For nearly three decades there has been a phenomenal growth in the field of Remote Sensing. The second edition of this widely acclaimed book has been fully revised and updated. The reader will find a wide range of information on various aspects of geological remote sensing, ranging from laboratory spectra of minerals and rocks, ground truth, to aerial and space-borne remote sensing. This volume describes the integration of photogeology into remote sensing as well as how remote sensing is used as a tool of geo-exploration. It also covers a wide spectrum of geoscientific applications of remote sensing ranging from meso- to global scale. The subject matter is presented at a basic level, serving students as an introductory text on remote sensing. The main part of the book will also be of great value to active researchers.

A guide to image interpretation, this book contains detailed color plates and tables that compare satellite imaging systems, list remote sensing web sites, and detail photointerpretation equipment. It includes case histories of the search for petroleum and mineral deposits and examines engineering uses of remote sensing. The volume comprises four sections: project initiation; exploration techniques; exploitation and engineering remote sensing; and environmental concerns. They combine to provide readers with a solid foundation of what image interpretation is and enables them to recognize features of interest and effectively use imagery in projects for the petroleum, mining, or groundwater industries.

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.

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.

Our planet is nowadays continuously monitored by powerful remote sensors operating in wide portions of the electromagnetic spectrum. Our capability of acquiring detailed information on the environment has been revolutionized by revealing its inner structure, morphology and dynamical changes. The way we now observe and study the evolution of the Earths status has even radically influenced our perception and conception of the world we live in. The aim of this book is to bring together contributions from experts to present new research results and prospects of the future developments in the area of geosciences and remote sensing, emerging research directions are discussed. The volume consists of twenty-six chapters, encompassing both theoretical aspects and application-oriented studies. An unfolding perspective on various current trends in this extremely rich area is offered. The book chapters can be categorized along different perspectives, among others, use of active or passive sensors, employed technologies and configurations, considered scenario on the Earth, scientific research area involved in the studies.

Remote Sensing Technology Is Today Widely Used In The Survey And Management Of Natural Resources. The Present Book Contains Much Informative And Well-Researched Articles, Contributed By Eminent Academics And Scientists In The Field. Topics Like Ground Water Prospecting Through Remote Sensing; Data Integration In Geographic Information System And Its Efficacy; Highlights Of Advanced Technologies In Remote Sensing; Utility Of Gis And Image Processing Methods For Agro-Based Commercial Ventures; Remote Sensing Methodologies For Indian Small Scale Mining Industry; Filtering Applications In Geosciences; Integration Of Collateral Data With Remote Sensing Data; Ground Water Budgeting Through Satellite Data; Neural Network And Fuzzy Logic In Remote Sensing; Image Enhancement Analysis For Improving Classification Accuracy Over Vegetated Areas; Evidence Classifier For Land Use/Land Cover Classification; Morphological Image Processing; Integration Of Spot And Sar Images For Monitoring Of Environmental Changes By A Fuzzy Neural Network; Correlation Of Landsat Images To Resistivity And Seismic Structures In A Sedimentary Basin; Novel Vegetation Indices For Remote Sensing Of Chlorophyll Contents In Higher Plants; Remote Sensing Of Chlorophyll; Evaluation Of Groundwater Potentials In Hard Rock Terrains Through Geomorphic Mapping; Application Of Remote Sensing To Land Slide Studies; Use Of Remotely Sensed Data To Study And Arid Terrain, Wadi Tabalah Area, Kingdom Of Saudi Arabia; Application Of Remote Sensing Technology In Mapping And Monitoring Salt Affected Soils; Lineament Mapping On Satellite Images For Deciphering Hydrogeologic Situation In Banas River Basin, Etc. Researchers, Scientists And Academics Will Find This Book Of Utmost Use.

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.