As remote sensing data and methods have become increasingly complex and varied - and increasingly reliable - so have their uses in forest management. New algorithms have been developed in virtually every aspect of image analysis, from classification to enhancements to estimating parameters. Remote Sensing for Sustainable Forest Management reviews the literature and provides the tools for understanding and choosing remote sensing solutions for management problems.
The book presents methods and operational examples of forest change detection, forest defoliation monitoring, forest classification, and forest growth modeling. The concluding chapters discuss research issues and the future of remote sensing technologies. The author draws a comprehensive picture of the state of the art in remote sensing data and methods applicable to sustainable forest management issues.
Additionally, and perhaps more importantly, the author addresses the 'I tried that once, didn't work, so the whole thing is useless' syndrome that has created institutional inertia in some management agencies. We now know the proper processing steps, the most efficient algorithms, what kinds of maps can be generated, and by whom, and what level of confidence managers can invest in the resulting products. We know under what conditions aerial remote sensing missions should be executed, what are the limits, and where investments in equipment and training should be made.
This authoritative book explores the remote sensing methods that need to be adopted and adapted to the forest science issues that are emerging through the sustainable forest management approach. This approach is not driven by technology, but by questions about its fundamental processes. Remote Sensing for Sustainable Forest Management shows you how this technology can be used to answer these questions and achieve the goals of sustainable forest management.