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Remote Sensing For Geoscientists

Author: Gary L. Prost
Publisher: CRC Press
ISBN: 1466561750
Size: 36.49 MB
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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.

Remote Sensing For Geologists

Author: Gary L. Prost
Publisher: CRC Press
ISBN: 9057026295
Size: 61.74 MB
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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.

Digital Analysis Of Remotely Sensed Imagery

Author: Jay Gao
Publisher: Mcgraw-hill
ISBN: 9780071604659
Size: 37.95 MB
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"Jay Gao’s book on the analysis of remote sensing imagery is a well-written, easy-to-read, and informative text best serving graduate students in geosciences, and practitioners in the field of digital image analysis. Although Dr. Gao states that he has targeted his book at upper-level undergraduates and lower-level postgraduate students, its rigor and depth of mathematical analysis would challenge most students without prior experience in remote sensing and college-level mathematics. The book covers a lot of ground quickly, beginning with a basic explanation of pixels, digital numbers and histograms and advancing rapidly through a description of the most well-known satellite systems to data storage formats, rectification and classification. It best serves students who have already taken an introductory course in remote sensing. Following a three-chapter description of the basics the remaining eleven chapters are dedicated to the description of the most common image processing systems and the details of the image analysis functions which can be carried out. The largest portion of the text covers classification – spectral and spatial, neural networks, decision trees and expert systems – and is an invaluable reference to anyone interested in understanding image analysis terminology and the algorithms behind these different systems. The last chapter of the text is addressed to practitioners wishing to integrate remote sensing image data with GIS and/or GPS data. The text is nicely structured so that individual chapters can easily be skipped when their content is not of interest to the reader without impairing the understanding of later chapters. "The first three chapters of the book cover introductory material that the reader should be familiar with for the most part, but also includes a very handy summary of today’s satellite systems. Chapter one addresses basic material, such as pixel DN, coordinates, feature space, histograms, and spatial, spectral, temporal and radiometric resolution normally covered in an introductory course in remote sensing. Chapter two presents a very informative and up-to-date overview of today’s satellite instruments including meteorological, oceanographic, earth resources, hyperspectral and radar instruments. Instrument and orbital parameters are presented in tabular form and make it easy to look up technical details such as spectral and spatial resolution, orbit type, repeat cycle and other instrument characteristics quickly. Written explanations are clear, readable and provide lots of interesting insight and useful tidbits of information such as potential problems and the cost of imagery. For technicians and programmers the third chapter provides details on storage formats, including descriptions of BSQ, BIL and BIP binary formats, and the most common graphics formats like GIF, TIFF and JPEG together with data compression techniques. Non-technicians can skip this chapter since image processing software will generally take care of format conversions internally without a need for understanding the nuances of each. "Chapters four will be of interest to anyone considering the purchase of image processing software, or trying to understand the differences between systems. Gao provides a useful overview of existing software – IDRISI, ERDAS Imagine, ENVI, ER Mapper, PCI, eCognition and GRASS. A brief history of each provides useful background, and a discussion of the features of each together with a comparison (also given in tabular form) is informative to anyone considering a purchase. "Chapter five can also be viewed as a stand-alone reference on rectification, but also serves as an excellent overview of the problems of dealing with mapping on a curved surface and has particular application for geographers and cartographers. It discusses the sources of geometric distortion, coordinated systems and projections, how image rectification is done – including the use of ground control points and implications for the order of transformation employed. There is a nice example showing how accuracy is influenced by the number of GCPs employed for SPOT and Landsat TM. For non-technical