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The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture, Forest Service is in the process of moving from a system of quasi-independent, regional, periodic inventories to an enhanced program featuring greater national consistency, a complete and annual sample of each State, new reporting requirements, and integration with the ground sampling component of the Forest Health Monitoring Program. This documentation presents an overview of the conceptual design, describes the sampling frame and plot configuration, presents the estimators that form the basis of FIA's National Information Management System (NIMS), and shows how annual data are combined for analysis. It also references a number of Web-based supplementary documents that provide greater detail about some of the more obscure aspects of the sampling and estimation system, as well as examples of calculations for most of the common estimators produced by FIA.
Life Cycle Inventory (LCI) Analysis is the second phase in the Life Cycle Assessment (LCA) framework. Since the first attempts to formalize life cycle assessment in the early 1970, life cycle inventory analysis has been a central part. Chapter 1 “Introduction to Life Cycle Inventory Analysis“ discusses the history of inventory analysis from the 1970s through SETAC and the ISO standard. In Chapter 2 “Principles of Life Cycle Inventory Modeling”, the general principles of setting up an LCI model and LCI analysis are described by introducing the core LCI model and extensions that allow addressing reality better. Chapter 3 “Development of Unit Process Datasets” shows that developing unit processes of high quality and transparency is not a trivial task, but is crucial for high-quality LCA studies. Chapter 4 “Multi-functionality in Life Cycle Inventory Analysis: Approaches and Solutions” describes how multi-functional processes can be identified. In Chapter 5 “Data Quality in Life Cycle Inventories”, the quality of data gathered and used in LCI analysis is discussed. State-of-the-art indicators to assess data quality in LCA are described and the fitness for purpose concept is introduced. Chapter 6 “Life Cycle Inventory Data and Databases“ follows up on the topic of LCI data and provides a state-of-the-art description of LCI databases. It describes differences between foreground and background data, recommendations for starting a database, data exchange and quality assurance concepts for databases, as well as the scientific basis of LCI databases. Chapter 7 “Algorithms of Life Cycle Inventory Analysis“ provides the mathematical models underpinning the LCI. Since Heijungs and Suh (2002), this is the first time that this aspect of LCA has been fundamentally presented. In Chapter 8 “Inventory Indicators in Life Cycle Assessment”, the use of LCI data to create aggregated environmental and resource indicators is described. Such indicators include the cumulative energy demand and various water use indicators. Chapter 9 “The Link Between Life Cycle Inventory Analysis and Life Cycle Impact Assessment” uses four examples to discuss the link between LCI analysis and LCIA. A clear and relevant link between these phases is crucial.
This book has been developed as a forest inventory textbook for students and could also serve as a handbook for practical foresters. We have set out to keep the mathematics in the book at a fairly non-technical level, and therefore, although we deal with many issues that include highly sophisticated methodology, we try to present first and foremost the ideas behind them. For foresters who need more details, references are given to more advanced scientific papers and books in the fields of statistics and biometrics. Forest inventory books deal mostly with sampling and measurement issues, as found here in section I, but since forest inventories in many countries involve much more than this, we have also included material on forestry applications. Most applications nowadays involve remote sensing technology of some sort, so that section II deals mostly with the use of remote sensing material for this purpose. Section III deals with national inventories carried out in different parts of world, and section IV is an attempt to outline some future possibilities of forest inventory methodologies. The editors, Annika Kangas Professor of Forest Mensuration and Management, Department of Forest Resource Management, University of Helsinki. Matti Maltamo Professor of Forest Mensuration, Faculty of Forestry, University of Joensuu. ACKNOWLEDGEMENTS
Provides an early warning of environmental change before irreversible loss has occurred. Monitoring is focused at 2 resource levels: individual species & specific ecosystem types. Selection of prospective indicators for the status of species or ecosystems is based on the development of conceptual models relating resource change to reliable, early warning signals of change. Ecosystems are monitored on the basis of critical structural & compositional elements that reflect the state of underlying ecological processes. Includes recommendations for staffing, funding, & establishing a long-term commitment for a large, interagency monitoring program. Includes, A Guide to Soil Sampling & Analysis on the Nat. Forests of the Inland NW U.S.Ó
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.
