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Book Vegetation Discrimination and Analysis

Download or read book Vegetation Discrimination and Analysis written by Samuel Kusangaya and published by LAP Lambert Academic Publishing. This book was released on 2012-04 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vegetation discrimination and analysis using multi-spectral and hyper-spectral remote sensing imagery has gained a lot of widespread application in agricultural and vegetation applications. Such imagery has been successfully used in estimating vegetation characteristics like plant health, stress mapping, identifying disease and estimating crop yields resulting in millions of documented studies. Several characteristics of vegetation makes the use of remote sensing a desired method for vegetation description and analysis. In particular, vegetation reflectance in the red edge region has enhanced the use of hyper spectral remote sensing. Several methods for vegetation discrimination and analysis will be illustrated here among them utility of some common multispectral image classification algorithms. For hyperspectral image analysis, use of vegetation indices such as NDVI, MSAVI & MSR will be showcased. Additionally, advanced hyperspectral derivative analysis like the first derivative transformation, 4-point interpolation, Lagrangian interpolation, continuum removal, absorption depth analysis and linear pixel un-mixing methods will also be shown through different application cases.

Book Hyperspectral Remote Sensing of Vegetation

Download or read book Hyperspectral Remote Sensing of Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2016-04-19 with total page 766 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Biophysical and Biochemical Characterization and Plant Species Studies

Download or read book Biophysical and Biochemical Characterization and Plant Species Studies written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2018-12-07 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing stateof- the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Hyperspectral remote sensing or imaging spectroscopy data has been increasingly used in studying and assessing the biophysical and biochemical properties of agricultural crops and natural vegetation. Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume III through the editors’ perspective. Key Features of Volume III: Covers recent abilities to better quantify, model, and map plant biophysical, biochemical water, and structural properties. Demonstrates characteristic hyperspectral properties through plant diagnostics or throughput phenotyping of plant biophysical, biochemical, water, and structural properties. Establishes plant traits through hyperspectral imaging spectroscopy data as well as its integration with other data, such as LiDAR, using data from various platforms (ground-based, UAVs, and earth-observing satellites). Studies photosynthetic efficiency and plant health and stress through hyperspectral narrowband vegetation indices. Uses hyperspectral data to discriminate plant species and\or their types as well as their characteristics, such as growth stages. Compares studies of plant species of agriculture, forests, and other land use\land cover as established by hyperspectral narrowband data versus multispectral broadband data. Discusses complete solutions from methods to applications, inventory, and modeling considering various platform (e.g., earth-observing satellites, UAVs, handheld spectroradiometers) from where the data is gathered. Dwells on specific applications to detect and map invasive species by using hyperspectral data.

Book Thermal Infrared Remote Sensing

Download or read book Thermal Infrared Remote Sensing written by Claudia Kuenzer and published by Springer Science & Business Media. This book was released on 2013-06-17 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techniques for analyzing thermal data. Ground-breaking chapters on applications present a wide variety of case studies leading to a deepened understanding of land and sea surface temperature dynamics, urban heat island effects, forest fires, volcanic eruption precursors, underground coal fires, geothermal systems, soil moisture variability, and temperature-based mineral discrimination. ‘Thermal Infrared Remote Sensing: Sensors, Methods, Applications’ is unique because of the large field it spans, the potentials it reveals, and the detail it provides. This book is an indispensable volume for scientists, lecturers, and decision makers interested in thermal infrared technology, methods, and applications.

Book Fundamentals  Sensor Systems  Spectral Libraries  and Data Mining for Vegetation

Download or read book Fundamentals Sensor Systems Spectral Libraries and Data Mining for Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2018-12-07 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.

Book An Introduction to Vegetation Analysis

Download or read book An Introduction to Vegetation Analysis written by David R. Causton and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: TO VEGETATION ANALYSIS Principles, practice and interpretation D.R. CAUSTON Department of Botany and Microbiology, University College of Wales, Aberystwyth London UNWIN HYMAN Boston Sydney Wellington © D.R. Causton, 1988 This book is copyright under the Berne Convention. No reproduction without permission. All rights reserved. Published by the Academic Division of Unwin Hyman Ltd 15/17 Broadwick Street, London W1V 1FP, UK Allen & Unwin Inc., 8 Winchester Place, Winchester, Mass. 01890, USA Allen & Unwin (Australia) Ltd, 8 Napier Street, North Sydney, NSW 2060, Australia Allen & Unwin (New Zealand) Ltd in association with the Port Nicholson Press Ltd, 60 Cambridge Terrace, Wellington, New Zealand First published in 1988 British Library Cataloguing in Publication Data Causton, David R. An introduction to vegetation analysis: principles, practice and intepretation. 1. Botany-Ecology-Mathematics I. Title 581.5'247 QK901 ISBN-13: 978-0-04-581025-3 e-ISBN-13: 978-94-011-7981-2 DOl: 10.1007/978-94-011-7981-2 Library of Congress Cataloging-in-Publication Data Causton, David R. An introduction to vegetation analysis. Bibliography: p. Includes index. 1. Botany-Ecology-Methodology. 2. Plant communities-Research-Methodology. 3. Vegetation surveys. 4. Vegetation classification. I. Title. QK90I.C33 1987 581.5 87-19327 ISBN-13: 978-0-04-581025-3 Typeset in 10 on 12 point Times by Mathematical Composition Setters Ltd, Salisbury and Biddies of Guildford Preface This book has been written to help students and their teachers, at various levels, to understand the principles, some of the methods, and ways of interpreting vegetational and environmental data acquired in the field.