students the transformation mathematics can be skipped. A rather minimal section on image subsetting and mosaicking is included. Chapter six continues in much the same vein as the previous chapter, but discussing image enhancement – techniques that improve the visual quality of an image. The terms introduced here, such as density slicing, linear enhancement, stretching, and histogram equalization, will be familiar to users of image processing software and Gao provides a useful explanation of each in turn. Other application-oriented utilities such as band ratioing, vegetation indices, IHS and Tasseled Cap transformations and principal component analysis are presented in a form which is understandable to students with good mathematical grounding. "The remainder of the text deals, to a large extent, with the topic of classification. Chapter seven initially discusses elements of image interpretation, but then devotes the chapter to a detailed presentation of the most common (and affordable) of these - spectral analysis. Gao presents the different algorithms used to define spectral distance, and then devotes text to a discussion of the inner workings of unsupervised classification systems. The section on supervised classification is a very useful reference for anyone undertaking this process – describing how to set about the classification process, the differences between the different classifiers, and how to choose an appropriate one. The concepts of fuzzy logic and sub-pixels classifiers are also presented briefly. "From this point on, the text becomes much more specialized and technical and is geared towards graduate students, those carrying out research projects, and those interested in algorithmic detail. Chapter 8 is the first dealing with artificial intelligence and describes the fundamentals of neural networks. It provides sufficient information for a technically-minded non-specialist to understand the workings of such a system and serves as a good introduction to someone who is considering this field of research. Chapter nine offers an explanation of decision trees with both a descriptive verbal approach and with mathematical algorithmic detail. Chapter ten addresses spatial classifiers – in particular the analysis of texture. This chapter again leans more heavily towards mathematics and the detail is more suited to readers with a strong technical bent. Gao goes on to discuss the process of image segmentation and thence the fundamentals of object-oriented classification. There is a useful overview of two popular software packages – eCognition and Feature Analyst – together with a discussion of the strengths and weaknesses of object-based classification. Chapter eleven presents an overview of expert systems. This is an advanced field of artificial intelligence and is an ambitious undertaking to describe in fifty or so pages. It is an interesting read for someone trying to gain a superficial knowledge of the workings of such a system and the associated terminology, but for anyone wishing to work in the field, a much more in-depth coverage is necessary. "At this point, the student who was just trying to understand the basics of image processing and classification (and who skipped chapters eight through eleven) should resume reading as the last three chapters provide very helpful practical information. Chapter twelve provides a useful discussion on the methodology for assessing the accuracy of a classification and includes sources of inaccuracy and interpretation of an error matrix. It provides worked examples of accuracy assessments using simple math. This is a valuable addition to the text and presents an important process that is often overlooked in reporting classification results. Chapters thirteen and fourteen also deal with very practical matters. Chapter thirteen describes procedures for handling the analysis of temporal changes via a variety of change detection algorithms, and chapter fourteen introduces the use of GIS and GPS data in image analysis. "Dr. Gao has written an excellent text describing technical information in a very readable manner. His book will serve as a good text for a course in remote sensing/image analysis, assuming that the student has received instruction in the fundamentals of remote sensing and been introduced to some image processing software. Students wishing to become adept at the practicalities of fundamental image processing skills and classification can easily skip the mid section of the text, whereas those who are keen to learn about more sophisticated classifiers will gain the fundamentals of these from this section. Overall I found the book very informative and a pleasure to read." Reviewed by Helen M. Cox, PhD. Associate Professor, Department of Geography, California State University, Northridge

