Kansas's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; W. Keith Moser; Charles J. Barnett

2011-01-01

The first full annual inventory of Kansas's forests was completed in 2005 after 8,868 plots were selected and 468 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of Kansas inventory is presented...

Advancements in LiDAR-based registration of FIA field plots

Treesearch

Demetrios Gatziolis

2012-01-01

Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for...

FIADB vegetation diversity and structure indicator (VEG)

Treesearch

Bethany K. Schulz; Kevin Dobelbower

2012-01-01

The Vegetation Diversity and Structure (VEG) Indicator is a suite of measurements including an inventory of vascular plants on an extensive systematic network of forest plots across the United States. This network is a subset of the standard forest inventory plots established by the U.S. Forest Service Forest Inventory and Analysis program. The VEG indicator provides...

Stocking, Forest Type, and Stand Size Class - The Southern Forest Inventory and Analysis Unit's Calculation of Three Important Stand Descriptors

Treesearch

Dennis M. May

1990-01-01

The procedures by which the Southern Forest Inventory and Analysis unit calculates stocking from tree data collected on inventory sample plots are described in this report. Stocking is then used to ascertain two other important stand descriptors: forest type and stand size class. Inventory data for three plots from the recently completed 1989 Tennessee survey are used...

Austrian National Forest Inventory: caught in the past and heading toward the future

Treesearch

Klemens Schadauer; Thomas Gschwantner; Karl Gabler

2007-01-01

The Austrian National Forest Inventory (AFI) started in 1961 on a temporary plot design with a systematic grid and a period of 10 years. For the first 30 years it was conducted as a continuous forest inventory. Since 1981 a permanent plot system has been used and the assessment period was reduced. Only slight changes in the plot design have occurred since the beginning...

An urban forest-inventory-and-analysis investigation in Oregon and Washington

Treesearch

Jacob L. Strunk; John R. Mills; Paul Ries; Hailemariam Temesgen; Lacey Jeroue

2016-01-01

The U.S. Department of Agriculture (USDA) Forest Service, Forest Inventory and Analysis program recently inventoried trees on 257 sample plots in the urbanized areas of Oregon and Washington. Plots were located on the standard grid (≈1 plot/2428 ha) and installed with the 4-subplot footprint (≈.067 ha with 4 circular subplots). Using these data, we examined: 1) use of...

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Estimating the number of tree species in forest populations using current vegetation survey and forest inventory and analysis approximation plots and grid intensities

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

We estimate number of tree species in National Forest populations using the nonparametric estimator. Data from the Current Vegetation Survey (CVS) of Region 6 of the USDA Forest Service were used to estimate the number of tree species with a plot close in size to the Forest Inventory and Analysis (FIA) plot and the actual CVS plot for the 5.5 km FIA grid and the 2.7 km...

Comparison of Imputation Procedures for Replacing Denied-access Plots

Treesearch

Susan L. King

2005-01-01

In forest inventories, missing plots are caused by hazardous terrain, inaccessible locations, or denied access. Maryland had a large number of denied-access plots in the latest periodic inventory conducted by the Northeastern Forest Inventory and Analysis unit. The denial pattern, which can introduce error into the estimates, was investigated by dropping the 1999...

New Method for Determining the Relative Stand Density of Forest Inventory Plots

Treesearch

Christopher W. Woodall; Patrick D. Miles

2006-01-01

Determining the relative density of Forest Inventory and Analysis plots is complicated by the various species and tree size combinations in the Nation?s forested ecosystems. Stand density index (SDI), although developed for use in even-aged monocultures, has been used for stand density assessment in largescale forest inventories. To improve application of SDI in uneven...

Prefield methods: streamlining forest or nonforest determinations to increase inventory efficiency

Treesearch

Sara Goeking; Gretchen Moisen; Kevin Megown; Jason Toombs

2009-01-01

Interior West Forest Inventory and Analysis has developed prefield protocols to distinguish forested plots that require field visits from nonforested plots that do not require field visits. Recent innovations have increased the efficiency of the prefield process. First, the incorporation of periodic inventory data into a prefield database increased the amount of...

FIA forest inventory data for wildlife habitat assessment

Treesearch

David C. Chojnacky

2000-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service maintains a network of permanent plots to monitor changing forest conditions. These plots were originally established to monitor the nation's timber supply; however, these data have great potential for evaluating other forest resources. To demonstrate a wildlife application, an assessment...

South Carolina, 2010 forest inventory and analysis factsheet

Treesearch

Roger C. Conner

2011-01-01

The Forest Inventory and Analysis (FIA) Program implemented a nationally consistent annual inventory system in 1998. Under the new design, one-fifth of all inventory plots in South Carolina are visited each year. The southern FIA unit, working cooperatively with South Carolina Forestry Commission crews, established the State’s initial annual inventory plots during the...

Adding uncertainty to forest inventory plot locations: effects on analyses using geospatial data

Treesearch

Alexia A. Sabor; Volker C. Radeloff; Ronald E. McRoberts; Murray Clayton; Susan I. Stewart

2007-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service alters plot locations before releasing data to the public to ensure landowner confidentiality and sample integrity, but using data with altered plot locations in conjunction with other spatially explicit data layers produces analytical results with unknown amounts of error. We calculated the...

Forest resources of the Clearwater National Forest

Treesearch

Ryan P. Hughes

2011-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Clearwater National Forest using a nationally standardized mapped-plot design (for more details see section "Inventory methods...

Forest resources of the Medicine Bow National Forest

Treesearch

Jim Steed

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Medicine Bow National Forest using a nationally standardized mapped-plot design (for more details see "Inventory methods"...

Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest.

PubMed

Levick, Shaun R; Hessenmöller, Dominik; Schulze, E-Detlef

2016-12-01

Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Estimation of wood volume from airborne LiDAR was most robust (R 2  = 0.92, RMSE = 50.57 m 3 ha -1  ~14.13 Mg C ha -1 ) when trained and tested with 1 ha experimental plot data (n = 50). Predictions based on a more extensive (n = 1100) plot network with considerably smaller (0.05 ha) plots were inferior (R 2  = 0.68, RMSE = 101.01 ~28.09 Mg C ha -1 ). Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R 2 and RMSE variability of the LiDAR-predicted wood volume model. Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We are moving into a forest management era where field-inventory and airborne LiDAR are inextricably linked, and we encourage field inventory campaigns to strive for increased plot size and give greater attention to precise stem geolocation for better integration with remote sensing strategies.

Towards a plot size for Canada's national forest inventory

Treesearch

Steen Magnussen; P. Boudewyn; M. Gillis

2000-01-01

A proposed national forest inventory for Canada is to report on the state and trends of resource attributes gathered mainly from aerial photos of sample plots located on a national grid. A pilot project in New Brunswick indicates it takes about 2,800 square 400-ha plots (10 percent inventoried) to achieve a relative standard error of 10 percent or less on 14 out of 17...

Forest resources of the Idaho Panhandle National Forest

Treesearch

Joshua C. Holte

2012-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Idaho Panhandle National Forest (IPNF) using a nationally standardized mapped-plot design (for more details see "The inventory...

Forest resources of the Black Hills National Forest

Treesearch

Larry T. DeBlander

2002-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Black Hills National Forest using a nationally standardized mapped-plot design (for more details see section "How was the inventory...

Forest resources of the Nez Perce National Forest

Treesearch

Michele Disney

2010-01-01

As part of a National Forest System cooperative inventory, the Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service conducted a forest resource inventory on the Nez Perce National Forest using a nationally standardized mapped-plot design (for more details see the section "Inventory methods"). This report presents highlights...

Forest resources of the Shoshone National Forest

Treesearch

James Menlove

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Shoshone National Forest using a nationally standardized mapped-plot design. This report presents the highlights of this 1999 inventory...

Redrawing the baseline: a method for adjusting biased historical forest estimates using a spatial and temporally representative plot network

Treesearch

Sara A. Goeking; Paul L. Patterson

2015-01-01

Users of Forest Inventory and Analysis (FIA) data sometimes compare historic and current forest inventory estimates, despite warnings that such comparisons may be tenuous. The purpose of this study was to demonstrate a method for obtaining a more accurate and representative reference dataset using data collected at co-located plots (i.e., plots that were measured...

Diameter Growth Models for Inventory Applications

Treesearch

Ronald E. McRoberts; Christopher W. Woodall; Veronica C. Lessard; Margaret R. Holdaway

2002-01-01

Distant-independent, individual-tree, diametar growth models were constructed to update information for forest inventory plots measured in previous years. The models are nonlinear in the parameters and were calibrated weighted nonlinear least squares techniques and forest inventory plot data. Analyses of residuals indicated that model predictions compare favorably to...

Forest Inventory and Analysis and Forest Health Monitoring: Piecing the Quilt

Treesearch

Joseph M. McCollum; Jamie K. Cochran

2005-01-01

Against the backdrop of a discussion about patchwork quilt assembly, the authors present background information on global grids. They show how to compose hexagons, an important task in systematically developing a subset of Forest Health Monitoring (FHM) Program plots from Forest Inventory and Analysis (FIA) plots. Finally, they outline the FHM and FIA grids, along with...

Land Use, Recreation, and Wildlife Habitats: GIS Applications Using FIA Plot Data

Treesearch

Victor A. Rudis

2001-01-01

Spatial contexts govern whether and how land is used. Forest surveys inventory land uses from sampled plots and provide common forest resource summaries with limited information about associated nearby uses, or the landscape context. I used the USDA Forest Service's Forest Inventory and Analysis program of the South-Central States survey region (Alabama, Arkansas...

North Dakota's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; David E. Haugen; Charles J. Barnett

2011-01-01

The first full annual inventory of North Dakota's forests was completed in 2005 after 7,622 plots were selected and 164 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the North Dakota...

South Dakota's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; Ronald J. Piva; Charles J. Barnett

2011-01-01

The first full annual inventory of South Dakota's forests was completed in 2005 after 8,302 plots were selected and 325 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the South Dakota...

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

Cooperative Alaska Forest Inventory

Treesearch

Thomas Malone; Jingjing Liang; Edmond C. Packee

2009-01-01

The Cooperative Alaska Forest Inventory (CAFI) is a comprehensive database of boreal forest conditions and dynamics in Alaska. The CAFI consists of field-gathered information from numerous permanent sample plots distributed across interior and south-central Alaska including the Kenai Peninsula. The CAFI currently has 570 permanent sample plots on 190 sites...

Assessing estimation techniques for missing plot observations in the U.S. forest inventory

Treesearch

Grant M. Domke; Christopher W. Woodall; Ronald E. McRoberts; James E. Smith; Mark A. Hatfield

2012-01-01

The U.S. Forest Service, Forest Inventory and Analysis Program made a transition from state-by-state periodic forest inventories--with reporting standards largely tailored to regional requirements--to a nationally consistent, annual inventory tailored to large-scale strategic requirements. Lack of measurements on all forest land during the periodic inventory, along...

Inventory of oaks on California's national forest lands

Treesearch

Thomas Gaman; Kevin Casey

2002-01-01

California has 18+ million acres of land owned by the USDA Forest Service. This is almost 20 percent of the area of the state. From 1994-2000 the Region 5 Remote Sensing Lab collected forest, vegetation and fuels inventory data from thousands of permanent monitoring plots established on diverse sites on Forest Service lands throughout the region. The plots are...

Patterns of exotic plant invasions in Pennsylvania's Allegheny National Forest using intensive Forest Inventory and Analysis plots

Treesearch

Cynthia D. Huebner; Randall S. Morin; Ann Zurbriggen; Robert L. White

2009-01-01

Intensive Forest Inventory and Analysis (FIA) plot data collected in the Allegheny National Forest (ANF), Pennsylvania, between 1999 and 2006 were evaluated for their ability to predict ANF's vulnerability to invasion by exotic plants. A total of 26 variables classified by biotic, abiotic, or disturbance characteristics were examined. Likelihood of colonization by...

Measurement repeatability of a large-scale inventory of forest fuels

Treesearch

J.A. Westfall; C.W. Woodall

2007-01-01

An efficient and accurate inventory of forest fuels at large scales is critical for assessment of forest fire hazards across landscapes. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of fuels along with blind remeasurement of a portion of inventory plots to monitor and improve data quality. The goal of this...

Compensating for missing plot observations inforest inventory estimation

Treesearch

Ronald E. McRoberts

2003-01-01

The Enhanced Forest Inventory and Analysis program of the U.S. Forest Service has established a nationwide array of permanent field plots, each representing approximately 2400 ha. Each plot has been assigned to one of five interpenetrating, nonoverlapping panels, with one panel selected for measurement on a rotating basis each year. As with most large surveys,...

Imputatoin and Model-Based Updating Technique for Annual Forest Inventories

Treesearch

Ronald E. McRoberts

2001-01-01

The USDA Forest Service is developing an annual inventory system to establish the capability of producing annual estimates of timber volume and related variables. The inventory system features measurement of an annual sample of field plots with options for updating data for plots measured in previous years. One imputation and two model-based updating techniques are...

A Simulation Algorithm to Approximate the Area of Mapped Forest Inventory Plots

Treesearch

William A. Bechtold; Naser E. Heravi; Matthew E. Kinkenon

2003-01-01

Calculating the area of polygons associated with mapped forest inventory plots can be mathematically cumbersome, especially when computing change between inventories. We developed a simulation technique that utilizes a computer-generated dot grid and geometry to estimate the area of mapped polygons within any size circle. The technique also yields a matrix of change in...

Forest resources of the Bighorn National Forest

Treesearch

Christopher Witt

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Bighorn National Forest (Bighorn) using a nationally standardized mapped-plot design. This report presents the highlights of this 2000...

Estimating down deadwood from FIA forest inventory variables in Maine

Treesearch

David C. Chojnacky; Linda S. Heath

2002-01-01

Down deadwood (DDW) is a carbon component important in the function and structure of forest ecosystems, but estimating DDW is problematic because these data are not widely available in forest inventory databases. However, DDW data were collected on USDA Forest Service Forest Inventory and Analysis (FIA) plots during Maine's 1995 inventory. This study examines ways...

Estimating down dead wood from FIA forest inventory variables in Maine

Treesearch

David C. Chojnacky; Linda S. Heath

2002-01-01

Down deadwood (DDW) is a carbon component important in the function and structure of forest ecosystems, but estimating DDW is problematic because these data are not widely available in forest inventory databases. However, DDW data were collected on USDA Forest Service Forest Inventory and Analysis (FIA) plots during Maine's 1995 inventory. This study examines ways...

Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM) data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/ forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest Inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM} data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

The new Brazilian national forest inventory

Treesearch

Joberto V. de Freitas; Yeda M. M. de Oliveira; Doadi A. Brena; Guilherme L.A. Gomide; Jose Arimatea Silva; < i> et al< /i>

2009-01-01

The new Brazilian national forest inventory (NFI) is being planned to be carried out through five components: (1) general coordination, led by the Brazilian Forest Service; (2) vegetation mapping, which will serve as the basis for sample plot location; (3) field data collection; (4) landscape data collection of 10 x 10-km sample plots, based on high-resolution...

Florida, 2011-forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Jarek Nowak

2013-01-01

Forest Inventory and Analysis (FIA) factsheets are produced periodically to keep the public up to date on the extent and condition of the forest lands in each State. The forestrelated estimates in the factsheets are based upon data collected from thousands of sample plots distributed across the landscape in a systematic manner. The total number of these plots is...

Forests of Michigan, 2013

Treesearch

Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in Michigan based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for current...

Forests of Vermont, 2013

Treesearch

Randall S. Morin; Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in Vermont based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for current...

Forests of New Hampshire, 2013

Treesearch

Randall S. Morin; Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in New Hampshire based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for...

A technique for identifying treatment opportunities from western Oregon and Washington forest survey plots.

Treesearch

Colin D. MacLean

1980-01-01

Identification of opportunities for silvicultural treatment from inventory data is an important objective of Renewable Resources Evaluation in the Pacific Northwest. This paper describes the field plot design and data analysis procedure used by what used to be known as Forest Survey to determine the treatment opportunity associated with each inventory plot in western...

The status of accurately locating forest inventory and analysis plots using the Global Positioning System

Treesearch

Michael Hoppus; Andrew Lister

2007-01-01

Historically, field crews used Global Positioning System (GPS) coordinates to establish and relocate plots, as well as document their general location. During the past 5 years, the increase in Geographic Information System (GIS) capabilities and in customer requests to use the spatial relationships between Forest Inventory and Analysis (FIA) plot data and other GIS...

Plot intensity and cycle-length effects on growth and removals estimates from forest inventories

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2015-01-01

Continuous forest inventory planners can allocate the budget to more plots per acre or a shorter remeasurement cycle. A higher plot intensity benefits small area estimation and allows for more precision in current status estimates. Shorter cycles may provide better estimates of growth, removals and mortality. On a fixed budget, the planner can't have both greater...

The National Inventory of Down Woody Materials: Methods, Outputs, and Future Directions

Treesearch

Christopher W. Woodall

2003-01-01

The Forest Inventory and Analysis Program (FIA) of the USDA Forest Service conducts a national inventory of forests of the United States. A subset of FIA permanent inventory plots are sampled every year for numerous forest health indicators ranging fiom soils to understory vegetation. Down woody material (DWM) is an FIA indicator that refines estimation of forest...

Accuracy assessment of biomass and forested area classification from modis, landstat-tm satellite imagery and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2007-01-01

The objective of this study was to determine how well forestfnon-forest and biomass classifications obtained from Landsat-TM and MODIS satellite data modeled with FIA plots, compare to each other and with forested area and biomass estimates from the national inventory data, as well as whether there is an increase in overall accuracy when pixel size (spatial resolution...

Estimating and circumventing the effects of perturbing and swapping inventory plot locations

Treesearch

Ronald E. McRoberts; Geoffrey R. Holden; Mark D. Nelson; Greg C. Liknes; Warren K. Moser; Andrew J. Lister; Susan L. King; Elizabeth B. LaPoint; John W. Coulston; W. Brad Smith; Gregory A. Reams

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service reports data and information about the Nation's forest resources. Increasingly, users request that FIA data and information be reported and distributed in a geospatial context, and they request access to exact plot locations for their own analyses. However, the FIA program is constrained by...

Use of FVS for a forest-wide inventory on the Spokane Indian Reservation

Treesearch

Ted Hensold

2008-01-01

The Forest Vegetation Simulator (FVS) was used with Continuous Forest Inventory (CFI) data on the Spokane Indian Reservation to provide predicted yields over a 100-year period for 994 1/5 acre plots. The plots were grouped into five strata based on habitat type groupings, projected separately, and the stratum results were combined after processing. Results from the...

Evaluating the potential of structure from motion technology for forest inventory data collection

Treesearch

Demetrios Gatziolis

2015-01-01

Since the inception of its annual plot design, the Forest Inventory and Analysis (FIA) Program of the USDA Forest Service has integrated into its data collection operations elements of digital technology, including data loggers, laser distance recorders and clinometers, and GPS devices. Data collected with the assistance of this technology during a typical plot visit...

Using Forest Service multiple species inventory and monitoring protocols to count birds at forest inventory and analysis plots on the Caribbean landscape: results, observations, and challenges from year 1 of a 2-year study

Treesearch

Sonja N. Oswalt; Thomas J. Brandeis; David W. Steadman; Scott K. Robinson

2009-01-01

We conducted double-observer point counts of birds from December 3 to December 31, 2005, on preestablished permanent Forest Inventory and Analysis (FIA) plots and National Park Service System trails within the Virgin Islands National Park, St. John, U.S. Virgin Islands. We had three objectives: (1) to collect abundance and distribution data for wintering land birds,...

Using publically available forest inventory data in climate-based modes of tree species distribution: Examining effects of true versus altered location coordinates

Treesearch

Jacob Gibson; Gretchen Moisen; Tracey Frescino; Thomas C. Edwards

2013-01-01

Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J....

Estimating forest conversion rates with annual forest inventory data

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2009-01-01

The rate of land-use conversion from forest to nonforest or natural forest to forest plantation is of interest for forest certification purposes and also as part of the process of assessing forest sustainability. Conversion rates can be estimated from remeasured inventory plots in general, but the emphasis here is on annual inventory data. A new estimator is proposed...

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

Effects of plot size on forest-type algorithm accuracy

Treesearch

James A. Westfall

2009-01-01

The Forest Inventory and Analysis (FIA) program utilizes an algorithm to consistently determine the forest type for forested conditions on sample plots. Forest type is determined from tree size and species information. Thus, the accuracy of results is often dependent on the number of trees present, which is highly correlated with plot area. This research examines the...

Strategies for Preserving Owner Privacy in the National Information Management System of the USDA Forest Service's Forest Inventory and Analysis Unit

Treesearch

Andrew Lister; Charles Scott; Susan King; Michael Hoppus; Brett Butler; Douglas Griffith

2005-01-01

The Food Security Act of 1985 prohibits the disclosure of any information collected by the USDA Forest Service's FIA program that would link individual landowners to inventory plot information. To address this, we developed a technique based on a "swapping" procedure in which plots with similar characteristics are exchanged, and on a ...

Modeling post-fire woody carbon dynamics with data from remeasured inventory plots

Treesearch

Bianca N.I. Eskelson; Jeremy Fried; Vicente Monleon

2015-01-01

In California, the Forest Inventory and Analysis (FIA) plots within large fires were visited one year after the fire occurred resulting in a time series of measurements before and after fire. During this additional plot visit, the standard inventory measurements were augmented for these burned plots to assess fire effects. One example of the additional measurements is...

Statistics and quality assurance for the Northern Research Station Forest Inventory and Analysis Program, 2016

Treesearch

Dale D. Gormanson; Scott A. Pugh; Charles J. Barnett; Patrick D. Miles; Randall S. Morin; Paul A. Sowers; Jim Westfall

2017-01-01

The U.S. Forest Service Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. FIA's primary objective is to determine the extent, condition, volume, growth, and use of trees on the Nation's forest land through a comprehensive inventory and analysis of the Nation's forest resources. The...

Evaluating Plot Designs for the Tropics

Treesearch

Paul C. van Deusen; Bruce Bayle

1991-01-01

Theory and procedures are reviewed for determining the best type of plot for a given forest inventory. A general methodology is given that clarifies the relationship between different plot designs and the associated methods to produce the inventory estimates.

A technique for conducting point pattern analysis of cluster plot stem-maps

Treesearch

C.W. Woodall; J.M. Graham

2004-01-01

Point pattern analysis of forest inventory stem-maps may aid interpretation and inventory estimation of forest attributes. To evaluate the techniques and benefits of conducting point pattern analysis of forest inventory stem-maps, Ripley`s K(t) was calculated for simulated tree spatial distributions and for over 600 USDA Forest Service Forest...

Forest inventory and management-based visual preference models of southern pine stands

Treesearch

Victor A. Rudis; James H. Gramann; Edward J. Ruddell; Joanne M. Westphal

1988-01-01

Statistical models explaining students' ratings of photographs of within stand forest scenes were constructed for 99 forest inventory plots in east Texas pine and oak-pine forest types. Models with parameters that are sensitive to visual preference yet compatible with forest management and timber inventories are presented. The models suggest that the density of...

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

The role of pre-field operations at four forest inventory units: We can see the trees, not just the forest

Treesearch

Sara A. Goeking; Greg C. Liknes

2009-01-01

The Forest Inventory and Analysis (FIA) program attempts to inventory all forested lands throughout the United States. Each of the four FIA units has developed a process to minimize inventory costs by refraining from visiting those plots in the national inventory grid that are undoubtedly nonforest. We refer to this process as pre-field operations. Until recently, the...

Optimizing variable radius plot size and LiDAR resolution to model standing volume in conifer forests

Treesearch

Ram Kumar Deo; Robert E. Froese; Michael J. Falkowski; Andrew T. Hudak

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

PubMed Central

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). PMID:23305341

Assessing the effect of snow/water obstructions on the measurement of tree seedlings in a large-scale temperate forest inventory

Treesearch

C.W. Woodall; J.A. Westfall; K. Zhu; D.J. Johnson

2013-01-01

National-scale forest inventories have endeavoured to include holistic measurements of forest health inclusive of attributes such as downed dead wood and tree regeneration that occur in the forest understory. Inventories may require year-round measurement of inventory plots with some of these measurements being affected by seasonal obstructions (e.g. snowpacks and...

Estimating mapped-plot forest attributes with ratios of means

Treesearch

S.J. Zarnoch; W.A. Bechtold

2000-01-01

The mapped-plot design utilized by the U.S. Department of Agriculture (USDA) Forest Inventory and Analysis and the National Forest Health Monitoring Programs is described. Data from 2458 forested mapped plots systematically spread across 25 States reveal that 35 percent straddle multiple conditions. The ratio-of-means estimator is developed as a method to obtain...

