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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 t
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.
Forests represent a remnant wilderness of high recreational value in the densely populated industrial societies, a threatened natural resource in some regions of the world and a renewable reservoir of essential raw materials for the wood processing industry. In June 1992 the United Nations Conference on the Environment and Development (UNCED) in Rio de Janeiro initiated a world-wide process of negotiation with the aim of ensuring sustainable management, conservation and development of forest resources. Although there seems to be unanimous support for sustainable development from all quarters, there is no generally accepted set of indicators which allows comparisons to be made between a given situation and a desirable one. In a recent summary paper prepared by the FAO Forestry and Planning Division, Ljungman et al. (1999) find that forest resources continue to diminish, while being called upon to produce a greater range of goods and services and that calls for sustainable forest management will simply go unheeded if the legal, policy and administrative environment do not effectively control undesirable practices. Does the concept of sustainable forest management represent not much more than a magic formula for achieving consensus, a vague idea which makes it difficult to match action to rhetoric? The concept of sustainable forest management is likely to remain an imprecise one, but we can contribute to avoiding management practices that are clearly unsustainable.
The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry.
This book is the most comprehensive and up-to-date treatment of computer applications in forestry. It is the first text on software for forest management to emphasize integration of computer applications. It also offers important new insights on how to continue advancing computational technologies in forest management. The authors are internationally-recognized authorities in the subjects presented.
Particularly about forests in the USA.
This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.
Forest Resources Resilience and Conflicts presents modern remote sensing and GIS techniques for Sustainable Livelihood. It provides an up-to-date critical analysis of the discourse surrounding forest resources and society, illustrating the relationship between forest resources and the livelihood of local people. The book is organized into four parts consisting of 31 chapters. Each chapter then reviews current understanding, present research, and future implications. Utilizing case studies and novel advances in geospatial technologies, Forest Resources Resilience and Conflicts provides a timely synthesis of a rapidly growing field and stimulates ideas for future work, especially considering sustainable development goals.In addition, the book presents the effective contribution of the forestry sector to populations' livelihoods through improved collection of forestry statistics that foster the understanding and integration of the forestry sector in poverty reduction processes and the national economy to enhance its integration in national planning. It is a valuable resource for researchers and students in environmental science, especially those interested in forestry, geography, and remote sensing. - Demonstrates tools and techniques for measurement, monitoring, mapping, and modeling of forest resources - Explores state-of-the-art techniques using open source software, statistical programming, and GIS, focusing on recent trends in data mining and machine learning - Addresses a wide range of issues with both environmental and societal implications - Provides a global review of the multiple roles of forest resources utilizing case studies to illustrate management strategies and techniques
Driven by the societal needs and improvement in sensor technology and image processing techniques, remote sensing has become an essential geospatial tool for understanding the Earth and managing Human-Earth interactions. Remote Sensing for Sustainability introduces the current state of the art remote sensing knowledge integral for monitoring the world's natural resources and environments, managing exposure to natural disasters and man-made risks, and helping understand the sustainability and productivity of natural ecosystems. Bridging the gap between remote sensing and sustainability science this book examines theories and methods as well as practical applications of sustainable development for cities using remote sensing; focuses on remote sensing methods and techniques for sustainable natural resources with emphasize on forests; answers questions on how and what the remote sensing methods and techniques can do for the sustainability of environmental systems; and examines the issues of energy use and sustainable energy sources using remote sensing technology in countries such as Germany, China, the U.S, drawing on case studies to demonstrate the applicability of remote sensing techniques. This comprehensive guide, which can serve to professors, researchers, and students alike, takes in consideration the United Nations set of sustainable development goals and intends to contribute to the GEO's Strategic Plan by addressing and exemplifying a number of societal benefit areas of remote sensing data sets, methods, and techniques for sustainable development.