Remote Sensing of Protected Lands: Remote Sensing Applications Series
Editat de Yeqiao Wangen Limba Engleză Hardback – 21 noi 2011
The first book of its kind, Remote Sensing of Protected Lands showcases state-of-the-art remote sensing applications for the inventory and monitoring of protected areas. Contributions from renowned scholars and experts from around the world are organized into four sections covering the use of remote sensing in:
- Changing landscapes and change detection
- Inventory, mapping, and conservation
- Inventory and monitoring of frontier lands
- Decision support for the management of protected lands
Combining reviews of theories and methods with analysis of case studies, the book gives readers both a systematic view of the field and detailed knowledge of specific topics. Case studies explore key topics in the context of a wide range of protected areas, including national parks in the United States and Canada, the Albertine Rift in eastern Africa, the Amazon forests, the Changbai Mountain region in Northeast Asia, the frontier lands in Siberia and the Tibetan Plateau, and marine protected areas along the tropical and temperate Pacific and Atlantic coasts.
Alongside each case study, the book examines advanced remote sensing technologies such as airborne and spaceborne high spatial resolution imageries, multispectral and multitemporal time series data, satellite interferometric synthetic aperture radar (InSAR), and the integration of r
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Specificații
ISBN-13: 9781439841877
ISBN-10: 143984187X
Pagini: 636
Ilustrații: Yes: 32 page color insert
Dimensiuni: 156 x 234 x 38 mm
Greutate: 1.02 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Remote Sensing Applications Series
ISBN-10: 143984187X
Pagini: 636
Ilustrații: Yes: 32 page color insert
Dimensiuni: 156 x 234 x 38 mm
Greutate: 1.02 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Remote Sensing Applications Series
Public țintă
Academic and Professional Practice & DevelopmentCuprins
Remote Sensing of Protected Lands: An Overview. Remote Sensing of Changing Landscape of Protected Lands. Remote Sensing for Inventory, Mapping, and Conservation of Protected Lands and Waters. Remote Sensing for Inventory and Monitoring of Frontier Lands. Remote Sensing in Decision Support for Management of Protected Lands. Index.
Notă biografică
Dr. Yeqiao Wang is a professor at the Department of Natural Resources Science, University of Rhode Island. He has received several awards for his work, including the prestigious Presidential Early Career Award for Scientists and Engineers (PECASE) from President William J. Clinton in 2000. Dr. Wang’s specialties are terrestrial remote sensing and modeling in natural resources analysis and mapping. He has published more than 50 peer-reviewed journal articles, 70 abstracts and conference papers, and contributed more than 20 peer-reviewed book chapters. He also edited Remote Sensing of Coastal Environments (CRC Press 2009). Dr. Wang serves as the editor in chief for Encyclopedia of Natural Resources (Taylor & Francis), a three-volume set of Land, Air, and Water. Besides his professional publications in English, he has also authored and edited several science books in Chinese.
For more information, see Dr. Wang’s web site at the University of Rhode Island.
For more information, see Dr. Wang’s web site at the University of Rhode Island.
Descriere
As debates about climate change and sustainability intensify, national parks and other protected lands become more important as indicators of ecosystem conditions. Providing a suite of remote sensing-based approaches for the protected lands around the world, this book addresses contemporary issues in monitoring, conservation planning, and ecosystem forecasting. Case studies explore remote sensing applications and examine advanced remote sensing technologies, including airborne and spaceborne high spatial resolution imageries, multispectral and multitemporal time series data, satellite interferometric synthetic aperture radar (InSAR), and the integration of remote sensing and field measurements for information extraction and modeling.