Remote Sensing And Digital Image Processing With R
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| Author | : John A. Richards |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 297 |
| Release | : 2013-04-17 |
| Genre | : Technology & Engineering |
| ISBN | : 3662024624 |
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.
| Author | : Courage Kamusoko |
| Publisher | : Springer |
| Total Pages | : 201 |
| Release | : 2019-07-24 |
| Genre | : Technology & Engineering |
| ISBN | : 9811380120 |
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.
| Author | : Marcelo de Carvalho Alves |
| Publisher | : CRC Press |
| Total Pages | : 537 |
| Release | : 2023-06-30 |
| Genre | : Technology & Engineering |
| ISBN | : 100089536X |
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.
| Author | : John R. Jensen |
| Publisher | : |
| Total Pages | : 584 |
| Release | : 2005 |
| Genre | : Computers |
| ISBN | : |
For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. This revision of Introductory Digital Image Processing: A Remote Sensing Perspective continues to focus on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications. 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.
| Author | : John R. Jensen |
| Publisher | : |
| Total Pages | : 362 |
| Release | : 1996 |
| Genre | : Computers |
| ISBN | : |
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.
| Author | : Marcelo de Carvalho Alves |
| Publisher | : CRC Press |
| Total Pages | : 189 |
| Release | : 2023-06-30 |
| Genre | : Technology & Engineering |
| ISBN | : 1000895394 |
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.
| Author | : Alka Rani |
| Publisher | : CRC Press |
| Total Pages | : 364 |
| Release | : 2021-02-24 |
| Genre | : |
| ISBN | : 9780367725624 |
Remote Sensing Data Analysis in R is a guide book containing codes for most of the operations which are being performed for analysing any satellite data for deriving meaningful information. The goal of this book is to provide hands on experience in performing all the activities from the loading of raster and vector data, mapping or visualisation of data, pre-processing, calculation of indices, classification and advanced machine learning algorithms on remote sensing data in R. The reader will be able to acquire skills to carry out most of the operations of raster data analysis - more flexibly - in open-source freely available software i.e. R which are generally available in the paid digital image processing software. Note: T& F does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. The title is co-published with New India Publishing Agency.
| Author | : John R. Jensen |
| Publisher | : Prentice Hall |
| Total Pages | : 544 |
| Release | : 2015-04-17 |
| Genre | : Science |
| ISBN | : 9780134058160 |
For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. Introductory Digital Image Processing: A Remote Sensing Perspective focuses on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects. Part of the Pearson Series Geographic Information Science. Now in full color, the Fourth Edition provides up-to-date information on analytical methods used to analyze digital remote sensing data. Each chapter contains a substantive reference list that can be used by students and scientists as a starting place for their digital image processing project or research. A new appendix provides sources of imagery and other geospatial information.
| Author | : John A. Richards |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 376 |
| Release | : 2009-10-08 |
| Genre | : Technology & Engineering |
| ISBN | : 3642020208 |
This book is concerned with remote sensing based on the technology of imaging radar. It assumes no prior knowledge of radar on the part of the reader, commencing with a treatment of the essential concepts of microwave imaging and progressing through to the development of multipolarisation and interferometric radar, modes which underpin contemporary applications of the technology. The use of radar for imaging the earth’s surface and its resources is not recent. Aircraft-based microwave systems were operating in the 1960s, ahead of optical systems that image in the visible and infrared regions of the spectrum. Optical remote sensing was given a strong impetus with the launch of the first of the Landsat series of satellites in the mid 1970s. Although the Seasat satellite launched in the same era (1978) carried an imaging radar, it operated only for about 12 months and there were not nearly so many microwave systems as optical platforms in service during the 1980s. As a result, the remote sensing community globally tended to develop strongly around optical imaging until Shuttle missions in the early to mid 1980s and free-flying imaging radar satellites in the early to mid 1990s became available, along with several sophisticated aircraft platforms. Since then, and particularly with the unique capabilities and flexibility of imaging radar, there has been an enormous surge of interest in microwave imaging technology. Unlike optical imaging, understanding the theoretical underpinnings of imaging radar can be challenging, particularly when new to the field.
| Author | : Robert A. Schowengerdt |
| Publisher | : Elsevier |
| Total Pages | : 585 |
| Release | : 2012-12-02 |
| Genre | : Technology & Engineering |
| ISBN | : 0080516106 |
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.
