Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany’s mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA). Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today’s minerology and petroleum engineers. Key Features • Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. • Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. • Includes over 200 equations that illustrate how to follow examples in the book.

Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany’s mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA). Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today’s minerology and petroleum engineers. Key Features • Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. • Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. • Includes over 200 equations that illustrate how to follow examples in the book.

There has been phenomenal growth in the field of remote sensing over the last two to three decades. It has been applied in the fields of geology, mineral exploration, forestry, agriculture, hydrology, soils, land use etc. - that is, in all pursuits of sciences dealing with the features, processes, and phenomena operating at the earth's surface. The status of geological remote sensing has rapidly advanced and the scientific literature is scattered. The aim of the present book is to systematically discuss the specific requirements of geological remote sensing, to summarize the techniques of remote sensing data collection and interpretation, and to integrate the technique into geoexploration. The main conceptual features of the book are: - To combine various aspects of geological remote sensing, ranging from the laboratory spectra of minerals and rocks to aerial and space-borne remote sensmg. - To integrate photogeology into remote sensing. - To promote remote sensing as a tool in integrated geoexploration. - To elucidate the wide-spectrum geoscientific applications of remote sensing, ranging from meso- to global scale. The book has been written to satisfy the needs of mainly graduate students and active research workers interested in applied earth sciences. It is primarily concept -oriented rather than system- or module-oriented.

Essential Image Processing and GIS for Remote Sensing is an accessible overview of the subject and successfully draws together these three key areas in a balanced and comprehensive manner. The book provides an overview of essential techniques and a selection of key case studies in a variety of application areas. Key concepts and ideas are introduced in a clear and logical manner and described through the provision of numerous relevant conceptual illustrations. Mathematical detail is kept to a minimum and only referred to where necessary for ease of understanding. Such concepts are explained through common sense terms rather than in rigorous mathematical detail when explaining image processing and GIS techniques, to enable students to grasp the essentials of a notoriously challenging subject area. The book is clearly divided into three parts, with the first part introducing essential image processing techniques for remote sensing. The second part looks at GIS and begins with an overview of the concepts, structures and mechanisms by which GIS operates. Finally the third part introduces Remote Sensing Applications. Throughout the book the relationships between GIS, Image Processing and Remote Sensing are clearly identified to ensure that students are able to apply the various techniques that have been covered appropriately. The latter chapters use numerous relevant case studies to illustrate various remote sensing, image processing and GIS applications in practice.

With the widespread availability of satellite and aircraft remote sensing image data in digital form, and the ready access most remote sensing practitioners have to computing systems for image interpretation, there is a need to draw together the range of digital image processing procedures and methodologies commonly used in this field into a single treatment. It is the intention of this book to provide such a function, at a level meaningful to the non-specialist digital image analyst, but in sufficient detail that algorithm limitations, alternative procedures and current trends can be appreciated. Often the applications specialist in remote sensing wishing to make use of digital processing procedures has had to depend upon either the mathematically detailed treatments of image processing found in the electrical engineering and computer science literature, or the sometimes necessarily superficial treatments given in general texts on remote sensing. This book seeks to redress that situation. Both image enhancement and classification techniques are covered making the material relevant in those applications in which photointerpretation is used for information extraction and in those wherein information is obtained by classification.

This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms. Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, spatial, and geometric models are used to introduce advanced image processing techniques such as hyperspectral image analysis, fusion of multisensor images, and digital elevationmodel extraction from stereo imagery. The material is suited for graduate level engineering, physical and natural science courses, or practicing remote sensing scientists. Each chapter is enhanced by student exercises designed to stimulate an understanding of the material. Over 300 figuresare produced specifically for this book, and numerous tables provide a rich bibliography of the research literature.