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.
Part of an ongoing series of manuals covering the range of applications of remotely sensed imagery, Volume 4 addresses the use of this technology in natural resource management and environmental monitoring. Comprehensive, authoritative, and up-to-date, it covers terrestrial ecosystems, aquatic ecosystems, and agriculture ecosystems, as well as future directions in technology and research.
This third edition of the bestselling Remote Sensing for Geologists: A Guide to Image Interpretation is now titled Remote Sensing for Geoscientists: Image Analysis and Integration. The title change reflects that this edition applies to a broad spectrum of geosciences, not just geology; stresses that remote sensing has become more than photointerpretation; and emphasizes integration of multiple remote sensing technologies to solve Earth science problems. The text reviews systems and applications, explains what to look for when analyzing imagery, and provides abundant case histories to illustrate the integration and application of these tools. See What’s New in the Second Edition: Broader coverage to include integration of multiple remote sensing technologies Expanded with significant new illustrations in color and reviews of new satellites and sensors Analysis of imagery for geobotanical remote sensing, remote geochemistry, modern analogs to ancient environments, and astrogeology The book covers how to initiate a project, including determining the objective, choosingthe right tools, and selecting imagery. It describes techniques used in geologic mapping and mineral and hydrocarbon exploration, image analysis used in mine development and petroleum exploitation, site evaluation, groundwaterdevelopment, surface water monitoring, geothermal resource exploitation, and logistics. It also demonstrates how imageryis used to establish environmental baselines; monitor land, air, and water quality; maphazards; and determine the effects of global warming. The many examples of geologic mapping on other planets and the moon highlight how to analyze planetary surface processes, map stratigraphy, and locate resources. The book then examines remote sensing and the public, geographic information systems and Google Earth, and how imagery is used by the media, in the legal system, in public relations, and by individuals. Readers should come away with a good understanding of what is involved in image analysis and interpretation and should be ableto recognize and identify geologic features of interest. Having read this book, they should be able to effectively use imagery in petroleum, mining, groundwater, surface water, engineering, and environmental projects.
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.
The cryosphere, that region of the world where water is temporarily or permanently frozen, plays a crucial role on our planet. Recent developments in remote sensing techniques, and the acquisition of new data sets, have resulted in significant advances in our understanding of all components of the cryosphere and its processes. This book, based on contributions from 40 leading experts, offers a comprehensive and authoritative overview of the methods, techniques and recent advances in applications of remote sensing of the cryosphere. Examples of the topics covered include: • snow extent, depth, grain-size and impurities • surface and subsurface melting • glaciers • accumulation over the Greenland and Antarctica ice sheets • ice thickness and velocities • gravimetric measurements from space • sea, lake and river ice • frozen ground and permafrost • fieldwork activities • recent and future cryosphere-oriented missions and experiments All figures are in color and provide an excellent visual accompaniment to the technical and scientific aspect of the book. Readership: Senior undergraduates, Masters and PhD Students, PostDocs and Researchers in cryosphere science and remote sensing. Remote Sensing of the Cryosphere is the significant first volume in the new Cryosphere Science Series. This new series comprises volumes that are at the cutting edge of new research, or provide focussed interdisciplinary reviews of key aspects of the science.
As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
Remote Sensing of Geomorphology, Volume 23, discusses the new range of remote-sensing techniques (lidar, structure from motion photogrammetry, advanced satellite platforms) that has led to a dramatic increase in terrain information, and as such provided new opportunities for a better understanding of surface morphology and related Earth surface processes. As several papers have been published (including paper reviews and special issues) on this topic, this book summarizes the major advances in remote sensing techniques for the analysis of Earth surface morphology and processes, also highlighting future challenges. Useful for MSc and PhD students, this book is also ideal for any scientists that want to have a single volume guideline to help them develop new ideas. In addition, technicians and private and public sectors working on remote sensing will find the information useful to their initiatives.
Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations.
Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences