Prasad S. Thenkabail, John G. Lyon, Alfredo Huete
December 6, 2018 Forthcoming
Reference - 296 Pages - 85 Color & 21 B/W Illustrations
ISBN 9781138066038 - CAT# K33412
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Evaluating the performance of various types of hyperspectral vegetation indices in characterizing agricultural crops, this volume discusses non-invasive quantification of foliar pigments, leaf nitrogen concentration of cereal crop, the estimation of nitrogen content in crops and pastures, forest leaf chlorophyll content, among others. Each chapter reviews existing “state-of-art” knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral images in study of vegetation. The concluding chapter provides readers with the editor’s view and guidance on the highlights and the essence of the Volume 2 and the editor’s perspective.
Hyperspectral Vegetation Indices. Chapter 1 Hyperspectral vegetation indices. Chapter 2 Derivative hyperspectral vegetation indices. Hyperspectral Image Classification Methods and Approaches. Chapter 3 Hyperpsectral image classification methods in vegetation and agricultural cropland studies.Chapter 4 Massively big hyperspectral sensing data processing on cloud computing Architectures.Hyperspectral Vegetation Indices Applications to Agriculture and Vegetation.Chapter 5 Non-invasive Quantification of Foliar Pigments: Principles and Implementation.Chapter 6 Estimating Leaf nitrogen concentration (LNC) of cereal crop with hyperspectral data.Chapter 7 Optical remote sensing of vegetation water content.Chapter 8 Estimation of nitrogen content in crops and pastures using hyperspectral vegetation Indices.Chapter 9 Forest leaf chlorophyll content study using hyperspectral remote sensing Conclusions.Chapter 10 Synthesis of Volume I: Theory, Sensor Systems, Data Preprocessing-Mining-Analysis Methods, and Algorithms.