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Hyperspectral Remote Sensing

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Hyperspectral Remote Sensing and Spectral Signature Applications

Hyperspectral Remote Sensing and Spectral Signature Applications Book
Author : S. Rajendran
Publisher : New India Publishing
Release : 2009
ISBN : 9788189422349
Language : En, Es, Fr & De

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Book Description :

Contributed papers presented at the National Seminar on "Hyperspectral Remote Sensing and Spectral Signature Databse Management System," held on February 14-15, 2008 at Annamalai University.

Hyperspectral Remote Sensing

Hyperspectral Remote Sensing Book
Author : Marcus Borengasser,William S. Hungate,Russell Watkins
Publisher : CRC Press
Release : 2007-12-13
ISBN : 9781420012606
Language : En, Es, Fr & De

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Book Description :

Land management issues, such as mapping tree species, recognizing invasive plants, and identifying key geologic features, require an understanding of complex technical issues before the best decisions can be made. Hyperspectral remote sensing is one the technologies that can help with reliable detection and identification. Presenting the fundamentals of remote sensing at an introductory level, Hyperspectral Remote Sensing: Principles and Applications explores all major aspects of hyperspectral image acquisition, exploitation, interpretation, and applications. The book begins with several chapters on the basic concepts and underlying principles of remote sensing images. It introduces spectral radiometry concepts, such as radiance, irradiance, flux, and blackbody radiation; covers imaging spectrometers, examining spectral range, full width half maximum (FWHM), resolution, sampling, signal-to-noise ratio (SNR), and multispectral and hyperspectral sensor systems; and addresses atmospheric interactions. The book then discusses information extraction, with chapters covering the underlying physics principles that lead to the creation of an image and the interpretation of the image's information. The final chapters describe case studies that illustrate the use of hyperspectral remote sensing in agriculture, environmental monitoring, forestry, and geology. After reading this book, you will have a better understanding of how to evaluate different approaches to hyperspectral analyses and to determine which approaches will work for your applications.

Hyperspectral Remote Sensing and Application

Hyperspectral Remote Sensing and Application Book
Author : Robert O. Green,Qingxi Tong
Publisher : Society of Photo Optical
Release : 1998
ISBN : 9780819429612
Language : En, Es, Fr & De

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Book Description :

Divided into four sections, these conference papers cover: sensors, calibration, and program overviews; minerals and geology; vegetation and forests; and feature extraction and classification algorithms.

Hyperspectral Remote Sensing of Tropical and Sub Tropical Forests

Hyperspectral Remote Sensing of Tropical and Sub Tropical Forests Book
Author : Margaret Kalacska,G. Arturo Sanchez-Azofeifa
Publisher : CRC Press
Release : 2008-02-26
ISBN : 1420053434
Language : En, Es, Fr & De

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Book Description :

While frequently used in temperate environments, hyperspectral sensors and data are still a novelty in the tropics. Exploring the potential of hyperspectral remote sensing for assessing ecosystem characteristics, Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests focuses on the complex and unique set of challenges involved in using t

Hyperspectral Remote Sensing

Hyperspectral Remote Sensing Book
Author : Ruiliang Pu
Publisher : CRC Press
Release : 2017-08-16
ISBN : 1351646931
Language : En, Es, Fr & De

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Book Description :

Advanced imaging spectral technology and hyperspectral analysis techniques for multiple applications are the key features of the book. This book will present in one volume complete solutions from concepts, fundamentals, and methods of acquisition of hyperspectral data to analyses and applications of the data in a very coherent manner. It will help readers to fully understand basic theories of HRS, how to utilize various field spectrometers and bioinstruments, the importance of radiometric correction and atmospheric correction, the use of analysis, tools and software, and determine what to do with HRS technology and data.

Hyperspectral Remote Sensing

Hyperspectral Remote Sensing Book
Author : Prem Chandra Pandey,Prashant K. Srivastava,Heiko Balzter,Bimal Bhattacharya,George P. Petropoulos
Publisher : Elsevier
Release : 2020-08-05
ISBN : 0081028954
Language : En, Es, Fr & De

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Book Description :

Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology. Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection Provides an overview of the state-of-the-art, including algorithms, techniques and case studies

Hyperspectral Remote Sensing of Vegetation

Hyperspectral Remote Sensing of Vegetation Book
Author : Prasad S. Thenkabail,John G. Lyon,Alfredo Huete
Publisher : CRC Press
Release : 2016-04-19
ISBN : 1439845387
Language : En, Es, Fr & De

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Book Description :

Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research. Hyperspectral Remote Sensing of Vegetation integrates this knowledge, guiding readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Taking a practical approach to a complex subject, the book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment. This comprehensive book brings together the best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, vegetation classification, biophysical and biochemical modeling, crop productivity and water productivity mapping, and modeling. It provides the pertinent facts, synthesizing findings so that readers can get the correct picture on issues such as the best wavebands for their practical applications, methods of analysis using whole spectra, hyperspectral vegetation indices targeted to study specific biophysical and biochemical quantities, and methods for detecting parameters such as crop moisture variability, chlorophyll content, and stress levels. A collective "knowledge bank," it guides professionals to adopt the best practices for their own work.

