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 II, Hyperspectral Indices and Image Classifications for Agriculture and Vegetation evaluates the performance of hyperspectral narrowband or imaging spectroscopy data with specific emphasis on the uses and applications of hyperspectral narrowband vegetation indices in characterizing, modeling, mapping, and monitoring agricultural crops and vegetation. This volume presents and discusses topics such as the non-invasive quantification of foliar pigments, leaf nitrogen concentration of cereal crop, the estimation of nitrogen content in crops and pastures, and forest leaf chlorophyll content, among others. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume II through the editors’ perspective.

Key Features of Volume II:

  • Provides the fundamentals of hyperspectral narrowband vegetation indices and hyperspectral derivative vegetation indices and their applications in agriculture and vegetation studies.

  • Discusses the latest advances in hyperspectral image classification methods and their applications.

  • Explains the massively big hyperspectral sensing data processing on cloud computing architectures.

  • Highlights the state-of-the-art methods in the field of hyperspectral narrowband vegetation indices for monitoring agriculture, vegetation, and their properties such as plant water content, nitrogen, chlorophyll, and others at leaf, canopy, field, and landscape scales.

  • Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.

section Section I|1 pages

Hyperspectral Vegetation Indices

chapter 1|24 pages

Hyperspectral Vegetation Indices

ByDar A. Roberts, Keely L. Roth, Erin B. Wetherley, Susan K. Meerdink, Ryan L. Perroy

chapter 2|37 pages

Derivative Hyperspectral Vegetation Indices in Characterizing Forest Biophysical and Biochemical Quantities

ByQuan Wang, Jia Jin, Rei Sonobe, Jing Ming Chen

section Section II|1 pages

Hyperspectral Image Classification Methods and Approaches

chapter 3|38 pages

Advances in Hyperspectral Image Classification Methods for Vegetation and Agricultural Cropland Studies

ByEdoardo Pasolli, Saurabh Prasad, Melba M. Crawford, James C. Tilton

chapter 4|28 pages

Big Data Processing on Cloud Computing Architectures for Hyperspectral Remote Sensing

ByZebin Wu, Jin Sun, Yi Zhang

section Section III|1 pages

Hyperspectral Vegetation Index Applications to Agriculture and Vegetation

chapter 5|28 pages

Noninvasive Quantification of Foliar Pigments

Principles and Implementation
ByAnatoly Gitelson, Alexei Solovchenko

chapter 6|20 pages

Hyperspectral Remote Sensing of Leaf Nitrogen Concentration in Cereal Crops

ByTao Cheng, Yan Zhu, Dong Li, Xia Yao, Kai Zhou

chapter 7|18 pages

Optical Remote Sensing of Vegetation Water Content

ByColombo Roberto, Busetto Lorenzo, Meroni Michele, Rossini Micol, Panigada Cinzia

chapter 8|25 pages

Estimation of Nitrogen Content in Herbaceous Plants Using Hyperspectral Vegetation Indices

ByD. Stroppiana, F. Fava, M. Boschetti, P. A. Brivio

chapter 9|22 pages

Hyperspectral Remote Sensing of Leaf Chlorophyll Content

From Leaf, Canopy, to Landscape Scales
ByYongqin Zhang

section Section IV|1 pages


chapter 10|36 pages

Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume II

Hyperspectral Indices and Image Classifications for Agriculture and Vegetation
ByPrasad S. Thenkabail, John G. Lyon, Alfredo Huete