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On The Classification Of Marine Surface Films In Multi Sensor Satellite Images Using Watershed Segmentation And Support Vector Machines
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Book Synopsis On the Classification of Marine Surface Films in Multi-sensor Satellite Images Using Watershed Segmentation and Support Vector Machines by : Jens Barthel
Download or read book On the Classification of Marine Surface Films in Multi-sensor Satellite Images Using Watershed Segmentation and Support Vector Machines written by Jens Barthel and published by . This book was released on 2011 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Very High Resolution (VHR) Satellite Imagery by : Francisco Eugenio
Download or read book Very High Resolution (VHR) Satellite Imagery written by Francisco Eugenio and published by MDPI. This book was released on 2019-11-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.
Book Synopsis Marine Surface Films by : Martin Gade
Download or read book Marine Surface Films written by Martin Gade and published by Springer Science & Business Media. This book was released on 2006-08-06 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the late 1960s, various groups have investigated the influence of marine surface films on mechanisms dominating energy and mass transfer across the ocean/atmosphere interface. However, a compendium summarizing the state-of-the-art research in this field is still missing. The book fills this gap and transfers the accumulated knowledge to the scientific community. After a brief historical chapter basic chemical insights are presented, followed by theoretical and experimental approaches carried out in laboratory facilities. Air-sea interaction experiments are then described and finally, remote sensing applications with sea slicks and crude oil spills are presented.
Book Synopsis Satellite Image Analysis: Clustering and Classification by : Surekha Borra
Download or read book Satellite Image Analysis: Clustering and Classification written by Surekha Borra and published by Springer. This book was released on 2019-02-08 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Book Synopsis Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification by : Anil Kumar
Download or read book Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification written by Anil Kumar and published by CRC Press. This book was released on 2020-07-19 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.
Book Synopsis An Overview of Technological Revolution in Satellite Image Analysis by : Jenice Aroma R.
Download or read book An Overview of Technological Revolution in Satellite Image Analysis written by Jenice Aroma R. and published by Infinite Study. This book was released on with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: The satellite image based applications are highly utilized nowadays from simple purposes like vehicle navigation to complex surveillance and virtual environment modeling projects. On increased population rate, the depletion of natural resources is highly unavoidable and it leads to increased threats on natural hazards. In order to protect and overcome the physical losses on devastation of properties, the risk mapping models such as weather forecasts, drought modeling and other hazard assessment models are in need.
Book Synopsis SUPPORT VECTOR MACHINES FOR BROAD AREA FEATURE CLASSIFICATION IN REMOTELY SENSED IMAGES. by :
Download or read book SUPPORT VECTOR MACHINES FOR BROAD AREA FEATURE CLASSIFICATION IN REMOTELY SENSED IMAGES. written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification of broad area features in satellite imagery is one of the most important applications of remote sensing. It is often difficult and time-consuming to develop classifiers by hand, so many researchers have turned to techniques from the fields of statistics and machine learning to automatically generate classifiers. Common techniques include maximum likelihood classifiers, neural networks and genetic algorithms. We present a new system called Afreet, which uses a recently developed machine learning paradigm called Support Vector Machines (SVMs). In contrast to other techniques, SVMs offer a solid mathematical foundation that provides a probabilistic guarantee on how well the classifier will generalize to unseen data. In addition the SVM training algorithm is guaranteed to converge to the globally optimal SVM classifier, can learn highly non-linear discrimination functions, copes extremely well with high-dimensional feature spaces (such as hype spectral data), and scales well to large problem sizes. Afreet combines an SVM with a sophisticated spatio-spectral feature construction mechanism that allows it to classify spectrally ambiguous pixels. We demonstrate the effectiveness of the system by applying Afreet to several broad area classification problems in remote sensing, and provide a comparison with conventional maximum likelihood classification.
