Samy Ismail Elmahdy,Maged Marghany,Jie Luo Pdf
Advancements in object-based image analysis, commercial high-resolution satellite sensors, and unmanned aerial vehicles, there is growing interest in studying terrestrial, pollution, catastrophe, and ocean dynamics using a range of high-resolution remote sensing data (UAV). High and extremely high-resolution optical and microwave images enable the extraction of more information from a variety of resource management domains, including agriculture, forestry, geological resources, water resources, cryosphere, atmosphere, and analytics for climate change. Researchers have started utilizing advanced techniques for fine-level information extraction, new sensors and platforms, improved quantification, and characterization of physical environments, patterns, and processes. High-quality articles addressing the use and application of remote sensing in environmental studies will be published in this Research Topic.
Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation by Prasad S. Thenkabail,John G. Lyon,Alfredo Huete Pdf
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.
Over the past decade, advances in sensor technology, processing algorithms, and computational capacity have taken remote sensing to a level where observations can be transformed into quantitative measurements, and the technology can be used in near real-time for mapping, monitoring and decision-making. For the third edition, this widely acclaimed book has been fully revised, enlarged and updated. It covers remote sensing in a wide range of optical, thermal, and microwave wavelengths and their host of geologic applications featuring sample applications from around the globe. In addition, it presents state-of-the-art content on emerging themes such as atmospheric interactions, spectroscopy, spectral indices, prospectivity modelling, and multi-sensor geodata integration. The subject matter is presented at a basic level, offering students an excellent introductory text on remote sensing. Further, the main part of the book will also be of great value to active researchers. Excerpt from the review of Remote Sensing Geology (2nd ed., 2003): International Journal of Applied Earth Observation and Geoinformation, 5 (2004) 239–240 “....Graduate students, research workers and professional earth scientists will use this book to their advantage and with pleasure; it is well-written, to the point and with an emphasis on understanding the principles underlying this wide spectre of technology in its application to the earth sciences. Remote sensing is a fascinating subject; so is geology. The author has fully succeeded in providing a fascinating book that combines them in a handy volume.” Jan J. Nossin
Manual of Remote Sensing, Remote Sensing for the Earth Sciences by Andrew N. Rencz,Robert A. Ryerson Pdf
Die großen Fortschritte in der Fernerkundung sowie die Verfügbarkeit umfangreicher neuer Satellitendaten machten die Neuauflage des bekannten 8-bändigen "Manual of Remote Sensing" erforderlich. Behandelt werden Theorie und praktische Anwendungsmöglichkeiten von Fernerkundungs-Satellitendaten auf geologische Problemstellungen. Darüber hinaus beschreibt Band 3 die technischen Mittel zur Erzielung der Daten (Radar, Licht-, Infrarot- und geophysikalische Sensoren) und deren Anwendungsbereiche (Exploration von Erz- und Kohlelagerstätten, Stratigraphie, technische Geologie und Umweltstudien). Dieser Band bietet eine ideale Kombination von Theorie, Datenanalyse und Fallstudien zur Veranschaulichung grundlegender Konzepte.
