Big Data Analytics For Satellite Image Processing And Remote Sensing
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Author |
: Swarnalatha, P. |
Publisher |
: IGI Global |
Total Pages |
: 272 |
Release |
: 2018-03-09 |
ISBN-10 |
: 9781522536444 |
ISBN-13 |
: 1522536442 |
Rating |
: 4/5 (44 Downloads) |
Synopsis Big Data Analytics for Satellite Image Processing and Remote Sensing by : Swarnalatha, P.
The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.
Author |
: Information Resources Management Association |
Publisher |
: Engineering Science Reference |
Total Pages |
: 0 |
Release |
: 2022 |
ISBN-10 |
: 1668436620 |
ISBN-13 |
: 9781668436622 |
Rating |
: 4/5 (20 Downloads) |
Synopsis Research Anthology on Big Data Analytics, Architectures, and Applications by : Information Resources Management Association
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
Author |
: B.S. Daya Sagar |
Publisher |
: Springer |
Total Pages |
: 911 |
Release |
: 2018-06-25 |
ISBN-10 |
: 9783319789996 |
ISBN-13 |
: 3319789996 |
Rating |
: 4/5 (96 Downloads) |
Synopsis Handbook of Mathematical Geosciences by : B.S. Daya Sagar
This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences.
Author |
: Nilanjan Dey |
Publisher |
: Springer |
Total Pages |
: 163 |
Release |
: 2018-05-23 |
ISBN-10 |
: 9783319899237 |
ISBN-13 |
: 3319899236 |
Rating |
: 4/5 (37 Downloads) |
Synopsis Big Data for Remote Sensing: Visualization, Analysis and Interpretation by : Nilanjan Dey
This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.
Author |
: D. Jude Hemanth |
Publisher |
: Springer Nature |
Total Pages |
: 277 |
Release |
: 2019-11-13 |
ISBN-10 |
: 9783030241780 |
ISBN-13 |
: 3030241785 |
Rating |
: 4/5 (80 Downloads) |
Synopsis Artificial Intelligence Techniques for Satellite Image Analysis by : D. Jude Hemanth
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.
Author |
: Wenzhong Shi |
Publisher |
: Springer Nature |
Total Pages |
: 941 |
Release |
: 2021-04-06 |
ISBN-10 |
: 9789811589836 |
ISBN-13 |
: 9811589836 |
Rating |
: 4/5 (36 Downloads) |
Synopsis Urban Informatics by : Wenzhong Shi
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Author |
: Haldorai, Anandakumar |
Publisher |
: IGI Global |
Total Pages |
: 285 |
Release |
: 2019-09-20 |
ISBN-10 |
: 9781522597520 |
ISBN-13 |
: 1522597522 |
Rating |
: 4/5 (20 Downloads) |
Synopsis Big Data Analytics for Sustainable Computing by : Haldorai, Anandakumar
Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Author |
: David Hall |
Publisher |
: CRC Press |
Total Pages |
: 564 |
Release |
: 2001-06-20 |
ISBN-10 |
: 9781420038545 |
ISBN-13 |
: 1420038540 |
Rating |
: 4/5 (45 Downloads) |
Synopsis Multisensor Data Fusion by : David Hall
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
Author |
: Ni-Bin Chang |
Publisher |
: CRC Press |
Total Pages |
: 627 |
Release |
: 2018-02-21 |
ISBN-10 |
: 9781351650632 |
ISBN-13 |
: 1351650637 |
Rating |
: 4/5 (32 Downloads) |
Synopsis Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by : Ni-Bin Chang
In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.
Author |
: Deepak Kumar |
Publisher |
: Elsevier |
Total Pages |
: 310 |
Release |
: 2024-11-15 |
ISBN-10 |
: 9780443235962 |
ISBN-13 |
: 0443235961 |
Rating |
: 4/5 (62 Downloads) |
Synopsis Data Analytics and Artificial Intelligence for Earth Resource Management by : Deepak Kumar
Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity. Resource monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources. - Provides a comprehensive understanding of data analytics and artificial intelligence (AI) for earth resource management - Includes real-world case studies and examples to demonstrate the practical applications of data analytics and AI in earth resource management - Presents clear illustrations, diagrams, and pictures that make the content more understandable and engaging