Where are the Black Walnut Trees in Michigan? 1995

Treesearch

J. Michael Vasievich; Neal P. Kingsley

1995-01-01

The latest Michigan forest inventory was completed in 1993 by the North Central Forest Experiment Station and the Michigan DNR, Forest Management Division. In total, 18,484 sample points were examined on aerial photographs to identify ground sample plots. Of these, 10,849 forest plots were visited and measured on the ground by field crews. These plot measurements...

A novel statistical methodology to overcome sampling irregularities in the forest inventory data and to model forest changes under dynamic disturbance regimes

Treesearch

Nikolay Strigul; Jean Lienard

2015-01-01

Forest inventory datasets offer unprecedented opportunities to model forest dynamics under evolving environmental conditions but they are analytically challenging due to irregular sampling time intervals of the same plot, across the years. We propose here a novel method to model dynamic changes in forest biomass and basal area using forest inventory data. Our...

Attributes of down woody materials in hardwood forests of the Eastern United States

Treesearch

Christopher W. Woodall; Sonja N. Oswalt; Randall S. Morin

2007-01-01

The Forest Inventory and Analysis Program (FIA) of the USDA Forest Service conducts a national inventory of down woody materials (DWM) on forestland in the United States. Estimates of DWM for inventory plots occurring in eastern U.S. hardwood forests facilitate large-scale assessment of hardwood forest fuel loadings and wildlife habitat. Therefore, the objectives of...

Bridging the gap between strategic and management forest inventories

Treesearch

Ronald E. McRoberts

2009-01-01

Strategic forest inventory programs collect information for a large number of variables on a relatively sparse array of field plots. Data from these inventories are used to produce estimates for large areas such as states and provinces, regions, or countries. The purpose of management forest inventories is to guide management decisions for small areas such as stands....

Tree-level imputation techniques to estimate current plot-level attributes in the Pacific Northwest using paneled inventory data

Treesearch

Bianca Eskelson; Temesgen Hailemariam; Tara Barrett

2009-01-01

The Forest Inventory and Analysis program (FIA) of the US Forest Service conducts a nationwide annual inventory. One panel (20% or 10% of all plots in the eastern and western United States, respectively) is measured each year. The precision of the estimates for any given year from one panel is low, and the moving average (MA), which is considered to be the default...

Improving Forest Inventory and Analysis efficiency with common land unit information

Treesearch

Greg C. Liknes; Mark D. Nelson

2009-01-01

The Forest Service, U.S. Department of Agriculture's (USDA's) Northern Research Station Forest Inventory and Analysis program (NRS-FIA) examines inventory locations on digital aerial imagery to determine if the land use at each plot location meets the FIA definition of forest and thereby becomes a field visit site. This manual image-interpretation effort...

Forests of Maryland, 2016

Treesearch

Tonya W. Lister

2017-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory measuring data on 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle...

Forests of Delaware, 2015

Treesearch

Tonya Lister; Richard Widmann

2016-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Forests of Maryland, 2015

Treesearch

Tonya Lister; Richard Widmann

2016-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory, measuring 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle,...

Forests of Delaware, 2016

Treesearch

Stephen Potter

2017-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Crown-condition classification: a guide to data collection and analysis

Treesearch

Michael E. Schomaker; Stanley J. Zarnoch; William A. Bechtold; David J. Latelle; William G. Burkman; Susan M. Cox

2007-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S. Department of Agriculture, conducts a national inventory of forests across the United States. A systematic subset of permanent inventory plots in 38 States is currently sampled every year for numerous forest health indicators. One of these indicators, crown-condition classification, is designed...

Forests of Delaware, 2014

Treesearch

T.W. Lister; R.H. Widmann

2015-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Forests of Maryland, 2014

Treesearch

T.W. Lister; R.H. Widmann

2015-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory measuring data on 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle...

The effect of blurred plot coordinates on interpolating forest biomass: a case study

Treesearch

J. W. Coulston

2004-01-01

Interpolated surfaces of forest attributes are important analytical tools and have been used in risk assessments, forest inventories, and forest health assessments. The USDA Forest Service Forest Inventory and Analysis program (FIA) annually collects information on forest attributes in a consistent fashion nation-wide. Users of these data typically perform...

Weighted analysis methods for mapped plot forest inventory data: Tables, regressions, maps and graphs

Treesearch

Paul C. Van Deusen; Linda S. Heath

2010-01-01

Weighted estimation methods for analysis of mapped plot forest inventory data are discussed. The appropriate weighting scheme can vary depending on the type of analysis and graphical display. Both statistical issues and user expectations need to be considered in these methods. A weighting scheme is proposed that balances statistical considerations and the logical...

Vision for the Future of FIA: Paean to Progress, Possibilities, and Partners

Treesearch

Susan L. King; Charles T. Scott

2006-01-01

The Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture Forest Service has made significant progress implementing the annualized inventory in 46 States in 2004. Major increases in program performance included the availability of plot data and the plots? corresponding approximate coordinates. A mill site study and biomass models were used...

Wisconsin's forest, 2004: statistics and quality assurance

Treesearch

Mark H. Hansen; Charles H. Perry; Gary Brand; Ronald E. McRoberts

2008-01-01

The first full, annualized inventory of Wisconsin's forests was completed in 2004 after 6,478 forested plots were visited. An earlier publication summarized the results and presented issue - driven analyses (Perry et al. 2008) . This report includes detailed information on forest inventory methods...

Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

Treesearch

Jacob L. Strunk; Peter J. Gould

2015-01-01

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Sampling protocol, estimation, and analysis procedures for the down woody materials indicator of the FIA program

Treesearch

Christopher Woodall

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of forests of the United States. A subset of FIA permanent inventory plots are sampled every year for numerous indicators of forest health ranging from soils to understory vegetation. Down woody material (DWM) is an FIA indicator that provides estimates of forest...

The enhanced forest inventory and analysis program of the USDA forest service: historical perspective and announcements of statistical documentation

Treesearch

Ronald E. McRoberts; William A. Bechtold; Paul L. Patterson; Charles T. Scott; Gregory A. Reams

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service has initiated a transition from regional, periodic inventories to an enhanced national FIA program featuring annual measurement of a proportion of plots in each state, greater national consistency, and integration with the ground sampling component of the Forest Health Monitoring (FHM) program...

Diameter Growth Models Using Minnesota Forest Inventory and Analysis Data

Treesearch

Veronica C. Lessard; Ronald E. McRoberts; Margaret R. Holdaway

2001-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service North Central Research Station (NCRS) has begun replacing the 12-to 13-yr periodic inventory cycles for the states in the North Central region with annual inventories featuring measurement of approximately 20% of all plots in each of the 11 states each year. State reports on summaries of the...

Forests of Wisconsin, 2016

Treesearch

Cassandra M. Kurtz

2017-01-01

Publication updated February 9, 2018 to correct the number of forest field plots (page 1). This resource update provides an overview of forest resources in Wisconsin based on an inventory conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program at the Northern Research Station in cooperation with the Wisconsin Department of...

Spatially Locating FIA Plots from Pixel Values

Treesearch

Greg C. Liknes; Geoffrey R. Holden; Mark D. Nelson; Ronald E. McRoberts

2005-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program is required to ensure the confidentiality of the geographic locations of plots. To accommodate user requests for data without releasing actual plot coordinates, FIA creates overlays of plot locations on various geospatial data, including satellite imagery. Methods for reporting pixel values associated...

Forest/non-forest mapping using inventory data and satellite imagery

Treesearch

Ronald E. McRoberts

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

Integrating P3 Data Into P2 Analyses: What is the Added Value

Treesearch

James R. Steinman

2001-01-01

The Forest Inventory and Analysis and Forest Health Monitoring Programs of the USDA Forest Service are integrating field procedures for measuring their networks of plots throughout the United States. These plots are now referred to as Phase 2 (P2) and Phase 3 (P3) plots, respectively, and 1 out of every 16 P2 plots will also be a P3 plot. Mensurational methods will be...

Statistics and quality assurance for the Northern Research Station Forest Inventory and Analysis Program

Treesearch

Dale D. Gormanson; Scott A. Pugh; Charles J. Barnett; Patrick D. Miles; Randall S. Morin; Paul A. Sowers; James A. Westfall

2018-01-01

The U.S. Forest Service Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. FIA’s primary objective is to determine the extent, condition, volume, growth, and use of trees on the Nation’s forest land through a comprehensive inventory and analysis of the Nation’s forest resources. The FIA program...

Assessing biomass and forest area classifications from modis satellite data while incrementing the number of FIA data panels

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2005-01-01

Our objective was to determine at what level biomass and forest area obtained from 2, 3, 4, or 5 panels of forest inventory data compares well with forested area and biomass estimates from the national inventory data. A subset of 2605 inventory plots (100% forested, 100% non-forested) was used to classify the land cover and model the biomass in South Carolina. Mixed...

The AFIS tree growth model for updating annual forest inventories in Minnesota

Treesearch

Margaret R. Holdaway

2000-01-01

As the Forest Service moves towards annual inventories, states may use model predictions of growth to update unmeasured plots. A tree growth model (AFIS) based on the scaled Weibull function and using the average-adjusted model form is presented. Annual diameter growth for four species was modeled using undisturbed plots from Minnesota's Aspen-Birch and Northern...

Abundance and characteristics of snags in western Montana forests

Treesearch

Richard B. Harris

1999-01-01

Plot data from the U.S. Forest Service's Forest Inventory and Analysis program was used to characterize the abundance and selected characteristics of snags from forests in western Montana. Plots were grouped by whether they had a history of timber harvest, and the U.S. Forest Service classifications of forest type, habitat type, and potential vegetation group were...

Forests of Illinois, 2017

Treesearch

Susan J. Crocker

2018-01-01

This update provides an overview of forest resources in Illinois following an inventory by the USDA Forest Service, Forest Inventory and Analysis program, Northern Research Station. Estimates are derived from field data collected using an annualized sample design. Current variable estimates such as area and volume are based on 5,994 (1,046 forested) plots measured in...

Volume equations for the Northern Research Station's Forest Inventory and Analysis Program as of 2010

Treesearch

Patrick D. Miles; Andrew D. Hill

2010-01-01

The U.S. Forest Service's Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. This report documents the methodology used to estimate live-tree gross, net, and sound volume for the 24 States inventoried by the Northern Research Station's (NRS) FIA unit. Sound volume is of particular interest...

Forest Inventory and Analysis Database of the United States of America (FIA)

Treesearch

Andrew N. Gray; Thomas J. Brandeis; John D. Shaw; William H. McWilliams; Patrick Miles

2012-01-01

Extensive vegetation inventories established with a probabilistic design are an indispensable tool in describing distributions of species and community types and detecting changes in composition in response to climate or other drivers. The Forest Inventory and Analysis Program measures vegetation in permanent plots on forested lands across the United States of America...

Preliminary Results of Double-Sample Forest Inventory of Pine and Mixed Stands with High- and Low-Density LiDAR

Treesearch

Robert C. Parker; Patrick A. Glass

2004-01-01

LiDAR data (0.5 and 1 m postings) were used in a double-sample forest inventory on the Lee Experimental Forest, Louisiana. Phase 2 plots were established with DGPS. Tree d.b.h. (> 4.5 inches) and two sample heights were measured on every 10 th plot of the Phase 1 sample. Volume was computed for natural and planted pine and mixed hardwood species. LiDAR trees were...

The poor man's Geographic Information System: plot expansion factors

Treesearch

Paul C. Van Deusen

2007-01-01

Plot expansion factors can serve as a crude Geographic Information System for users of Forest Inventory and Analysis (FIA) data. Each FIA plot has an associated expansion factor that is often interpreted as the number of forested acres that the plot represents. The derivation of expansion factors is discussed and it is shown that the mapped plot design requires a...

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Forest Resources of East Oklahoma, 2008

Treesearch

Richard A. Harper; Tony G. Johnson

2012-01-01

The Forest Inventory and Analysis Program conducted the seventh survey of east Oklahoma forests. This was the establishment of the annual plot methodology and closeout of the prism remeasurement plots. Forest land area remained stable at 5.7 million acres and covered almost 57 percent of the land area. About 5.1 million acres of forest land was considered timberland...

Evaluating kriging as a tool to improve moderate resolution maps of forest biomass

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen

2007-01-01

The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We...

Using SaTScanTM spatial-scan software with national forest inventory data: a case study in South Carolina

Treesearch

KaDonna Randolph

2017-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program makes and keeps current an inventory of all forest land in the United States. To comply with privacy laws while at the same time offering its data to the public, FIA makes approximate plot locations available through a process known as perturbing ("fuzzing") and swapping. The free spatial...

Determining stocking, forest type and stand-size class from forest inventory data

Treesearch

Mark H. Hansen; Jerold T. Hahn

1992-01-01

This paper describes the procedures used by North Central Forest Experiment Station's Forest Inventory and Analysis Work Unit (NCFIA) in determining stocking, forest type, and stand-size class. The stocking procedure assigns a portion of the stocking to individual trees measured on NCFIA 10-point field plots. Stand size and forest type are determined as functions...

Assessing the Effects of Forest Fragmentation Using Satellite Imagery and Forest Inventory Data

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2005-01-01

For a study area in the North Central region of the USA, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and forest attributes observed on...

The Finnish national forest inventory

Treesearch

Erkki Tomppo

2009-01-01

The National Forest Inventory (NFI) of Finland has produced large-area forest resource information since the beginning of 1920s (Ilvessalo 1927). When the 10th inventory (NFI10) started in 2004, the design was changed and the rotation shortened to 5 years. Measurements are done in the entire country each year through measuring one-fifth of the plots. About one-fifth of...

An investigation of condition mapping and plot proportion calculation issues

Treesearch

Demetrios Gatziolis

2007-01-01

A systematic examination of Forest Inventory and Analysis condition data collected under the annual inventory protocol in the Pacific Northwest region between 2000 and 2004 revealed the presence of errors both in condition topology and plot proportion computations. When plots were compiled to generate population estimates, proportion errors were found to cause...

Measurement of forest disturbance and regrowth with Landsat and forest inventory and analysis data: anticipated benefits from forest and inventory analysis' collaboration with the national aeronautics and space administration and university partners

Treesearch

Sean Healey; Gretchen Moisen; Jeff Masek; Warren Cohen; Sam Goward; < i> et al< /i>

2007-01-01

The Forest Inventory and Analysis (FIA) program has partnered with researchers from the National Aeronautics and Space Administration, the University of Maryland, and other U.S. Department of Agriculture Forest Service units to identify disturbance patterns across the United States using FIA plot data and time series of Landsat satellite images. Spatially explicit...

Basic truths for planning and executing an inventory

Treesearch

2000-01-01

A number of basic truths are presented. The importance of carefully developing the objectives for an inventory is stressed. The use of permanent plots and temporary plots is covered. The necessity of obtaining a representative sample, training effectively, and collecting quality data is discussed. The future direction for forest inventories is suggested.

Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

USGS Publications Warehouse

Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

2013-01-01

Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

Florida's forests-2005 update

Treesearch

Mark J. Brown

2007-01-01

This bulletin highlights principal findings of an annual inventory of Florida's forests. Data summaries are based on measurements of 60 percent of the plots in the State. Additional data summaries and bulletins will be published as the remaining plots are measured.

Annual design-based estimation for the annualized inventories of forest inventory and analysis: sample size determination

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

The Forest Inventory and Analysis units in the USDA Forest Service have been mandated by Congress to go to an annualized inventory where a certain percentage of plots, say 20 percent, will be measured in each State each year. Although this will result in an annual sample size that will be too small for reliable inference for many areas, it is a sufficiently large...

Progress in adapting k-NN methods for forest mapping and estimation using the new annual Forest Inventory and Analysis data

Treesearch

Reija Haapanen; Kimmo Lehtinen; Jukka Miettinen; Marvin E. Bauer; Alan R. Ek

2002-01-01

The k-nearest neighbor (k-NN) method has been undergoing development and testing for applications with USDA Forest Service Forest Inventory and Analysis (FIA) data in Minnesota since 1997. Research began using the 1987-1990 FIA inventory of the state, the then standard 10-point cluster plots, and Landsat TM imagery. In the past year, research has moved to examine...

Delaware Forests 2013

Treesearch

Tonya W. Lister; Brett J. Butler; Susan J. Crocker; Cassandra M. Kurtz; Andrew J. Lister; William G. Luppold; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Ronald J. Piva; Rachel I. Riemann; James E. Smith; James A. Westfall; Richard H. Widmann; Christopher W. Woodall

2017-01-01

This report summarizes the 2013 results of the annualized inventory of Delaware’s forests conducted by the U.S. Forest Service, Forest Inventory and Analysis program. Results are based on data collected from 389 plots located across the State. There are an estimated 362,000 acres of forest land in Delaware with a total live- tree volume of 936 million cubic feet. There...

A Comparison of Various Estimators for Updating Forest Area Coverage Using AVHRR and Forest Inventory Data

Treesearch

Francis A. Roesch; Paul C. van Deusen; Zhiliang Zhu

1995-01-01

Various methods of adjusting low-cost and possibly biased estimates of percent forest coverage from AVHRR data with a subsample of higher-cost estimates from the USDA Forest Service's Forest Inventory and Analysis plots were investigated. Two ratio and two regression estimators were evaluated. Previous work (Zhu and Teuber, 1991) finding that the estimates from...

Procedures to handle inventory cluster plots that straddle two or more conditions

Treesearch

Jerold T. Hahn; Colin D. MacLean; Stanford L. Arner; William A. Bechtold

1995-01-01

We review the relative merits and field procedures for four basic plot designs to handle forest inventory plots that straddle two or more conditions, given that subplots will not be moved. A cluster design is recommended that combines fixed-area subplots and variable-radius plot (VRP) sampling. Each subplot in a cluster consists of a large fixed-area subplot for...

Conterminous U.S. and Alaska Forest Type Mapping Using Forest Inventory and Analysis Data

Treesearch

B. Ruefenacht; M.V. Finco; M.D. Nelson; R. Czaplewski; E.H. Helmer; J. A. Blackard; G.R. Holden; A.J. Lister; D. Salajanu; D. Weyermann; K. Winterberger

2008-01-01

Classification-trees were used to model forest type groups and forest types for the conterminous United States and Alaska. The predictor data were a geospatial data set with a spatial resolution of 250 m developed by the U.S. Department of Agriculture Forest Service (USFS). The response data were plot data from the USFS Forest Inventory and Analysis program. Overall...

Current forest and woodland carbon storage and flux in California: An estimate for the 2010 statewide assessment

Treesearch

Timothy A. Robards

2012-01-01

This study used USDA Forest Service Forest Inventory and Analysis (FIA) plot data, forest growth models, wildland fire emission estimates and timber harvest data to estimate the live tree carbon storage and flux of California's forests and woodlands. Approximately 30 Tg C02e per year was estimated as the annual flux for all California forests. The forest inventory...

Modeled forest inventory data suggest climate benefits from fuels management

Treesearch

Jeremy S. Fried; Theresa B. Jain; Jonathan. Sandquist

2013-01-01

As part of a recent synthesis addressing fuel management in dry, mixed-conifer forests we analyzed more than 5,000 Forest Inventory and Analysis (FIA) plots, a probability sample that represents 33 million acres of these forests throughout Washington, Oregon, Idaho, Montana, Utah, and extreme northern California. We relied on the BioSum analysis framework that...

Precise FIA plot registration using field and dense LIDAR data

Treesearch

Demetrios Gatziolis

2009-01-01

Precise registration of forest inventory and analysis (FIA) plots is a prerequisite for an effective fusion of field data with ancillary spatial information, which is an approach commonly employed in the mapping of various forest parameters. Although the adoption of Global Positioning System technology has improved the precision of plot coordinates obtained during...

Updating older forest inventory data with a growth model and satellite records to improve the responsiveness and currency of national carbon monitoring

NASA Astrophysics Data System (ADS)

Healey, S. P.; Zhao, F. R.; McCarter, J. B.; Frescino, T.; Goeking, S.

2017-12-01

International reporting of American forest carbon trends depends upon the Forest Service's nationally consistent network of inventory plots. Plots are measured on a rolling basis over a 5- to 10-year cycle, so estimates related to any variable, including carbon storage, reflect conditions over a 5- to 10-year window. This makes it difficult to identify the carbon impact of discrete events (e.g., a bad fire year; extraction rates related to home-building trends), particularly if the events are recent.We report an approach to make inventory estimates more sensitive to discrete and recent events. We use a growth model (the Forest Vegetation Simulator - FVS) that is maintained by the Forest Service to annually update the tree list for every plot, allowing all plots to contribute to a series of single-year estimates. Satellite imagery from the Landsat platform guides the FVS simulations by providing information about which plots have been disturbed, which are recovering from disturbance, and which are undergoing undisturbed growth. The FVS model is only used to "update" plot tree lists until the next field measurement is made (maximum of 9 years). As a result, predicted changes are usually small and error rates are low. We present a pilot study of this system in Idaho, which has experienced several major fire events in the last decade. Empirical estimates of uncertainty, accounting for both plot sampling error and FVS model error, suggest that this approach greatly increases temporal specificity and sensitivity to discrete events without sacrificing much estimate precision at the level of a US state. This approach has the potential to take better advantage of the Forest Service's rolling plot measurement schedule to report carbon storage in the US, and it offers the basis of a system that might allow near-term, forward-looking analysis of the effects of hypothetical forest disturbance patterns.

Comparison of three annual inventory designs, a periodic design, and a midcycle design

Treesearch

Stanford L. Arner

2000-01-01

Three annual inventory designs, a periodic design, and a periodic measurement with midcycle update design are compared using a population created from 14,754 remeasured Forest Inventory and Analysis plots. Two of the annual designs and the midcycle update design allow updating of plots using sampling with partial replacement procedures. Individual year and moving...

Estimating Uncertainty in Annual Forest Inventory Estimates

Treesearch

Ronald E. McRoberts; Veronica C. Lessard

1999-01-01

The precision of annual forest inventory estimates may be negatively affected by uncertainty from a variety of sources including: (1) sampling error; (2) procedures for updating plots not measured in the current year; and (3) measurement errors. The impact of these sources of uncertainty on final inventory estimates is investigated using Monte Carlo simulation...

Inventory-based landscape-scale simulation of management effectiveness and economic feasibility with BioSum

Treesearch

Jeremy S. Fried; Larry D. Potts; Sara M. Loreno; Glenn A. Christensen; R. Jamie Barbour

2017-01-01

The Forest Inventory and Analysis (FIA)-based BioSum (Bioregional Inventory Originated Simulation Under Management) is a free policy analysis framework and workflow management software solution. It addresses complex management questions concerning forest health and vulnerability for large, multimillion acre, multiowner landscapes using FIA plot data as the initial...

Down woody material, soil and tree core collection and analysis from the 2014 Tanana pilot plots

Treesearch

Robert R. Pattison; Andrew N. Gray; Patrick F. Sullivan; Kristen L. Manies

2015-01-01

In the summer of 2014 the US Forest Service’s Forest Inventory and Analysis (FIA) Program of the Pacific Northwest (PNW) Research Station in conjunction with NASA Goddard carried out a pilot inventory of the forests of interior Alaska. This inventory was conducted on the State of Alaska’s Tanana Valley State Forest and on the Tetlin National Wildlife Refuge. As part of...

Models for estimation and simulation of crown and canopy cover

Treesearch

John D. Shaw

2005-01-01

Crown width measurements collected during Forest Inventory and Analysis and Forest Health Monitoring surveys are being used to develop individual tree crown width models and plot-level canopy cover models for species and forest types in the Intermountain West. Several model applications are considered in the development process, including remote sensing of plot...

Oregon’s forest resources, 2001–2010: ten-year Forest Inventory and Analysis report

Treesearch

Sheel Bansal; Leslie Brodie; Sharon Stanton; Karen Waddell; Marin Palmer; Glenn Christensen; Olaf Kuegler; John Chase; Joel Thompson; Sarah Jovan; Andrew Gray; Morgan Todd

2017-01-01

This report highlights key findings from a comprehensive vegetation survey of all forested land across the state of Oregon. A total of 5,180 forested field plots in Oregon were visited by Forest Inventory and Analysis (FIA) crews over a 10-year period from 2001 to 2010. Oregon has 30 million acres of forest, covering nearly half the state. The structure and composition...

Errors in terrain-based model preditions caused by altered forest inventory plot locations in the Southern Appalachian Mountains, USA.

Treesearch

Huei-Jin Wang; Stephen Prisley; Philip Radtke; John Coulston

2012-01-01

Forest modeling applications that cover large geographic area can benefit from the use of widely-held knowledge about relationships between forest attributes and topographic variables. A noteworthy example involved the coupling of field survey data from the Forest Inventory Analysis (FIA) program of USDA Forest Service with digital elevation model (DEM) data in...

