Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests  book cover
1st Edition

Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests

ISBN 9780367452728
Published December 18, 2019 by CRC Press
352 Pages

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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 this technology and the data it provides.

Special Features

  • A CD-ROM including hyperspectral color images

  • Coverage of in situ spectroscopy, airborne and satellite-based remote sensing, and fusion with other forms of data such as LiDAR

  • Peer-reviewed chapters that highlight the most innovative achievements

  • Discussion of the potential of hyperspectral remote sensing to provide tools for assessing ecosystem characteristics at various spatial and temporal scales

Experts from Diverse Backgrounds Share Their Successes

The book explores a range of analysis techniques, including hyperspectral reflectance indices, spectral mixture analysis, pattern classification, band selection, partial least-squares, linear discriminant analysis, and radiative transfer models. The chapter authors present a comprehensive review of the current status and innovative achievements in the field, citing approximately six hundred studies. As illustrated by the diverse backgrounds of the contributors, the most successful use of hyperspectral data requires a multidisciplinary approach spanning a wide range of fields.

Go Beyond the Basics to Actual Application

Although it begins by touching on the basics, this book is not a tutorial in remote sensing, but a reference that illustrates the potential applications and analysis techniques that can be used when facing the unique challenge of working in the tropics. It presents real-world examples and a suite of analysis t

Table of Contents

Tropical Dry Forest Phenology and Discrimination of Tropical Tree Species Using Hyperspectral Data. Remote Sensing and Plant Functional Groups: Physiology, Ecology, and Spectroscopy in Tropical Systems. Hyperspectral Data for Assessing Carbon Dynamics and Biodiversity of Forests. Effect of Soil Type on Plant Growth, Leaf Nutrient/Chlorophyll Concentration, and Leaf Reflectance of Tropical Tree and Grass Species. Spectral Expression of Gender: A Pilot Study with Two Dioecious Neotropical Tree Species. Species Classification of Tropical Tree Leaf Reflectance and Dependence on Selection of Spectral Bands. Discriminating Sirex noctilio Attack in Pine Forest Plantations in South Africa Using High Spectral Resolution Data. Hyperspectral Remote Sensing of Exposed Wood and Deciduous Trees in Seasonal Tropical Forests. Assessing Recovery Following Selective Logging of Lowland Tropical Forests Based on Hyperspectral Imagery. A Technique for Reflectance Calibration of Airborne Hyperspectral Spectrometer Data Using a Broad, Multiband Radiometer. Assessment of Phenologic Variability in Amazon Tropical Rainforests Using Hyperspectral Hyperion and MODIS Satellite Data. Hyperspectral Remote Sensing of Canopy Chemistry, Physiology, and Biodiversity in Tropical Rainforests. Tropical Remote Sensing —Opportunities and Challenges. Index.

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Margaret Kalacska, Ph.D., obtained both her M.S. and Ph.D. from the Earth and Atmospheric Sciences Department at the University of Alberta, Canada. Her doctoral research focused on the application of remote sensing to tropical dry forest ecology. She is a former TROPI-DRY postdoctoral fellow (University of Alberta) and National Sciences and Engineering Research Council of Canada postdoctoral fellow (Simon Fraser University). She is currently a research fellow in the Centre for Forensic Sciences and the School of Criminology at Simon Fraser University, Canada. Her research interests are the application of hyperspectral data/imagery, machine learning, and Bayesian networks for predictive models and the development of remote sensing techniques in the forensic and environmental sciences. She has experience with ecological, remote sensing, and spectrometry research in Costa Rica, Panama, Mexico, and Japan and has been involved in two airborne multi-/hyperspectral missions over Costa Rica (CARTA I and II). G. Arturo Sanchez-Azofeifa, Ph.D., conducts research related to the study of impacts of land use/cover change (LUCC) on biodiversity loss and habitat fragmentation in tropical dry forest environments. His research involves the study of theoretical linkages between remote sensing (multispectral and hyperspectral) and the spatial/temporal dynamics of leaf area index (LAI), primary productivity (PP), and photosynthetically active radiation (PAR). In addition, his research interests involve the development of techniques for the analysis and interpretation of the presence of non-self-supporting tropical systems (lianas) and tropical hardwood species (e.g., mahogany) at the leaf and canopy level. Dr. Sanchez-Azofeifa is one of the 2006 recipients of an Aldo Leopold Leadership Program fellowship.