The use of airborne hyperspectral remote sensing imagery for automated mapping of submersed aquatic vegetation in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery, together with in-situ spectral reflectance measurements using a field spectrometer, were obtained for the pilot sites in spring and early fall of Field-based shoreline surveys for the study area determined SAV presence, species, and distribution.
Hyperspectral Remote Sensing of Vegetation
A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The goal of the spectral database is to automate the image processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV Myriophyllum spicatum and Vallisneria americana.
Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. Map accuracy was high and had very low false positive detections. Jump to main content. The second edition includes extensive discussions on data processing and how to implement data processing mechanisms in a standard, fast, and efficient manner for their applications. Prasad S. Thenkabail is a well known global expert in remote sensing and spatial sciences.
Currently, he works as a Research Geographer with the U. Thenkabail has conducted pioneering scientific research work in two major areas: Hyperspectral remote sensing of vegetation; Global Irrigated and Rainfed Cropland Mapping. John G. Lyon has conducted scientific and engineering research and administrative functions throughout his career. He is formerly the senior physical scientist in the U. His main research interest is in using remote sensing to study and analyze broad scale vegetation health and functioning.
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Recently, he used remote sensing and field measurements to understand the phenology patterns of tropical rainforests and savannas in the Amazon and Southeast Asia and his Amazon work was featured in a National Geographic television special entitled The Big Picture. Currently his research involves coupling eddy covariance tower flux measurements with ground spectral sensors and satellite observations to study carbon and water cycling across Australian landscapes.
Reviews of the first edition: "The authors solicited the help of numerous high-quality hyperspectral remote sensing scientists to write this book.
The characteristics of hyperspectral remote sensing systems are explained clearly. Fundamental hyperspectral data analysis, hyperspectral indices, and data mining methods are introduced.www.tdovize.com/wp-includes/4562-samsung-galaxy.php
Hyperspectral Remote Sensing of Vegetation, Second Edition, Four Volume Set - CRC Press Book
I am particularly impressed with the in-depth treatment on leaf and plant biophysical and biochemical properties, especially related to remote sensing of: chlorophyll content, leaf nitrogen concentration, photosynthetic efficiency, quantifying plant litter, leaf-area-index, and vegetation stress detection.
The book documents numerous practical applications of hyperspectral remote sensing for forest management, precision farming, monitoring invasive species, and local to global land cover change detection. No other book contains such detailed information about hyperspectral remote sensing of vegetation. John R. This comprehensive text covers all aspects of hyperspectral sensing of plants and vegetation, from sensor systems, data mining, biophysical properties and plant functioning, to species mapping and land cover applications.
This book will greatly increase the research communities' understanding of how to use hyperspectral data to solve otherwise intractable problems in plant applications from crops to forests. Ustin, Professor of Environmental and Resource Sciences, Department of Land, Air, and Water Resources, University of California at Davis, USA " Hyperspectral Remote Sensing of Vegetation provides excellent coverage of the research and application of high spectral resolution measurements for vegetation mapping, monitoring and analysis.
This book brings together an enormous range of topical areas, leaving the reader with a much improved understanding of the vital role and use of the hyperspectral sensing for plant and ecosystem studies. This book shows not only the breadth of international involvement in the use of hyperspectral data but also in the breadth of innovative application of mathematical techniques to extract information from the image data. Newsletter Google 4. Help pages.
Hyperspectral remote sensing of vegetation
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- Hyperspectral Remote Sensing of Vegetation (4-Volume Set) | NHBS Academic & Professional Books.