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Remote Sensing Digital Image Analysis

Author : John A. Richards
ISBN : 9783540297116
Genre : Technology & Engineering
File Size : 58.80 MB
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Revised and enlarged to reflect new developments in the field, the fourth edition of this well-established text provides an introduction to quantitative evaluation of satellite- and aircraft-derived remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations.
Category: Technology & Engineering

Introductory Digital Image Processing

Author : John R. Jensen
ISBN : 0132058405
Genre : Cluster analysis
File Size : 86.57 MB
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For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. This text focuses exclusively on the art and science of digital image processing of satellite and aircraft-derived remotely-sensed data for resource management. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects. Part of the Prentice Hall Series Geographic Information Science.
Category: Cluster analysis

Remote Sensing Image Analysis Including The Spatial Domain

Author : Steven M. de Jong
ISBN : 1402025602
Genre : Technology & Engineering
File Size : 21.16 MB
Format : PDF, Kindle
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Remote Sensing image analysis is mostly done using only spectral information on a pixel by pixel basis. Information captured in neighbouring cells, or information about patterns surrounding the pixel of interest often provides useful supplementary information. This book presents a wide range of innovative and advanced image processing methods for including spatial information, captured by neighbouring pixels in remotely sensed images, to improve image interpretation or image classification. Presented methods include different types of variogram analysis, various methods for texture quantification, smart kernel operators, pattern recognition techniques, image segmentation methods, sub-pixel methods, wavelets and advanced spectral mixture analysis techniques. Apart from explaining the working methods in detail a wide range of applications is presented covering land cover and land use mapping, environmental applications such as heavy metal pollution, urban mapping and geological applications to detect hydrocarbon seeps. The book is meant for professionals, PhD students and graduates who use remote sensing image analysis, image interpretation and image classification in their work related to disciplines such as geography, geology, botany, ecology, forestry, cartography, soil science, engineering and urban and regional planning.
Category: Technology & Engineering

Digital Image Processing Of Remotely Sensed Data

Author : R. Michael Hord
ISBN : UOM:39015004565704
Genre : Technology & Engineering
File Size : 46.34 MB
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Of basic concepts. Data sources. Computer processing. Algorithms. Applications examples. Research topics. Practical issues.
Category: Technology & Engineering

Image Analysis Classification And Change Detection In Remote Sensing

Author : Morton John Canty
ISBN : 9780429875342
Genre : Technology & Engineering
File Size : 35.6 MB
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Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty’s fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.
Category: Technology & Engineering

Techniques For Image Processing And Classifications In Remote Sensing

Author : Robert A. Schowengerdt
ISBN : 9780323138550
Genre : Technology & Engineering
File Size : 22.49 MB
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Techniques for Image Processing and Classifications in Remote Sensing provides an introduction to the fundamentals of computer image processing and classification (commonly called ""pattern recognition"" in other applications). The book begins with a discussion of digital scanners and imagery, and two key mathematical concepts for image processing and classification—spatial filtering and statistical pattern recognition. This is followed by separate chapters on image processing and classification techniques that are widely used in the remote sensing community. The emphasis throughout is on techniques that assist in the analysis of images, not particular applications of these techniques. The book also has four appendixes, featuring a bibliography; an introduction to computer binary data representation and image data formats; a discussion of interactive image processing; and a selection of exam questions from the Image Processing Laboratory course at the University of Arizona. This book is intended for use as either a primary source in an introductory image processing course or as a supplementary text in an intermediate-level remote sensing course. The academic level addressed is upper-division undergraduate or beginning graduate, and familiarity with calculus and basic vector and matrix concepts is assumed.
Category: Technology & Engineering

Image Analysis Classification And Change Detection In Remote Sensing

Author : Morton J. Canty
ISBN : 9781466570375
Genre : Mathematics
File Size : 23.90 MB
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Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Category: Mathematics

Remote Sensing Models And Methods For Image Processing

Author : Robert A. Schowengerdt
ISBN : 0126289816
Genre : Technology & Engineering
File Size : 82.53 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.
Category: Technology & Engineering