An assessment of autumn olive in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2016-01-01

This publication is part of a series of research notes that provide an overview of the invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by...

An assessment of nonnative bush honeysuckle in northern U.S. forests

Treesearch

Cassandra Kurtz; M.H. Hansen

2015-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by NRS...

An assessment of common buckthorn in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2018-01-01

This publication is part of a series of that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the USDA Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by...

An assessment of Japanese honeysuckle in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2015-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by NRS...

An assessment of garlic mustard in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2014-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by FIA...

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S. Forest Service Forest Inventory and Analysis data

Treesearch

Todd A. Schroeder; Sean P. Healey; Gretchen G. Moisen; Tracey S. Frescino; Warren B. Cohen; Chengquan Huang; Robert E. Kennedy; Zhiqiang Yang

2014-01-01

With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these...

Analysis of down wood volme and percent ground cover for the Missouri Ozark forest ecosystem project

Treesearch

Laura A. Herbeck

2000-01-01

Volume and percent ground cover of down wood were estimated on the MOFEP sites from two separate sampling inventories, line transects and fixed-area plots. Line transects were used to sample down wood in the 1990-91 and 1994-95 inventories and fixed-area plots were used in an additional inventory in 1995. Line transect inventories estimated a range in ground cover...

Estimating forestland area change from inventory data

Treesearch

Paul Van Deusen; Francis Roesch; Thomas Wigley

2013-01-01

Simple methods for estimating the proportion of land changing from forest to nonforest are developed. Variance estimators are derived to facilitate significance tests. A power analysis indicates that 400 inventory plots are required to reliably detect small changes in net or gross forest loss. This is an important result because forest certification programs may...

Updating Indiana Annual Forest Inventory and Analysis Plot Data Using Eastern Broadleaf Forest Diameter Growth Models

Treesearch

Veronica C. Lessard

2001-01-01

The Forest Inventory and Analysis (FIA) program of the North Central Research Station (NCRS), USDA Forest Service, has developed nonlinear, individual-tree, distance-independent annual diameter growth models. The models are calibrated for species groups and formulated as the product of an average diameter growth component and a modifier component. The regional models...

Analyzing lichen indicator data in the Forest Inventory and Analysis Program

Treesearch

Susan Will-Wolf

2010-01-01

Lichens are one of several forest health indicators sampled every year for a subset of plots on the permanent grid established by the Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service. This report reviews analysis procedures for standard FIA lichen indicator data. Analyses of lichen data contribute to state, regional, and...

A Proposal for Phase 4 of the Forest Inventory and Analysis Program

Treesearch

Ronald E. McRoberts

2005-01-01

Maps of forest cover were constructed using observations from forest inventory plots, Landsat Thematic Mapper satellite imagery, and a logistic regression model. Estimates of mean proportion forest area and the variance of the mean were calculated for circular study areas with radii ranging from 1 km to 15 km. The spatial correlation among pixel predictions was...

Big trees in the southern forest inventory

Treesearch

Christopher M. Oswalt; Sonja N. Oswalt; Thomas J. Brandeis

2010-01-01

Big trees fascinate people worldwide, inspiring respect, awe, and oftentimes, even controversy. This paper uses a modified version of American Forests’ Big Trees Measuring Guide point system (May 1990) to rank trees sampled between January of 1998 and September of 2007 on over 89,000 plots by the Forest Service, U.S. Department of Agriculture, Forest Inventory and...

Forest inventory and analysis data for FVS modelers

Treesearch

Patrick D. Miles

2008-01-01

The USDA Forest Service, Forest Inventory and Analysis (FIA) program has been in continuous operation for over 70 years. FIA’s primary objective is to determine the extent, condition, volume, growth, and depletion of timber on the Nation’s forest land. To accomplish this objective, FIA collects sample plot information on all ownerships across the United States.

Comparing alternatives for increasing sampling intensity in forest inventories

Treesearch

J. Blackard; P. Patterson

2014-01-01

Each of the U.S. Forest Service’s Forest Inventory and Analysis (FIA) regions has an occasional need to intensify the national sampling grid. A variety of methodologies exist within the various FIA regions and National Forest Systems regions for constructing plot intensifications, and there is no consensus on a national procedure The primary objectives of this paper...

A stem-map model for predicting tree canopy cover of Forest Inventory and Analysis (FIA) plots

Treesearch

Chris Toney; John D. Shaw; Mark D. Nelson

2009-01-01

Tree canopy cover is an important stand characteristic that affects understory light, fuel moisture, decomposition rates, wind speed, and wildlife habitat. Canopy cover also is a component of most definitions of forest land used by US and international agencies. The USDA Forest Service Forest Inventory and Analysis (FIA) Program currently does not provide a national...

Using FIA inventory plot data to assess NTFP production possibilities

Treesearch

Jobriath Kauffman; James Chamberlain; Stephen Prisley

2015-01-01

The US Forest Service, Forest Inventory and Analysis (FIA) program collects data on a wealth of variables related to trees and understory species in forests. Some of these trees and plants produce non-timber forest products (NTFPs; e.g., seeds, fruit, bark, sap, roots) that are harvested for their culinary and medicinal values. As example, the cones of Pinus...

Corrections for Cluster-Plot Slop

Treesearch

Harry T. Valentine; Mark J. Ducey; Jeffery H. Gove; Adrian Lanz; David L.R. Affleck

2006-01-01

Cluster-plot designs, including the design used by the Forest Inventory and Analysis program of the USDA Forest Service (FIA), are attended by a complicated boundary slopover problem. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. The dispersed nature of inclusion zones that arise from the use of cluster plots...

Boundary pint corrections for variable radius plots - simulation results

Treesearch

Margaret Penner; Sam Otukol

2000-01-01

The boundary plot problem is encountered when a forest inventory plot includes two or more forest conditions. Depending on the correction method used, the resulting estimates can be biased. The various correction alternatives are reviewed. No correction, area correction, half sweep, and toss-back methods are evaluated using simulation on an actual data set. Based on...

The 2002 RPA Plot Summary database users manual

Treesearch

Patrick D. Miles; John S. Vissage; W. Brad Smith

2004-01-01

Describes the structure of the RPA 2002 Plot Summary database and provides information on generating estimates of forest statistics from these data. The RPA 2002 Plot Summary database provides a consistent framework for storing forest inventory data across all ownerships across the entire United States. The data represents the best available data as of October 2001....

Selection of Plot Remeasurement in an Annual Inventory

Treesearch

Mark H. Hansen; Hans T. Schreuder; Dave Heinzen

2000-01-01

A plot selection approach is proposed based on experience from the Annual Forest Inventory System (AFIS) in the Aspen-Birch Unit of northestern Minnesota. The emphasisis on a mixture of strategies. Although the Agricultural Act of 1998 requires that a fixed 20 percent of plots be measured each year in each state, sooner or later we will need to vary the scheme to...

South Carolina's forest resources - 2000 update

Treesearch

Roger C. Conner; Raymond M. Sheffield

2001-01-01

This bulletin highlights the principal findings of an annual inventory of South Carolina's forest resources. Data summaries are based upon 60 percent of the plots in the State. Additional data summaries and bulletins will be published as the full set of plots are completed.

The Effects of Removing Condition Boundaries on FIA Estimates

Treesearch

David Gartner; Gregory Reams

2005-01-01

When Forest Inventory and Analysis (FIA) changed to the national standards for the inventory system, plots with multiple condition codes were introduced to the Southern Station's FIA unit. FIA maps up to five different conditions on completely or partially forested 1/24-acre subplots. This change has made producing inventory estimates more complex because the data...

Stratifying to reduce bias caused by high nonresponse rates: A case study from New Mexico’s forest inventory

Treesearch

Sara A. Goeking; Paul L. Patterson

2013-01-01

The USDA Forest Service’s Forest Inventory and Analysis (FIA) Program applies specific sampling and analysis procedures to estimate a variety of forest attributes. FIA’s Interior West region uses post-stratification, where strata consist of forest/nonforest polygons based on MODIS imagery, and assumes that nonresponse plots are distributed at random across each stratum...

Forests of Vermont and New Hampshire 2012

Treesearch

Randall S. Morin; Chuck J. Barnett; Brett J. Butler; Susan J. Crocker; Grant M. Domke; Mark H. Hansen; Mark A. Hatfield; Jonathan Horton; Cassandra M. Kurtz; Tonya W. Lister; Patrick D. Miles; Mark D. Nelson; Ronald J. Piva; Sandy Wilmot; Richard H. Widmann; Christopher W. Woodall; Robert. Zaino

2015-01-01

The first full remeasurement of the annual inventory of the forests of Vermont and New Hampshire was completed in 2012 and covers nearly 9.5 million acres of forest land, with an average volume of nearly 2,300 cubic feet per acre. The data in this report are based on visits to 1,100 plots located across Vermont and 1,091 plots located across New Hampshire. Forest land...

Preliminary Evaluation of Methods for Classifying Forest Site Productivity Based on Species Composition in Western North Carolina

Treesearch

W. Henry McNab; F. Thomas Lloyd; David L. Loftis

2002-01-01

The species indicator approach to forest site classification was evaluated for 210 relatively undisturbed plots established by the USDA Forest Service Forest Inventory and Analysis uni (FIA) in western North Carolina. Plots were classified by low, medium, and high levels of productivity based on 10-year individual tree basal area increment data standardized for initial...

Regional variation in Caribbean dry forest tree species composition

Treesearch

Janet Franklin; Julie Ripplinger; Ethan H. Freid; Humfredo Marcano-Vega; David W. Steadman

2015-01-01

How does tree species composition vary in relation to geographical and environmental gradients in a globally rare tropical/subtropical broadleaf dry forest community in the Caribbean? We analyzed data from 153 Forest Inventory and Analysis (FIA) plots from Puerto Rico and the U.S. Virgin Islands (USVI), along with 42 plots that we sampled in the Bahamian Archipelago (...

Mortality rates associated with crown health for eastern forest tree species

Treesearch

Randall S. Morin; KaDonna C. Randolph; Jim Steinman

2015-01-01

The condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during inventories of the US Forest Service Forest Inventory and Analysis (FIA) program since 1999. In this study, remeasured data from 55,013 trees on 2616 FIA plots in the eastern USA were used to assess the probability of survival among various tree...

Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

Treesearch

James E. Smith; Linda S. Heath

2015-01-01

Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

North Carolina, 2011 forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Barry D. New

2013-01-01

Forest Inventory and Analysis (FIA) factsheets are produced periodically to keep the public updated on the extent and condition of forest lands in each State. Estimates in the factsheets are based upon data collected from thousands of sample plots distributed across the landscape in a systematic manner. In North Carolina, this process is a collaborative effort between...

Evaluating Classified MODIS Satellite Imagery as a Stratification Tool

Treesearch

Greg C. Liknes; Mark D. Nelson; Ronald E. McRoberts

2004-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service collects forest attribute data on permanent plots arranged on a hexagonal network across all 50 states and Puerto Rico. Due to budget constraints, sample sizes sufficient to satisfy national FIA precision standards are seldom achieved for most inventory variables unless the estimation process is...

A density management diagram for even-aged Sierra Nevada mixed-conifer stands

Treesearch

James N. Long; John D. Shaw

2012-01-01

We have developed a density management diagram (DMD) for even-aged mixed-conifer stands in the Sierra Nevada Mountains using forest inventory and analysis (FIA) data. Analysis plots were drawn from FIA plots in California, southern Oregon, and western Nevada which included those conifer species associated with the mixed-conifer forest type. A total of 204 plots met the...

Selection of plot remeasurement in an annual inventory

Treesearch

Mark H. Hansen; Hans T. Schreuder; Dave Heinzen

2000-01-01

A plot selection approach is proposed based on experience from the Annual Forest Inventory System (AFIS) in the Aspen-Birch Unit of northeastern Minnesota. The emphasis is on a mixture of strategies. Although the Agricultural Act of 1998 requires that a fixed 20 percent of plots be measured each year in each state, sooner or later we will need to vary the scheme to...

Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

PubMed

Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

2015-12-01

Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

Comparing the accuracy of terrestrial laser scanner in measuring forest inventory variables to enhance better decision making for potential fire hazards

NASA Astrophysics Data System (ADS)

Ghimire, Suman; Xystrakis, Fotios; Koutsias, Nikos

2017-04-01

Forest inventory variables are essential in accessing the potential of wildfire hazard, obtaining above ground biomass and carbon sequestration which helps developing strategies for sustainable management of forests. Effective management of forest resources relies on the accuracy of such inventory variables. This study aims to compare the accuracy in obtaining the forest inventory variables like diameter at breast height (DBH) and tree height from Terrestrial Laser Scanner (Faro Focus 3D X 330) with that from the traditional forest inventory techniques in the Mediterranean forests of Greece. The data acquisition was carried out on an area of 9,539.8 m2 with six plots each of radius 6 m. Computree algorithm was applied for automatic detection of DBH from terrestrial laser scanner data. Similarly, tree height was estimated manually using CloudCompare software for the terrestrial laser scanner data. The field estimates of DBH and tree height was carried out using calipers and Nikon Forestry 550 Laser Rangefinder. The comparison of DBH measured between field estimates and Terrestrial Laser Scanner (TLS), resulted in R squared values ranging from 0.75 to 0.96 at the plot level. An average R2 and RMSE value of 0.80 and 1.07 m respectively was obtained when comparing the tree height between TLS and field data. Our results confirm that terrestrial laser scanner can provide nondestructive, high-resolution, and precise determination of forest inventory for better decision making in sustainable forest management and assessing potential of forest fire hazards.

FIA Quality Assurance Program: Evaluation of a Tree Matching Algorithm for Paired Forest Inventory Data

Treesearch

James E. Pollard; James A. Westfall; Paul A. Patterson; David L. Gartner

2005-01-01

The quality of Forest Inventory and Analysis inventory data can be documented by having quality assurance crews remeasure plots originally measured by field crews within 2 to 3 weeks of the initial measurement, and assessing the difference between the original and remeasured data. Estimates of measurement uncertainty for the data are generated using paired data...

Use of USDA forest inventory and analysis data to assess oak tree health in Minnesota

Treesearch

Kathryn W. Kromroy; Jennifer Juzwik; Paul D. Castillo

2003-01-01

As a precursor to a regional assessment for the Upper Midwest, three variables were examined as measures of oak health in Minnesota between 1974 and 1990 using USDA Forest Service Inventory and Analysis data. Mortality was 6 percent in the 1986-1990 inventory based on numbers of dead oaks per total oaks on plots with...

Remeasured FIA plots reveal tree-level diameter growth and tree mortality impacts of nitrogen deposition on California’s forests

Treesearch

Mark E. Fenn; Jeremy S. Fried; Haiganoush K. Preisler; Andrzej Bytnerowicz; Susan Schilling; Sarah Jovan; Olaf Kuegler

2015-01-01

The air in California’s forests spans a broad range of purity, from virtually no locally generated pollutants to highly elevated levels of pollutants in forests downwind of urban and agricultural source areas. Ten-year remeasurement data from Forest Inventory and Analysis (FIA) plots in California were used in combination with modelled atmospheric nitrogen (N)...

A comparison of FIA plot data derived from image pixels and image objects

Treesearch

Charles E. Werstak

2012-01-01

The use of Forest Inventory and Analysis (FIA) plot data for producing continuous and thematic maps of forest attributes (e.g., forest type, canopy cover, volume, and biomass) at the regional level from satellite imagery can be challenging due to differences in scale. Specifically, classification errors that may result from assumptions made between what the field data...

FIAMODEL: Users Guide Version 3.0.

Treesearch

Scott A. Pugh; David D. Reed; Kurt S. Pregitzer; Patrick D. Miles

2002-01-01

FIAMODEL is a geographic information system (GIS program used to summarize Forest Inventory and Analysis (FIA, USDA Forest Service) data such as volume. The model runs in ArcView and allows users to select FIA plots with heads-up-digitizing, overlays of digital map layers, or queries based on specific plot attributes.

Where are the Walnut Trees in Minnesota? 1995.

Treesearch

J. Michael Vasievich; Neal P. Kingsley

1995-01-01

The forests of each state are inventoried by the USDA-Forest Service and the state?s forestry agency on a periodic basis. In the Midwest, the North Central Forest Experiment Station coordinates the inventory. The job takes a long time-- sometimes several years from start to finish -- because lots of trees are measured on lots of plots. For example, during the last...

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Virginia, 2012 - forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2014-01-01

This science update is a brief look at some of the basic metrics that describe the status of and changes in forest resources in Virginia. Estimates presented here are for the measurement year 2012. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel)...

Virginia, 2011 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2013-01-01

This science update is a brief look at some of the basic metrics that describe the status and trends of forest resources in Virginia. Estimates presented here are for the measurement year 2011. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in...

Virginia, 2010 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2012-01-01

This science update is a brief look at some of the basic metrics that describe the status of forest resources in Virginia. Estimates presented here are for the measurement year 2010. Information for this factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State and each year...

Virginia, 2009 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2011-01-01

This science update is a brief look at some of the basic metrics that describe forest resources in Virginia. Estimates presented here are for the measurement year 2009. Information for the factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State, and each year 20 percent of...

The use of multiple imputation in the Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Joseph M. McCollum

2000-01-01

The Southern Research Station is currently implementing an annual forest survey in 7 of the 13 States that it is responsible for surveying. The Southern Annual Forest Inventory System (SAFIS) sampling design is a systematic sample of five interpenetrating grids, whereby an equal number of plots are measured each year. The area-representative and time-series...

The use of multiple imputation in the Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Joseph M. McCollum

2000-01-01

The Southern Research Station is currently implementing an annual forest survey in 7 of the 13 states that it is responsible for surveying. The Southern Annual Forest Inventory System (SAFIS) sampling design is a systematic sample of five interpenetrating grids, whereby an equal number of plots are measured each year. The area representative and time series nature of...

K-nearest neighbor imputation of forest inventory variables in New Hampshire

Treesearch

Andrew Lister; Michael Hoppus; Raymond L. Czaplewski

2005-01-01

The k-nearest neighbor (kNN) method was used to map stand volume for a mosaic of 4 Landsat scenes covering the state of New Hampshire. Data for gross cubic foot volume and trees per acre were summarized from USDA Forest Service Forest Inventory and Analysis (FIA) plots and used as training for kNN. Six bands of...

The Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Paul C. van Deusen

1999-01-01

The Southern Annual Forest Inventory System (SAFIS) is in various stages of implementation in 7 of the 13 southern states serviced by the Southern Research Station. The SAFIS design is an interpenetrating design where the n units (1/6 acre plots) are divided into k = 5 panels, each panel containing m = n...

Using forest inventory plot data and satellite imagery from MODIS and Landsat-TM to model spatial distribution patterns of honeysuckle and privet

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2009-01-01

Forest inventory and analysis data monitor the presence and extent of certain non-native invasive species. Onforestland, non-native species are considered part of the understory vegetation and can be found near canopyopenings as well as and...

Approach of regionalisation c-stocks in forest soils on a national level

NASA Astrophysics Data System (ADS)

Wellbrock, Nicole; Höhle, Juliane; Dühnelt, Petra; Holzhausen, Marieanna

2010-05-01

Introduction In December 2006, the German government decided to manage forests as carbon sinks to reduce greenhouse gas emissions in accordance with Article 3.4 of the Kyoto Protocol. The National Forest Monitoring data contribute to the fulfilment of these reporting commitments. In Germany, National Forest Monitoring includes the systematical extensive National Soil Condition Survey (BZE) and the detailed case studies (Level-II) which determine the processes within forests. This complex monitoring system is appropriate to Germany's greenhouse gas reporting (THG 2008 to 2012). The representative BZE plots can be used to obtain regional data for the National Carbon Stock Inventory. Here, an approach adopting a combination of geostatistics and regression analysis is preferred. The difficulty of showing the statistical significance of expected small changes while carbon stocks are generally high is one of the major challenges in carbon stock monitoring. However, through intensive preparation and cooperation with the forestry authorities of each federal state, the errors uncured in determining changes in carbon stocks in forest soils, which must be stipulated in greenhouse gas monitoring, could be minimised. In contrast to the detailed soil case studies, in which essentially the sources of error occur repeatedly in carbon stock change calculations, the BZE data can be stratified to form plots with homogenous properties, thereby reducing the standard error of estimate. Subsequently, the results of the stratification are projected across Germany, the reporting unit for greenhouse gas monitoring. National Forest Monitoring The BZE represents a national, systematic sampling inventory of the condition of forest soils. The first BZE inventory (BZE I: 1987 to 1993) was carried out on a systematic 8 x 8 km grid on the same sampling plots adopted in the Forest Condition Survey (WZE). In some areas the network of sampling plots involves 1900 grid points. The first BZE I survey was repeated after 15 years, between 2006 and 2008, by the national and the state authorities in cooperation. Afterwards, extensive laboratory and statistical analyses were conducted. Necessary parameters are listed in table 1. Upscaling approach There are different approaches for presenting extensive carbon stock data (Baritz et al., 2006). The availability of georeference plots means one can merge the point data with map data. In Germany, an approach was tested that used homogenous soil areas und plot-information from the national soil inventory. For every soil area c-stocks were regionalised. Only information form BZE-plots were involved which were characteristic for the soil area. The indicators were soil type and substrate class. For every soil area the forest areas were taken in account to calculate c-stock per forest area. The sum of every c-stock per soil area is the c-stock in forest soils of Germany. Tab.1: List of parameters for the carbon inventory (BZE II) Components Parameters Point level Field sampling Width of depth classes, Fine roots, humus (< 2 cm), dry bulk density, stone content, area of humus layer sampled, height a.s.l., litterfall, deadwood (from 10 cm) Analysis C content, fine soil fraction, weight of humus layer, Carbon stock calculations Carbon stock Regional Level Plot Soil type, parent material, vegetation type or forest Regionalisation Soil and land use maps, statistical models, ecological regions, digital elevation models, climate regions

A GIS-based tool for estimating tree canopy cover on fixed-radius plots using high-resolution aerial imagery

Treesearch

Sara A. Goeking; Greg C. Liknes; Erik Lindblom; John Chase; Dennis M. Jacobs; Robert. Benton

2012-01-01

Recent changes to the Forest Inventory and Analysis (FIA) Program's definition of forest land precipitated the development of a geographic information system (GIS)-based tool for efficiently estimating tree canopy cover for all FIA plots. The FIA definition of forest land has shifted from a density-related criterion based on stocking to a 10 percent tree canopy...

Exploring the association of the Minnesota Department of Natural Resources' satellite-detected change with the Forest Inventory and Analysis system of observed removals and mortality

Treesearch

Dale D. Gormanson; Timothy J. Aunan; Mark H. Hansen; Michael Hoppus

2009-01-01

Since 2001, the Minnesota Department of Natural Resources (MN-DNR) has mapped forest change annually by comparison of Landsat satellite image pairs. Over the same timeframe, 1,761 U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) plots in Minnesota have been remeasured on a 5-year cycle, providing field data on growth, removals, and...

Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique

Treesearch

Ronald E. McRoberts; Mark D. Nelson; Daniel G. Wendt

2002-01-01

For two large study areas in Minnesota, USA, stratified estimation using classified Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-stratum estimates. These measurements further...

Using interpreted large scale aerial photo data to enhance satellite-based mapping and explore forest land definitions

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2009-01-01

The Interior-West, Forest Inventory and Analysis (FIA), Nevada Photo-Based Inventory Pilot (NPIP), launched in 2004, involved acquisition, processing, and interpretation of large scale aerial photographs on a subset of FIA plots (both forest and nonforest) throughout the state of Nevada. Two objectives of the pilot were to use the interpreted photo data to enhance...

Assessment of fire effects based on Forest Inventory and Analysis data and a long-term fire mapping data set

Treesearch

John D. Shaw; Sara A. Goeking; James Menlove; Charles E. Werstak

2017-01-01

Integration of Forest Inventory and Analysis (FIA) plot data with Monitoring Trends in Burn Severity (MTBS) data can provide new information about fire effects on forests. This integration allowed broad-scale assessment of the cover types burned in large fires, the relationship between prefire stand conditions and fire severity, and postfire stand conditions. Of the 42...

The relationship between diversity and productivity in selected forests of the Lake States Region (USA): relative impact of species versus structural diversity

Treesearch

W. Keith Moser; Mark Hansen

2009-01-01

Ecological theory suggests that diversity and productivity (at some measure) are positively correlated, presumably because individuals engage in niche partitioning to occupy any unclaimed growing space. We examined this theory using inventory information from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis program. The study uses plot-...

