Remote Sensing For The Earth Sciences

Die großen Fortschritte in der Fernerkundung sowie die Verfügbarkeit umfangreicher neuer Satellitendaten machten die Neuauflage des bekannten 8-bändigen "Manual of Remote Sensing" erforderlich. Behandelt werden Theorie und praktische Anwendungsmöglichkeiten von Fernerkundungs-Satellitendaten auf geologische Problemstellungen. Darüber hinaus beschreibt Band 3 die technischen Mittel zur Erzielung der Daten (Radar, Licht-, Infrarot- und geophysikalische Sensoren) und deren Anwendungsbereiche (Exploration von Erz- und Kohlelagerstätten, Stratigraphie, technische Geologie und Umweltstudien). Dieser Band bietet eine ideale Kombination von Theorie, Datenanalyse und Fallstudien zur Veranschaulichung grundlegender Konzepte.

This book provides information on the Earth science remote sensing data information and data format such as HDF-EOS. It evaluates the current data processing approaches and introduces data searching and ordering from different public domains. It further explores the remote sensing and GIS migration products and WebGIS applications. Both volumes are designed to give an introduction to current and future NASA, NOAA and other Earth science remote sensing.

Part of an ongoing series of manuals covering the range of applications of remotely sensed imagery, Volume 4 addresses the use of this technology in natural resource management and environmental monitoring. Comprehensive, authoritative, and up-to-date, it covers terrestrial ecosystems, aquatic ecosystems, and agriculture ecosystems, as well as future directions in technology and research.

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.

Remote Sensing Applications in Environmental and Earth System Sciences is a contemporary, multi-disciplinary, multi-scaling, updated, and upgraded approach of applied remote sensing in the environment. The book begins with an overview of remote sensing technology, and then explains the types of data that can be used as well as the image processing and analysis methods that can be applied to each type of application through the use of case studies throughout. Includes a wide spectrum of environmental applications and issues Explains methodological image analysis and interpretation procedures for conducting a variety of environmental analyses Discusses the development of early warning systems Covers monitoring of the environment as a whole – atmosphere, land, and water Explores the latest remote sensing systems in environmental applications This book is an excellent resource for anyone who is interested in remote sensing technologies and their use in Earth systems, natural resources, and environmental science.

This book provides information on the Earth science remote sensing data information and data format such as HDF-EOS. It evaluates the current data processing approaches and introduces data searching and ordering from different public domains. It further explores the remote sensing and GIS migration products and WebGIS applications. Both volumes are designed to give an introduction to current and future NASA, NOAA and other Earth science remote sensing.