Book Vegetation Discrimination Using AVHRR Global Vegetation Index Data

Download or read book Vegetation Discrimination Using AVHRR Global Vegetation Index Data written by Jesslyn F. Brown and published by . This book was released on 1990 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation

Download or read book Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2018-12-07 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.

Book Geobotanical Discrimination of Ultramafic Parent Materials  An Evaluation of Remote Sensing Techniques

Download or read book Geobotanical Discrimination of Ultramafic Parent Materials An Evaluation of Remote Sensing Techniques written by D. A. Mouat and published by . This book was released on 1982 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: Color and color infrared aerial photography and imagery acquired from a Daedalus DEI-1260 multispectral airborne scanner were employed in an investigation to discriminate ultramafic rock types in a test site in southwest Oregon. An analysis of the relationships between vegetation characteristics and parent materials was performed using a vegetation classification and map developed for the project, lithologic information derived from published geologic maps of the region, and terrain information gathered in the field. Several analytical methods including visual image analysis, band ratioing, principal components analysis, and contrast enhancementg and subsequent color composite generation were used in the investigation. There was a close correspondence between vegetation types and major rock types. These were readily discriminated by the remote sensing techniques. It was found that ultramafic rock types were separable from non-ultramafic rock types and serpentine was distinguishable from non-serpentinized peridotite. Further investigations involving spectroradiometric and digital classification techniques are being performed to further identify rock types and to discriminate chromium and nickel-bearing rock types. (Author).

Book Vegetation Description and Data Analysis

Download or read book Vegetation Description and Data Analysis written by Martin Kent and published by John Wiley & Sons. This book was released on 2011-11-14 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vegetation Description and Data Analysis: A PracticalApproach, Second Edition is a fully revised and up-datededition of this key text. The book takes account of recent advancesin the field whilst retaining the original reader-friendly approachto the coverage of vegetation description and multivariate analysisin the context of vegetation data and plant ecology. Since the publication of the hugely popular first edition therehave been significant developments in computer hardware andsoftware, new key journals have been established in the field andscope and application of vegetation description and analysis hasbecome a truly global field. This new edition includes fullcoverage of new developments and technologies. This contemporary and comprehensive edition of this well-known andrespected textbook will prove invaluable to undergraduate andgraduate students in biological sciences, environmental science,geography, botany, agriculture, forestry and biologicalconservation. * Fully international approach * Includes illustrative case studies throughout * Now with new material on: the nature of plant communities;transitional areas between plant communities; induction anddeduction of plant ecology; diversity indices and dominancediversity curves; multivariate analysis in ecology. * Accessible, reader-friendly style * Now with new and improved illustrations

Book Hyperspectral Remote Sensing of Agriculture and Vegetation

Download or read book Hyperspectral Remote Sensing of Agriculture and Vegetation written by Simone Pascucci and published by MDPI. This book was released on 2021-01-20 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows recent and innovative applications of the use of hyperspectral technology for optimal quantification of crop, vegetation, and soil biophysical variables at various spatial scales, which can be an important aspect in agricultural management practices and monitoring. The articles collected inside the book are intended to help researchers and farmers involved in precision agriculture techniques and practices, as well as in plant nutrient prediction, to a higher comprehension of strengths and limitations of the application of hyperspectral imaging to agriculture and vegetation. Hyperspectral remote sensing for studying agriculture and natural vegetation is a challenging research topic that will remain of great interest for different sciences communities in decades.

Book Sensitivity Analysis in Earth Observation Modelling

Download or read book Sensitivity Analysis in Earth Observation Modelling written by George P. Petropoulos and published by Elsevier. This book was released on 2016-10-07 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling. Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement. Outlines challenges and future prospects of sensitivity analysis implementation in earth observation modeling Provides readers with a roadmap for directing future efforts Includes case studies with applications from different regions around the globe, helping readers to explore strengths and weaknesses of the different methods in earth observation modeling Presents a step-by-step guide, providing the principles of each method followed by the application of variants, making the reference easy to use and follow

Book NASA Reference Publication

Download or read book NASA Reference Publication written by and published by . This book was released on 1977 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Discrimination of Wetland Vegetation Using Close range Remote Sensing

Download or read book Discrimination of Wetland Vegetation Using Close range Remote Sensing written by Deborah Marie DeMarey and published by . This book was released on 2002 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Spatial Regression Analysis Using Eigenvector Spatial Filtering

Download or read book Spatial Regression Analysis Using Eigenvector Spatial Filtering written by Daniel Griffith and published by Academic Press. This book was released on 2019-09-14 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics