Download or read book 4th Workshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing WHISPERS 2012 written by and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hyperspectral Image and Signal Processing Evolution in Remote Sensing 2009 WHISPERS 09 First Workshop on written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book 2022 12th Workshop on Hyperspectral Imaging and Signal Processing Evolution in Remote Sensing WHISPERS written by IEEE Staff and published by . This book was released on 2022-09-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: hyperspectral data processing
Download or read book 2010 2nd Workshop on Hyperspectral Image and Signal Processing written by IEEE Staff and published by . This book was released on 2010 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hyperspectral Remote Sensing of Agriculture and Vegetation written by Simone Pascucci and published by MDPI. This book was released on 2021-01-20 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows recent and innovative applications of the use of hyperspectral technology for optimal quantification of crop, vegetation, and soil biophysical variables at various spatial scales, which can be an important aspect in agricultural management practices and monitoring. The articles collected inside the book are intended to help researchers and farmers involved in precision agriculture techniques and practices, as well as in plant nutrient prediction, to a higher comprehension of strengths and limitations of the application of hyperspectral imaging to agriculture and vegetation. Hyperspectral remote sensing for studying agriculture and natural vegetation is a challenging research topic that will remain of great interest for different sciences communities in decades.
Download or read book Advances in Remote Sensing for Infrastructure Monitoring written by Vernon Singhroy and published by Springer Nature. This book was released on 2020-12-23 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides international case studies of practical and advanced methods using satellite images integrated with other airborne, drone images and field data to monitor infrastructure. The book is timely, as infrastructure spending by national governments is increasing and robust monitoring techniques are needed to keep pace with climate change impacts affecting infrastructures globally. The expert international contributions that comprise the book provide examples of advanced methods using InSAR, high-resolution optical and radar images, LIDAR, UAV, geophysical techniques and their applications to civil infrastructure. The case studies focus on high-resolution, rapid time-series radar interferometry to monitor highways, railways, pipelines, bridges, urban, and water conveyance infrastructures. Other case studies use optical and radar images to characterize urban infrastructure and monitor damages from floods, oil spills and conflicts. The case studies are global focusing on infrastructure projects in Canada, Dominica Guyana, India Italy, Syria Taiwan, United States and the United Kingdom. This compilation of selected case studies will provide useful guidelines for the civil infrastructure characterization and monitoring communities. The book will be of interest to infrastructure consultants and professionals, scientific communities in earth observation and advanced imaging methods, and researchers and professors in earth sciences, climate change, and civil and geoengineering.
Download or read book Knowledge Guided Machine Learning written by Anuj Karpatne and published by CRC Press. This book was released on 2022-08-15 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML
Download or read book Hyperspectral Remote Sensing written by Prem Chandra Pandey and published by Elsevier. This book was released on 2020-08-05 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology. - Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines - Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection - Provides an overview of the state-of-the-art, including algorithms, techniques and case studies
Download or read book Change Detection and Image Time Series Analysis 1 written by Abdourrahmane M. Atto and published by John Wiley & Sons. This book was released on 2022-01-06 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.
Download or read book Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2018-12-07 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.
Download or read book Real Time Recursive Hyperspectral Sample and Band Processing written by Chein-I Chang and published by Springer. This book was released on 2017-04-23 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016.
Download or read book Southern Iraq s Marshes written by Laith A. Jawad and published by Springer Nature. This book was released on 2021-05-06 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Mesopotamian marshes are important for economic, social, and biodiversity values and have been home to indigenous human communities for millennia. They are regarded as a legendary site. This multi-authored book contains chapters written by world-renowned experts in their field. Both basic and applied information are made available, making the book a must-have for a wide spectrum of users. For example, an understanding of the natural and the social aspects of the marshes, as described here, is an obvious prerequisite for a pest management plan in this area. Scholars interested in wetlands can use this book as a guide to compare different wetlands areas in Asia. The bibliography section contains valuable references to the marsh areas and research in the field. This book serves as an up-to-date comprehensive source of information on different aspects of the southern marshes of Iraq and is aimed at academic scholars, environmentalists, and decision makers.
Download or read book Proceedings of International Conference on Computational Intelligence and Data Engineering written by Nabendu Chaki and published by Springer. This book was released on 2017-12-19 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents high quality research work in cutting edge technologies and most-happening areas of computational intelligence and data engineering. It contains selected papers presented at International Conference on Computational Intelligence and Data Engineering (ICCIDE 2017). The conference was conceived as a forum for presenting and exchanging ideas and results of the researchers from academia and industry onto a common platform and help them develop a comprehensive understanding of the challenges of technological advancements from different viewpoints. This book will help in fostering a healthy and vibrant relationship between academia and industry. The topics of the conference include, but are not limited to collective intelligence, intelligent transportation systems, fuzzy systems, Bayesian network, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.
Download or read book Progress in Computer Recognition Systems written by Robert Burduk and published by Springer. This book was released on 2019-05-07 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent research on computer recognition systems, one of the most promising directions in artificial intelligence. Offering the most comprehensive study on this field to date, it gathers 36 carefully selected articles contributed by experts on pattern recognition. Presenting recent research on methodology and applications, the book offers a valuable reference tool for scientists whose work involves designing computer pattern recognition systems. Its target audience also includes researchers and students in computer science, artificial intelligence, and robotics.
Download or read book Satellite Remote Sensing of Terrestrial Hydrology written by Christopher Ndehedehe and published by Springer Nature. This book was released on 2022-07-15 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights several opportunities that exist in satellite remote sensing of large-scale terrestrial hydrology. It lays bare the novel concept of remote sensing hydrology and demonstrates key applications of advance satellite technology and new methods in advancing our fundamental understanding of environmental systems. This includes, using state-of-the-art satellite hydrology missions like the Gravity Recovery and Climate Experiment and other multi-mission satellite systems as important tools that underpin water resources planning and accounting. This book discusses and demonstrates how the efficacy, simplicity, and sophistication in novel computing platforms for big earth observation data can help facilitate environmental monitoring and improve contemporary understanding of climate change impacts on freshwater resources. It also provides opportunities for practitioners and relevant government agencies to leverage satellite-based information in a transdisciplinary context to address several environmental issues affecting society. This book provides a general framework and highlights methods to help improve our understanding of hydrological processes and impact analysis from extreme events (e.g., droughts, floods) and climate change.
Download or read book Source Separation in Physical Chemical Sensing written by Christian Jutten and published by John Wiley & Sons. This book was released on 2023-12-11 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Source Separation in Physical-Chemical Sensing Master advanced signal processing for enhanced physical and chemical sensors with this essential guide In many domains (medicine, satellite imaging and remote sensing, food industry, materials science), data is obtained from large sets of physical/chemical sensors or sensor arrays. Such sophisticated measurement techniques require advanced and smart processing for extracting useful information from raw sensing data. Usually, sensors are not very selective and record a mixture of the useful latent variables. An innovative technique called Blind Source Separation (BSS) can isolate and retrieve the individual latent variables from a mixed-source data array, allowing for refined analysis that fully exploits these cutting-edged imaging and signal-sensing technologies. Source Separation in Physical-Chemical Sensing, supplies a thorough introduction to the principles of BSS, main methods and algorithms and its potential applications in various domains where data are obtained through physical or chemical sensors. Designed to bridge the gap between chemical/physical analysis and signal processing, it promises to be invaluable in many fields. Its alertness to the latest technologies and the full range of potential BSS applications make it an indispensable introduction to this cutting-edge method. Source Separation in Physical-Chemical Sensing readers will also find: BSS examples on chemical and physical sensors and devices to enhance processing and analysis. Detailed treatment of source separation in potentiometric sensors, ion-sensitive sensors, hyperspectral imaging, Raman and fluorescence spectroscopy, chromatography, and others. Thorough discussion of Bayesian source separation, nonnegative matrix factorization, tensorial methods, geometrical methods, constrained optimization, and more. Source Separation in Physical-Chemical Sensing is a must-have for researchers and engineers working in signal processing and statistical analysis, as well as for chemists, physicists or engineers looking to apply source separation in various application domains.
Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2023-09-12 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Conference on Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023. The 63 full papers included in this book were carefully reviewed and selected from 218 submissions. They are organized in topical sections as follows: collective intelligence and collective decision-making; deep learning techniques; natural language processing; data mining and machine learning; social networks and intelligent systems; cybersecurity, blockchain technology and Internet of Things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; knowledge engineering and application for Industry 4.0; computational intelligence in medical applications; and ensemble models and data fusion.
