The Use of Remote Sensing in the Modeling of Forest Productivity: 50 (Forestry Sciences, 50) - Softcover

Softcover

ISBN 10: 9401062900 ISBN 13: 9789401062909

Publisher: Springer, 2012

Synopsis

Forests comprise the greatest storage of carbon on land, provide fuel for millions, are the habitat for most terrestrial biodiversity, and are critical to the economies of many countries. Yet changes in the extent and dynamics of forests are inherently difficult to detect and quantify. Remote sensing technologies may facilitate the measurement of some key forest properties which, when combined with other information contained in various computer models, may allow for the quantification of critical forest functions. This book explores how remote sensing and computer modeling can be combined to estimate changes in the carbon storage, or productivity, of forests - from the level of the leaf to the level of the globe. Land managers, researchers, policy makers and students will all find stimulating discussions among an international set of experts at the cutting edge of the interface between science, technology and management.

About this title

Review

`The approaches discussed in the book are not limited to forests only they can easily be utilized in evaluation of other types of ecosystems. This is why the book will certainly be highly valuable for a wide range of scientists and land managers.'
Biologia Plantarum, 40:4 (1997/8)

From the Back Cover

This book explores how remote sensing and computer modeling can be combined to estimate changes in the carbon storage, or productivity, of forests - from the level of the leaf to the level of the globe. Land managers, researchers, policy makers and students will all find stimulating discussions among an international set of experts at the cutting edge of the interface between science, technology and management.

Edition details

• Publisher: Springer
• Publication date: 2012
• Language: English
• ISBN 10: 9401062900
• ISBN 13: 9789401062909
• Binding: Paperback
• Number of pages: 334
• Editor: Gholz H.L., Nakane Kaneyuki, Shimoda H.