Earth Observation Data Analytics Using Machine And Deep Learning

Author : Sanjay Garg
Publisher : Computing and Networks
ISBN 13 : 9781839536175
Total Pages : 0 pages
Book Rating : 4.79/5 ( download)

DOWNLOAD NOW!

Download or read book Earth Observation Data Analytics Using Machine and Deep Learning written by Sanjay Garg and published by Computing and Networks. This book was released on 2023-07-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using machine and deep learning techniques the authors introduce pre-processing methods applied to satellite images to identify land cover features, detect object, classify crops, recognize targets, and monitor and support earth resources. Readers will need a basic understanding of computing, remote sensing and image interpretation.

Author : Gustau Camps-Valls
Publisher : John Wiley & Sons
ISBN 13 : 1119646162
Total Pages : 436 pages
Book Rating : 4.67/5 ( download)

DOWNLOAD NOW!

Download or read book Deep Learning for the Earth Sciences written by Gustau Camps-Valls and published by John Wiley & Sons. This book was released on 2021-08-18 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

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

DOWNLOAD NOW!

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 : Gustau Camps-Valls
Publisher : John Wiley & Sons
ISBN 13 : 1119646146
Total Pages : 436 pages
Book Rating : 4.43/5 ( download)

DOWNLOAD NOW!

Download or read book Deep Learning for the Earth Sciences written by Gustau Camps-Valls and published by John Wiley & Sons. This book was released on 2021-08-16 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Author : Saurabh Prasad
Publisher : Elsevier
ISBN 13 : 044319078X
Total Pages : 366 pages
Book Rating : 4.80/5 ( download)

DOWNLOAD NOW!

Download or read book Advances in Machine Learning and Image Analysis for GeoAI written by Saurabh Prasad and published by Elsevier. This book was released on 2024-06-01 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter

Author : Pierre-Philippe Mathieu
Publisher : Springer
ISBN 13 : 3319656333
Total Pages : 328 pages
Book Rating : 4.35/5 ( download)

DOWNLOAD NOW!

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 : Dileep Kumar Gupta
Publisher : Elsevier
ISBN 13 : 9780443273728
Total Pages : 0 pages
Book Rating : 4.23/5 ( download)

DOWNLOAD NOW!

Download or read book Google Earth Engine and Artificial Intelligence for Earth Observation written by Dileep Kumar Gupta and published by Elsevier. This book was released on 2025-02-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techqnieus. It includes a wide range of scientific domains that can utilise remote sensing and geographic information systems (GIS) through detailed case studies. The book delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth Observation. Google Earth Engine and Artificial Intelligence for Earth Observation is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilising remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.

Author : Gregory Giuliani
Publisher :
ISBN 13 : 9783039280933
Total Pages : 302 pages
Book Rating : 4.37/5 ( download)

DOWNLOAD NOW!

Download or read book Earth Observation Data Cubes written by Gregory Giuliani and published by . This book was released on 2020 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10.

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

DOWNLOAD NOW!

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 : Gwanggil Jeon
Publisher : Mdpi AG
ISBN 13 : 9783036579467
Total Pages : 0 pages
Book Rating : 4.6X/5 ( download)

DOWNLOAD NOW!

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.