Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation / (Record no. 128899)

000 -LEADER
fixed length control field 06926nam a2200565Ii 4500
001 - CONTROL NUMBER
control field 9781315164151
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220509193041.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190122t20182019fluab ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781315164151(e-book : PDF)
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1076543429
040 ## - CATALOGING SOURCE
Original cataloging agency FlBoTFG
Transcribing agency FlBoTFG
Description conventions rda
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QK46.5.V44
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC
Subject category code subdivision 036000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC
Subject category code subdivision 003000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code SCI
Subject category code subdivision 019000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TVB
Source bicscc
245 00 - TITLE STATEMENT
Title Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation /
Statement of responsibility, etc edited by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete.
250 ## - EDITION STATEMENT
Edition statement Second edition.
264 #1 -
-- Boca Raton, FL :
-- CRC Press,
-- [2018].
264 #4 -
-- ©2019.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (489 pages) :
Other physical details 201 illustrations, text file, PDF
336 ## -
-- text
-- rdacontent
337 ## -
-- computer
-- rdamedia
338 ## -
-- online resource
-- rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 00 - FORMATTED CONTENTS NOTE
Title Section I: Introduction to Hyperspectral Remote Sensing of Agricultural Crops and Vegetation -- 1. Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Crops -- [Prasad S. Thenkabail, John G. Lyon, and Alfredo Huete] -- Section II: Hyperspectral Sensor Systems -- 2. Hyperspectral Sensor Characteristics: Airborne, Spaceborne, Hand-Held, and Truck-Mounted; Integration of Hyperspectral Data with LiDAR -- [Fred Ortenberg] -- 3. Hyperspectral Remote Sensing in Global Change Studies -- [Jiaguo Qi, Yoshio Inoue, and Narumon Wiangwang] -- Section III: Hyperspectral Libraries of Agricultural Crops and Vegetation -- 4. Monitoring Vegetation Diversity and Health through Spectral Traits and Trait Variations Based on Hyperspectral Remote Sensing -- [Angela Lausch and Pedro J. Leito] -- 5. The Use of Hyperspectral Proximal Sensing for Phenotyping of Plant Breeding Trials -- [Andries B. Potgieter, James Watson, Barbara George-Jaeggli, Gregory McLean, Mark Eldridge, Scott C. Chapman, Kenneth Laws, Jack Christopher, Karine Chenu, Andrew Borrell, Graeme L. Hammer, and David R. Jordan] -- 6. Linking Online Spectral Libraries with Hyperspectral Test Data through Library Building Tools and Code -- [Muhammad Al-Amin Hoque and Stuart Phinn] -- 7. The Use of Spectral Databases for Remote Sensing of Agricultural Crops -- [Andreas Hueni, Lola Suarez, Laurie A. Chisholm, and Alex Held] -- 8. Characterization of Soil Properties Using Reflectance Spectroscopy -- [E. Ben-Dor, S. Chabrillat, and Jos A. M. Dematt] -- Section IV: Hyperspectral Data Mining, Data Fusion, and Algorithms -- 9. Spaceborne Hyperspectral EO-1 Hyperion Data Pre-Processing: Methods, Approaches, and Algorithms -- [Itiya P. Aneece, Prasad S. Thenkabail, John G. Lyon, Alfredo Huete, and Terrance Slonecker] -- 10. Hyperspectral Image Data Mining -- [Sreekala G. Bajwa, Yu Zhang, and Alimohammad Shirzadifar] -- 11. Hyperspectral Data Processing Algorithms -- [Antonio Plaza, Javier Plaza, Gabriel Martn, and Sergio Snchez] -- 12. Methods for Linking Drone and Field Hyperspectral Data to Satellite Data -- [Muhammad Al-Amin Hoque and Stuart Phinn] -- 13. Integrating Hyperspectral and LiDAR Data in the Study of Vegetation -- [Jessica J. Mitchell, Nancy F. Glenn, Kyla M. Dahlin, Nayani Ilangakoon, Hamid Dashti, and Megan C. Maloney] -- 14. Fifty-Years of Advances in Hyperspectral Remote Sensing of Agriculture and VegetationSummary, Insights, and Highlights of Volume I: Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation -- [Prasad S. Thenkabail, John G. Lyon, and Alfredo Huete].
520 3# - SUMMARY, ETC.
Summary, etc 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.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print format.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element TECHNOLOGY & ENGINEERING / Agriculture / General.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element SCIENCE / Earth Sciences / General.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Broad-band data from sensors; Landsat ETM+.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Cloud computing.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Crop water use and water productivity modeling and mapping.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Hyperspectral sensor systems.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Spaceborne hyperspectral EO-1 Hyperion pre-processing.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element UAV and field hyperspectral data.
Source of heading or term bisacsh
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Vegetation monitoring.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Plants
General subdivision Remote sensing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Crops
General subdivision Remote sensing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Multispectral imaging.
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Thenkabail, Prasad S.,
Relator term editor.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lyon, John G.,
Relator term editor.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huete, Alfredo ,
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Taylor and Francis.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
International Standard Book Number 9781138058545
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781315164151
Public note Click here to view

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