Life Cycle Inventory (LCI) Analysis is the second phase in the Life Cycle Assessment (LCA) framework. Since the first attempts to formalize life cycle assessment in the early 1970, life cycle inventory analysis has been a central part. Chapter 1 “Introduction to Life Cycle Inventory Analysis“ discusses the history of inventory analysis from the 1970s through SETAC and the ISO standard. In Chapter 2 “Principles of Life Cycle Inventory Modeling”, the general principles of setting up an LCI model and LCI analysis are described by introducing the core LCI model and extensions that allow addressing reality better. Chapter 3 “Development of Unit Process Datasets” shows that developing unit processes of high quality and transparency is not a trivial task, but is crucial for high-quality LCA studies. Chapter 4 “Multi-functionality in Life Cycle Inventory Analysis: Approaches and Solutions” describes how multi-functional processes can be identified. In Chapter 5 “Data Quality in Life Cycle Inventories”, the quality of data gathered and used in LCI analysis is discussed. State-of-the-art indicators to assess data quality in LCA are described and the fitness for purpose concept is introduced. Chapter 6 “Life Cycle Inventory Data and Databases“ follows up on the topic of LCI data and provides a state-of-the-art description of LCI databases. It describes differences between foreground and background data, recommendations for starting a database, data exchange and quality assurance concepts for databases, as well as the scientific basis of LCI databases. Chapter 7 “Algorithms of Life Cycle Inventory Analysis“ provides the mathematical models underpinning the LCI. Since Heijungs and Suh (2002), this is the first time that this aspect of LCA has been fundamentally presented. In Chapter 8 “Inventory Indicators in Life Cycle Assessment”, the use of LCI data to create aggregated environmental and resource indicators is described. Such indicators include the cumulative energy demand and various water use indicators. Chapter 9 “The Link Between Life Cycle Inventory Analysis and Life Cycle Impact Assessment” uses four examples to discuss the link between LCI analysis and LCIA. A clear and relevant link between these phases is crucial.
Forest inventory may be defined as the technique of collecting, evaluating and presenting specified information on forest areas. Because of the generally la~ge extent of forest areas, data are usually collected by sampling, i.e. by making observations on only part of the area of interest. As there are many different sampling methods (e.g. Appendix 1), a choice must first be made as to which method suits the given field and financial circumstances best. On completion of the sampling procedure, the numerous data collected have next to be condensed to manageable representative quantities. Finally, from these quantities, inferences about the situation in the entire forest area are made, preferably accompanied by an indication of their reliability. This book is intended for students who want to know the whepefope of the sampling techniques used in forest inventory. The danger of lack of knowledge is a blind following of instructions and copying statistical formulae, or, even worse, feeding data into a computer loaded with a program that is said to print out the required information. In serious persons, such approaches may leave a feeling of dissatisfaction or even of professional incompetence, be cause of inability to direct or evaluate the procedure critically. If a student tries to improve his or her situation, he/she will find that the few existing forest inventory textbooks, though some with merit, either use confusing statistical symbols or do not adequately cover theoretical principles.
"This publication presents a history of the Forest Survey (now known as Forest Inventory and Analysis) program in the United States as it evolved within the U.S. Department of Agriculture (USDA) Forest Service over a period of more than 100 years. It draws on the writings of several authors who have published on various aspects of the Forest Survey program. A review is presented of nine ground plot designs used in the Forest Survey and Forest Inventory and Analysis (FIA) programs since 1931. This publication also highlights the major events contributing to the current FIA program, beginning as far back as 1830. It is impressive to look at the many contributions of various people working with the Nation's Forest Survey program, as well as the various methodologies that have contributed to understanding and updating the national forest survey statistics. It is especially timely that this historical report should occur at the time the Forest Service just celebrated the anniversary of its 100 years of service to the American people."--Publisher's website.