Learning To Understand Remote Sensing Images
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Learning To Understand Remote Sensing Images
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Author : Qi Wang
language : en
Publisher: MDPI
Release Date : 2019-09-30
Learning To Understand Remote Sensing Images written by Qi Wang and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-30 with Computers categories.
With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Learning To Understand Remote Sensing Images
DOWNLOAD
Author : Qi Wang
language : en
Publisher: MDPI
Release Date : 2019-09-30
Learning To Understand Remote Sensing Images written by Qi Wang and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-30 with Computers categories.
With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Learning To Understand Remote Sensing Images Volume 2
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Author : Qi Wang
language : en
Publisher:
Release Date : 2019
Learning To Understand Remote Sensing Images Volume 2 written by Qi Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Electronic books categories.
With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Advanced Deep Learning Strategies For The Analysis Of Remote Sensing Images
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Author : Yakoub Bazi
language : en
Publisher: MDPI
Release Date : 2021-06-15
Advanced Deep Learning Strategies For The Analysis Of Remote Sensing Images written by Yakoub Bazi and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Science categories.
The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer—at least partially—such demands. The recent advent of cutting-edge processing facilities has fostered the adoption of deep learning architectures owing to their generalization capabilities. In this respect, it seems evident that the pace of deep learning in the remote sensing domain remains somewhat lagging behind that of its computer vision counterpart. This is due to the scarce availability of ground truth information in comparison with other computer vision domains. In this book, we aim at advancing the state of the art in linking deep learning methodologies with remote sensing image processing by collecting 20 contributions from different worldwide scientists and laboratories. The book presents a wide range of methodological advancements in the deep learning field that come with different applications in the remote sensing landscape such as wildfire and postdisaster damage detection, urban forest mapping, vine disease and pavement marking detection, desert road mapping, road and building outline extraction, vehicle and vessel detection, water identification, and text-to-image matching.
Deep Learning For Remote Sensing Images With Open Source Software
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Author : Rémi Cresson
language : en
Publisher: CRC Press
Release Date : 2020-07-15
Deep Learning For Remote Sensing Images With Open Source Software written by Rémi Cresson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-15 with Technology & Engineering categories.
In today’s world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source Software is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data. Specific Features of this Book: The first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow) Presents approaches suited for real world images and data targeting large scale processing and GIS applications Introduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration) Suited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills. Includes deep learning techniques through many step by step remote sensing data processing exercises.
Remote Sensing And Digital Image Processing With R Lab Manual
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Author : Marcelo de Carvalho Alves
language : en
Publisher: CRC Press
Release Date : 2023-06-30
Remote Sensing And Digital Image Processing With R Lab Manual written by Marcelo de Carvalho Alves and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Technology & Engineering categories.
This Lab Manual is a companion to the textbook Remote Sensing and Digital Image Processing with R. It covers examples of natural resource data analysis applications including numerous, practical problem-solving exercises, and case studies that use the free and open-source platform R. The intuitive, structural workflow helps students better understand a scientific approach to each case study in the book and learn how to replicate, transplant, and expand the workflow for further exploration with new data, models, and areas of interest. Features Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages. Engages students in learning theory through hands-on real-life projects. All chapters are structured with solved exercises and homework and encourage readers to understand the potential and the limitations of the environments. Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer. Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution information. Undergraduate- and graduate-level students will benefit from the exercises in this Lab Manual, because they are applicable to a variety of subjects including environmental science, agriculture engineering, as well as natural and social sciences. Students will gain a deeper understanding and first-hand experience with remote sensing and digital processing, with a learn-by-doing methodology using applicable examples in natural resources.
Interpreting Remote Sensing Imagery
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Author : Robert R. Hoffman
language : en
Publisher: CRC Press
Release Date : 2001-02-26
Interpreting Remote Sensing Imagery written by Robert R. Hoffman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-02-26 with Technology & Engineering categories.
No matter how advanced the technology, there is always the human factor involved - the power behind the technology. Interpreting Remote Sensing Imagery: Human Factors draws together leading psychologists, remote sensing scientists, and government and industry scientists to consider the factors involved in expertise and perceptual skill. This book covers the cognitive issues of learning, perception, and expertise, the applied issues of display design, interface design, software design, and mental workload issues, and the practitioner's issues of workstation design, human performance, and training. It tackles the intangibles of data interpretation, based on information from experts who do the job. You will learn: Information and perception What do experts perceive in remote sensing and cartographic displays? Reasoning and perception How do experts "see through" the data display to understand its meaning and significance? Human-computer interaction How do experts work with their displays and what happens when the "fiddle" with them? Learning and training What are the milestones in training development from novice to expert image interpreter? Interpreting Remote Sensing Imagery: Human Factors breaks down the mystery of what experts do when they interpret data, how they learn, and what individual factors speed or impede training. Even more importantly, it gives you the tools to train efficiently and understand how the human factor impacts data interpretation.
Remote Sensing And Digital Image Processing With R
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Author : Marcelo de Carvalho Alves
language : en
Publisher: CRC Press
Release Date : 2023-06-30
Remote Sensing And Digital Image Processing With R written by Marcelo de Carvalho Alves and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Technology & Engineering categories.
This new textbook on remote sensing and digital image processing of natural resources includes numerous, practical problem-solving exercises and applications of sensors and satellite systems using remote sensing data collection resources, and emphasizes the free and open-source platform R. It explains basic concepts of remote sensing and multidisciplinary applications using R language and R packages, by engaging students in learning theory through hands-on, real-life projects. All chapters are structured with learning objectives, computation, questions, solved exercises, resources, and research suggestions. Features Explains the theory of passive and active remote sensing and its applications in water, soil, vegetation, and atmosphere. Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer. Includes case studies from different environments with free software algorithms and an R toolset for active learning and a learn-by-doing approach. Provides hands-on exercises at the end of each chapter and encourages readers to understand the potential and the limitations of the environments, remote sensing targets, and process. Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution data sources for target recognition with image processing techniques. While the focus of the book is on environmental and agriculture engineering, it can be applied widely to a variety of subjects such as physical, natural, and social sciences. Students in upper-level undergraduate or graduate programs, taking courses in remote sensing, geoprocessing, civil and environmental engineering, geosciences, environmental sciences, electrical engineering, biology, and hydrology will also benefit from the learning objectives in the book. Professionals who use remote sensing and digital processing will also find this text enlightening.
Computer Processing Of Remotely Sensed Images
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Author : Paul M. Mather
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-28
Computer Processing Of Remotely Sensed Images written by Paul M. Mather and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-28 with Technology & Engineering categories.
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.
Digital Analysis Of Remotely Sensed Imagery
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Author : Jay Gao
language : en
Publisher: McGraw Hill Professional
Release Date : 2009-05-01
Digital Analysis Of Remotely Sensed Imagery written by Jay Gao and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-01 with Technology & Engineering categories.
An important text that identifies and introduces new trends in image analysis Digital Analysis of Remotely Sensed Imagery provides thorough coverage of the entire process of analyzing remotely sensed data for the purpose of producing accurate representations in thematic map format. Written in easy-to-follow language with minimal technical jargon, the book explores cutting-edge techniques and trends in image analysis, as well as the relationship between image processing and other recently emerged special technologies.