Abundance and Size Distribution of Cavity Trees in Second-Growth and Old-Growth Central Hardwood Forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson III; David R. Larsen

2005-01-01

In central hardwood forests, mean cavity-tree abundance increases with increasing standsize class (seedling/sapling, pole, sawtimber, old-growth). However, within a size class, the number of cavity trees is highly variable among 0.1-ha inventory plots. Plots in young stands are most likely to have no cavity trees, but some plots may have more than 50 cavity trees/ha....

Abundance and size distribution of cavity trees in second-growth and old-growth central hardwood forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson; David R. Larsen

2005-01-01

In central hardwood forests, mean cavity-tree abundance increases with increasing standsize class (seedling/sapling, pole, sawtimber, old-growth). However, within a size class, the number of cavity trees is highly variable among 0.1-ha inventory plots. Plots in young stands are most likely to have no cavity trees, but some plots may have more than 50 cavity trees/ha....

Effects of cycle length and plot density on estimators for a national-scale forest monitoring sample design

Treesearch

Francis A. Roesch; Todd A. Schroeder; James T. Vogt

2017-01-01

The resilience of a National Forest Inventory and Monitoring sample design can sometimes depend upon the degree to which it can adapt to fluctuations in funding. If a budget reduction necessitates the observation of fewer plots per year, some practitioners weigh the problem as a tradeoff between reducing the total number of plots and measuring the original number of...

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

2016-12-01

Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

Estimating tree species richness from forest inventory plot data

Treesearch

Ronald E. McRoberts; Dacia M. Meneguzzo

2007-01-01

Montreal Process Criterion 1, Conservation of Biological Diversity, expresses species diversity in terms of number of forest dependent species. Species richness, defined as the total number of species present, is a common metric for analyzing species diversity. A crucial difficulty in estimating species richness from sample data obtained from sources such as inventory...

Evaluating imputation and modeling in the North Central region

Treesearch

Ronald E. McRoberts

2000-01-01

The objectives of the North Central Research Station, USDA Forest Service, in developing procedures for annual forest inventories include establishing the capability of producing annual estimates of timber volume and related variables. The inventory system developed to accomplish these objectives features an annual sample of measured field plots and techniques for...

The effects of removing condition boundaries on FIA estimates

Treesearch

David Gartner; Gregory Reams

2002-01-01

When Forest Inverltory and Analysis (FIA) changed to the national standards for the inventory system, plots with lnultiplc condition codes were introduced to the Southern Station's FIA unit. FIA maps up to five different conditions on completely or partially forested 1124-acre subplots. This change has madc producing inventory estimates more complex because the...

Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest

Treesearch

Carine Klauberg; Edson Vidal; Carlos Alberto Silva; Michelliny de M. Bentes; Andrew Thomas Hudak

2016-01-01

Titica vine provides useful raw fiber material. Using sampling schemes that reduce sampling error can provide direction for sustainable forest management of this vine. Sampling systematically with rectangular plots (10× 25 m) promoted lower error and greater accuracy in the inventory of titica vines in tropical rainforest.

A Computer Program for Displaying Forest Survey Type Information

Treesearch

B. Bruce Bare; Robert N. Stone

1968-01-01

Presents a computerized procedure for displaying forest type information from inventory plots. Although the development of general forest type maps in emphasized, the program can be used to display any locational data having rectangular coordinates

An assessment of invasive plant species monitored by the Northern Research Station Forest Inventory and Analysis Program, 2005 through 2010

Treesearch

Cassandra M. Kurtz

2013-01-01

Invasive plant species are a worldwide concern due to the high ecological and economic costs associated with their presence. This document describes the plant characteristics and regional distribution of the 50 invasive plant species monitored from 2005 through 2010 on forested Phase 2 (P2) Forest Inventory and Analysis (FIA) plots in the 24 states of the Northern...

Searching for American chestnut: the estimation of rare species attributes in a national forest inventory

Treesearch

Francis A. Roesch; William H. McWilliams

2007-01-01

American chestnut, once a dominant tree species in forests of the Northeastern United States, has become extremely rare. It is so rare, in fact, that on completion of 80 percent of the plot measurements of the U.S. Department of Agriculture Forest Service's most recent inventory in Pennsylvania, only 33 American chestnut trees with a diameter at breast height !Y 1...

Searching for American chestnut: the estimation of rare species attributes in a national forest inventory

Treesearch

Francis A. Roesch; William H. McWilliams

2005-01-01

American chestnut, once a dominant tree species in forests of the Northeastern United States, has become extremely rare. It is so rare, in fact, that on completion of 80 percent of the plot measurements of the U.S. Department of Agriculture Forest Service's most recent inventory in Pennsylvania, only 33 American chestnut trees with a diameter at breast height 2: 1...

Utility of tree crown condition indicators to predict tree survival using remeasured Forest Inventory and Analysis data

Treesearch

Randall S. Morin; Jim Steinman; KaDonna C. Randolph

2012-01-01

The condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during surveys of Forest Inventory and Analysis (FIA) Phase 3 (P3) plots since 1999. In this study, remeasured data from 39,357 trees in the northern United States were used to assess the probability of survival among various tree species using the...

Quantifying allometric model uncertainty for plot-level live tree biomass stocks with a data-driven, hierarchical framework

Treesearch

Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall

2016-01-01

Accurate uncertainty assessments of plot-level live tree biomass stocks are an important precursor to estimating uncertainty in annual national greenhouse gas inventories (NGHGIs) developed from forest inventory data. However, current approaches employed within the United States’ NGHGI do not specifically incorporate methods to address error in tree-scale biomass...

Forest land area estimates from vegetation continuous fields

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Matthew C. Hansen

2004-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) program provides data, information, and knowledge about our Nation's forest resources. FIA regional units collect data from field plots and remotely sensed imagery to produce statistical estimates of forest extent (area); volume, growth, and removals; and health and condition. There is increasing...

Forest/Nonforest Classification of Landsat TM Data For Annual Inventory Phase One Stratification

Treesearch

Jim Rack

2001-01-01

Launch of Landsat 7 creates the opportunity to use relatively inexpensive and regularly acquired land cover data as an alternative to high altitude aerial photography. Creating a forest/nonforest mask from satellite imagery may offer a cost-effective alternative to interpretation of aerial photography for Phase One stratification of annual inventory plots. This paper...

Implementing a land cover stratification on-the-fly

Treesearch

Ronald E. McRoberts; Daniel G. Wendt

2002-01-01

Stratified estimation is used by the Forest Inventory and Analysis program of the USDA Forest Service to increase the precision of county-level inventory estimates. Stratified estimation requires that plots be assigned to strata and that proportions of land area in each strata be determined. Classified satellite imagery has been found to be an efficient and effective...

Building the Forest Inventory and Analysis Tree-Ring Data set

Treesearch

Robert J. DeRose; John D. Shaw; James N. Long

2017-01-01

The Interior West Forest Inventory and Analysis (IW-FIA) program measures forestland conditions at great extent with relatively high spatial resolution, including the collection of tree-ring data. We describe the development of an unprecedented spatial tree-ring data set for the IW-FIA that enhances the baseline plot data by incorporating ring-width increment measured...

The great carbon push-pull: where science is pushing and policy is pulling the official forest carbon inventory of the US

Treesearch

C.W. Woodall; G.M. Domke; J. Coulston; M.B. Russell; J.A. Smith; C.H. Perry; S. Healey; A. Gray

2015-01-01

A national system of field inventory plots (FIA) is the primary data source for the annual assessment of US forest carbon (C) stocks and stock-change to meet reporting requirements under the United Nations Framework Convention on Climate Change (UNFCCC). The inventory data and their role in national carbon reporting continue to evolve. The framework of the previous C...

Implementing a national process for estimating growth, removals, and mortality at the Pacific Northwest’s Forest Inventory and Analysis’s Region: modeling diameter growth

Treesearch

Olaf. Kuegler

2015-01-01

The Pacific Northwest Research Station’s Forest Inventory and Analysis Unit began remeasurement of permanently located FIA plots under the annualized design in 2011. With remeasurement has come the need to implement the national FIA system for compiling estimates of forest growth, removals, and mortality. The national system requires regional diameter-growth models to...

The effects of forest fragmentation on forest stand attributes

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and...

TRIM timber projections: an evaluation based on forest inventory measurements.

Treesearch

John R. Mills

1989-01-01

Two consecutive timberland inventories collected from permanent plots in the natural pine type in North Carolina were used to evaluate the timber resource inventory model (TRIM). This study compares model predictions with field measurements and examines the effect of inventory data aggregation on the accuracy of projections. Projections were repeated for two geographic...

A first look at measurement error on FIA plots using blind plots in the Pacific Northwest

Treesearch

Susanna Melson; David Azuma; Jeremy S. Fried

2002-01-01

Measurement error in the Forest Inventory and Analysis work of the Pacific Northwest Station was estimated with a recently implemented blind plot measurement protocol. A small subset of plots was revisited by a crew having limited knowledge of the first crew's measurements. This preliminary analysis of the first 18 months' blind plot data indicates that...

Differences in forest area classification based on tree tally from variable- and fixed-radius plots

Treesearch

David Azuma; Vicente J. Monleon

2011-01-01

In forest inventory, it is not enough to formulate a definition; it is also necessary to define the "measurement procedure." In the classification of forestland by dominant cover type, the measurement design (the plot) can affect the outcome of the classification. We present results of a simulation study comparing classification of the dominant cover type...

Calibration and Application of FOREST-BGC in NorthWestern of Portugal

NASA Astrophysics Data System (ADS)

Rodrigues, M. A.; Lopes, D. M.; Leite, M. S.; Tabuada, V. M.

2010-05-01

Net primary production (NPP) is one of the most important variables in terms of ecosystems inventory and management, because it quantifies its growth and reflects the impact of biotic and abiotic factors, which could affect it. Interest in NP has increased recently because of the increasing interesting in climate change and the need in understanding its impact on the environment. There are ecophysiologic models, as Forest-BGC that allow for estimating NPP. The types of models offer a possible methodology to test these phenomena, beyond temporal and spatial scales, not available with tradicional inventory methodologies. To analyze the Forest-BGC performance, NPP data obtained with model were compared with collected data in the field, in the same sampling plots. For a parameterization and validation of the FOREST-BGC, this study was carried on based on 500m2 sampling plots from the National Forest Inventory 2006 and are located in several County Halls of the district of Vila Real, Portugal (Montalegre, Chaves, Valpaços, Boticas, Vila Pouca de Aguiar, Murça, Mondim de Basto, Alijó, Sabrosa and Vila Real). In order to quantify Biomass dinamics, we have selected 45 sampling plots: 19 from Pinus pinaster stands, 17 from Quercus pyreneica and 10 from mixed of Quercus with Pinus. Adaptation strategies for climate change impacts can be proposed based on these research results.

K-Nearest Neighbor Estimation of Forest Attributes: Improving Mapping Efficiency

Treesearch

Andrew O. Finley; Alan R. Ek; Yun Bai; Marvin E. Bauer

2005-01-01

This paper describes our efforts in refining k-nearest neighbor forest attributes classification using U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot data and Landsat 7 Enhanced Thematic Mapper Plus imagery. The analysis focuses on FIA-defined forest type classification across St. Louis County in northeastern Minnesota. We outline...

Using inventory-based tree-ring data as a proxy for historical climate: Investigating the Pacific decadal oscillation and teleconnections

Treesearch

J. DeRose; S. Wang; J. Shaw

2014-01-01

In 2009, the Interior West Forest Inventory and Analysis (FIA) program of the U.S. Forest Service started to archive approximately 11 000 increment cores collected in the Interior West states during the periodic inventories of the 1980s and 1990s. The two primary goals for use of the data were to provide a plot-linked database of radial growth to be used for growth...

An evaluation of the properties of the variance estimator used by FIA

Treesearch

John P. Brown; James A. Westfall

2012-01-01

The Forest Inventory and Analysis (FIA) program of the U.S. Forest Service currently conducts inventories utilizing the protocols of the national enhanced FIA Program. Due to the permanent locations of the sample plots, the stratification of the population occurs after the selection of sample units, i.e., post-stratification. In situations where the population is of...

A System to Derive Optimal Tree Diameter Increment Models from the Eastwide Forest Inventory Data Base (EFIDB)

Treesearch

Don C. Bragg

2002-01-01

This article is an introduction to the computer software used by the Potential Relative Increment (PRI) approach to optimal tree diameter growth modeling. These DOS programs extract qualified tree and plot data from the Eastwide Forest Inventory Data Base (EFIDB), calculate relative tree increment, sort for the highest relative increments by diameter class, and...

State-of-the-art technologies of forest inventory and monitoring in Taiwan

Treesearch

Fong-Long Feng

2000-01-01

Ground surveys, remote sensing (RS), global positioning systems (GPS), geographic information systems (GIS), and permanent sampling plots (PSP) were used to inventory and monitor forests in the development of an ecosystem management plan for the island of Taiwan. While the entire island has been surveyed, this study concentrates on the Hui-Sun and Hsin-Hua Experimental...

A simplified Forest Inventory and Analysis database: FIADB-Lite

Treesearch

Patrick D. Miles

2008-01-01

This publication is a simplified version of the Forest Inventory and Analysis Data Base (FIADB) for users who do not need to compute sampling errors and may find the FIADB unnecessarily complex. Possible users include GIS specialists who may be interested only in identifying and retrieving geographic information and per acre values for the set of plots used in...

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Treesearch

Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

Rapid assessment of wildfire damage using Forest Inventory data: A case in Georgia

Treesearch

Richard A. Harper; John W. Coulsten; Jeffery A. Turner

2009-01-01

The rapid assessment of damage caused by natural disasters is essential for planning the appropriate amount of disaster relief funds and public communication. Annual Forest Inventory and Analysis (FIA) data provided initial estimates of damage to timberland in a timely manner to State leaders during the 2007 Georgia Bay Complex Wildfire in southeast Georgia. FIA plots...

Assessing soil compaction on Forest Inventory & Analysis phase 3 field plots using a pocket penetrometer

Treesearch

Michael C. Amacher; Katherine P. O' Neill

2004-01-01

Soil compaction is an important indicator of soil quality, yet few practical methods are available to quantitatively measure this variable. Although an assessment of the areal extent of soil compaction is included as part of the soil indicator portion of the Forest Inventory & Analysis (FIA) program, no quantitative measurement of the degree of soil compaction...

Michigan's forests 2004

Treesearch

Scott A. Pugh; Mark H. Hansen; Lawrence D. Pedersen; Douglas C. Heym; Brett J. Butler; Susan J. Crocker; Dacia Meneguzzo; Charles H. Perry; David E. Haugen; Christopher Woodall; Ed Jepsen

2009-01-01

The first annual inventory of Michigan's forests, completed in 2004, covers more than 19.3 million acres of forest land. The data in this report are based on visits to 10,355 forested plots from 2000 to 2004. In addition to detailed information on forest attributes, this report includes data on forest health, biomass, land-use change, and timber-product outputs....

Michigan forests 2014

Treesearch

Scott A. Pugh; Douglas C. Heym; Brett J. Butler; David E. Haugen; Cassandra M. Kurtz; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Rachel I. Riemann; James E. Smith; James A. Westfall; Christopher W. Woodall

2017-01-01

The eighth inventory of Michigan's forests, completed in 2014, describes more than 20.3 million acres of forest land. The data in this report are based on visits to 4,289 forested plots from 2009 to 2014. Timberland accounts for 95 percent of this forest land, and 62 percent is privately owned. The sugar maple/beech/yellow birch forest type accounts for 19 percent...

Michigan's Forests 2009

Treesearch

Scott A. Pugh; Lawrence D. Pedersen; Douglas C. Heym; Ronald J. Piva; Christopher W. Woodall; Charles J. Barnett; Cassandra M. Kurtz; W. Keith Moser

2012-01-01

The seventh inventory of Michigan's forests, completed in 2009, describes more than 19.9 million acres of forest land. The data in this report are based on visits to 7,516 forested plots from 2005 to 2009. Timberland accounts for 97 percent of this forest land, and 62 percent is privately owned. The sugar maple/beech/yellow birch forest type accounts for 18...

A universal airborne LiDAR approach for tropical forest carbon mapping.

PubMed

Asner, Gregory P; Mascaro, Joseph; Muller-Landau, Helene C; Vieilledent, Ghislain; Vaudry, Romuald; Rasamoelina, Maminiaina; Hall, Jefferson S; van Breugel, Michiel

2012-04-01

Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ( 2 ) = 0.80, RMSE = 27.6 Mg C ha(-1)). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.

North Carolina, 2010 forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Barry D. New

2012-01-01

North Carolina’s first annualized forest survey was completed in 2007 and results were published in e-Science Update SRS–029. There were 5,800 ground based samples distributed across the State. At that time, field measurements were collected on 20 percent (a panel) of these plots annually until all plots were completed. This factsheet is an annualized update of panel...

Comparison of a fully mapped plot design to three alternative designs for volume and area estimates using Maine inventory data

Treesearch

Stanford L. Arner

1998-01-01

A fully mapped plot design is compared to three alternative designs using data collected for the recent inventory of Maine's forest resources. Like the fully mapped design, one alternative eliminates the bias of previous procedures, and should be less costly and more consistent. There was little difference in volume and area estimates or in sampling errors among...

Maine's forests 2008

Treesearch

George L. McCaskill; William H. McWilliams; Charles J. Barnett; Brett J. Butler; Mark A. Hatfield; Cassandra M. Kurtz; Randall S. Morin; W. Keith Moser; Charles H. Perry; Christopher W. Woodall

2011-01-01

The second annual inventory of Maine's forests was completed in 2008 after more than 3,160 forested plots were measured. Forest land occupies almost 17.7 million acres, which represents 82 percent of the total land area of Maine. The dominant forest-type groups are maple/beech/yellow birch, spruce/fir, white/red/jack pine, and aspen/white birch. Statewide volume...

Estimating forest floor fuels in eastern U.S. forests

Treesearch

David C. Chojnacky; Steven G. McNulty; Jennifer Moore Myers; Michael K. Gavazzi

2005-01-01

The Forest Inventory Analysis (FIA) program (U.S. Department of Agriculture, Forest Service) systematically samples the nation's forests and currently measures variable related to down woody material (DWM) on a subsample of its plots in the third phase of a 3-phase sampling design. This paper focuses on: (1) compiling estimates of DWM within limitations of...

A Forested Tract-Size Profile of Florida's NIPF Landowners

Treesearch

Michael T. Thompson

1999-01-01

Abstract: Information gathered from 2,713 permanent Forest Inventory and Analysis (FIA) sample plots showed that over 1.0 million acres, or 15 percent of the nonindustrial private forest (NIPF) timberland in Florida is in forested tracts £ 10 acres. Forested tracts ranging from 11 to 100 acres accounted for the largest proportion of NIPF...

Wisconsin's forests, 2004

Treesearch

Charles H. (Hobie) Perry; Vern A. Everson; Ian K. Brown; Jane Cummings-Carlson; Sally E. Dahir; Edward A. Jepsen; Joe Kovach; Michael D. Labissoniere; Terry R. Mace; Eunice A. Padley; Richard B. Rideout; Brett J. Butler; Susan J. Crocker; Greg C. Liknes; Randall S. Morin; Mark D. Nelson; Barry T. (Ty) Wilson; Christopher W. Woodall

2008-01-01

The first full, annualized inventory of Wisconsin's forests was completed in 2004 after 6,478 forested plots were visited. There are more than 16.0 million acres of forest land in the Wisconsin, nearly half of the State's land area; 15.8 million acres meet the definition of timberland. The total area of both forest land and timberland continues an upward...

Forest Resources of Isle Royale National Park 2010

Treesearch

Wilfred J. Previant; Linda M. Nagel; Scott A. Pugh; Christopher W. Woodall

2012-01-01

This publication provides a baseline overview of forest resources for Isle Royale National Park (Isle Royale) using data from the Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture, Forest Service. The availability of permanent FIA plots allows for the first-ever comparison of Isle Royale's forest conditions (2006-2010) to reserved...

Comparison of estimation techniques for a forest inventory in which double sampling for stratification is used

Treesearch

Michael S. Williams

2001-01-01

A number of different estimators can be used when forest inventory plots cover two or more distinctly different condition classes. In this article the properties of two approximate Horvitz- Thompson (HT) estimators, a ratio of means (RM), and a mean of ratios (MR) estimator are explored in the framework of double sampling for stratification. Relevant theoretical...

Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Treesearch

Kristofer D. Johnson; Richard Birdsey; Andrew O Finley; Anu Swantaran; Ralph Dubayah; Craig Wayson; Rachel Riemann

2014-01-01

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland...

New Mexico Forest Inventory and Analysis: American Recovery and Reinvestment Act Project, Field Report: 2010-2012

Treesearch

Mary Stuever; John Capuano

2014-01-01

For a 3-year period, from 2010-2012, the New Mexico Forestry Division utilized contractors to collect Forest Inventory and Analysis (FIA) data in New Mexico. Funded through the American Recovery and Reinvestment Act, the State partnered with the Interior West FIA Program. Together, both agencies collected data on approximately 6,450 plots. This effort represents the...

Long-term patterns in vegetation-site relationships in a southern Appalachian forest

Treesearch

Katherine J. Elliott; James M. Vose; Wayne T. Swank; Paul V. Bolstad

1999-01-01

The authors used permanent plot inventories from 1969-1973 and 1988-1993 to describe forest species distribution patterns of the Coweeta Hydrologic Laboratory, a 2,185 ha basin in Western North Carolina, USA. They used canonical correspondence analysis to explore the vegetation-site patterns for the 1970’s and 1990’s inventories combined. Site variables were determined...

A density management diagram for even-aged ponderosa pine stands

Treesearch

James N. Long; John D. Shaw

2005-01-01

We developed a density management diagram (DMD) for ponderosa pine using Forest Inventory and Analysis (FIA) data. Analysis plots were drawn from all FIA plots in the western United States on which ponderosa pine occurred. A total of 766 plots met the criteria for analysis. Selection criteria were for purity, defined as ponderosa pine basal area 80% of plot basal area...

Guam's forest resources, 2002.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Walter Grabowiecki; Bruce A. Hiserote; David. Limtiaco

2004-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 46 forested plots on the island of Guam. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide a summary of Guam...

An assessment of multiflora rose in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2013-01-01

This publication provides an overview of multiflora rose (Rosa multiflora) on forest land across the 24 states of the midwestern and northeastern United States based on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS).

Estimates of the occurrence of dwarf mistletoe on the Deschutes National Forest.

Treesearch

Donald J. DeMars

1980-01-01

The proportion of forest area infested and of trees infected were calculated for the Deschutes National Forest by using 10-point plot inventory data. The proportion of commercial forest acres infested with dwarf mistletoe is 0.476, and the proportion of trees infected on these acres is 0.308.

Mapping and imputing potential productivity of Pacific Northwest forests using climate variables

Treesearch

Gregory Latta; Hailemariam Temesgen; Tara Barrett

2009-01-01

Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we...

Palau's forest resources, 2003.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Brent J. Stroud; Bruce A. Hiserote; Kashgar. Rengulbai

2007-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 54 forested plots on the islands in the Republic of Palau. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide...

West Virginia Forests 2013

Treesearch

Randall S. Morin; Gregory W. Cook; Charles J. Barnett; Brett J. Butler; Susan J. Crocker; Mark A. Hatfield; Cassandra M. Kurtz; Tonya W. Lister; William G. Luppold; William H. McWilliams; Patrick D. Miles; Mark D. Nelson; Charles H. (Hobie) Perry; Ronald J. Piva; James E. Smith; Jim Westfall; Richard H. Widmann; Christopher W. Woodall

2016-01-01

The annual inventory of West Virginia's forests, completed in 2013, covers nearly 12.2 million acres of forest land with an average volume of more than 2,300 cubic feet per acre. This report is based data collected from 2,808 plots located across the State. Forest land is dominated by the oak/hickory forest-type group, which occupies 74 percent of total forest...

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Treesearch

F.D.B. Espirito-Santo; M. Gloor; M. Keller; Y. Malhi; S. Saatchi; B. Nelson; R.C. Oliveira Junior; C. Pereira; J. Lloyd; S. Frolking; M. Palace; Y.E. Shimabukuro; V. Duarte; A. Monteagudo Mendoza; G. Lopez-Gonzalez; T.R. Baker; T.R. Feldpausch; R.J.W. Brienen; G.P. Asner; D.S. Boyd; O.L. Phillips

2014-01-01

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel...

Refining FIA plot locations using LiDAR point clouds

Treesearch

Charlie Schrader-Patton; Greg C. Liknes; Demetrios Gatziolis; Brian M. Wing; Mark D. Nelson; Patrick D. Miles; Josh Bixby; Daniel G. Wendt; Dennis Kepler; Abbey Schaaf

2015-01-01

Forest Inventory and Analysis (FIA) plot location coordinate precision is often insufficient for use with high resolution remotely sensed data, thereby limiting the use of these plots for geospatial applications and reducing the validity of models that assume the locations are precise. A practical and efficient method is needed to improve coordinate precision. To...

