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Machine Processing Of Remotely Sensed Data
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Book Synopsis Computer Processing of Remotely-Sensed Images by : Paul M. Mather
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 2005-12-13 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remotely-sensed images of the Earth's surface provide a valuable source of information about the geographical distribution and properties of natural and cultural features. This fully revised and updated edition of a highly regarded textbook deals with the mechanics of processing remotely-senses images. Presented in an accessible manner, the book covers a wide range of image processing and pattern recognition techniques. Features include: New topics on LiDAR data processing, SAR interferometry, the analysis of imaging spectrometer image sets and the use of the wavelet transform. An accompanying CD-ROM with: updated MIPS software, including modules for standard procedures such as image display, filtering, image transforms, graph plotting, import of data from a range of sensors. A set of exercises, including data sets, illustrating the application of discussed methods using the MIPS software. An extensive list of WWW resources including colour illustrations for easy download. For further information, including exercises and latest software information visit the Author's Website at: http://homepage.ntlworld.com/paul.mather/ComputerProcessing3/
Book Synopsis Remote Sensing Digital Image Analysis by : John A. Richards
Download or read book Remote Sensing Digital Image Analysis written by John A. Richards and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the widespread availability of satellite and aircraft remote sensing image data in digital form, and the ready access most remote sensing practitioners have to computing systems for image interpretation, there is a need to draw together the range of digital image processing procedures and methodologies commonly used in this field into a single treatment. It is the intention of this book to provide such a function, at a level meaningful to the non-specialist digital image analyst, but in sufficient detail that algorithm limitations, alternative procedures and current trends can be appreciated. Often the applications specialist in remote sensing wishing to make use of digital processing procedures has had to depend upon either the mathematically detailed treatments of image processing found in the electrical engineering and computer science literature, or the sometimes necessarily superficial treatments given in general texts on remote sensing. This book seeks to redress that situation. Both image enhancement and classification techniques are covered making the material relevant in those applications in which photointerpretation is used for information extraction and in those wherein information is obtained by classification.
Book Synopsis Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by : Pramod K. Varshney
Download or read book Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data written by Pramod K. Varshney and published by Springer. This book was released on 2014-03-12 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.
Book Synopsis Remote Sensing of Forest Environments by : Michael A. Wulder
Download or read book Remote Sensing of Forest Environments written by Michael A. Wulder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing of Forest Environments: Concepts and Case Studies is an edited volume intended to provide readers with a state-of-the-art synopsis of the current methods and applied applications employed in remote sensing the world's forests. The contributing authors have sought to illustrate and deepen our understanding of remote sensing of forests, providing new insights and indicating opportunities that are created when forests and forest practices are considered in concert with the evolving paradigm of remote sensing science. Following background and methods sections, this book introduces a series of case studies that exemplify the ways in which remotely sensed data are operationally used, as an element of the decision-making process, and in the scientific study of forests. Remote Sensing of Forest Environments: Concepts and Case Studies is designed to meet the needs of a professional audience composed of both practitioners and researchers. This book is also suitable as a secondary text for graduate-level students in Forestry, Environmental Science, Geography, Engineering, and Computer Science.
Book Synopsis Remote Sensing by : Robert A. Schowengerdt
Download or read book Remote Sensing written by Robert A. Schowengerdt and published by Elsevier. This book was released on 2012-12-02 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by : Ni-Bin Chang
Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.
Book Synopsis Big Data Analytics for Satellite Image Processing and Remote Sensing by : Swarnalatha, P.
Download or read book Big Data Analytics for Satellite Image Processing and Remote Sensing written by Swarnalatha, P. and published by IGI Global. This book was released on 2018-03-09 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.
Book Synopsis Frontiers of Remote Sensing Information Processing by : C. H. Chen
Download or read book Frontiers of Remote Sensing Information Processing written by C. H. Chen and published by World Scientific. This book was released on 2003 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leaders in the field of remote sensing information processing, this book covers the frontiers of remote sensors, especially with effective algorithms for signal/image processing and pattern recognition with remote sensing data. Sensor and data fusion issues, SAR images, hyperspectral images, and related special topics are also examined. Techniques making use of neural networks, wavelet transforms, and knowledge-based systems are emphasized. A special set of three chapters is devoted to seismic analysis and discrimination. In summary, the book provides an authoritative treatment of major topics in remote sensing information processing and defines new frontiers for these areas. Contents: Data Mining; SAR Image Processing; Wavelet Analysis and Applications; Military Applications of Remote Sensing; Microwave Remote Sensing; Statistical Pattern Recognition; Automatic Target Segmentation; Neural Networks; Change Detection; Seismic Signal Processing; Time Series Prediction; Image Compression; Emerging Topics. Readership: Engineers and scientists dealing with remote sensing data in particular, and signals and images in general; computer scientists involved in software development on geophysical data analysis.
Book Synopsis Machine Processing of Remotely Sensed Data by : Darlys C. McDonald
Download or read book Machine Processing of Remotely Sensed Data written by Darlys C. McDonald and published by . This book was released on 1983 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Processing of Remotely Sensed Data by : S. K. Mengel
Download or read book Machine Processing of Remotely Sensed Data written by S. K. Mengel and published by . This book was released on 1985 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Classification Methods for Remotely Sensed Data by : Paul Mather
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 Synopsis Processing of Remote Sensing Data by : ColetteM. Girard
Download or read book Processing of Remote Sensing Data written by ColetteM. Girard and published by Routledge. This book was released on 2018-04-27 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing useful information sources for the management of natural resources, this comprehensive text covers a large range of spatial resolutions and spectral characteristics. The book deals with the data sources and their physical interpretation, as well as processing techniques, such as visual interpretation and automated classifications, textural and structural processing and photogrammetry. There is a section on accuracy assessment and various applications relating to crops, grasslands, soils, landscapes, mines and coasts. The CD-ROM contains software and image data sets explaining the statistical methods of reference and contains a light version of the TeraVue software enabling the reader to compute the different processing spatial data.
Book Synopsis Machine Processing of Remotely Sensed Data by : M. M. Klepfer
Download or read book Machine Processing of Remotely Sensed Data written by M. M. Klepfer and published by Purdue University Press. This book was released on 1984 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Annual Symposium on Machine Processing of Remotely Sensed Data by :
Download or read book Annual Symposium on Machine Processing of Remotely Sensed Data written by and published by . This book was released on 1977 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Processing of Remotely Sensed Data by : P. G. Burroff
Download or read book Machine Processing of Remotely Sensed Data written by P. G. Burroff and published by . This book was released on 1981 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Conference on Machine Processing of Remotely Sensed Data by :
Download or read book Conference on Machine Processing of Remotely Sensed Data written by and published by . This book was released on 1973 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Remote Sensing Image Processing by : Gustavo Camps-Valls
Download or read book Remote Sensing Image Processing written by Gustavo Camps-Valls and published by Springer Nature. This book was released on 2022-06-01 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / Classification / Spectral Mixture Analysis / Estimation of Physical Parameters
