EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book Land Cover Classification of Remotely Sensed Images

Download or read book Land Cover Classification of Remotely Sensed Images written by S. Jenicka and published by Springer. This book was released on 2022-03-11 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab source codes. The sixth chapter describes land cover classification procedure using multivariate (statistical and spectral) texture models and minimum distance classifier with Matlab source codes. A few performance metrics are also explained. The seventh chapter explains how texture based segmentation and land cover classification are performed using the hidden Markov model with relevant Matlab source codes. The eighth chapter gives an overview of spatial data analysis and other existing land cover classification methods. The ninth chapter addresses the research issues and challenges associated with land cover classification using textural approaches. This book is useful for undergraduates in Computer Science and Civil Engineering and postgraduates who plan to do research or project work in digital image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab source codes listed. In short, the book will be a valuable resource for growing academicians to gain expertise in their area of specialization and students who aim at gaining in-depth knowledge through practical implementations. The exercises given under texture based segmentation (excluding land cover classification exercises) can serve as lab exercises for the undergraduate students who learn texture based image processing.

Book Land Cover Classification of Remotely Sensed Images

Download or read book Land Cover Classification of Remotely Sensed Images written by S. Jenicka and published by Springer Nature. This book was released on 2021-03-10 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab source codes. The sixth chapter describes land cover classification procedure using multivariate (statistical and spectral) texture models and minimum distance classifier with Matlab source codes. A few performance metrics are also explained. The seventh chapter explains how texture based segmentation and land cover classification are performed using the hidden Markov model with relevant Matlab source codes. The eighth chapter gives an overview of spatial data analysis and other existing land cover classification methods. The ninth chapter addresses the research issues and challenges associated with land cover classification using textural approaches. This book is useful for undergraduates in Computer Science and Civil Engineering and postgraduates who plan to do research or project work in digital image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab source codes listed. In short, the book will be a valuable resource for growing academicians to gain expertise in their area of specialization and students who aim at gaining in-depth knowledge through practical implementations. The exercises given under texture based segmentation (excluding land cover classification exercises) can serve as lab exercises for the undergraduate students who learn texture based image processing.

Book Historical Land Use Land Cover Classification Using Remote Sensing

Download or read book Historical Land Use Land Cover Classification Using Remote Sensing written by Wafi Al-Fares and published by Springer Science & Business Media. This book was released on 2013-06-25 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the development of remote sensing techniques focuses greatly on construction of new sensors with higher spatial and spectral resolution, it is advisable to also use data of older sensors (especially, the LANDSAT-mission) when the historical mapping of land use/land cover and monitoring of their dynamics are needed. Using data from LANDSAT missions as well as from Terra (ASTER) Sensors, the authors shows in his book maps of historical land cover changes with a focus on agricultural irrigation projects. The kernel of this study was whether, how and to what extent applying the various remotely sensed data that were used here, would be an effective approach to classify the historical and current land use/land cover, to monitor the dynamics of land use/land cover during the last four decades, to map the development of the irrigation areas, and to classify the major strategic winter- and summer-irrigated agricultural crops in the study area of the Euphrates River Basin.

Book Remote Sensing of Land Use and Land Cover

Download or read book Remote Sensing of Land Use and Land Cover written by Chandra P. Giri and published by CRC Press. This book was released on 2016-04-19 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling the need for a comprehensive book that covers both theory and application, Remote Sensing of Land Use and Land Cover: Principles and Applications provides a synopsis of how remote sensing can be used for land-cover characterization, mapping, and monitoring from the local to the global scale. With contributions by leading scientists from aro

Book Optical Remote Sensing

Download or read book Optical Remote Sensing written by Saurabh Prasad and published by Springer Science & Business Media. This book was released on 2011-03-23 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.