A simulation of image-assisted forest monitoring for national inventories

Treesearch

Francis Roesch

2016-01-01

The efficiency of national forest monitoring efforts can be increased by the judicious incorporation of ancillary data. For instance, a fixed number of ground plots might be used to inform a larger set of annual estimates by observing a smaller proportion of the plots each year while augmenting each annual estimate with ancillary data in order to reduce overall costs...

American Samoa's forest resources, 2001.

Treesearch

Joseph A. Donnegan; Sheri S. Mann; Sarah L. Butler; Bruce A. Hiserote

2004-01-01

The Forest Inventory and Analysis Program of the Pacific Northwest Research Station collected, analyzed, and summarized data from field plots, and mapped land cover on four islands in American Samoa. This statistical sample provides estimates of forest area, stem volume, biomass, numbers of trees, damages to trees, and tree size distribution. The summary provides...

Forests of Virginia,2013

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in Virginia. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year, 20 percent of the sample plots (one panel) in Virginia are measured by field crews, the data compiled, and new estimates produced.

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

Controls on fallen leaf chemistry and forest floor element masses in native and novel forests across a tropical island

Treesearch

H.E. Erickson; E.H. Helmer; T.J. Brandeis; A.E. Lugo

2014-01-01

Litter chemistry varies across landscapes according to factors rarely examined simultaneously. We analyzed 11 elements in forest floor (fallen) leaves and additional litter components from 143 forest inventory plots systematically located across Puerto Rico, a tropical island recovering from large-scale forest clearing. We assessed whether three existing, independently...

Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots

Treesearch

Karin Riley; Isaac C. Grenfell; Mark A. Finney

2016-01-01

Maps of the number, size, and species of trees in forests across the western United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical...

Use of ancillary data to improve the analysis of forest health indicators

Treesearch

Dave Gartner

2013-01-01

In addition to its standard suite of mensuration variables, the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service also collects data on forest health variables formerly measured by the Forest Health Monitoring program. FIA obtains forest health information on a subset of the base sample plots. Due to the sample size differences, the two sets of...

The extent and characteristics of low productivity aspen areas in Minnesota.

Treesearch

Gerhard K. Raile; Jerold T. Hahn

1982-01-01

Plot data from 1977 Minnesota forest inventory were used to evaluate the productivity of Minnesota's aspen forest. Computer simulation was used to develop equations for evaluating the current and potential productivity of aspen forest stands. The analysis showed that 49% of the state's aspen forest type was producing less than half of potential volume yields...

Federated States of Micronesia's forest resources, 2006

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 73 forested field plots on the islands of Kosrae, Chuuk, Pohnpei, and Yap in the Federated States of Micronesia (FSM). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden

2005-01-01

Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...

Preliminary results of spatial modeling of selected forest health variables in Georgia

Treesearch

Brock Stewart; Chris J. Cieszewski

2009-01-01

Variables relating to forest health monitoring, such as mortality, are difficult to predict and model. We present here the results of fitting various spatial regression models to these variables. We interpolate plot-level values compiled from the Forest Inventory and Analysis National Information Management System (FIA-NIMS) data that are related to forest health....

The role of remote sensing in process‐scaling studies of managed forest ecosystems

Treesearch

Jeffrey G. Masek; Daniel J. Hayes; M. Joseph Hughes; Sean P. Healey; David P. Turner

2015-01-01

Sustaining forest resources requires a better understanding of forest ecosystem processes, and how management decisions and climate change may affect these processes in the future. While plot and inventory data provide our most detailed information on forest carbon, energy, and water cycling, applying this understanding to broader spatial and temporal domains...

Analysis issues due to mapped conditions changing over time

Treesearch

Paul. Van Deusen

2015-01-01

Plot mapping is one of the innovations that were implemented when FIA moved to the annual forest inventory system. Mapped plots can improve the precision of estimates if the mapped conditions are carefully chosen and used judiciously. However, after plots are remeasured multiple times, it can be difficult to properly track changes in conditions and incorporate this...

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America.

PubMed

Stevens, Jens T; Safford, Hugh D; North, Malcolm P; Fried, Jeremy S; Gray, Andrew N; Brown, Peter M; Dolanc, Christopher R; Dobrowski, Solomon Z; Falk, Donald A; Farris, Calvin A; Franklin, Jerry F; Fulé, Peter Z; Hagmann, R Keala; Knapp, Eric E; Miller, Jay D; Smith, Douglas F; Swetnam, Thomas W; Taylor, Alan H

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the "stand age" variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical "mixed-severity" fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data.

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America

PubMed Central

Stevens, Jens T.; Safford, Hugh D.; North, Malcolm P.; Fried, Jeremy S.; Gray, Andrew N.; Brown, Peter M.; Dolanc, Christopher R.; Dobrowski, Solomon Z.; Falk, Donald A.; Farris, Calvin A.; Franklin, Jerry F.; Fulé, Peter Z.; Hagmann, R. Keala; Knapp, Eric E.; Miller, Jay D.; Smith, Douglas F.; Swetnam, Thomas W.; Taylor, Alan H.

2016-01-01

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the “stand age” variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical “mixed-severity” fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data. PMID:27196621

Adding net growth, removals, and mortality estimates for biomass and carbon in FIADB

Treesearch

Jeffery A. Turner

2015-01-01

Traditional growth, removals, and mortality (GRM) estimates produced from Forest Inventory and Analysis (FIA) periodic inventories were limited to changes in volume on timberland. Estimates on forestland were added in the east as the first installment of annual inventory plots was remeasured. The western FIA units have begun annual remeasurement, precipitating the need...

Analyzing Forest Inventory Data from Geo-Located Photographs

NASA Astrophysics Data System (ADS)

Toivanen, Timo; Tergujeff, Renne; Andersson, Kaj; Molinier, Matthieu; Häme, Tuomas

2015-04-01

Forests are widely monitored using a variety of remote sensing data and techniques. Remote sensing offers benefits compared to traditional in-situ forest inventories made by experts. One of the main benefits is that the number of ground reference plots can be significantly reduced. Remote sensing of forests can provide reduced costs and time requirement compared to full forest inventories. The availability of ground reference data has been a bottleneck in remote sensing analysis over wide forested areas, as the acquisition of this data is an expensive and slow process. In this paper we present a tool for estimating forest inventory data from geo-located photographs. The tool can be used to estimate in-situ forest inventory data including estimated biomass, tree species, tree height and diameter. The collected in-situ forest measurements can be utilized as a ground reference material for spaceborne or airborne remote sensing data analysis. The GPS based location information with measured forest data makes it possible to introduce measurements easily as in-situ reference data. The central projection geometry of digital photographs allows the use of the relascope principle [1] to measure the basal area of stems per area unit, a variable very closely associated with tree biomass. Relascope is applied all over the world for forest inventory. Experiments with independent ground reference data have shown that in-situ data analysed from photographs can be utilised as reference data for satellite image analysis. The concept was validated by comparing mobile measurements with 54 independent ground reference plots from the Hyytiälä forest research station in Finland [2]. Citizen scientists could provide the manpower for analysing photographs from forests on a global level and support researchers working on tasks related to forests. This low-cost solution can also increase the coverage of forest management plans, particularly in regions where possibilities to invest on expensive planning work are limited. References [1] Bitterlich, W. (1984) The Relascope Idea: Relative Measurements in Forestry, Commonwealth Agricultural Bureaux, Farnham Royal, 1984. [2] Molinier, M., Hame, T., Toivanen, T., Andersson, K., Mutanen, T., Relasphone -- Mobile phone and interactive applications to collect ground reference biomass data for satellite image analysis, Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, pp. 836-839, 13-18 July 2014, doi: 10.1109/IGARSS.2014.6946554

Model-assisted estimation of forest resources with generalized additive models

Treesearch

Jean D. Opsomer; F. Jay Breidt; Gretchen G. Moisen; Goran Kauermann

2007-01-01

Multiphase surveys are often conducted in forest inventories, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from...

Forests of Virginia, 2014

Treesearch

Anita Rose

2016-01-01

This resource update provides an overview of forest resources in Virginia. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year, 20 percent of the sample plots (one panel) in Virginia are measured by field crews, the data compiled, and new estimates produced. After 5 years of measurements,...

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S

Treesearch

Todd A. Schroeder; Sean P. Healey; Gretchen G. Moisen; Tracey S. Frescino; Warren B. Cohen; Chengquan Huang; Robert E. Kennedy; Zhiqiang Yang

2014-01-01

With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these...

Effects of rural residential development on forest communities in Oregon and Washington, USA

Treesearch

David L. Azuma; Bianca N.I. Eskelson; Joel L. Thompson

2014-01-01

Rural residential development in forests of Oregon and Washington continues to be a key driver of land use change. This type of development can have a variety of effects on the goods and services forests provide to the region. We used structure density from photo-interpreted points around forest inventory and analysis plots to examine differences in forest attributes...

Map of distribution of six forest ownership types in the conterminous United States

Treesearch

Jaketon H. Hewes; Brett J. Butler; Greg C. Liknes; Mark D. Nelson; Stephanie A. Snyder

2014-01-01

This map depicts the spatial distribution of ownership types across forest land in the conterminous United States circa 2009. The distribution is derived, in part, from Forest Inventory and Analysis (FIA) data that are collected at a sample intensity of approximately one plot per 2400 ha across the United States (U.S. Forest Service 2012). Ownership categories were...

Maine Forests 2013

Treesearch

George L. McCaskill; Thomas Albright; Charles J. Barnett; Brett J. Butler; Susan J. Crocker; Cassandra M. Kurtz; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Richard H. Widmann; Christopher W. Woodall

2016-01-01

The third 5-year annualized inventory of Maine's forests was completed in 2013 after more than 3170 forested plots were measured. Maine contains more than 17.6 million acres of forest land, an area that has been quite stable since 1960, covering more than 82 percent of the total land area. The number of live trees greater than 1 inch in diameter are approaching 24...

Tracking changes in the susceptibility of forest land infested with gypsy moth

Treesearch

David A. Gansner; John W. Quimby; Susan L. King; Stanford L. Arner; David A. Drake

1994-01-01

Does forest land subject to intensive outbreaks of gypsy moth (Lymantria dispar L.) become less susceptible to defoliation? A model for estimating the likelihood of gypsy moth defoliation has been developed and validated. It was applied to forest-inventory plot data to quantify trends in the susceptibility of forest land in south-central Pennsylvania during a period of...

Status of the Longleaf Pine Forests of the West Gulf Coastal Plain

Treesearch

Kenneth W. Outcalt

1997-01-01

Datafrom the USDA Forest Service, forest inventory and analyses permanent field plot were used to track changes in longleaf pine (Pinuspalustris Mill.) communities in Texas and Louisiana between 1985 and 1995. The decline of longleaf forest has continued in Louisiana. Texas had much less longleaf type in 1985, but unlike Louisiana there has been a small increase in the...

Fuel load modeling from mensuration attributes in temperate forests in northern Mexico

Treesearch

Maricela Morales-Soto; Marín Pompa-Garcia

2013-01-01

The study of fuels is an important factor in defining the vulnerability of ecosystems to forest fires. The aim of this study was to model a dead fuel load based on forest mensuration attributes from forest management inventories. A scatter plot analysis was performed and, from explanatory trends between the variables considered, correlation analysis was carried out...

Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

Treesearch

Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...

Forest resources of southeast Alaska, 2000: results of a single-phase systematic sample.

Treesearch

Willem W.S. van Hees

2003-01-01

A baseline assessment of forest resources in southeast Alaska was made by using a single-phase, unstratified, systematic-grid sample, with ground plots established at each grid intersection. Ratio-of-means estimators were used to develop population estimates. Forests cover an estimated 48 percent of the 22.9-million-acre southeast Alaska inventory unit. Dominant forest...

Multi-scale modeling of relationships between forest health and climatic factors

Treesearch

Michael K. Crosby; Zhaofei Fan; Xingang Fan; Martin A. Spetich; Theodor D. Leininger

2015-01-01

Forest health and mortality trends are impacted by changes in climate. These trends can vary by species, plot location, forest type, and/or ecoregion. To assess the variation among these groups, Forest Inventory and Analysis (FIA) data were obtained for 10 states in the southeastern United States and combined with downscaled climate data from the Weather Research and...

Access and Use of FIA Data Through FIA Spatial Data Services

Treesearch

Elizabeth LaPoint

2005-01-01

Forest Inventory and Analysis (FIA) Spatial Data Services (SDS) was established in May 2002 to facilitate outside access to FIA data and allow use of georeferenced plot data while protecting the confidentiality of plot locations. Modification of the Food Security Act of 1985 legislated the protection of information on plot location and ownership. Penalties were put in...

Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the southwestern USA

Treesearch

M. A. White; J. D. Shaw; R. D. Ramsey

2005-01-01

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado....

Field strategies for the calibration and validation of high-resolution forest carbon maps: Scaling from plots to a three state region MD, DE, & PA, USA.

NASA Astrophysics Data System (ADS)

Dolan, K. A.; Huang, W.; Johnson, K. D.; Birdsey, R.; Finley, A. O.; Dubayah, R.; Hurtt, G. C.

2016-12-01

In 2010 Congress directed NASA to initiate research towards the development of Carbon Monitoring Systems (CMS). In response, our team has worked to develop a robust, replicable framework to quantify and map aboveground forest biomass at high spatial resolutions. Crucial to this framework has been the collection of field-based estimates of aboveground tree biomass, combined with remotely detected canopy and structural attributes, for calibration and validation. Here we evaluate the field- based calibration and validation strategies within this carbon monitoring framework and discuss the implications on local to national monitoring systems. Through project development, the domain of this research has expanded from two counties in MD (2,181 km2), to the entire state of MD (32,133 km2), and most recently the tri-state region of MD, PA, and DE (157,868 km2) and covers forests in four major USDA ecological providences. While there are approximately 1000 Forest Inventory and Analysis (FIA) plots distributed across the state of MD, 60% fell in areas considered non-forest or had conditions that precluded them from being measured in the last forest inventory. Across the two pilot counties, where population and landuse competition is high, that proportion rose to 70% Thus, during the initial phases of this project 850 independent field plots were established for model calibration following a random stratified design to insure the adequate representation of height and vegetation classes found across the state, while FIA data were used as an independent data source for validation. As the project expanded to cover the larger spatial tri-state domain, the strategy was flipped to base calibration on more than 3,300 measured FIA plots, as they provide a standardized, consistent and available data source across the nation. An additional 350 stratified random plots were deployed in the Northern Mixed forests of PA and the Coastal Plains forests of DE for validation.

A general method for assessing the effects of uncertainty in individual-tree volume model predictions on large-area volume estimates with a subtropical forest illustration

Treesearch

Ronald E. McRoberts; Paolo Moser; Laio Zimermann Oliveira; Alexander C. Vibrans

2015-01-01

Forest inventory estimates of tree volume for large areas are typically calculated by adding the model predictions of volumes for individual trees at the plot level, calculating the mean over plots, and expressing the result on a per unit area basis. The uncertainty in the model predictions is generally ignored, with the result that the precision of the large-area...

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

Placing man in regional landscape classification: Use of Forest Survey data to assess human influences for southern U.S. forest ecosystems

Treesearch

Victor A. Rudis; John B. Tansey

1991-01-01

Information from plots surveyed by U.S.D.A., Forest Service, Forest Inventory and Analysis (FIA) units provides a basis for classifying human-dominated ecosystems at the regional scale of resolution.Attributes include forest stand measures, evidence of human influence, and other disturbances.Data from recent FIA surveys suggest that human influences are common to...

Does tree diversity increase wood production in pine forests?

PubMed

Vilà, Montserrat; Vayreda, Jordi; Gracia, Carles; Ibáñez, Joan Josep

2003-04-01

Recent experimental advances on the positive effect of species richness on ecosystem productivity highlight the need to explore this relationship in communities other than grasslands and using non-synthetic experiments. We investigated whether wood production in forests dominated by Aleppo pine (Pinus halepensis) and Pyrenean Scots pine (Pinus sylvestris) differed between monospecific and mixed forests (2-5 species) using the Ecological and Forest Inventory of Catalonia (IEFC) database which contains biotic and environmental characteristics for 10,644 field plots distributed within a 31,944 km(2) area in Catalonia (NE Spain). We found that in Pyrenean Scots pine forests wood production was not significantly different between monospecific and mixed plots. In contrast, in Aleppo pine forests wood production was greater in mixed plots than in monospecific plots. However, when climate, bedrock types, radiation and successional stage per plot were included in the analysis, species richness was no longer a significant factor. Aleppo pine forests had the highest productivity in plots located in humid climates and on marls and sandstone bedrocks. Climate did not influence wood production in Pyrenean Scots pine forests, but it was highest on sandstone and consolidated alluvial materials. For both pine forests wood production was negatively correlated with successional stage. Radiation did not influence wood production. Our analysis emphasizes the influence of macroenvironmental factors and temporal variation on tree productivity at the regional scale. Well-conducted forest surveys are an excellent source of data to test for the association between diversity and productivity driven by large-scale environmental factors.

Needs and Opportunities for Longleaf Pine Ecosystem Restoration in Florida

Treesearch

Kenneth W. Outcalt

1997-01-01

Data from permanent plots measured periodically by Forest Inventory and Analyses of the Southern Research Station, USDA Forest Service shows a continuing decline in the longleaf pine (Pinus pulustris Mill,) ecosystem in Florida from 1987 to 1995. Conversion to some other forest type resulted in a net loss of 58,000 ha natural stands of longleaf pine...

Extrapolating intensified forest inventory data to the surrounding landscape using landsat

Treesearch

Evan B. Brooks; John W. Coulston; Valerie A. Thomas; Randolph H. Wynne

2015-01-01

In 2011, a collection of spatially intensified plots was established on three of the Experimental Forests and Ranges (EFRs) sites with the intent of facilitating FIA program objectives for regional extrapolation. Characteristic coefficients from harmonic regression (HR) analysis of associated Landsat stacks are used as inputs into a conditional random forests model to...

Optimized endogenous post-stratification in forest inventories

Treesearch

Paul L. Patterson

2012-01-01

An example of endogenous post-stratification is the use of remote sensing data with a sample of ground data to build a logistic regression model to predict the probability that a plot is forested and using the predicted probabilities to form categories for post-stratification. An optimized endogenous post-stratified estimator of the proportion of forest has been...

A discrete global grid of photointerpretation

Treesearch

Joseph M McCollum; Jamie K. Cochran; Anita K. Rose

2008-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S.Department of Agriculture, collects its data in three phases. The first phase is collection of photointerpretation data or dot counts, the second phase is field collection of FIA plot data, and the third phase is collection of Forest Health Monitoring data. This paper describes the development...

Forests of South Carolina, 2014

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in South Carolina. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in South Carolina are measured by field crews, the data compiled, and new estimates produced. After 5 years of...

Forests of South Carolina, 2013

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in South Carolina. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in South Carolina are measured by field crews, the data compiled, and new estimates produced. After 5 years of...

Commonwealth of the Northern Mariana Islands' forest resources, 2004

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 37 field plots on the islands of Rota, Tinian, and Saipan in the Commonwealth of the Northern Mariana Islands (CNMI). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Evaluating a model to predict timber harvesting in Austria

Treesearch

Hubert Sterba; Michael Golser; Klemens Schadauer

2000-01-01

Between 1981 and 1985, the Austrian National Forest Inventory (ANF) established a set of 5,500 clusters, each with four permanent plots, covering all Austrian forests. After the first remeasurement between 1986 and 1990, models were developed to predict tree growth, mortality, and the behavior of forest owners in harvesting timber. A set of logistic equations describes...

Development and applications of the LANDFIRE forest structure layers

Treesearch

Chris Toney; Birgit Peterson; Don Long; Russ Parsons; Greg Cohn

2012-01-01

The LANDFIRE program is developing 2010 maps of vegetation and wildland fuel attributes for the United States at 30-meter resolution. Currently available vegetation layers include ca. 2001 and 2008 forest canopy cover and canopy height derived from Landsat and Forest Inventory and Analysis (FIA) plot measurements. The LANDFIRE canopy cover layer for the conterminous...

Change in area and ownership of private timberland in western Oregon between 1961-1962 and 1973-1976.

Treesearch

Donald R. Gedney

1981-01-01

A reinventory in 1973-76 of permanent inventory plots established in 1961-62 on western Oregon's forest industry and other private timberland provides data by ownership of timberland losses to nonforest land uses and changes in private ownership of timberland between inventories.

Monitoring stand structure in mature coastal Douglas-fir forests: effect of plot size.

Treesearch

Andrew Gray

2003-01-01

National and regional interest in the distribution and trends of forest habitat structure and diversity have placed demands on forest inventories for accurate stand-level data. a primary need in the coastal Pacific Northwest of the United States is information on the extent and rate of development of mature forest structure. The objective of this study was to evaluate...

A model-based approach to estimating forest area

Treesearch

Ronald E. McRoberts

2006-01-01

A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios

Treesearch

Jennifer K. Costanza; John W. Coulston; David N. Wear

2017-01-01

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and...

Average stand age from forest inventory plots does not describe historical fire regimes in ponderosa pine and mixed-conifer forests of western North America

Treesearch

Jens T. Stevens; Hugh D. Safford; Malcolm P. North; Jeremy S. Fried; Andrew N. Gray; Peter M. Brown; Christopher R. Dolanc; Solomon Z. Dobrowski; Donald A. Falk; Calvin A. Farris; Jerry F. Franklin; Peter Z. Fulé; R. Keala Hagmann; Eric E. Knapp; Jay D. Miller; Douglas F. Smith; Thomas W. Swetnam; Alan H. Taylor; Julia A. Jones

2016-01-01

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests...

Impact of ecological and socioeconomic determinants on the spread of tallow tree in southern forest lands

Treesearch

Yuan Tan; Joseph Z. Fan; Christopher M. Oswalt

2010-01-01

Based on USDA Forest Service Forest Inventory and Analysis (FIA) database, relationships between the presence of tallow tree and related driving variables including forest landscape metrics, stand and site conditions, as well as natural and anthropogenic disturbances were analyzed for the southern states infested by tallow trees. Of the 9,966 re-measured FIA plots in...

Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy.

PubMed

Gasparini, Patrizia; Di Cosmo, Lucio; Cenni, Enrico; Pompei, Enrico; Ferretti, Marco

2013-07-01

In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7%) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4% of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5% of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have-in general-smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample composition in terms of DBH (and likely age and structure) are desirable in Italy. As the adoption of a plot-based approach will keep a large share of the trees formerly selected, direct tree-by-tree comparison will remain possible, thus limiting the impact on the time series comparability. In addition, the plot-based design will favour the integration with NFI_2.

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

NASA Technical Reports Server (NTRS)

Morton, D. C.; Keller, M.; Cook, B. D.; Hunter, Maria; Sales, Marcio; Spinelli, L.; Victoria, D.; Andersen, H.-E.; Saleska, S.

2012-01-01

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Defoliation potential of gypsy moth

Treesearch

David A. Gansner; David A. Drake; Stanford L. Arner; Rachel R. Hershey; Susan L. King; Susan L. King

1993-01-01

A model that uses forest stand characteristics to estimate the likelihood of gypsy moth (Lymantria dispar L.) defoliation has been developed. It was applied to recent forest inventory plot data to produce susceptibility ratings and maps showing current defoliation potential in a seven-state area where gypsy moth is an immediate threat.

Predicting the Probability of Stand Disturbance

Treesearch

Gregory A. Reams; Joseph M. McCollum

1999-01-01

Forest managers are often interested in identifying and scheduling future stand treatment opportunities. One of the greatest management opportunities is presented following major stand level disturbances that result from natural or anthropogenic forces. Remeasurement data from the Forest Inventory and Analysis (FIA) permanent plot system are used to fit a set of...

Mapping the defoliation potential of gypsy moth

Treesearch

David A. Gansner; Stanford L. Arner; Rachel Riemann Hershey; Susan L. King

1993-01-01

A model that uses forest stand characteristics to estimate the likelihood of gypsy moth (Lymantria dispar) defoliation has been developed. It was applied to recent forest inventory plot data to produce susceptibility ratings and a map showing defoliation potential for counties in Pennsylvania and six adjacent states on new frontiers of infestation.

Observed effects of an exceptional drought on tree mortality in a tropical dry forest

NASA Astrophysics Data System (ADS)

Medvigy, D.; Vargas, G.; Xu, X.; Smith, C. M.; Becknell, J.; Brodribb, T.; Powers, J. S.

