Authors Background Acknowledgments User Guide UpdatesChanges from the Previous Database Version AbstractThis document is based on previous documentation of the nationally standardized Forest Inventory and Analysis database (Hansen and others 1992;Woudenberg and Farrenkopf 1995; Miles and others 2001; Woudenberg and others 2010). Documentation of the structure of the Forest Inventory and Analysis database (FIADB) for Phase 2 data, as well as codes and definitions, is provided. Examples for producing population-level estimates are also presented. This database provides a consistent framework for storing forest inventory data across all ownerships for the entire United States. These data are available to the public. Keywords:Forest Inventory and Analysis, inventory database, user manual, user guide, monitoringThe use of trade or firm names in this publication is for reader information and does not imply endorsement by the U.S. Department of Agriculture of any product or service. BackgroundThe Forest Inventory and Analysis (FIA) research program has been in existence since mandated by Congress in 1928. FIA's primary objective is to determine the extent, condition, volume, growth, and use of trees on the Nation's forest land. Before 1999, all inventories were conducted on a periodic basis. The passage of the 1998 Farm Bill requires FIA to collect data annually on plots within each State. This kind of up-to-date information is essential to frame realistic forest policies and programs. USDA Forest Service regional research stations are responsible for conducting these inventories and publishing summary reports for individual States.In addition to published reports, the Forest Service provides data collected in each inventory to those interested in further analysis. This report describes a standard format in which data can be obtained. This standard format, referred to as the Forest Inventory and Analysis Database (FIADB) structure, was developed to provide users with as much data as possible in a consistent manner among States. A number of inventories conducted prior to the implementation of the annual inventory are available in the FIADB. However, various data attributes may be empty or the items may have been collected or computed differently. Annual inventories use a common plot design and common data collection procedures nationwide, resulting in greater consistency among FIA work units than earlier inventories. Data field definitions note inconsistencies caused by different sampling designs and processing methods. AcknowledgmentsIn addition to those listed as authors, the following people provided additional contributions to this document: This particular document, version 6.0.2, has undergone some major updates and reorganization since version 6.0. Many of the updates were made to make this document more accessible to all users. Other changes to this document, such as the addition of hypertext links, are reflective of the ePUB environment and will allow users to quickly access particular section...

There are several new and imminent space-based sensors intended to support mapping of forest structure and biomass. These instruments, along with advancing cloud-based mapping platforms, will soon contribute to a proliferation of biomass maps. One means of differentiating the quality of different maps and estimation strategies will be comparison of results against independent field-based estimates at various scales. The Forest Inventory and Analysis Program of the US Forest Service (FIA) maintains a designed sample of uniformly measured field plots across the conterminous United States. This paper reports production of a map of statistical estimates of mean biomass, created at approximately the finest scale (64,000-hectare hexagons) allowed by FIA’s sample density. This map may be useful for assessing the accuracy of future remotely sensed biomass estimates. Equally important, fine-scale mapping of FIA estimates highlights several ways in which field- and remote sensing-based methods must be aligned to ensure comparability. For example, the biomass in standing dead trees, which may or may not be included in biomass estimates, represents a source of potential discrepancy that FIA shows to be particularly important in the Western US. Likewise, alternative allometric equations (which link measurable tree dimensions such as diameter to difficult-to-measure variables like biomass) strongly impact biomass estimates in ways that can vary over short distances. Potential mismatch in the conditions counted as forests also varies greatly over space. Field-to-map comparisons will ideally minimize these sources of uncertainty by adopting common allometry, carbon pools, and forest definitions. Our national hexagon-level benchmark estimates, provided in Supplementary Files, therefore addresses multiple pools and allometric approaches independently, while providing explicit forest area and uncertainty information. This range of information is intended to allow scientists to minimize potential discrepancies in support of unambiguous validation.

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The Forest Inventory and Analysis program (FIA) of the U.S. Forest Service monitors status and trends in forested ecoregions nationwide. The complex nature of this broad-scale, strategic-level inventory demands constant evolution and evaluation of methods to get the best information possible while continuously increasing efficiency. In 2004, the "Nevada Photo-Based Inventory Pilot" (NPIP) was launched and involved the acquisition and processing of large-scale aerial photography (LSP) throughout the State of Nevada. The over-arching goals of this pilot are to exceed information requirements, accelerate inventory timelines, and reduce inventory costs. Meeting these objectives requires the development of several complex and inter-related procedures, including photo-sampling protocol, statistical estimators, cover measurement techniques, and improved methods for mapping forest and nonforest attributes. This report documents the first of these procedures, the photo-sampling protocol for the NPIP project.