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Multi-Source National Forest Inventory: Methods and Applications (Vol. 18)

by Erkki Tomppo , Others
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Original price Rs. 21,297.00
Original price Rs. 21,297.00 - Original price Rs. 21,297.00
Original price Rs. 21,297.00
Current price Rs. 14,908.00
Rs. 14,908.00 - Rs. 14,908.00
Current price Rs. 14,908.00

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Book cover type: Hardcover
  • ISBN13: 9781402087127
  • Binding: Hardcover
  • Subject: Earth-Science/Environment
  • Publisher: Springer Verlag
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 374
  • Original Price: 229.0 EUR
  • Language: English
  • Edition: N/A
  • Item Weight: 772 grams

About the Book Building on more than a decade of innovative research into multi-source forest inventory (MS-NFI) this book presents full details of the development, outputs and applications of the improved k-NN method. The method, which was pioneered in Finland in 1990, is rapidly becoming a world standard in forest inventory, having been adopted as standard in Finland and Sweden, and recently introduced in Austria and across the US. The book describes in detail the full MS-NFI process, and the input data used - including field data, satellite images, and digital map data, as well as coarse-scale variation of forest variables. It also presents comprehensive information on the types of outputs which can be derived, including maps and statistics, describing, for example, stock volumes and development, dominant tree species, age-class distribution, and large and small-scale variation. The book will provide an invaluable resource for those involved in forest inventory, including government departments and bodies involved in forest policy, management and monitoring, forest managers, and researchers and graduate students interested in forest inventory, modelling and analysis. It will find an additional market among those interested in Earth observation, ecology and broader areas of environmental and natural resource management. Erkki Tomppo was the winner of the 1997 Marcus Wallenberg Prize for his work on the k-NN method.