Artificial Intelligence Applied To Satellite Based Remote Sensing Data For Earth Observation

Author : Maria Pia Del Rosso
Publisher : IET
ISBN 13 : 1839532122
Total Pages : 283 pages
Book Rating : 4.22/5 ( download)

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Download or read book Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation written by Maria Pia Del Rosso and published by IET. This book was released on 2021-09-14 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how artificial intelligence, including neural networks and deep learning, can be applied to the processing of satellite data for Earth observation. The authors explain how to develop a set of libraries for the implementation of artificial intelligence that encompass different aspects of research.

Author : Gustavo Camps-Valls
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608458199
Total Pages : 195 pages
Book Rating : 4.96/5 ( download)

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Download or read book Remote Sensing Image Processing written by Gustavo Camps-Valls and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / {Classification / Spectral Mixture Analysis / Estimation of Physical Parameters

Author : Sumit Kumar
Publisher : Springer Nature
ISBN 13 : 9811976988
Total Pages : 219 pages
Book Rating : 4.88/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Satellite Data Processing and Services written by Sumit Kumar and published by Springer Nature. This book was released on 2023-01-02 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, Artificial Intelligence and Machine Learning in Satellite: Data Processing and Services, presents the selected proceedings of the International Conference on Small Satellites (ICSS 2022) that aims to provide an opportunity for academicians, scientists, researchers, and industry experts, engaged in teaching, research, and development on satellite data processing and its services by employing advanced artificial intelligence-based machine learning techniques. This book covers the application of artificial intelligence and machine learning techniques in various domains of earth observations like natural resources and environmental management, water resources, urban and rural development, climate change, and other contemporary subjects. The book will surely be a valuable asset for beginners, researchers, and professionals working in satellite data processing and services using artificial intelligence and machine learning approaches.

Author : Nilanjan Dey
Publisher : Springer
ISBN 13 : 3319899236
Total Pages : 154 pages
Book Rating : 4.37/5 ( download)

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Download or read book Big Data for Remote Sensing: Visualization, Analysis and Interpretation written by Nilanjan Dey and published by Springer. This book was released on 2018-05-23 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Pierre-Philippe Mathieu
Publisher : Springer
ISBN 13 : 3319656333
Total Pages : 328 pages
Book Rating : 4.35/5 ( download)

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Download or read book Earth Observation Open Science and Innovation written by Pierre-Philippe Mathieu and published by Springer. This book was released on 2018-01-23 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is published open access under a CC BY 4.0 license. Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites. This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.

Author : D. Jude Hemanth
Publisher : Springer Nature
ISBN 13 : 3030241785
Total Pages : 274 pages
Book Rating : 4.80/5 ( download)

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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.

Author : Ni-Bin Chang
Publisher : CRC Press
ISBN 13 : 1351650637
Total Pages : 647 pages
Book Rating : 4.32/5 ( download)

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Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Gwanggil Jeon
Publisher : Mdpi AG
ISBN 13 : 9783036579467
Total Pages : 0 pages
Book Rating : 4.6X/5 ( download)

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Download or read book Advanced Machine Learning and Deep Learning Approaches for Remote Sensing written by Gwanggil Jeon and published by Mdpi AG. This book was released on 2023-06-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.

Author : Anil Kumar
Publisher : CRC Press
ISBN 13 : 100009152X
Total Pages : 194 pages
Book Rating : 4.26/5 ( download)

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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.

Author : Chang-Wook Lee
Publisher : Mdpi AG
ISBN 13 : 9783036516042
Total Pages : 166 pages
Book Rating : 4.42/5 ( download)

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Download or read book Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS written by Chang-Wook Lee and published by Mdpi AG. This book was released on 2021-11-11 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.