Book Synopsis International Aerospace Abstracts by :
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1999 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Image Segmentation for Environmental Monitoring by : Brian Alan Johnson
Download or read book Image Segmentation for Environmental Monitoring written by Brian Alan Johnson and published by MDPI. This book was released on 2020-12-02 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: OBIA, based on image segmentation and as an important remote sensing monitoring technology, has been widely used in forestry, vegetation, wetland, urban, crop, conservation, ecology, and agriculture areas. Although OBIA has considerably progressed in the past 20 years, OBIA still much room for further development, regardless of the technological aspect of OBIA or the prospective expansion field of applications. Therefore, this book was organized to further encourage OBIA technology development and expand OBIA applications. This book collects a total of eight papers, which compile the current state-of-the-art research and technology in the area of image segmentation, and highlight prominent current application directions. Therefore, this book not only contains innovative methods, but also covers the innovation of application-driven OBIA technology. The eight papers in this highlight both the popular applications (urban, vegetation, ecology) and several subjects that require additional research attention (landslide, arid-land).
Book Synopsis Very High Resolution (VHR) Satellite Imagery: Processing and Applications by : Javier Marcello
Download or read book Very High Resolution (VHR) Satellite Imagery: Processing and Applications written by Javier Marcello and published by . This book was released on 2019 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.
Book Synopsis Artificial Intelligence Techniques for Satellite Image Analysis by : D. Jude Hemanth
Download or read book Artificial Intelligence Techniques for Satellite Image Analysis written by D. Jude Hemanth and published by Springer Nature. This book was released on 2019-11-13 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing.
Book Synopsis Regional Satellite Oceanography by : Serge Victorov
Download or read book Regional Satellite Oceanography written by Serge Victorov and published by CRC Press. This book was released on 2003-09-02 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work addresses the whole range of problems relating to the application of satellite technology to studies of regional seas and sea phenomona - the Gulf Stream, the Kuroshia Current - and coastal zones. It argues that to emphasize global applications is to fail to take into account fundamental idiosyncracies specific to the regional perspective. In addition, it describes implementation techniques - data gathering; in situ data assurance, algorithms for parameter retrieval; data storage; and data output.; The book contains satellite imagery and incorporates case studies from areas such as the Baltic and the Black Sea.
Book Synopsis Image Segmentation and Compression Using Hidden Markov Models by : Jia Li
Download or read book Image Segmentation and Compression Using Hidden Markov Models written by Jia Li and published by Springer Science & Business Media. This book was released on 2000-08-31 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book. Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally. The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization. Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling.
Book Synopsis Satellites, Oceanography and Society by : D. Halpern
Download or read book Satellites, Oceanography and Society written by D. Halpern and published by Elsevier. This book was released on 2000-06-06 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book shows how the new observations from satellites required advances in theory and influenced societal decision-making. Chapters have a review with an extensive reference list, making the book an excellent source of information for biological and physical oceanographers and atmospheric scientists.A large range of state-of-the art applications of satellite data (altimeter, color, infrared radiometer, scatterometer, synthetic aperture radar) visible in regional-to-global scale ocean studies integrating satellite and in-situ measurements with circulation models are covered in the book. Subjects include forecasting of surface waves, both swell and windsea, and surface wind; El Niño/La Niña; exchange of water masses between ocean basins, Rossby waves; eddies and filaments; fisheries; coastal ocean dynamics; phytoplankton dynamics; and ideas to measure sea surface salinity.
Download or read book Science Abstracts written by and published by . This book was released on 1993 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multivariate Time Series Model Based Support Vector Machine for Multiclass Remote Sensing Image Classification and Region Segmentation by : Pei-Gee Peter Ho
Download or read book Multivariate Time Series Model Based Support Vector Machine for Multiclass Remote Sensing Image Classification and Region Segmentation written by Pei-Gee Peter Ho and published by . This book was released on 2008 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781729258040 Total Pages :50 pages Book Rating :4.2/5 (58 download)
Book Synopsis Sea Surface Velocities from Visible and Infrared Multispectral Atmospheric Mapping Sensor Imagery by : National Aeronautics and Space Adm Nasa
Download or read book Sea Surface Velocities from Visible and Infrared Multispectral Atmospheric Mapping Sensor Imagery written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-10-26 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared brightness
