January 20, 2020 Forthcoming
Reference - 336 Pages - 170 Color Illustrations
ISBN 9781498711777 - CAT# K25081
Series: Remote Sensing Applications Series
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This book explores the applicability of multiple remote sensors to acquire information relevant to restoration and conservation efforts in wetlands using data collected from airborne and space multispectral/hyperspectral sensors, light detection and ranging (LiDAR), Unmanned Aircraft Systems (UAS), and a hand-held spectroradiometer. This book also examines digital data processing techniques such as object-based image analysis, machine learning, texture analysis, and data fusion. After an introduction to the Everglades and to remote sensing, the book is divided into four parts based on the sensor systems used. There are chapters on vegetation mapping, biomass and water quality modeling, applications of hyperspectral data for plant stress analysis and coral reef mapping, studies of airborne LiDAR data for coastal vulnerability analysis and DEM improvement, as well as chapters that explore a fusion of multiple sensors for different datasets.
Multi-sensor System Applications in the Everglades Ecosystems provides a comprehensive application of remote sensing techniques in the Florida Everglades and its coastal ecosystems. It will prove an invaluable resource for the restoration and conservation of the Florida Everglades and beyond, for global wetlands in general. Any professional, scientist, engineer, or student working with remote sensing and wetland ecosystems will reap enormous benefits from this book.
Recent Advances in Environmental Remote Sensing. Hyperspectral Remote Sensing. LiDAR Remote Sensing. Machine Learning Algorithms. Object-based Image Analysis. Remote Sensing Data Fusion Techniques. Hyperspectral and LiDAR Systems for Benthic Habitat Mapping in Florida Keys. Application of Hyperspectral Data for Modeling Harmful Algal Blooms on the West Florida Shelf. Application of EO-1/Hyperion for Assessing Sea Grass Abundance along the West Central Coast of Florida.