2016-12-01

Climate models predict that the coming century will bring reduced rainfall to Neotropical dry forests. It is unknown how tropical dry forest trees will respond to such rainfall reductions. Will there be increased mortality? If so, what will be the dominant mechanism of mortality? Will certain functional groups or size classes be more susceptible to unusually dry conditions and do functional traits underlie these patterns? With these questions in mind, we analyzed the response of trees from 18 Costa Rican tropical dry forest inventory plots and from additional transects to the exceptional 2015 drought that coincided with a strong ENSO event. We compared stand-level mortality rates observed during pre-drought years (2008-2014) and during the drought year of 2015 in the inventory plots. For both inventory plots and transects, we analyzed whether particular functional groups or size classes experienced exceptional mortality after the drought. We found that mortality rates were two to three times higher during the drought than before the drought. In contrast to observations at moist tropical forests, tree size had little influence on mortality. In terms of functional groups, mortality rates of evergreen oaks growing on nutrient-poor soils particularly increased during drought. Legumes seemed less affected by the drought than non-legumes. However, elevated mortality rates were not clearly correlated with commonly-measured traits like wood density or specific leaf area. Instead, hydraulic traits like P50 or turgor loss point may be better predictors of drought-driven mortality. In addition, trees that died during the drought tended to have smaller relative growth rate prior to the drought than trees that survived the drought.

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

Treesearch

Nicholas Skowronski; Kenneth Clark; Ross Nelson; John Hom; Matt Patterson

2007-01-01

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were...

Modeling forest mortality caused by drought stress: implications for climate change

Treesearch

Eric J Gustafson; Brian R. Sturtevant

2013-01-01

Climate change is expected to affect forest landscape dynamics in many ways, but it is possible that the most important direct impact of climate change will be drought stress. We combined data from weather stations and forest inventory plots (FIA) across the upper Great Lakes region (USA) to study the relationship between measures of drought stress and mortality for...

An assessment of Japanese stiltgrass in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2017-01-01

This publication is part of a series of research notes that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on...

Incidence of insects, diseases, and other damaging agents in Oregon forests.

Treesearch

Paul A. Dunham

2008-01-01

This report uses data from a network of forest inventory plots sampled at two points in time, annual aerial insect and disease surveys, and specialized pest damage surveys to quantify the incidence and impact of insects, diseases, and other damaging agents on Oregon's forests. The number and volume of trees damaged or killed by various agents is summarized....

From detection monitoring to evaluation monitoring - a case study involving crown dieback in northern white-cedar

Treesearch

KaDonna Randolph; William Bechtold; Randall Morin; Stanley Zarnoch

2009-01-01

The Forest Inventory and Analysis (FIA) Phase 3 plot network is a crucial part of the U.S. Forest Health Monitoring program's detection monitoring system, where select indicators are monitored for signals that may indicate deteriorating forest health. When a negative signal is identified, evaluation monitoring provides a mechanism whereby a potential problem can...

Development of forest regeneration imputation models using permanent plots in Oregon and Washington

Treesearch

Karin Kralicek; Andrew Sánchez Meador; Leah Rathbun

2015-01-01

Imputation models were developed and tested to estimate tree regeneration on Forest Service land in Oregon and Washington. The models were based on Forest Inventory and Analysis and Pacific Northwest Regional NFS Monitoring data. The data was processed into sets of tables containing estimates of regeneration by broad plant associations and spanning a large variety in...

The power of FIA Phase 3 Crown-Indicator variables to detect change

Treesearch

William Bechtold; KaDonna Randolph; Stanley Zarnoch

2009-01-01

The goal of Phase 3 Detection Monitoring as implemented by the Forest Inventory and Analysis Program is to identify forest ecosystems where conditions might be deteriorating in subtle ways over large areas. At the relatively sparse sampling intensity of the Phase 3 plot network, a rough measure of success for the forest health indicators developed for this purpose is...

Quantifying forest fragmentation using Geographic Information Systems and Forest Inventory and Analysis plot data

Treesearch

Dacia M. Meneguzzo; Mark H. Hansen

2009-01-01

Fragmentation metrics provide a means of quantifying and describing forest fragmentation. The most common method of calculating these metrics is through the use of Geographic Information System software to analyze raster data, such as a satellite or aerial image of the study area; however, the spatial resolution of the imagery has a significant impact on the results....

Forest area and conditions: a 2010 update of Chapter 16 of the Southern Forest Resource Assessment

Treesearch

Andrew J. Hartsell; Roger C. Conner

2013-01-01

This report updates the findings of Chapter 16 of the Southern Forest Resource Assessment (Wear and Greis 2002), based on 2010 report year data. Analysis focuses on changes in the South’s forest resources since 1999 using annual inventory, mapped-plot design data available for the first time for all 13 Southern States (excluding west Oklahoma and west Texas). The...

Evaluating elevated levels of crown dieback among northern white-cedar (Thuja occidentalis L.) trees in Maine and Michigan: a summary of evaluation monitoring

Treesearch

KaDonna Randolph; William A. Bechtold; Randall S. Morin; Stanley J. Zarnoch

2012-01-01

Analysis of crown condition data for the 2006 national technical report of the Forest Health Monitoring (FHM) Program of the Forest Service, U.S. Department of Agriculture, exposed clusters of phase 3 plots (by the Forest Inventory and Analysis [FIA] Program of the Forest Service) with northern white-cedar (Thuja occidentalis L.) crown dieback...

Amazonian landscapes and the bias in field studies of forest structure and biomass.

PubMed

Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul

2014-12-02

Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

A timer inventory based upon manual and automated analysis of ERTS-1 and supporting aircraft data using multistage probability sampling. [Plumas National Forest, California

NASA Technical Reports Server (NTRS)

Nichols, J. D.; Gialdini, M.; Jaakkola, S.

1974-01-01

A quasi-operational study demonstrating that a timber inventory based on manual and automated analysis of ERTS-1, supporting aircraft data and ground data was made using multistage sampling techniques. The inventory proved to be a timely, cost effective alternative to conventional timber inventory techniques. The timber volume on the Quincy Ranger District of the Plumas National Forest was estimated to be 2.44 billion board feet with a sampling error of 8.2 percent. Costs per acre for the inventory procedure at 1.1 cent/acre compared favorably with the costs of a conventional inventory at 25 cents/acre. A point-by-point comparison of CALSCAN-classified ERTS data with human-interpreted low altitude photo plots indicated no significant differences in the overall classification accuracies.

Alternative sampling designs and estimators for annual surveys

Treesearch

Paul C. Van Deusen

2000-01-01

Annual forest inventory systems in the United States have generally converged on sampling designs that: (1) measure equal proportions of the total number of plots each year; and (2) call for the plots to be systematically dispersed. However, there will inevitably be a need to deviate from the basic design to respond to special requests, natural disasters, and budgetary...

Using US Forest Inventory (FIA) Data to Test for Growth Enhancement

NASA Astrophysics Data System (ADS)

Masek, J. G.; Collatz, G. J.; Williams, C. A.

2015-12-01

It is recognized that land ecosystems sequester a significant fraction of anthropogenic carbon emissions, and that the magnitude of the "land sink" appears to be increasing through time. This observation has led to the hypothesis that forest ecosystems are experiencing more rapid growth than their historical norm, due to some combination of CO2 fertilization, longer growing seasons, nitrogen deposition, and more intensive management. Direct evidence for growth enhancment has been reported from experimental plots, where long-term (historical) rates of biomass accumulation appear lower than contemporary rates derived from remeasurement of individual trees. However, the approach has not been pursued at a national scale. Since the late 1990's the US Forest Inventory and Analysis (FIA) program has standardized plot locations across the United States, and has systematically remeasured tree and plot attributes on 5-year (east) or 10-year (west) cycles. In principle, these remeasured plots provide a robust dataset for comparing contemporary and historical growth rates. In this talk we review approaches for performing this comparison at both plot and tree scales. We find that recent plot-level biomass accumulation rates from the eastern US do show more rapid growth than would be expected from historical biomass-age curves, with enhancement factors of up 2x. However, the implicit inclusion of "cryptic" or older disturbances in the historical curves hinders a definitive interpretation. Stand-level age-biomass simulations confirm that disturbance events must be included in the remeasured data set in order to provide comparability with historical curves. Remeasured DBH measurements from individual trees may provide a more robust approach for examining the issue.

Stratified estimates of forest area using the k-nearest neighbors technique and satellite imagery

Treesearch

Ronald E. McRoberts; Mark D. Nelson; Daniel Wendt

2002-01-01

For two study areas in Minnesota, stratified estimation using Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-strata estimates. These measurements further served as calibration data...

Is there a better metric than site index to indicate the productivity of forested lands?

Treesearch

Maria E. Blanco Martin; Michael Hoppus; Andrew Lister; James A. Westfall

2009-01-01

The Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program selects site trees for each plot that are used to measure site productivity. The ability of a site to produce wood volume is indicated indirectly by comparing total tree height with tree age. This comparison assumes that the rate of height growth is strongly related to...

Aspen, climate, and sudden decline in western USA

Treesearch

Gerald E. Rehfeldt; Dennis E. Ferguson; Nicholas L. Crookston

2009-01-01

A bioclimate model predicting the presence or absence of aspen, Populus tremuloides, in western USA from climate variables was developed by using the Random Forests classification tree on Forest Inventory data from about 118,000 permanent sample plots. A reasonably parsimonious model used eight predictors to describe aspen's climate profile. Classification errors...

Opportunities to improve monitoring of temporal trends with FIA panel data

Treesearch

Raymond Czaplewski; Michael Thompson

2009-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, Department of Agriculture, is an annual monitoring system for the entire United States. Each year, an independent "panel" of FIA field plots is measured. To improve accuracy, FIA uses the "Moving Average" or "Temporally Indifferent" method to combine estimates from...

Sensitivity of FIA Volume Estimates to Changes in Stratum Weights and Number of Strata

Treesearch

James A. Westfall; Michael Hoppus

2005-01-01

In the Northeast region, the USDA Forest Service Forest Inventory and Analysis (FIA) program utilizes stratified sampling techniques to improve the precision of population estimates. Recently, interpretation of aerial photographs was replaced with classified remotely sensed imagery to determine stratum weights and plot stratum assignments. However, stratum weights...

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

Challenges of working with FIADB17 data: the SOLE experience

Treesearch

Michael Spinney; Paul Van Deusen

2007-01-01

The Southern On Line Estimator (SOLE) is an Internet-based Forest Inventory and Analysis (FIA) data analysis tool. SOLE is based on data downloaded from the publicly available FIA database (FIADB) and summarized by plot condition. The tasks of downloading, processing, and summarizing FIADB data require specialized expertise in inventory theory and data manipulation....

Comparison of carbon uptake estimates from forest inventory and Eddy-Covariance for a montane rainforest in central Sulawesi

NASA Astrophysics Data System (ADS)

Heimsch, Florian; Kreilein, Heiner; Rauf, Abdul; Knohl, Alexander

2016-04-01

Rainforests in general and montane rainforests in particular have rarely been studied over longer time periods. We aim to provide baseline information of a montane tropical forest's carbon uptake over time in order to quantify possible losses through land-use change. Thus we conducted a re-inventory of 22 10-year old forest inventory plots, giving us a rare opportunity to quantify carbon uptake over such a long time period by traditional methods. We discuss shortfalls of such techniques and why our estimate of 1.5 Mg/ha/a should be considered as the lower boundary and not the mean carbon uptake per year. At the same location as the inventory, CO2 fluxes were measured with the Eddy-Covariance technique. Measurements were conducted at 48m height with an LI 7500 open-path infrared gas analyser. We will compare carbon uptake estimates from these measurements to those of the more conventional inventory method and discuss, which factors are probably responsible for differences.

A baseline assessment of forest composition, structure, and health in the Hawai‘i experimental tropical forests

Treesearch

Robert R. Pattison; Andrew N. Gray; Lori Tango

2015-01-01

The US Forest Service’s Forest Inventory and Analysis (FIA) Program of the Pacific Northwest (PNW) Research Station has been working in the Hawaiian islands since 2010. During this time they have installed a base grid of field plots across all of the Hawaiian Islands and an intensified sample of two experimental forests, the Laupāhoehoe and Pu‘u Wa‘awa‘a units of the...

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

PubMed

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

Remeasurement of permanent vegetation plots in the Great Smoky Mountains National Park, Tennessee, USA, and the implications of climatic changes on vegetation. Environmental Sciences Division publication No. 1111

DOE Office of Scientific and Technical Information (OSTI.GOV)

Becking, R. W.; Olson, J. S.

1978-03-01

This report summarizes field work over two summers (1976 and 1977) to relocate, monument and reinventory permanent vegetation plots in the Great Smoky Mountains National Park. These plots were first established by the senior author and R.H. Whittaker in 1959-62. The inventory results are discussed in terms of vegetation changes in high-altitudinal forest ecosystems, in particular the spruce-fir forests, and the factors, climate shift and biotic and abiotic agents, bringing about vegetation change. A second aspect of the report summarizes experience and offers recommendations for establishment of permanent vegetation plots for the purpose of providing a monitoring tool with whichmore » to measure long-term ecological change.« less

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Treesearch

Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

2017-01-01

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

Location uncertainty and the tri-areal design

Treesearch

Francis A. Roesch

2007-01-01

The U.S. Department of Agriculture Forest Service Forest Inventory and Analysis Program (FIA) uses a field plot design that incorporates multiple sample selection mechanisms. Not all of the five FIA units currently use the entire suite of available sample selection mechanisms. These sampling selection mechanisms could be described in a number of ways with respect to...

Estimating mangrove in Florida: trials monitoring rare ecosystems

Treesearch

Mark J. Brown

2015-01-01

Mangrove species are keystone components in coastal ecosystems and are the interface between forest land and sea. Yet, estimates of their area have varied widely. Forest Inventory and Analysis (FIA) data from ground-based sample plots provide one estimate of the resource. Initial FIA estimates of the mangrove resource in Florida varied dramatically from those compiled...

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Treesearch

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia Wang

2014-01-01

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

Landsat TM Classifications For SAFIS Using FIA Field Plots

Treesearch

William H. Cooke; Andrew J. Hartsell

2001-01-01

Wall-to-wall Landsat Thematic Mapper (TM) classification efforts in Georgia require field validation. We developed a new crown modeling procedure based on Forest Health Monitoring (FHM) data to test Forest Inventory and Analysis (FIA) data. These models simulate the proportion of tree crowns that reflect light on a FIA subplot basis. We averaged subplot crown...

Sampling coarse woody debris along spoked transects

Treesearch

Paul C. Van Deusen; Jeffery H. Gove

2011-01-01

Line transects are commonly used for sampling coarse woody debris (CWD). The USDA Forest Service Forest Inventory and Analysis programme uses a variant of this method that involves sampling for CWD along transects that radiate from the centre of a circular plot-like spokes on a wheel. A new approach for analysis of data collected with spoked transects is developed....

Forest statistics for Arkansas' delta counties

Treesearch

Richard T. Quick; Mary S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 21 counties comprising the North and South Delta Units of Arkansas (fig. 1). Forest area was estimated from aerial photos with an adjustment for ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid oriented roughly N-S and E-W. At...

Forest statistics for Arkansas' Ouachita counties

Treesearch

T. Richard Quick; Marry S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 10 counties comprising the Quachita Unit of Arkansas (fig. 1). Forest area was estimated from aerial photos with an adjustment of ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid orientated roughly N-S and E-W. At each locations,...

Forest statistics for Arkansas' Ozark counties

Treesearch

T. Richard Quick; Mary S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 24 counties comprising the Ozark Unit of Arkansas (fib. 1). Forest area was estimated from aerial photos with an adjustment of ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid orientated roughly N-S and E-W. At each location,...

On FIA Variables For Ecological Use

Treesearch

David C. Chojnacky

2001-01-01

The Forest Inventory and Analysis (FIA) program collects or calculates over 300 variables for its national network of permanent forest plots. However, considerable ecological analysis can be done with only a few key variables. Two examples--Mexican spotted owl habitat in New Mexico and down deadwood in Maine--are used to illustrate the potential of FIA data for...

Fire effects assessment using FIA data in the northern and central Rocky Mountains

Treesearch

Theresa B. Jain; Ralph Their; Wilson Michael

2003-01-01

Wildfires of 2000 and 2001 burned thousands of hectares in the Northern Rocky Mountains. Within the fire parameters, 162 Forest Inventory and Analysis (FIA) plots burned in Idaho and Montana where pre-wildfire information on forest structure, vegetation composition, soil productivity, and surface fuels was documented; thus providing a unique opportunity to assess...

Long-term changes in fusiform rust incidence in the southeastern United States

Treesearch

KaDonna C. Randolph; Ellis B. Cowling; Dale A. Starkey

2015-01-01

Fusiform rust is the most devastating disease of slash pine (Pinus elliottii) and loblolly pine (Pinus taeda) in the southeastern United States. Since the 1970s, the USDA Forest Service Forest Inventory and Analysis (FIA) Program has assessed fusiform rust incidence on its network of ground plots in 13 states across the...

Location uncertainty and the tri-areal design

Treesearch

Francis A. Roesch

2005-01-01

The U.S. Department of Agriculture Forest Service Forest Inventory and Analysis Program (FTA) uses a field plot design that incorporates multiple sample selection mechanisms. Not all of the five FIA units currently use the entire suite of available sample selection mechanisms. These sampling selection mechanisms could be described in a number of ways with respect to...

Detecting tree-fall gap disturbances in tropical rain forests with airborne lidar

NASA Astrophysics Data System (ADS)

Espirito-Santo, F. D. B.; Saatchi, S.; Keller, M.

2017-12-01

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of tree-fall gap disturbances in natural forests of tropical forests using a novel combination of forest inventory and airborne lidar data. We quantify gap size frequency distribution along vertical and horizontal dimensions in ten Neotropical forest canopies distributed across gradients of climate and landscapes using airborne lidar measurements. We assessed all canopy openings related to each class of tree height which yields a three dimensional structure of the distribution of canopy gaps. Gap frequency distributions from lidar CHM data vary markedly with minimum gap size thresholds, but we found that natural forest disturbances (tree-fall gaps) follow a power-law distribution with narrow range of power-law exponents (-1.2 to -1.3). These power-law exponents from gap frequency distributions provide insights into how natural forest disturbances are distributed over tropical forest landscape.

Calibrating and testing a gap model for simulating forest management in the Oregon Coast Range

USGS Publications Warehouse

Pabst, R.J.; Goslin, M.N.; Garman, S.L.; Spies, T.A.

2008-01-01

The complex mix of economic and ecological objectives facing today's forest managers necessitates the development of growth models with a capacity for simulating a wide range of forest conditions while producing outputs useful for economic analyses. We calibrated the gap model ZELIG to simulate stand-level forest development in the Oregon Coast Range as part of a landscape-scale assessment of different forest management strategies. Our goal was to incorporate the predictive ability of an empirical model with the flexibility of a forest succession model. We emphasized the development of commercial-aged stands of Douglas-fir, the dominant tree species in the study area and primary source of timber. In addition, we judged that the ecological approach of ZELIG would be robust to the variety of other forest conditions and practices encountered in the Coast Range, including mixed-species stands, small-scale gap formation, innovative silvicultural methods, and reserve areas where forests grow unmanaged for long periods of time. We parameterized the model to distinguish forest development among two ecoregions, three forest types and two site productivity classes using three data sources: chronosequences of forest inventory data, long-term research data, and simulations from an empirical growth-and-yield model. The calibrated model was tested with independent, long-term measurements from 11 Douglas-fir plots (6 unthinned, 5 thinned), 3 spruce-hemlock plots, and 1 red alder plot. ZELIG closely approximated developmental trajectories of basal area and large trees in the Douglas-fir plots. Differences between simulated and observed conifer basal area for these plots ranged from -2.6 to 2.4 m2/ha; differences in the number of trees/ha ???50 cm dbh ranged from -8.8 to 7.3 tph. Achieving these results required the use of a diameter-growth multiplier, suggesting some underlying constraints on tree growth such as the temperature response function. ZELIG also tended to overestimate regeneration of shade-tolerant trees and underestimate total tree density (i.e., higher rates of tree mortality). However, comparisons with the chronosequences of forest inventory data indicated that the simulated data are within the range of variability observed in the Coast Range. Further exploration and improvement of ZELIG is warranted in three key areas: (1) modeling rapid rates of conifer tree growth without the need for a diameter-growth multiplier; (2) understanding and remedying rates of tree mortality that were higher than those observed in the independent data; and (3) improving the tree regeneration module to account for competition with understory vegetation. ?? 2008 Elsevier B.V.

Mapping forest structure and composition from low-density LiDAR for informed forest, fuel, and fire management at Eglin Air Force Base, Florida, USA

Treesearch

Andrew T. Hudak; Benjamin C. Bright; Scott M. Pokswinski; E. Louise Loudermilk; Joseph J. O' Brien; Benjamin S. Hornsby; Carine Klauberg; Carlos A. Silva

2016-01-01

Eglin Air Force Base (AFB) in Florida, in the United States, conserves a large reservoir of native longleaf pine (Pinus palustris Mill.) stands that land managers maintain by using frequent fires. We predicted tree density, basal area, and dominant tree species from 195 forest inventory plots, low-density airborne LiDAR, and Landsat data available across the entirety...

Stochastically generating tree diameter lists to populate forest stands based on the linkage variables forest type and stand age

Treesearch

Bernard R. Parresol; F. Thomas Lloyd

2003-01-01

Forest inventory data were used to develop a standage-driven, stochastic predictor of unit-area, frequency weighted lists of breast high tree diameters (DBH). The average of mean statistics from 40 simulation prediction sets of an independent 78-plot validation dataset differed from the observed validation means by 0.5 cm for DBH, and by 12 trees/h for density. The 40...

A density management diagram for longleaf pine stands with application to red-cockaded woodpecker habitat

Treesearch

John D. Shaw; James N. Long

2007-01-01

We developed a density management diagram (DMD) for longleaf pine (Pinus palustris P. Mill.) using data from Forest Inventory and Analysis plots. Selection criteria were for purity, defined as longleaf pine basal area (BA) that is 90% or more of plot BA, and even-agedness, as defined by a ratio between two calculations of stand density index. The...

A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data

Treesearch

B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann

2012-01-01

The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...

Thinning strategies to increase the regional availability of oak timber in the Mid-Appalachian Region

Treesearch

John R. Brooks; Jingxin Wang; Chris. LeDoux

2011-01-01

Plot data from 6,727 fully stocked oak-hickory stands were selected from Forest Inventory and Analysis data from five ecoregions common to West Virginia, Pennsylvania, Maryland, Virginia, Kentucky, and Ohio. Each plot was thinned from below using an existing thinning algorithm, where 30, 50, and 70 percent of the existing basal area was removed. These thinning...

Dominant height-based height-diameter equations for trees in southern Indiana

Treesearch

John A., Jr. Kershaw; Robert C. Morrissey; Douglass F. Jacobs; John R. Seifert; James B. McCarter

2008-01-01

Height-diameter equations are developed based on dominant tree data collected in 1986 in 8- to 17-year-old clearcuts and the phase 2 Forest Inventory and Analysis plots on the Hoosier National Forest in south central Indiana. Two equation forms are explored: the basic, three-parameter Chapman-Richards function, and a modification of the three-parameter equation...

Assessing forest mortality patterns using climate and FIA data at multiple scales

Treesearch

Michael K. Crosby; Zhaofei Fan; Xingang Fan; Theodor D. Leininger; Martin A. Spetich

2012-01-01

Forest Inventory and Analysis (FIA) and PRISM climate data from 1991-2000 were obtained for 10 states in the southeastern United States. Mortality was calculated for each plot, and annual values for precipitation and maximum and minimum temperature were extracted from the PRISM data. Data were then stratified by upland/bottomland for red oak species, and classification...

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

Treesearch

Barry Tyler Wilson; Christopher W. Woodall; Douglas M. Griffith

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these...

Missouri Ozark Forest Ecosystem Project: site history, soils, landforms, woody and herbaceous vegetation, down wood, and inventory methods for the landscape experiment.

Treesearch

Stephen R. Shifley; Brian L., eds. Brookshire

2000-01-01

Describes vegetation and physical site conditions at the initiation (1991-1995) of the Missouri Ozark Forest Ecosystem Project (MOFEP) in the southeastern Missouri Ozarks. Provides detailed information on sampling protocols and summarizes initial conditions of the landscape experiment prior to harvest treatments. Summaries are by plot, by ~800-acre...