Remote Sensing Image Fusion

Author: Luciano Alparone
Publisher: CRC Press
ISBN: 1466587504
Size: 10.31 MB
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A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as compressive sensing and sparse signal representations. The book brings a new perspective to a multidisciplinary research field that is becoming increasingly articulate and comprehensive. It fosters signal/image processing methodologies toward the goal of information extraction, either by humans or by machines, from remotely sensed images. The authors explain how relatively simple processing methods tailored to the specific features of the images may be winning in terms of reliable performance over more complex algorithms based on mathematical theories and models unconstrained from the physical behaviors of the instruments. Ultimately, the book covers the births and developments of three generations of RS image fusion. Established textbooks are mainly concerned with the earliest generation of methods. This book focuses on second generation methods you can use now and new trends that may become third generation methods. Only the lessons learned with second generation methods will be capable of fostering the excellence among the myriad of methods that are proposed almost every day by the scientific literature.

Observation Of The Earth And Its Environment

Author: Herbert J. Kramer
Publisher: Springer Science & Business Media
ISBN: 9783540423881
Size: 16.96 MB
Format: PDF
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This book is about spaceborne missions and instruments. In addition, surveys of airborne missions and of campaigns can be found on the accompanying CD-ROM in pdf-format. Compared with the 3rd edition the spaceborne part grew from about 300 to 1000 pages. The complete text - including the electronic-only chapters - contains more than 1900 pages. New chapters treat the history of Earth observation and university missions. The number of commercial Earth imaging missions has grown significantly. A chapter contains reference data and definitions. Extensive appendices provide a comprehensive glossary, acronyms and abbreviations and an index of sensors. An effort has been made to present the information in context, to point out relationships and interconnections. The book may serve as a reference and guide to all involved in the various national and international space programs: researchers and managers, service providers and data users, teachers and students.

Advanced Remote Sensing

Author: Shunlin Liang
Publisher: Academic Press
ISBN: 0123859557
Size: 22.76 MB
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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

Remote Sensing

Author: Robert A. Schowengerdt
Publisher: Elsevier
ISBN: 0080516106
Size: 67.61 MB
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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.

Physical Principles Of Remote Sensing

Author: Gareth Rees
Publisher: Cambridge University Press
ISBN: 110700473X
Size: 28.17 MB
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A quantitative yet accessible introduction to remote sensing techniques, this new edition covers a broad spectrum of Earth science applications.

Comprehensive Remote Sensing

Publisher: Elsevier
ISBN: 0128032219
Size: 29.11 MB
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Comprehensive Remote Sensing covers all aspects of the topic, with each volume edited by well-known scientists and contributed to by frontier researchers. It is a comprehensive resource that will benefit both students and researchers who want to further their understanding in this discipline. The field of remote sensing has quadrupled in size in the past two decades, and increasingly draws in individuals working in a diverse set of disciplines ranging from geographers, oceanographers, and meteorologists, to physicists and computer scientists. Researchers from a variety of backgrounds are now accessing remote sensing data, creating an urgent need for a one-stop reference work that can comprehensively document the development of remote sensing, from the basic principles, modeling and practical algorithms, to various applications. Fully comprehensive coverage of this rapidly growing discipline, giving readers a detailed overview of all aspects of Remote Sensing principles and applications Contains ‘Layered content’, with each article beginning with the basics and then moving on to more complex concepts Ideal for advanced undergraduates and academic researchers Includes case studies that illustrate the practical application of remote sensing principles, further enhancing understanding

A Wavelet Tour Of Signal Processing

Author: Stephane Mallat
Publisher: Academic Press
ISBN: 9780080922027
Size: 29.19 MB
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Mallat's book is the undisputed reference in this field - it is the only one that covers the essential material in such breadth and depth. - Laurent Demanet, Stanford University The new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications. Features: * Balances presentation of the mathematics with applications to signal processing * Algorithms and numerical examples are implemented in WaveLab, a MATLAB toolbox New in this edition * Sparse signal representations in dictionaries * Compressive sensing, super-resolution and source separation * Geometric image processing with curvelets and bandlets * Wavelets for computer graphics with lifting on surfaces * Time-frequency audio processing and denoising * Image compression with JPEG-2000 * New and updated exercises A Wavelet Tour of Signal Processing: The Sparse Way, Third Edition, is an invaluable resource for researchers and R&D engineers wishing to apply the theory in fields such as image processing, video processing and compression, bio-sensing, medical imaging, machine vision and communications engineering. Stephane Mallat is Professor in Applied Mathematics at École Polytechnique, Paris, France. From 1986 to 1996 he was a Professor at the Courant Institute of Mathematical Sciences at New York University, and between 2001 and 2007, he co-founded and became CEO of an image processing semiconductor company. Includes all the latest developments since the book was published in 1999, including its application to JPEG 2000 and MPEG-4 Algorithms and numerical examples are implemented in Wavelab, a MATLAB toolbox Balances presentation of the mathematics with applications to signal processing