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Remote Sensing of Protected Lands.

Remote Sensing of Protected Lands.

・ISBN 978-0-367-38212-4 paper GB£ 72.99

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電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9780429105678
著者・編者Wang, Yeqiao (ed.),
シリーズ (Remote Sensing Applications Series)
出版社 (CRC Press, UK)
出版年月2019
ページ数636 pp.
言語ENG
ニュース番号<A01-58997>

解説

National parks, wildlife refuges and sanctuaries, natural reserves, conservation areas, frontier lands, and marine-protected areas are increasingly recognized as essential providers of ecosystem services and biological resources. As debates about climate change and sustainability intensify, protected areas become more important as indicators of ecosystem conditions in particular environments or in comparison with adjacent environments.

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

A View of Both the Forest and the Trees

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