Big Data for Remote Sensing: Visualization, Analysis and Interpretation - Digital Earth and Smart Earth - Rilegato

Rilegato

ISBN 10: 3319899228 ISBN 13: 9783319899220

Casa editrice: Springer Nature, 2018

Riassunto

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.

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Informazioni sull?autore

Nilanjan Dey is an Assistant Professor at the Department of Information Technology, Techno India College of Technology, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, BULGARIA. Associate Researcher of Laboratoire RIADI, University of Manouba, TUNISIA. His research topic is Medical Imaging, Soft computing, Data mining, Machine learning, Rough set, Computer Aided Diagnosis, Atherosclerosis. He has 20 books and 300 international conferences and journal papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IJSE), IGI Global, US, and International Journal of Natural Computing Research (IGI Global), US. Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, and Associated Editor of IEEE Access journal and the International Journal of Service Science, Management, Engineering and Technology, IGI Global. He is a life member of IE, UACEE, ISOC 

Chintan Bhatt is an Assistant Professor of U & P U Patel Department of Computer Engineering at Charotar University of Science And Technology. His PhD in Computer Science, he was M.Tech. in Computer Engineering, Dharmsinh Desai University, 2009 - 2011, B.E. in Computer Engineering, Gujarat University (Charotar Institute of Technology), 2005 – 2009.  His research interests include Data Mining, Software Engineering, Networking, Big Data, Internet of Things (IoT), Mobile Computing. He received an award on 2015, Paper Publication at International Conference Award and Faculty with Maximum Publication in CSIC Award during CSI Annual Convention, New Delhi. He had organized special sessions on Internet of Things (IoT), CSNT, Gwalior during 4-6 April, 2015 and on Internet of Things (IoT) and big data in IoT , ICTCS, at Udaipur during 14-16 November, 2014. He is an active reviewer in the Wireless Communications, IEEE and Internet of Things Journal, IEEE, as well as Mobile Networks and Applications, Springer. He has several publications in repute journals and two books.

Amira S. Ashour is currently an Assistant Professor and Head of Department-EEC, Faculty of Engineering, Tanta University, Egypt. She has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the vice chair of CS department, CIT college, Taif University, KSA for 5 years. Her research interests are Smart antenna, Direction of arrival estimation, Targets tracking, Image processing, Medical imaging, Machine learning, Signal/image/video processing, Image analysis, Computer vision, and Optimization. She has 6 books and about 70 published journal papers. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US. She is an Associate Editor for the IJRSDA, IGI Global, US as well as the IJACI, IGI Global, US. She is an Editorial Board Member of the International Journal of Image Mining (IJIM), Inderscience.

Dalla quarta di copertina

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.

Dettagli dell?edizione

• Editore: Springer Nature
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 3319899228
• ISBN 13: 9783319899220
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 154
• Redattore: Dey Nilanjan, Bhatt Chintan, Ashour Amira S.
• Contatto del produttore: {language_tag:it_IT,value:"Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com"}