Hyperspectral Remote Sensing

Hyperspectral Remote Sensing Book
Author : Michael Theodore Eismann
Publisher : Society of Photo Optical
Release : 2012-01-01
ISBN : 9780819487872
Language : En, Es, Fr & De

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Book Description :

Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment that thoroughly captures its multidisciplinary nature. The content is oriented toward the physical principles of hyperspectral remote sensing as opposed to applications of hyperspectral technology. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available in this technology area and apply their knowledge to the understanding of material spectral properties, the design of hyperspectral systems, the analysis of hyperspectral imagery, and the application of the technology to specific problems.

Multispectral and Hyperspectral Remote Sensing Instruments and Applications II

Multispectral and Hyperspectral Remote Sensing Instruments and Applications II Book
Author : Allen M. Larar,Makoto Suzuki,Qingxi Tong,Society of Photo-optical Instrumentation Engineers
Publisher : Society of Photo Optical
Release : 2005
ISBN :
Language : En, Es, Fr & De

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Book Description :

Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.

Hyperspectral Remote Sensing of Nearshore Water Quality

Hyperspectral Remote Sensing of Nearshore Water Quality Book
Author : Sima Bagheri
Publisher : Springer
Release : 2016-11-11
ISBN : 3319469495
Language : En, Es, Fr & De

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Book Description :

This book provides details on of the utility of hyperspectral remote sensing – NASA/AVIRIS in nearshore water quality issues of NY/NJ. It demonstrates the use of bio optical modeling and retrieval techniques to derive the concentrations of important water quality parameters (chlorophyll, color dissolved organic matter and suspended sediments) in the study area. The case study focuses on the nearshore waters of NY/NJ considered as a valued ecological, economic and recreational resource within the New York metropolitan area. During field campaigns (1998-2001) measurements were made to establish hydrological optical properties of the NY/NJ nearshore waters with concurrent NASA/AVIRIS overflights. The field measurements included: 1) concurrent above and below surface spectral reflectance; 2) shipboard sampling for determination of inherent optical properties (IOP); and 3) concentrations of optically important water quality parameters. Understanding the relationship between reflectance, absorption and scattering is essential for developing the analytical algorithm necessary to use remote sensing as a monitoring /management tool in the nearshore environment.

Efficient Analysis of Hyperspectral Remote Sensing Imagery

Efficient Analysis of Hyperspectral Remote Sensing Imagery Book
Author : Yan Xu
Publisher :
Release : 2019
ISBN :
Language : En, Es, Fr & De

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Book Description :

This dissertation develops new techniques to reduce the computational complexity for hyperspectral remote sensing image analysis. Specific techniques are applied with regards to different applications of hyperspectral imagery, i.e., classification, target detection. The contribution of this dissertation can be summarized as follows. 1. A time-efficient version combining multiple collaborative representations model is proposed for hyperspectral image classification. Collaborative representation (CR) can be implemented either with a dictionary containing training samples of all-classes or class specific. A collaborative representation optimized classifier with Tikhonov regularization (CROCT) is proposed to avoid the redundant operations in all-class and class-specific versions. 2. An efficient probabilistic collaborative representation is presented for hyperspectral image classification. Its performance is evaluated on different types of spatial features of hyperspectral imagery including shape feature (i.e., extended multi-attribute feature), global feature (i.e., Gabor feature), and local feature (i.e., Local Binary Pattern). Experimental results show the probabilistic collaborative representation based classifier (PROCRC) has excellent performance in terms of both accuracy and computational cost compared with the original CRC and regularized versions of CRC. 3. Fast nonlinear classification and an explicit kernel approach are built for multispectral and hyperspectral imagery respectively to improve the kernel version of collaborative representation based algorithms. Experimental results show that using artificial bands generated from a simple band ratio function can yield better classification accuracy than the nonlinear kernel method and also reduce computational cost. In addition, the explicit kernel mapping approach can yield high accuracy as the original kernel versions of CR-based algorithms but with similarly low computational cost as in the original linear CRC classifiers. 4. Efficient band selection approaches are proposed for hyperspectral target detection. A maximum-sub-maximum ratio (MSR) metric has been applied for band selection, which can well gauge the target background separation. Efficient evolutionary searching methods such as particle swarm optimization and firefly algorithm are used in conjunction with maximum-sub-maximum ratio metric for band selection. Experimental results show that the proposed band selection approach can select a small band set while yielding similar detection performance compared with using all the original bands.

Spectral Spatial Classification of Hyperspectral Remote Sensing Images

Spectral Spatial Classification of Hyperspectral Remote Sensing Images Book
Author : Jon Atli Benediktsson,Pedram Ghamisi
Publisher : Artech House
Release : 2015-09-01
ISBN : 1608078132
Language : En, Es, Fr & De

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Book Description :

This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspectral classification has been one of the most active and relevant innovative lines of research in remote sensing during recent years. This book gives you insight into several important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. This book also shows you how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide.