On-Board Processing for Satellite Remote Sensing Images, Zhou, Guoqing
Автор: John J. Qu; Wei Gao; Menas Kafatos; Robert E. Murp Название: Earth Science Satellite Remote Sensing ISBN: 3642421555 ISBN-13(EAN): 9783642421556 Издательство: Springer Рейтинг: Цена: 32651.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: V. B. H. (Gini) Ketelaar Название: Satellite Radar Interferometry ISBN: 9048181259 ISBN-13(EAN): 9789048181254 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book investigates the applicability of satellite radar interferometry (InSAR) for deformation monitoring. The presented methodologies are demonstrated in an integrated way for the entire northern part of the Netherlands and a part of Germany.
Описание: This is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches are generic and adapted to suit applications for various remote sensing images processing in landcover mapping, forestry, urban, in disaster mapping, image restoration, etc.
Автор: Mehdi Khaki Название: Satellite Remote Sensing in Hydrological Data Assimilation ISBN: 3030373746 ISBN-13(EAN): 9783030373740 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.
Автор: Gabriele Moser; Josiane Zerubia Название: Mathematical Models for Remote Sensing Image Processing ISBN: 3319663283 ISBN-13(EAN): 9783319663289 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses highly topical subjects involving remote sensing data types (e.g., very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g., probabilistic graphical models, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.
Автор: Gabriele Moser; Josiane Zerubia Название: Mathematical Models for Remote Sensing Image Processing ISBN: 3319882198 ISBN-13(EAN): 9783319882192 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Поставка под заказ.
Описание: This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses highly topical subjects involving remote sensing data types (e.g., very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g., probabilistic graphical models, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.
Описание: This is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches are generic and adapted to suit applications for various remote sensing images processing in landcover mapping, forestry, urban, in disaster mapping, image restoration, etc.
Автор: Donald B. Percival, Andrew T. Walden Название: Spectral Analysis for Univariate Time Series ISBN: 1107028140 ISBN-13(EAN): 9781107028142 Издательство: Cambridge Academ Рейтинг: Цена: 14573.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.
Автор: Rosa Lasaponara; Nicola Masini Название: Satellite Remote Sensing ISBN: 9400796153 ISBN-13(EAN): 9789400796157 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This overview of satellite archeology focuses on the use of Earth Observation in archaeology not only for probing the subsurface to unveil sites and artifacts but also for the management, valorization, monitoring and preservation of cultural resources.
Автор: P. Swarnalatha, Prabu Sevugan Название: Big Data Analytics for Satellite Image Processing and Remote Sensing ISBN: 1522536434 ISBN-13(EAN): 9781522536437 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 31324.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
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.
Автор: Thiago Nunes Kehl; Viviane Todt; Maur?cio Roberto Название: Real time deforestation detection using ANN and Satellite images ISBN: 331915740X ISBN-13(EAN): 9783319157405 Издательство: Springer Рейтинг: Цена: 7836.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks.
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