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.
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.
Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology. - Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines - Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection - Provides an overview of the state-of-the-art, including algorithms, techniques and case studies
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.
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.
Following the successful publication of the 1st edition in 2009, the 2nd edition maintains its aim to provide an application-driven package of essential techniques in image processing and GIS, together with case studies for demonstration and guidance in remote sensing applications. The book therefore has a “3 in 1” structure which pinpoints the intersection between these three individual disciplines and successfully draws them together in a balanced and comprehensive manner. The book conveys in-depth knowledge of image processing and GIS techniques in an accessible and comprehensive manner, with clear explanations and conceptual illustrations used throughout to enhance student learning. The understanding of key concepts is always emphasised with minimal assumption of prior mathematical experience. The book is heavily based on the authors’ own research. Many of the author-designed image processing techniques are popular around the world. For instance, the SFIM technique has long been adopted by ASTRIUM for mass-production of their standard “Pan-sharpen” imagery data. The new edition also includes a completely new chapter on subpixel technology and new case studies, based on their recent research.
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
Remote sensing has undergone profound changes over the past two decades as GPS, GIS, and sensor advances have significantly expanded the user community and availability of images. New tools, such as automation, cloud-based services, drones, and artificial intelligence, continue to expand and enhance the discipline. Along with comprehensive coverage and clarity, Sabins and Ellis establish a solid foundation for the insightful use of remote sensing with an emphasis on principles and a focus on sensor technology and image acquisition. The Fourth Edition presents a valuable discussion of the growing and permeating use of technologies such as drones and manned aircraft imaging, DEMs, and lidar. The authors explain the scientific and societal impacts of remote sensing, review digital image processing and GIS, provide case histories from areas around the globe, and describe practical applications of remote sensing to the environment, renewable and nonrenewable resources, land use/land cover, natural hazards, and climate change. • Remote Sensing Digital Database includes 27 examples of satellite and airborne imagery that can be used to jumpstart labs and class projects. The database includes descriptions, georeferenced images, DEMs, maps, and metadata. Users can display, process, and interpret images with open-source and commercial image processing and GIS software. • Flexible, revealing, and instructive, the Digital Image Processing Lab Manual provides 12 step-by-step exercises on the following topics: an introduction to ENVI, Landsat multispectral processing, image processing, band ratios and principal components, georeferencing, DEMs and lidar, IHS and image sharpening, unsupervised classification, supervised classification, hyperspectral, and change detection and radar. • Introductory and instructional videos describe and guide users on ways to access and utilize the Remote Sensing Digital Database and the Digital Image Processing Lab Manual. • Answer Keys are available for instructors for questions in the text as well as the Digital Image Processing Lab Manual.
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.