Ecological impacts and management strategies for western larch in the face of climate-change

Treesearch

Gerald E. Rehfeldt; Barry C. Jaquish

2010-01-01

Approximately 185,000 forest inventory and ecological plots from both USA and Canada were used to predict the contemporary distribution of western larch (Larix occidentalis Nutt.) from climate variables. The random forests algorithm, using an 8-variable model, produced an overall error rate of about 2.9 %, nearly all of which consisted of predicting presence at...

Rate of value change in Pennsylvania timber stands

Treesearch

Owen W. Herrick

1984-01-01

Data from remeasured Pennsylvania forest inventory plots revealed that during a 13-year period the compound rate of value change in uncut hardwood forest stands averaged 4.7 percent, and ranged from -5.5 to 18.8 percent. No well-defined means for predicting a stand's rate of value change could be identified, However, some measures of initial stand condition can be...

Modeling biophysical properties of broad-leaved stands in the hyrcanian forests of Iran using fused airborne laser scanner data and ultraCam-D images

NASA Astrophysics Data System (ADS)

Mohammadi, Jahangir; Shataee, Shaban; Namiranian, Manochehr; Næsset, Erik

2017-09-01

Inventories of mixed broad-leaved forests of Iran mainly rely on terrestrial measurements. Due to rapid changes and disturbances and great complexity of the silvicultural systems of these multilayer forests, frequent repetition of conventional ground-based plot surveys is often cost prohibitive. Airborne laser scanning (ALS) and multispectral data offer an alternative or supplement to conventional inventories in the Hyrcanian forests of Iran. In this study, the capability of a combination of ALS and UltraCam-D data to model stand volume, tree density, and basal area using random forest (RF) algorithm was evaluated. Systematic sampling was applied to collect field plot data on a 150 m × 200 m sampling grid within a 1100 ha study area located at 36°38‧- 36°42‧N and 54°24‧-54°25‧E. A total of 308 circular plots (0.1 ha) were measured for calculation of stand volume, tree density, and basal area per hectare. For each plot, a set of variables was extracted from both ALS and multispectral data. The RF algorithm was used for modeling of the biophysical properties using ALS and UltraCam-D data separately and combined. The results showed that combining the ALS data and UltraCam-D images provided a slight increase in prediction accuracy compared to separate modeling. The RMSE as percentage of the mean, the mean difference between observed and predicted values, and standard deviation of the differences using a combination of ALS data and UltraCam-D images in an independent validation at 0.1-ha plot level were 31.7%, 1.1%, and 84 m3 ha-1 for stand volume; 27.2%, 0.86%, and 6.5 m2 ha-1 for basal area, and 35.8%, -4.6%, and 77.9 n ha-1 for tree density, respectively. Based on the results, we conclude that fusion of ALS and UltraCam-D data may be useful for modeling of stand volume, basal area, and tree density and thus gain insights into structural characteristics in the complex Hyrcanian forests.

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

Predicting spatial distribution of privet (liguestrum spp.) in South Carolina from MODIS and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2009-01-01

Privet's aggressive competitive behavior causes environmental harm to the ecosystem by degrading species diversity and wildlife habitat. Effective control of its spread requires high-quality spatial distribution information. Our...

Mapping site index and volume increment from forest inventory, Landsat, and ecological variables in Tahoe National Forest, California, USA

USGS Publications Warehouse

Huang, Shengli; Ramirez, Carlos; Conway, Scott; Kennedy, Kama; Kohler, Tanya; Liu, Jinxun

2016-01-01

High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by (i) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, (ii) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and (iii) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m3·ha−1·year−1. Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

An analytical method to assess spruce beetle impacts on white spruce resources, Kenai Peninsula, Alaska.

Treesearch

Willem W.S. van Hees

1992-01-01

Forest inventory data collected in 1987 fTom sample plots established on the Kenai Peninsula were analyzed to provide point-in-time estimates of the trend and current status of a spruce beetle infestation. Ground plots were categorized by stage of infestation. Estimates of numbers of live and dead white spruce trees, cubic-foot volume in those trees, and areal extent...

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites.

PubMed

Mitchard, Edward T A; Feldpausch, Ted R; Brienen, Roel J W; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R; Lewis, Simon L; Lloyd, Jon; Quesada, Carlos A; Gloor, Manuel; Ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragão, Luiz E O C; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I; Cerón, Carlos E; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R C; Di Fiore, Anthony; Domingues, Tomas F; Erwin, Terry L; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N; Killeen, Tim J; Laurance, William F; Levis, Carolina; Magnusson, William E; Marimon, Beatriz S; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T; Neill, David; Núñez Vargas, Mario P; Palacios, Walter A; Parada, Alexander; Pardo Molina, Guido; Peña-Claros, Marielos; Pitman, Nigel; Peres, Carlos A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H; Rudas, Agustin; Salomão, Rafael P; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F; Steininger, Marc K; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R; van der Heijden, Geertje M F; Vieira, Ima C G; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A; Wang, Ophelia; Zartman, Charles E; Malhi, Yadvinder; Phillips, Oliver L

2014-08-01

The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

PubMed Central

Mitchard, Edward T A; Feldpausch, Ted R; Brienen, Roel J W; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R; Lewis, Simon L; Lloyd, Jon; Quesada, Carlos A; Gloor, Manuel; ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragão, Luiz E O C; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I; Cerón, Carlos E; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R C; Di Fiore, Anthony; Domingues, Tomas F; Erwin, Terry L; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N; Killeen, Tim J; Laurance, William F; Levis, Carolina; Magnusson, William E; Marimon, Beatriz S; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T; Neill, David; Núñez Vargas, Mario P; Palacios, Walter A; Parada, Alexander; Pardo Molina, Guido; Peña-Claros, Marielos; Pitman, Nigel; Peres, Carlos A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H; Rudas, Agustin; Salomão, Rafael P; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F; Steininger, Marc K; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R; van der Heijden, Geertje M F; Vieira, Ima C G; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A; Wang, Ophelia; Zartman, Charles E; Malhi, Yadvinder; Phillips, Oliver L

2014-01-01

Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space. PMID:26430387

Comparative genetic responses to climate for the varieties of Pinus ponderosa and Pseudotsuga menziesii: realized climate niches

Treesearch

Gerald E. Rehfeldt; Barry C. Jaquish; Javier Lopez-Upton; Cuauhtemoc Saenz-Romero; J. Bradley St Clair; Laura P. Leites; Dennis G. Joyce

2014-01-01

The Random Forests classification algorithm was used to predict the occurrence of the realized climate niche for two sub-specific varieties of Pinus ponderosa and three varieties of Pseudotsuga menziesii from presence-absence data in forest inventory ground plots. Analyses were based on ca. 271,000 observations for P. ponderosa and ca. 426,000 observations for P....

Phytosociology of vascular plants on an international biosphere reserve: Virgin Islands National Park, St. John, US Virgin Islands

Treesearch

Sonja N. Oswalt; Thomas J. Brandies; Britta P. Dimick

2006-01-01

We investigated the relationships of vegetation communities to environmental variables and compared the relative contribution of native and introduced species in extant forest communities on St. John, US Virgin Islands, using an island-wide forest vegetation inventory and monitoring network of permanent plots. We detected 2,415 individuals of 203 species, 5 percent of...

Reproduction in Group Selection Openings 8 Years After Harvest in a Bottomland Mixed Hardwood Forest

Treesearch

Michael S. Golden

2002-01-01

Eight-year reproduction was inventoried in permanent plots in 10 small patch cuts in a mixed bottomland forest by the Tombigbee River in western Alabama. Overall, there was adequate reproduction of commercial tree species (1174 stems per acre), but there were some scattered unstacked areas. The overall reproduction of oaks was relatively poor (an average of 340 per...

Severity of a mountain pine beetle outbreak across a range of stand conditions in Fraser Experimental Forest, Colorado, United States

Treesearch

Anthony G. Vorster; Paul H. Evangelista; Thomas J. Stohlgren; Sunil Kumar; Charles C. Rhoades; Robert M. Hubbard; Antony S. Cheng; Kelly Elder

2017-01-01

The recent mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreaks had unprecedented effects on lodgepole pine (Pinus contorta var. latifolia) in western North America. We used data from 165 forest inventory plots to analyze stand conditions that regulate lodgepole pine mortality across a wide range of stand structure and species composition at the Fraser...

Phytosociology of Vascular Plants on an International Biosphere Reserve: Virgin Islands National Park, St. John, US Virgin Islands.

Treesearch

Sonja N. Oswalt; Thomas J. Brandeis; Britta P. Dimick

2006-01-01

We investigated the relationships of vegetation communities to environmental variables and compared the relative contribution of native and introduced species in extant forest communities on St. John, US Virgin Islands, using an island-wide forest vegetation inventory and monitoring network of permanent plots. We detected 2,415 individuals of 203 species, 5 percent of...

Forest dynamics in the temperate rainforests of Alaska: from individual tree to regional scales

Treesearch

Tara M. Barrett

2015-01-01

Analysis of remeasurement data from 1079 Forest Inventory and Analysis (FIA) plots revealed multi-scale change occurring in the temperate rainforests of southeast Alaska. In the western half of the region, including Prince William Sound, aboveground live tree biomass and carbon are increasing at a rate of 8 ( ± 2 ) percent per decade, driven by an increase in Sitka...

Genetic Linkage Mapping of Genomic Regions Conferring Tolerance to High Aluminum in Slash Pine

Treesearch

Thomas L. Kubisiak; C. Dana Nelson; J. Nowak; A.L. Friend

2000-01-01

Reports of reduced growth and vigor of forest trees in Europe and North America have been accumulating in recent years. In eastern North America, increased mortality and reduced radial growth rates have been noted for red spruce, frasier fir, and sugar maple. USDA Forest Service inventory data from permanent survey plots has revealed an unexpected reduction of radial...

Diversity and carbon storage across the tropical forest biome

NASA Astrophysics Data System (ADS)

Sullivan, Martin J. P.; Talbot, Joey; Lewis, Simon L.; Phillips, Oliver L.; Qie, Lan; Begne, Serge K.; Chave, Jerôme; Cuni-Sanchez, Aida; Hubau, Wannes; Lopez-Gonzalez, Gabriela; Miles, Lera; Monteagudo-Mendoza, Abel; Sonké, Bonaventure; Sunderland, Terry; Ter Steege, Hans; White, Lee J. T.; Affum-Baffoe, Kofi; Aiba, Shin-Ichiro; de Almeida, Everton Cristo; de Oliveira, Edmar Almeida; Alvarez-Loayza, Patricia; Dávila, Esteban Álvarez; Andrade, Ana; Aragão, Luiz E. O. C.; Ashton, Peter; Aymard C., Gerardo A.; Baker, Timothy R.; Balinga, Michael; Banin, Lindsay F.; Baraloto, Christopher; Bastin, Jean-Francois; Berry, Nicholas; Bogaert, Jan; Bonal, Damien; Bongers, Frans; Brienen, Roel; Camargo, José Luís C.; Cerón, Carlos; Moscoso, Victor Chama; Chezeaux, Eric; Clark, Connie J.; Pacheco, Álvaro Cogollo; Comiskey, James A.; Valverde, Fernando Cornejo; Coronado, Eurídice N. Honorio; Dargie, Greta; Davies, Stuart J.; de Canniere, Charles; Djuikouo K., Marie Noel; Doucet, Jean-Louis; Erwin, Terry L.; Espejo, Javier Silva; Ewango, Corneille E. N.; Fauset, Sophie; Feldpausch, Ted R.; Herrera, Rafael; Gilpin, Martin; Gloor, Emanuel; Hall, Jefferson S.; Harris, David J.; Hart, Terese B.; Kartawinata, Kuswata; Kho, Lip Khoon; Kitayama, Kanehiro; Laurance, Susan G. W.; Laurance, William F.; Leal, Miguel E.; Lovejoy, Thomas; Lovett, Jon C.; Lukasu, Faustin Mpanya; Makana, Jean-Remy; Malhi, Yadvinder; Maracahipes, Leandro; Marimon, Beatriz S.; Junior, Ben Hur Marimon; Marshall, Andrew R.; Morandi, Paulo S.; Mukendi, John Tshibamba; Mukinzi, Jaques; Nilus, Reuben; Vargas, Percy Núñez; Camacho, Nadir C. Pallqui; Pardo, Guido; Peña-Claros, Marielos; Pétronelli, Pascal; Pickavance, Georgia C.; Poulsen, Axel Dalberg; Poulsen, John R.; Primack, Richard B.; Priyadi, Hari; Quesada, Carlos A.; Reitsma, Jan; Réjou-Méchain, Maxime; Restrepo, Zorayda; Rutishauser, Ervan; Salim, Kamariah Abu; Salomão, Rafael P.; Samsoedin, Ismayadi; Sheil, Douglas; Sierra, Rodrigo; Silveira, Marcos; Slik, J. W. Ferry; Steel, Lisa; Taedoumg, Hermann; Tan, Sylvester; Terborgh, John W.; Thomas, Sean C.; Toledo, Marisol; Umunay, Peter M.; Gamarra, Luis Valenzuela; Vieira, Ima Célia Guimarães; Vos, Vincent A.; Wang, Ophelia; Willcock, Simon; Zemagho, Lise

2017-01-01

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.

Diversity and carbon storage across the tropical forest biome.

PubMed

Sullivan, Martin J P; Talbot, Joey; Lewis, Simon L; Phillips, Oliver L; Qie, Lan; Begne, Serge K; Chave, Jerôme; Cuni-Sanchez, Aida; Hubau, Wannes; Lopez-Gonzalez, Gabriela; Miles, Lera; Monteagudo-Mendoza, Abel; Sonké, Bonaventure; Sunderland, Terry; Ter Steege, Hans; White, Lee J T; Affum-Baffoe, Kofi; Aiba, Shin-Ichiro; de Almeida, Everton Cristo; de Oliveira, Edmar Almeida; Alvarez-Loayza, Patricia; Dávila, Esteban Álvarez; Andrade, Ana; Aragão, Luiz E O C; Ashton, Peter; Aymard C, Gerardo A; Baker, Timothy R; Balinga, Michael; Banin, Lindsay F; Baraloto, Christopher; Bastin, Jean-Francois; Berry, Nicholas; Bogaert, Jan; Bonal, Damien; Bongers, Frans; Brienen, Roel; Camargo, José Luís C; Cerón, Carlos; Moscoso, Victor Chama; Chezeaux, Eric; Clark, Connie J; Pacheco, Álvaro Cogollo; Comiskey, James A; Valverde, Fernando Cornejo; Coronado, Eurídice N Honorio; Dargie, Greta; Davies, Stuart J; De Canniere, Charles; Djuikouo K, Marie Noel; Doucet, Jean-Louis; Erwin, Terry L; Espejo, Javier Silva; Ewango, Corneille E N; Fauset, Sophie; Feldpausch, Ted R; Herrera, Rafael; Gilpin, Martin; Gloor, Emanuel; Hall, Jefferson S; Harris, David J; Hart, Terese B; Kartawinata, Kuswata; Kho, Lip Khoon; Kitayama, Kanehiro; Laurance, Susan G W; Laurance, William F; Leal, Miguel E; Lovejoy, Thomas; Lovett, Jon C; Lukasu, Faustin Mpanya; Makana, Jean-Remy; Malhi, Yadvinder; Maracahipes, Leandro; Marimon, Beatriz S; Junior, Ben Hur Marimon; Marshall, Andrew R; Morandi, Paulo S; Mukendi, John Tshibamba; Mukinzi, Jaques; Nilus, Reuben; Vargas, Percy Núñez; Camacho, Nadir C Pallqui; Pardo, Guido; Peña-Claros, Marielos; Pétronelli, Pascal; Pickavance, Georgia C; Poulsen, Axel Dalberg; Poulsen, John R; Primack, Richard B; Priyadi, Hari; Quesada, Carlos A; Reitsma, Jan; Réjou-Méchain, Maxime; Restrepo, Zorayda; Rutishauser, Ervan; Salim, Kamariah Abu; Salomão, Rafael P; Samsoedin, Ismayadi; Sheil, Douglas; Sierra, Rodrigo; Silveira, Marcos; Slik, J W Ferry; Steel, Lisa; Taedoumg, Hermann; Tan, Sylvester; Terborgh, John W; Thomas, Sean C; Toledo, Marisol; Umunay, Peter M; Gamarra, Luis Valenzuela; Vieira, Ima Célia Guimarães; Vos, Vincent A; Wang, Ophelia; Willcock, Simon; Zemagho, Lise

2017-01-17

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.

Diversity and carbon storage across the tropical forest biome

PubMed Central

Sullivan, Martin J. P.; Talbot, Joey; Lewis, Simon L.; Phillips, Oliver L.; Qie, Lan; Begne, Serge K.; Chave, Jerôme; Cuni-Sanchez, Aida; Hubau, Wannes; Lopez-Gonzalez, Gabriela; Miles, Lera; Monteagudo-Mendoza, Abel; Sonké, Bonaventure; Sunderland, Terry; ter Steege, Hans; White, Lee J. T.; Affum-Baffoe, Kofi; Aiba, Shin-ichiro; de Almeida, Everton Cristo; de Oliveira, Edmar Almeida; Alvarez-Loayza, Patricia; Dávila, Esteban Álvarez; Andrade, Ana; Aragão, Luiz E. O. C.; Ashton, Peter; Aymard C., Gerardo A.; Baker, Timothy R.; Balinga, Michael; Banin, Lindsay F.; Baraloto, Christopher; Bastin, Jean-Francois; Berry, Nicholas; Bogaert, Jan; Bonal, Damien; Bongers, Frans; Brienen, Roel; Camargo, José Luís C.; Cerón, Carlos; Moscoso, Victor Chama; Chezeaux, Eric; Clark, Connie J.; Pacheco, Álvaro Cogollo; Comiskey, James A.; Valverde, Fernando Cornejo; Coronado, Eurídice N. Honorio; Dargie, Greta; Davies, Stuart J.; De Canniere, Charles; Djuikouo K., Marie Noel; Doucet, Jean-Louis; Erwin, Terry L.; Espejo, Javier Silva; Ewango, Corneille E. N.; Fauset, Sophie; Feldpausch, Ted R.; Herrera, Rafael; Gilpin, Martin; Gloor, Emanuel; Hall, Jefferson S.; Harris, David J.; Hart, Terese B.; Kartawinata, Kuswata; Kho, Lip Khoon; Kitayama, Kanehiro; Laurance, Susan G. W.; Laurance, William F.; Leal, Miguel E.; Lovejoy, Thomas; Lovett, Jon C.; Lukasu, Faustin Mpanya; Makana, Jean-Remy; Malhi, Yadvinder; Maracahipes, Leandro; Marimon, Beatriz S.; Junior, Ben Hur Marimon; Marshall, Andrew R.; Morandi, Paulo S.; Mukendi, John Tshibamba; Mukinzi, Jaques; Nilus, Reuben; Vargas, Percy Núñez; Camacho, Nadir C. Pallqui; Pardo, Guido; Peña-Claros, Marielos; Pétronelli, Pascal; Pickavance, Georgia C.; Poulsen, Axel Dalberg; Poulsen, John R.; Primack, Richard B.; Priyadi, Hari; Quesada, Carlos A.; Reitsma, Jan; Réjou-Méchain, Maxime; Restrepo, Zorayda; Rutishauser, Ervan; Salim, Kamariah Abu; Salomão, Rafael P.; Samsoedin, Ismayadi; Sheil, Douglas; Sierra, Rodrigo; Silveira, Marcos; Slik, J. W. Ferry; Steel, Lisa; Taedoumg, Hermann; Tan, Sylvester; Terborgh, John W.; Thomas, Sean C.; Toledo, Marisol; Umunay, Peter M.; Gamarra, Luis Valenzuela; Vieira, Ima Célia Guimarães; Vos, Vincent A.; Wang, Ophelia; Willcock, Simon; Zemagho, Lise

2017-01-01

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity. PMID:28094794

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information.

PubMed

Mauro, Francisco; Monleon, Vicente J; Temesgen, Hailemariam; Ford, Kevin R

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey's height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates.

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information

PubMed Central

Monleon, Vicente J.; Temesgen, Hailemariam; Ford, Kevin R.

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey’s height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates. PMID:29216290

Airborne Laser Scanning of Forest Stem Volume in a Mountainous Environment

PubMed Central

Hollaus, Markus; Wagner, Wolfgang; Maier, Bernhard; Schadauer, Klemens

2007-01-01

Airborne laser scanning (ALS) is an active remote sensing technique that uses the time-of-flight measurement principle to capture the three-dimensional structure of the earth's surface with pulsed lasers that transmit nanosecond-long laser pulses with a high pulse repetition frequency. Over forested areas most of the laser pulses are reflected by the leaves and branches of the trees, but a certain fraction of the laser pulses reaches the forest floor through small gaps in the canopy. Thus it is possible to reconstruct both the three-dimensional structure of the forest canopy and the terrain surface. For the retrieval of quantitative forest parameters such as stem volume or biomass it is necessary to use models that combine ALS with inventory data. One approach is to use multiplicative regression models that are trained with local inventory data. This method has been widely applied over boreal forest regions, but so far little experience exists with applying this method for mapping alpine forest. In this study the transferability of this approach to a 128 km2 large mountainous region in Vorarlberg, Austria, was evaluated. For the calibration of the model, inventory data as operationally collected by Austrian foresters were used. Despite these inventory data are based on variable sample plot sizes, they could be used for mapping stem volume for the entire alpine study area. The coefficient of determination R2 was 0.85 and the root mean square error (RMSE) 90.9 m3ha−1 (relative error of 21.4%) which is comparable to results of ALS studies conducted over topographically less complex environments. Due to the increasing availability, ALS data could become an operational part of Austrian's forest inventories.

Forest above ground biomass estimation and forest/non-forest classification for Odisha, India, using L-band Synthetic Aperture Radar (SAR) data

NASA Astrophysics Data System (ADS)

Suresh, M.; Kiran Chand, T. R.; Fararoda, R.; Jha, C. S.; Dadhwal, V. K.

2014-11-01

Tropical forests contribute to approximately 40 % of the total carbon found in terrestrial biomass. In this context, forest/non-forest classification and estimation of forest above ground biomass over tropical regions are very important and relevant in understanding the contribution of tropical forests in global biogeochemical cycles, especially in terms of carbon pools and fluxes. Information on the spatio-temporal biomass distribution acts as a key input to Reducing Emissions from Deforestation and forest Degradation Plus (REDD+) action plans. This necessitates precise and reliable methods to estimate forest biomass and to reduce uncertainties in existing biomass quantification scenarios. The use of backscatter information from a host of allweather capable Synthetic Aperture Radar (SAR) systems during the recent past has demonstrated the potential of SAR data in forest above ground biomass estimation and forest / nonforest classification. In the present study, Advanced Land Observing Satellite (ALOS) / Phased Array L-band Synthetic Aperture Radar (PALSAR) data along with field inventory data have been used in forest above ground biomass estimation and forest / non-forest classification over Odisha state, India. The ALOSPALSAR 50 m spatial resolution orthorectified and radiometrically corrected HH/HV dual polarization data (digital numbers) for the year 2010 were converted to backscattering coefficient images (Schimada et al., 2009). The tree level measurements collected during field inventory (2009-'10) on Girth at Breast Height (GBH at 1.3 m above ground) and height of all individual trees at plot (plot size 0.1 ha) level were converted to biomass density using species specific allometric equations and wood densities. The field inventory based biomass estimations were empirically integrated with ALOS-PALSAR backscatter coefficients to derive spatial forest above ground biomass estimates for the study area. Further, The Support Vector Machines (SVM) based Radial Basis Function classification technique was employed to carry out binary (forest-non forest) classification using ALOSPALSAR HH and HV backscatter coefficient images and field inventory data. The textural Haralick's Grey Level Cooccurrence Matrix (GLCM) texture measures are determined on HV backscatter image for Odisha, for the year 2010. PALSAR HH, HV backscatter coefficient images, their difference (HHHV) and HV backscatter coefficient based eight textural parameters (Mean, Variance, Dissimilarity, Contrast, Angular second moment, Homogeneity, Correlation and Contrast) are used as input parameters for Support Vector Machines (SVM) tool. Ground based inputs for forest / non-forest were taken from field inventory data and high resolution Google maps. Results suggested significant relationship between HV backscatter coefficient and field based biomass (R2 = 0.508, p = 0.55) compared to HH with biomass values ranging from 5 to 365 t/ha. The spatial variability of biomass with reference to different forest types is in good agreement. The forest / nonforest classified map suggested a total forest cover of 50214 km2 with an overall accuracy of 92.54 %. The forest / non-forest information derived from the present study showed a good spatial agreement with the standard forest cover map of Forest Survey of India (FSI) and corresponding published area of 50575 km2. Results are discussed in the paper.