Book Remote Sensing of Land Use and Land Cover

Download or read book Remote Sensing of Land Use and Land Cover written by Chandra P. Giri and published by CRC Press. This book was released on 2012-05-02 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling the need for a comprehensive book that covers both theory and application, Remote Sensing of Land Use and Land Cover: Principles and Applications provides a synopsis of how remote sensing can be used for land-cover characterization, mapping, and monitoring from the local to the global scale. With contributions by leading scientists from around the world, this well-structured volume offers an international perspective on the science, technologies, applications, and future needs of remote sensing of land cover and land use. After an overview of the key concepts and history of land-use and land-cover mapping, the book discusses the relationship between land cover and land use and addresses the land-cover classification system. It then presents state-of-the-art methods and techniques in data acquisition, preprocessing, image interpretation, and accuracy assessment for land-use and land-cover characterization and mapping. Case studies from around the world illustrate land-cover applications at global, continental, and national scales. These examples use multiple data sources and provide in-depth understanding of land cover and land-cover dynamics in multiple spatial, thematic, and temporal resolutions. Looking to the future, the book also identifies new frontiers in land-cover mapping and forecasting. The availability and accessibility of accurate and timely land-cover data sets play an important role in many global change studies, highlighting the need for better land-use and land-cover change information at multiple scales. A synthesis of current knowledge in remote sensing of land-use and land-cover science, this book promotes more effective use of Earth observation data and technology to assess, monitor, and manage land resources.

Book Remote Sensing Image Classification in R

Download or read book Remote Sensing Image Classification in R written by Courage Kamusoko and published by Springer. This book was released on 2019-07-24 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and classification. This book is divided into five chapters. Chapter 1 introduces remote sensing digital image processing in R, while chapter 2 covers pre-processing. Chapter 3 focuses on image transformation, and chapter 4 addresses image classification. Lastly, chapter 5 deals with improving image classification. R is advantageous in that it is open source software, available free of charge and includes several useful features that are not available in commercial software packages. This book benefits all undergraduate and graduate students, researchers, university teachers and other remote- sensing practitioners interested in the practical implementation of remote sensing in R.

Book Classification Methods for Remotely Sensed Data

Download or read book Classification Methods for Remotely Sensed Data written by Paul Mather and published by CRC Press. This book was released on 2001-12-06 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pul

Book Mapping Land Cover from Satellite Images

Download or read book Mapping Land Cover from Satellite Images written by and published by . This book was released on 1978 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Key Methods in Geography

    Book Details:
  • Author : Nicholas Clifford
  • Publisher : SAGE Publications
  • Release : 2010-05-30
  • ISBN : 1412935091
  • Pages : 569 pages

Download or read book Key Methods in Geography written by Nicholas Clifford and published by SAGE Publications. This book was released on 2010-05-30 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Its range is far broader than the majority of methods texts, being concerned with both human and physical geography... Given the seriousness with which Key Methods in Geography approaches all aspects of research, it will continue to find wide favour among undergraduate geographers." - Times Higher Education Textbook Guide "All geographers, whatever their interest, need to do research. This book will help them get started in the best possible way, with thoughtful advice on everything from project design, through choice of methods, to data analysis and presentation. The editors have assembled an impressive array of authors, all experts in their chosen field." - Tim Burt, University of Durham "Excellent book. Valuable teaching aid. Well written and covers a wide range of methods thoroughly." - Sue Rodway-Dyer, Exeter University "This is an excellent book and deals with a number of topics (which I teach) outside of the tutorial module where it is a recommended text for geographers. A very useful textbook throughout a 3 year Geography programme." - Ian Harris, Bangor University Key Methods in Geography is an introduction to the principal methodological issues involved in the collection, analysis and presentation of geographical information. It is unique in the reference literature for providing an overview of qualitative and quantitative methods for human and physical geography. An accessible primer, it will be used by students as a reference throughout their degree, on all issues from research design to presentation. This second edition has been fully revised and updated and includes new chapters on internet mediated research, diaries as a research method, making observations and measurements in the field, and the analysis of natural systems. Organized into four sections: Getting Started in Geographical Research; Generating and Working with Data in Human Geography; Generating and Working with Data in Physical Geography; Representing and Interpreting Geographical Data; each chapter comprises: A short definition A summary of the principal arguments A substantive 5,000-word discussion Use of real-life examples Annotated notes for further reading. The teaching of research methods is integral to all geography courses: Key Methods in Geography, 2nd Edition explains all of the key methods with which geography undergraduates must be conversant.

