Conference On Machine Processing Of Remotely Sensed Data
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Conference On Machine Processing Of Remotely Sensed Data
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Author : Conference on machine processing of remotely sensed data
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Of Remotely Sensed Data written by Conference on machine processing of remotely sensed data and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
Conference On Machine Processing Of Remotely Sensed Data
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Author :
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Of Remotely Sensed Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Electronic data processing categories.
Conference On Machine Processing Remotely Sensed Data
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Author :
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Remotely Sensed Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Remote sensing categories.
Machine Processing Of Remotely Sensed Data With Special Emphasis On Range Forest And Wetlands Assessment
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Author : P. G. Burroff
language : en
Publisher:
Release Date : 1981
Machine Processing Of Remotely Sensed Data With Special Emphasis On Range Forest And Wetlands Assessment written by P. G. Burroff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Forests and forestry categories.
Machine Processing Of Remotely Sensed Data
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Author : S. K. Mengel
language : en
Publisher:
Release Date : 1985
Machine Processing Of Remotely Sensed Data written by S. K. Mengel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Remote sensing categories.
Machine Processing Of Remotely Sensed Data Symposium Proceedings
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Author : Laboratory for Applications of Remote Sensing (West Lafayette, Ind.)
language : en
Publisher:
Release Date : 1973
Machine Processing Of Remotely Sensed Data Symposium Proceedings written by Laboratory for Applications of Remote Sensing (West Lafayette, Ind.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
Kernel Methods For Remote Sensing Data Analysis
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Author : Gustau Camps-Valls
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-03
Kernel Methods For Remote Sensing Data Analysis written by Gustau Camps-Valls and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-03 with Technology & Engineering categories.
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.
Remote Sensing For Environmental Sciences
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Author : E. Schanda
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Remote Sensing For Environmental Sciences written by E. Schanda and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The public's serious concern about the uncertainties and dangers of the conse quences of human activities on environmental quality demands policies to control the situation and to prevent its deterioration. But far-reaching decisions on the environmental policy are impaired or even made impossible as long as the relevant ecological relations are not sufficiently understood and large-scale quantitative information on the most important parameters is not available in sufficient quality and quantity. The techniques of remote sensing offer new ways of procuring data on natural phenomena with three main advantages - the large distance between sensor and object prevents interference with the environmental conditions to be measured, - the potentiality for large-scale and even global surveys yields a new dimension for the investigations of the environmental parameters, - the extremely wide, spectral range covered by the whole diversity of sensors discloses many properties of the environmental media not detectable within a single wave band (as e.g. the visible). These significant additions to the conventional methods of environmental studies and the particular qualification of several remote sensing methods for quantitative determination of the natural parameters makes this new investigation technique an important tool both to the scientists studying the ecological relationship and the administration in charge of the environmental planning and protection.
Earth Resources
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Author :
language : en
Publisher:
Release Date : 1983
Earth Resources written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Astronautics in earth sciences categories.
Big Data Analytics For Satellite Image Processing And Remote Sensing
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Author : Swarnalatha, P.
language : en
Publisher: IGI Global
Release Date : 2018-03-09
Big Data Analytics For Satellite Image Processing And Remote Sensing written by Swarnalatha, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-09 with Technology & Engineering categories.
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.