Validation of Rochester Institute of Technology's (RIT's) Digital Image and Remote Sensing Image Generation (DIRSIG) Model, Reflective Region PDF Download
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Author: Russell A. White
Publisher:
ISBN:
Category : Imaging systems
Languages : en
Pages : 404
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Book Description
"The performance of RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is validated. The model is robust enough to treat solar, atmospheric, target/background, and sensor interactions. It operates over the 0.28 - 28 micrometers (Ultraviolet- Long Wavelength Infra-Red) spectral region. However, this study focuses only on the 0.4 - 1.0 micrometer (reflective) region. To validate the model, reference (actual) imagery from an airborne frame sensor is compared to synthetic imagery of the same scene. This study also evaluates DIRSIG's treatment of reflectivity and recommends improvements."--Abstract.
Author: Russell A. White
Publisher:
ISBN:
Category : Imaging systems
Languages : en
Pages : 404
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Book Description
"The performance of RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is validated. The model is robust enough to treat solar, atmospheric, target/background, and sensor interactions. It operates over the 0.28 - 28 micrometers (Ultraviolet- Long Wavelength Infra-Red) spectral region. However, this study focuses only on the 0.4 - 1.0 micrometer (reflective) region. To validate the model, reference (actual) imagery from an airborne frame sensor is compared to synthetic imagery of the same scene. This study also evaluates DIRSIG's treatment of reflectivity and recommends improvements."--Abstract.
Author: David J. Joseph
Publisher:
ISBN:
Category : Imaging systems
Languages : en
Pages : 410
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Book Description
ABSTRACT: "The Digital Imaging Remote Sensing Image Generation (DIRSIG) model is a synthetic image generation (SIG) tool developed by the Digital Imaging/Remote Sensing (DIRS) group at Rochester Institute of Technology's (RIT) Center for Imaging Science (CIS). Validation of a series of DIRSIG scenes over a broad spectral range has been presented. The validation scenario makes use of airborne and ground truth data collected during the Western Rainbow study conducted from October 18-24, 1995 at the United States Army Proving Ground in Yuma, Arizona. Three sensors were simulated in the validation scenario: the Daedalus multispectral sensor, the Hyperspectral Digital Imagery Collection Experiment (HYDICE), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS), and collectively, they covered the spectrum from 0.4 to 14 microns. As part of the study, various emissivity extraction techniques have been reviewed, and DIRSIG's potential as an imaging spectroscopy tool in the 8 to 14 um atmospheric window has been evaluated. One procedure: the Planck curve fitting technique, has been implemented and utilized with DIRSIG, SEBASS and ground truth data to extract emissivity spectra."
Author: Donna D. Rankin
Publisher:
ISBN:
Category : Infrared imaging
Languages : en
Pages :
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Book Description
"A validation and sensitivity study was performed in which the accuracy of an infrared synthetic image generation model (DIRSIG) was examined. The majority of the error in the model is derived from two major programs: a temperature predictor and a radiative transfer model. A thermodynamic model computes kinetic temperatures of objects in a computer generated three-dimensional scene. These temperatures, atmospheric data, and sensor parameters are used as input to a ray_tracer which models the propagation of radiation in a source-target-sensor path within this scene. The output is a simulated infrared image which a sensor with the given input parameters would record. The accuracy of the model and the impact of uncertainties in individual input variables were determined by error propagation methods and comparison of the simulated imagery with actual imagery. The average theoretical error in radiance reaching the sensor was determined to be 1.58 W/m2-sr, while the measured average error in radiance for an actual predicted scene was determined to be 2.98 W/m2-sr (13.99%). Variables which had the greatest impact on the final predictive error of the model were identified and ranked accordingly. In addition, problem areas within the model were identified and suggestions for improvement were made."--Abstract.
Author: Marcelo de Carvalho Alves
Publisher: CRC Press
ISBN: 100089536X
Category : Technology & Engineering
Languages : en
Pages : 537
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Book Description
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: Marcelo de Carvalho Alves
Publisher: CRC Press
ISBN: 1000895440
Category : Technology & Engineering
Languages : en
Pages : 224
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Book Description
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: John A. Richards
Publisher: Springer Nature
ISBN: 303082327X
Category : Technology & Engineering
Languages : en
Pages : 576
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Book Description
Remote Sensing Digital Image Analysis provides a comprehensive treatment of the methods used for the processing and interpretation of remotely sensed image data. Over the past decade there have been continuing and significant developments in the algorithms used for the analysis of remote sensing imagery, even though many of the fundamentals have substantially remained the same. As with its predecessors this new edition again presents material that has retained value but also includes newer techniques, covered from the perspective of operational remote sensing. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image analysis in remote sensing. The presentation level is for the mathematical non-specialist. Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a level commensurate with their background. The chapters progress logically through means for the acquisition of remote sensing images, techniques by which they can be corrected, and methods for their interpretation. The prime focus is on applications of the methods, so that worked examples are included and a set of problems conclude each chapter.
Author: John A. Richards
Publisher: Springer Science & Business Media
ISBN: 3642300618
Category : Computers
Languages : en
Pages : 503
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Book Description
Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same. This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing. The presentation level is for the mathematical non-specialist. Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a level commensurate with their background. Each chapter covers a different aspect of the analysis of digital remotely sensed data, without an excessively detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations. Problems conclude each chapter.
Author: Jacqueline Le Moigne
Publisher: Cambridge University Press
ISBN: 1139494376
Category : Technology & Engineering
Languages : en
Pages : 515
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Book Description
This book provides a summary of current research in the application of image registration to satellite imagery. Presenting algorithms for creating mosaics and tracking changes on the planet's surface over time, it is an indispensable resource for researchers and advanced students in Earth and space science, and image processing.
Author: Robert R. Hoffman
Publisher: CRC Press
ISBN: 1000612090
Category : Technology & Engineering
Languages : en
Pages : 326
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Book Description
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 boo
Author: John Alan Richards
Publisher: Springer Science & Business Media
ISBN:
Category : Science
Languages : en
Pages : 396
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Book Description
Remote Sensing Digital Image Analysis provides the non-specialist with 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. Problems conclude each chapter. This fourth edition has been developed to reflect the changes that have occurred in this area over the past several years. Its focus is on those procedures that seem now to have become part of the set of tools regularly used to perform thematic mapping. As with previous revisions, the fundamental material has been preserved in its original form because of its tutorial value; its style has been revised in places and it has been supplemented if newer aspects have emerged in the time since the third edition appeared. It still meets, however, the needs of the senior student and practitioner.