Book Remote Sensing Image Analysis  Including the Spatial Domain

Download or read book Remote Sensing Image Analysis Including the Spatial Domain written by Steven M. de Jong and published by Springer Science & Business Media. This book was released on 2007-07-26 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Computer Processing of Remotely Sensed Images

Download or read book Computer Processing of Remotely Sensed Images written by Paul M. Mather and published by John Wiley & Sons. This book was released on 2011-07-28 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fourth and full colour edition updates and expands a widely-used textbook aimed at advanced undergraduate and postgraduate students taking courses in remote sensing and GIS in Geography, Geology and Earth/Environmental Science departments. Existing material has been brought up to date and new material has been added. In particular, a new chapter, exploring the two-way links between remote sensing and environmental GIS, has been added. New and updated material includes: A website at www.wiley.com/go/mather4 that provides access to an updated and expanded version of the MIPS image processing software for Microsoft Windows, PowerPoint slideshows of the figures from each chapter, and case studies, including full data sets, Includes new chapter on Remote Sensing and Environmental GIS that provides insights into the ways in which remotely-sensed data can be used synergistically with other spatial data sets, including hydrogeological and archaeological applications, New section on image processing from a computer science perspective presented in a non-technical way, including some remarks on statistics, New material on image transforms, including the analysis of temporal change and data fusion techniques, New material on image classification including decision trees, support vector machines and independent components analysis, and Now in full colour throughout. This book provides the material required for a single semester course in Environmental Remote Sensing plus additional, more advanced, reading for students specialising in some aspect of the subject. It is written largely in non-technical language yet it provides insights into more advanced topics that some may consider too difficult for a non-mathematician to understand. The case studies available from the website are fully-documented research projects complete with original data sets. For readers who do not have access to commercial image processing software, MIPS provides a licence-free, intuitive and comprehensive alternative.

Book Image Analysis  Classification and Change Detection in Remote Sensing

Download or read book Image Analysis Classification and Change Detection in Remote Sensing written by Morton J. Canty and published by CRC Press. This book was released on 2014-06-06 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Multispectral Satellite Image Understanding

Download or read book Multispectral Satellite Image Understanding written by Cem Ünsalan and published by Springer Science & Business Media. This book was released on 2011-05-18 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

Book Integrated Use of Remotely Sensed and Existing Data Sources with Man machine Interaction to Achieve Level II Land Use and Land Cover Classification

Download or read book Integrated Use of Remotely Sensed and Existing Data Sources with Man machine Interaction to Achieve Level II Land Use and Land Cover Classification written by Wayne L. Myers and published by . This book was released on 1987 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Classification of Remotely Sensed Images

Download or read book Classification of Remotely Sensed Images written by I.L Thomas and published by CRC Press. This book was released on 1987-01-01 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remotely sensed images are an indispensable tool to researchers in disciplines such as cartography, forestry and geology in which mapping by satellite or aircraft is often a far more acurate, efficient and cost-effective method than conventional survey. Most users of remote sensing data are now familiar with using photographic images prepared to standard prescriptions by others to relate colours or grey tones to what actually exists on the ground. This book is aimed at the discipline-oriented user who wishes to move away from these traditional photographic interpretation methods towards interactive analysis systems. Such systems permit the classification of the digital data in ways that enable locations and quantitative information on specific themes to be extracted and portrayed. The empasis is upon the integration of these new techniques into existing discipline skills: the user is not expected to become a 'computer operator'. The book covers the fundamental theory of image classification, and illustrates it with practical examples in the form of a structured outline of a total research project. It is therefore an essential reference manual to 'sit at the elbow' of the user working with an image processing system for remotely sensed data.