Analysis And Assessment Of Forest Cover Change For The State Of Wisconsin

NASA Astrophysics Data System (ADS)

Perry, C. H.; Nelson, M. D.; Stueve, K.; Gormanson, D.

2010-12-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service is charged with documenting the status and trends of forest resources of the United States. Since the 1930s, FIA has implemented an intensive field campaign that collects measurements on plots distributed across all ownerships, historically completing analyses which include estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Originally a periodic inventory, FIA has been measuring plots on an annual basis since the passage of the Agriculture Research, Extension and Education Reform Act of 1998 (Farm Bill). The resulting change in sampling design and intensity presents challenges to establishing baseline and measuring changes in forest area and biomass. A project jointly sponsored by the Forest Service and the National Aeronautics and Space Agency (NASA) titled “Integrating Landscape-scale Forest Measurements with Remote Sensing and Ecosystem Models to Improve Carbon Management Decisions” seeks to improve estimates of landscape- and continental-scale carbon dynamics and causes of change for North American forest land, and to use this information to support land management decisions. Specifically, we are developing and applying methods to scale up intensive biomass and carbon measurements from the field campaign to larger land management areas while simultaneously estimating change in the above-ground forest carbon stocks; the State of Wisconsin is being used as the testbed for this large-scale integration remote sensing with field measurements. Once defined, the temporal and spatial patterns of forest resources by watershed for Lake Superior and Lake Michigan outputs are being integrated into water quality assessments for the Great Lakes.

Long-term tree inventory data from mountain forest plots in France.

PubMed

Fuhr, Marc; Cordonnier, Thomas; Courbaud, Benoît; Kunstler, Georges; Mermin, Eric; Riond, Catherine; Tardif, Pascal

2017-04-01

We present repeated tree measurement data from 63 permanent plots in mountain forests in France. Plot elevations range from 800 (lower limit of the montane belt) to 1942 m above sea level (subalpine belt). Forests mainly consist of pure or mixed stands dominated by European beech (Fagus sylvatica), Silver fir (Abies alba), and Norway spruce (Picea abies), in association with various broadleaved species at low elevation and with Arolla pine (Pinus cembra) at high elevation. The plot network includes 23 plots in stands that have not been managed for the last 40 years (at least) and 40 plots in plots managed according to an uneven-aged system with single-tree or small-group selection cutting. Plot sizes range from 0.2 to 1.9 ha. Plots were installed from 1994 to 2004 and remeasured two to five times during the 1994-2015 period. During the first census (installation), living trees more than 7.5 cm in dbh were identified, their diameter at breast height (dbh) was measured and their social status (strata) noted. Trees were spatially located, either with x, y, and z coordinates (40 plots) or within 0.25-ha square subplots (23 plots). In addition, in a subset of plots (58 plots), tree heights and tree crown dimensions were measured on a subset of trees and dead standing trees and stumps were included in the census. Remeasurements after installation include live tree diameters (including recruited trees), tree status (living, damaged, dead, stump), and for a subset of trees, height. At the time of establishment of the plots, plot densities range from 181 to 1328 stems/ha and plot basal areas range from 13.6 to 81.3 m 2 /ha. © 2017 by the Ecological Society of America.

Implications of land-use change on forest carbon stocks in the eastern United States

NASA Astrophysics Data System (ADS)

Puhlick, Joshua; Woodall, Christopher; Weiskittel, Aaron

2017-02-01

Given the substantial role that forests play in removing CO2 from the atmosphere, there has been a growing need to evaluate the carbon (C) implications of various forest management and land-use decisions. Although assessment of land-use change is central to national-level greenhouse gas monitoring guidelines, it is rarely incorporated into forest stand-level evaluations of C dynamics and trajectories. To better inform the assessment of forest stand C dynamics in the context of potential land-use change, we used a region-wide repeated forest inventory (n = 71 444 plots) across the eastern United States to assess forest land-use conversion and associated changes in forest C stocks. Specifically, the probability of forest area reduction between 2002-2006 and 2007-2012 on these plots was related to key driving factors such as proportion of the landscape in forest land use, distance to roads, and initial forest C. Additional factors influencing the actual reduction in forest area were then used to assess the risk of forest land-use conversion to agriculture, settlement, and water. Plots in forests along the Great Plains had the highest periodic (approximately 5 years) probability of land-use change (0.160 ± 0.075; mean ± SD) with forest conversion to agricultural uses accounting for 70.5% of the observed land-use change. Aboveground forest C stock change for plots with a reduction in forest area was -4.2 ± 17.7 Mg ha-1 (mean ± SD). The finding that poorly stocked stands and/or those with small diameter trees had the highest probability of conversion to non-forest land uses suggests that forest management strategies can maintain the US terrestrial C sink not only in terms of increased net forest growth but also retention of forest area to avoid conversion. This study highlights the importance of considering land-use change in planning and policy decisions that seek to maintain or enhance regional C sinks.

Stand Dynamics in an Old-Growth Hardwood Forest in Southern Illinois, USA

Treesearch

James J. Zaczek; John W. Groninger; J. W. Van Sambeek

2002-01-01

Kaskaskia Woods, a 7.4-ha old-growth hardwood forest in southern Illinois, USA, has been managed as a natural area and protected from disturbance since 1933. In 1935, eight 0.1-ha plots were installed and all trees 4 cm dbh or larger were tagged and inventoried. Trees were remeasured for survival, ingrowth (new trees >4 cm), and diameter (dbh) in 1940, 1958, 1965,...

Baseline results from the Lichen Community Indicator Program in the Pacific Northwest: Air quality patterns and evidence of a nitrogen pollution problem

Treesearch

Sarah Jovan

2009-01-01

Why Are Epiphytic Lichen Communities Important? Lichens are one of the bioindicators used by the Forest Inventory and Analysis (FIA) Program to monitor forest health. To obtain data for use in its Lichen Community Indicator Program, FIA samples a regular network of permanent field plots to determine the composition of epiphytic, i.e., tree dwelling, lichen communities...

Use of the Weibull function to predict future diameter distributions from current plot data

Treesearch

Quang V. Cao

2012-01-01

The Weibull function has been widely used to characterize diameter distributions in forest stands. The future diameter distribution of a forest stand can be predicted by use of a Weibull probability density function from current inventory data for that stand. The parameter recovery approach has been used to “recover” the Weibull parameters from diameter moments or...

Storage and flux of carbon in live trees, snags, and logs in the Chugach and Tongass national forests

Treesearch

Tara Barrett

2014-01-01

Carbon storage and flux estimates for the two national forests in Alaska are provided using inventory data from permanent plots established in 1995–2003 and remeasured in 2004–2010. Estimates of change are reported separately for growth, sapling recruitment, harvest, mortality, snag recruitment, salvage, snag falldown, and decay. Although overall aboveground carbon...

Can cover data be used as a surrogate for seedling counts in regeneration stocking evaluations in northern hardwood forests?

Treesearch

Todd E. Ristau; Susan L. Stout

2014-01-01

Assessment of regeneration can be time-consuming and costly. Often, foresters look for ways to minimize the cost of doing inventories. One potential method to reduce time required on a plot is use of percent cover data rather than seedling count data to determine stocking. Robust linear regression analysis was used in this report to predict seedling count data from...

Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

Treesearch

Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

2017-01-01

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

Assessing Forest NPP: BIOME-BGC Predictions versus BEF Derived Estimates

NASA Astrophysics Data System (ADS)

Hasenauer, H.; Pietsch, S. A.; Petritsch, R.

2007-05-01

Forest productivity has always been a major issue within sustainable forest management. While in the past terrestrial forest inventory data have been the major source for assessing forest productivity, recent developments in ecosystem modeling offer an alternative approach using ecosystem models such as Biome-BGC to estimate Net Primary Production (NPP). In this study we compare two terrestrial driven approaches for assessing NPP: (i) estimates from a species specific adaptation of the biogeochemical ecosystem model BIOME-BGC calibrated for Alpine conditions; and (ii) NPP estimates derived from inventory data using biomass expansion factors (BEF). The forest inventory data come from 624 sample plots across Austria and consist of repeated individual tree observations and include growth as well as soil and humus information. These locations are covered with spruce, beech, oak, pine and larch stands, thus addressing the main Austrian forest types. 144 locations were previously used in a validating effort to produce species-specific parameter estimates of the ecosystem model. The remaining 480 sites are from the Austrian National Forest Soil Survey carried out at the Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW). By using diameter at breast height (dbh) and height (h) volume and subsequently biomass of individual trees were calculated, aggregated for the whole forest stand and compared with the model output. Regression analyses were performed for both volume and biomass estimates.

Modeling the uncertainty of estimating forest carbon stocks in China

NASA Astrophysics Data System (ADS)

Yue, T. X.; Wang, Y. F.; Du, Z. P.; Zhao, M. W.; Zhang, L. L.; Zhao, N.; Lu, M.; Larocque, G. R.; Wilson, J. P.

2015-12-01

Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA). The estimates produced with HASM-SOA were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

Biomass and carbon dynamics of a tropical mountain rain forest in China.

PubMed

Chen, DeXiang; Li, YiDe; Liu, HePing; Xu, Han; Xiao, WenFa; Luo, TuShou; Zhou, Zhang; Lin, MingXian

2010-07-01

Biometric inventories for 25 years, from 1983 to 2005, indicated that the Jianfengling tropical mountain rain forest in Hainan, China, was either a source or a modest sink of carbon. Overall, this forest was a small carbon sink with an accumulation rate of (0.56+/-0.22) Mg C ha(-1)yr(-1), integrated from the long-term measurement data of two plots (P9201 and P8302). These findings were similar to those for African and American rain forests ((0.62+/-0.23) Mg C ha(-1)yr(-1)). The carbon density varied between (201.43+/-29.38) Mg C ha(-1) and (229.16+/-39.2) Mg C ha(-1), and averaged (214.17+/-32.42) Mg C ha(-1) for plot P9201. Plot P8302, however, varied between (223.95+/-45.92) Mg C ha(-1) and (254.85+/-48.86) Mg C ha(-1), and averaged (243.35+/-47.64) Mg C ha(-1). Quadratic relationships were found between the strength of carbon sequestration and heavy rainstorms and dry months. Precipitation and evapotranspiration are two major factors controlling carbon sequestration in the tropical mountain rain forest.

Historical Human Footprint on Modern Tree Species Composition in the Purus-Madeira Interfluve, Central Amazonia

PubMed Central

Levis, Carolina; de Souza, Priscila Figueira; Schietti, Juliana; Emilio, Thaise; Pinto, José Luiz Purri da Veiga; Clement, Charles R.; Costa, Flavia R. C.

2012-01-01

Background Native Amazonian populations managed forest resources in numerous ways, often creating oligarchic forests dominated by useful trees. The scale and spatial distribution of forest modification beyond pre-Columbian settlements is still unknown, although recent studies propose that human impact away from rivers was minimal. We tested the hypothesis that past human management of the useful tree community decreases with distance from rivers. Methodology/Principal Findings In six sites, we inventoried trees and palms with DBH≥10 cm and collected soil for charcoal analysis; we also mapped archaeological evidence around the sites. To quantify forest manipulation, we measured the relative abundance, richness and basal area of useful trees and palms. We found a strong negative exponential relationship between forest manipulation and distance to large rivers. Plots located from 10 to 20 km from a main river had 20–40% useful arboreal species, plots between 20 and 40 km had 12–23%, plots more than 40 km had less than 15%. Soil charcoal abundance was high in the two sites closest to secondary rivers, suggesting past agricultural practices. The shortest distance between archaeological evidence and plots was found in sites near rivers. Conclusions/Significance These results strongly suggest that past forest manipulation was not limited to the pre-Columbian settlements along major rivers, but extended over interfluvial areas considered to be primary forest today. The sustainable use of Amazonian forests will be most effective if it considers the degree of past landscape domestication, as human-modified landscapes concentrate useful plants for human sustainable use and management today. PMID:23185264

Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

NASA Astrophysics Data System (ADS)

Karila, K.; Karjalainen, M.; Yu, X.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

2015-04-01

Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project "Advanced_SAR" was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m2). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better performance in forest attribute (i.e. mean tree height, basal area, mean stem diameter, stem volume, and biomass) prediction than stereo-radargrammetry. The results were 20.1% and 28.6% in relative root mean square error (RMSE) for biomass prediction, for TDX and TSX respectively.

A multi-scale assessment of forest primary production across the eastern USA using Forest Inventory and Analysis (FIA) and MODIS data

NASA Astrophysics Data System (ADS)

Kwon, Youngsang

As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale MODIS and FIA were most strongly correlated while maximizing the number of observation. The maps conveyed both local-scale spatial structure from FIA and broad-scale climatic trends from MODIS. The third objective examined whether carbon use efficiency (CUE) was constant or variable in relation to forest types, and to geographic and climatic variables. The results indicated that while CUEs exhibited unclear patterns by forest types, CUEs are variable to other environmental variables. CUEs are most strongly related to the climatic factors of precipitation followed by temperature. More complex and weaker relationships were found for the geographic factors of latitude and altitude, as they reflected a combination of phenomenological driving forces. The results of the three objectives will help us to identify factors that control carbon cycles and to quantify forest productivity. This will help improve our knowledge about how forest primary productivity may change in relation to ongoing climate change.

The extent and characteristics of low-productivity aspen areas in Wisconsin.

Treesearch

Allen L. Lundgren; Jerold T. Hahn

1978-01-01

An analysis of inventory plots from Wisconsin's forest survey showed that 18% of the state's 3.7 million acres of aspen type was producing less than a quarter of potential volume yields and 47% was producing less than half of potential volume yields.

Relative abundance, habitat use, and long-term population changes of wintering and resident landbirds on St. John, U.S. Virgin Islands

Treesearch

D.W. Steadman; J.R. Montambault; Scott K. Robinson; S.N. Oswalt; T.J. Brandeis; A. Gustavo Londoño; M.J. Reetz; W.M. Schelsky; N.A. Wright; J.P. Hoover; J. Jankowski; A.W. Kratter; A.E. Martinez; J. Smith

2009-01-01

St. John, U.S. Virgin Islands, is one of the most forested islands in the West Indies and provides an opportunity to conserve both resident birds and wintering neotropical migrants.We conducted double-observer point counts of landbirds in December 2005 and 2006 in Forest Inventory and Analysis (FIA) plots and National] Park Service (NPS) trails in Virgin Islands...

Relative abundance, habitat use, and long-term population changes of wintering and resident landbirds on St. John, U.S. Virgin Islands

Treesearch

David Steadman; Jensen Montambault; Scott Robinson; Sonja Oswalt; Thomas Brandeis; Agustavo Londono; Matthew Reetz; Wendy Schelsky; Natalie Wright; Jeffrey Hoover; Jill Jankowski; Andrew Kratter; Arie Martínez; Jordan Smith

2009-01-01

St. John, U.S. Virgin Islands, is one of the most forested islands in the West Indies and provides an opportunity to conserve both resident birds and wintering neotropical migrants.We conducted double-observer point counts of landbirds in December 2005 and 2006 in Forest Inventory and Analysis (FIA) plots and National Park Service (NPS) trails in Virgin Islands...

Alternative interpretation and scale-based context for “No evidence of recent (1995–2013) decrease of yellow-cedar in Alaska” (Barrett and Pattison 2017)

Treesearch

Allison Bidlack; Sarah Bisbing; Brian Buma; David D’Amore; Paul Hennon; Thomas Heutte; John Krapek; Robin Mulvey; Lauren Oakes

2017-01-01

In their analysis of resampled and remeasured plot data from the USDA Forest Service Forest Inventory and Analysis (FIA) program, Barrett and Pattison (2017, Can. J. For. Res. 47(1): 97–105, doi:10.1139/cjfr-2016-0335) suggest that there is neither evidence of a recent regional decrease in yellow-cedar (Callitropsis nootkatensis...

Spatio-Temporal Trends of Oak Decline and Mortality under Periodic Regional Drought in the Ozark Highlands of Arkansas and Missouri

Treesearch

Zhaofei Fan; Xiuli Fan; Michael K. Crosby; W. Keith Moser; Hong He; Martin A. Spetich; Stephen R. Shifley

2012-01-01

At the forest landscape/region level, based on annual Forest Inventory and Analysis plot data from 1999 to 2010, oak decline and mortality trends for major oak species (groups) were examined in the Ozark Highlands of Arkansas and Missouri. Oak decline has elevated cumulative mortality of red oak species to between 11 and 15 percent in terms of relative density and...

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

PubMed Central

Espírito-Santo, Fernando D.B.; Gloor, Manuel; Keller, Michael; Malhi, Yadvinder; Saatchi, Sassan; Nelson, Bruce; Junior, Raimundo C. Oliveira; Pereira, Cleuton; Lloyd, Jon; Frolking, Steve; Palace, Michael; Shimabukuro, Yosio E.; Duarte, Valdete; Mendoza, Abel Monteagudo; López-González, Gabriela; Baker, Tim R.; Feldpausch, Ted R.; Brienen, Roel J.W.; Asner, Gregory P.; Boyd, Doreen S.; Phillips, Oliver L.

2014-01-01

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink. PMID:24643258

Size and frequency of natural forest disturbances and the Amazon forest carbon balance.

PubMed

Espírito-Santo, Fernando D B; Gloor, Manuel; Keller, Michael; Malhi, Yadvinder; Saatchi, Sassan; Nelson, Bruce; Junior, Raimundo C Oliveira; Pereira, Cleuton; Lloyd, Jon; Frolking, Steve; Palace, Michael; Shimabukuro, Yosio E; Duarte, Valdete; Mendoza, Abel Monteagudo; López-González, Gabriela; Baker, Tim R; Feldpausch, Ted R; Brienen, Roel J W; Asner, Gregory P; Boyd, Doreen S; Phillips, Oliver L

2014-03-18

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y(-1) over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y(-1), and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y(-1). Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Multiscale assessment of water limitations on forest carbon cycling in the western United States

NASA Astrophysics Data System (ADS)

Berner, L. T.; Law, B. E.

2016-12-01

Water is a key environmental constraint on carbon uptake, storage, and release by forests in the western United States. Climate in this region is becoming warmer and drier, thus highlighting the need to better understand how forest carbon cycling responds to variation in water availability. Here, we describe how forest carbon cycling varied spatially along local to regional gradients in climatic water availability. We examined local variation in net primary productivity (NPP) and aboveground biomass (AGB) using 12 intensive field plots in Oregon's Cascade Mountains. Regional analysis of forest NPP and AGB was based on federal forest inventories (>8,000 plots) in Washington, Oregon, and California, multiple biomass maps and MODIS NPP (2003-2012). We also quantified annual forest AGB mortality due to bark beetles and fires across the region from 2003-2012 by combining several disturbance and biomass data sets. Over each spatial extent, forest NPP and AGB increased curvilinearly with average growing-year climate moisture index, computed as the cumulative difference between precipitation and potential evapotranspiration from October-September and averaged over preceding decades. Thus, climatic water availability strongly constrains forest carbon uptake and storage, particularly in the driest areas, but also in the wettest. Forest AGB mortality rates from bark beetles and fires peaked in moderately dry forests and then declining rapidly in the wettest areas. Annual forest AGB mortality from bark beetles was about twice as high as from fires. Bark beetle impacts were most pronounced in the Rock Mountains, while fire impacts were most pronounced in western portion of the region. Our multiscale analysis based on field inventory and remote sensing data sets demonstrates that climatic water availability is a key environmental constraint on forest carbon cycling in the western US. Consequently, continued warming and drying can be expected to have substantial impacts on forest carbon cycling in this region over the coming century.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

PubMed

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables

NASA Astrophysics Data System (ADS)

Nurminen, Kimmo; Karjalainen, Mika; Yu, Xiaowei; Hyyppä, Juha; Honkavaara, Eija

2013-09-01

Recent research results have shown that the performance of digital surface model extraction using novel high-quality photogrammetric images and image matching is a highly competitive alternative to laser scanning. In this article, we proceed to compare the performance of these two methods in the estimation of plot-level forest variables. Dense point clouds extracted from aerial frame images were used to estimate the plot-level forest variables needed in a forest inventory covering 89 plots. We analyzed images with 60% and 80% forward overlaps and used test plots with off-nadir angles of between 0° and 20°. When compared to reference ground measurements, the airborne laser scanning (ALS) data proved to be the most accurate: it yielded root mean square error (RMSE) values of 6.55% for mean height, 11.42% for mean diameter, and 20.72% for volume. When we applied a forward overlap of 80%, the corresponding results from aerial images were 6.77% for mean height, 12.00% for mean diameter, and 22.62% for volume. A forward overlap of 60% resulted in slightly deteriorated RMSE values of 7.55% for mean height, 12.20% for mean diameter, and 22.77% for volume. According to our results, the use of higher forward overlap produced only slightly better results in the estimation of these forest variables. Additionally, we found that the estimation accuracy was not significantly impacted by the increase in the off-nadir angle. Our results confirmed that digital aerial photographs were about as accurate as ALS in forest resources estimation as long as a terrain model was available.

Selective logging: does the imprint remain on tree structure and composition after 45 years?

PubMed

Osazuwa-Peters, Oyomoare L; Chapman, Colin A; Zanne, Amy E

2015-01-01

Selective logging of tropical forests is increasing in extent and intensity. The duration over which impacts of selective logging persist, however, remains an unresolved question, particularly for African forests. Here, we investigate the extent to which a past selective logging event continues to leave its imprint on different components of an East African forest 45 years later. We inventoried 2358 stems ≥10 cm in diameter in 26 plots (200 m × 10 m) within a 5.2 ha area in Kibale National Park, Uganda, in logged and unlogged forest. In these surveys, we characterized the forest light environment, taxonomic composition, functional trait composition using three traits (wood density, maximum height and maximum diameter) and forest structure based on three measures (stem density, total basal area and total above-ground biomass). In comparison to unlogged forests, selectively logged forest plots in Kibale National Park on average had higher light levels, different structure characterized by lower stem density, lower total basal area and lower above-ground biomass, and a distinct taxonomic composition driven primarily by changes in the relative abundance of species. Conversely, selectively logged forest plots were like unlogged plots in functional composition, having similar community-weighted mean values for wood density, maximum height and maximum diameter. This similarity in functional composition irrespective of logging history may be due to functional recovery of logged forest or background changes in functional attributes of unlogged forest. Despite the passage of 45 years, the legacy of selective logging on the tree community in Kibale National Park is still evident, as indicated by distinct taxonomic and structural composition and reduced carbon storage in logged forest compared with unlogged forest. The effects of selective logging are exerted via influences on tree demography rather than functional trait composition.

Selective logging: does the imprint remain on tree structure and composition after 45 years?

PubMed Central

Osazuwa-Peters, Oyomoare L.; Chapman, Colin A.; Zanne, Amy E.

2015-01-01

Selective logging of tropical forests is increasing in extent and intensity. The duration over which impacts of selective logging persist, however, remains an unresolved question, particularly for African forests. Here, we investigate the extent to which a past selective logging event continues to leave its imprint on different components of an East African forest 45 years later. We inventoried 2358 stems ≥10 cm in diameter in 26 plots (200 m × 10 m) within a 5.2 ha area in Kibale National Park, Uganda, in logged and unlogged forest. In these surveys, we characterized the forest light environment, taxonomic composition, functional trait composition using three traits (wood density, maximum height and maximum diameter) and forest structure based on three measures (stem density, total basal area and total above-ground biomass). In comparison to unlogged forests, selectively logged forest plots in Kibale National Park on average had higher light levels, different structure characterized by lower stem density, lower total basal area and lower above-ground biomass, and a distinct taxonomic composition driven primarily by changes in the relative abundance of species. Conversely, selectively logged forest plots were like unlogged plots in functional composition, having similar community-weighted mean values for wood density, maximum height and maximum diameter. This similarity in functional composition irrespective of logging history may be due to functional recovery of logged forest or background changes in functional attributes of unlogged forest. Despite the passage of 45 years, the legacy of selective logging on the tree community in Kibale National Park is still evident, as indicated by distinct taxonomic and structural composition and reduced carbon storage in logged forest compared with unlogged forest. The effects of selective logging are exerted via influences on tree demography rather than functional trait composition. PMID:27293697

Lichen-based indices to quantify responses to climate and air pollution across northeastern U.S.A

Treesearch

Susan Will-Wolf; Sarah Jovan; Peter Neitlich; JeriLynn E. Peck; Roger Rosentreter

2015-01-01

Lichens are known to be indicators for air quality; they also respond to climate. We developed indices for lichen response to climate and air quality in forests across the northeastern United States of America (U.S.A.), using 218–250 plot surveys with 145–161 macrolichen taxa from the Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture,...

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

Pilot Inventory of mammals, reptiles, and amphibians, Golden Gate National Recreation Area, California, 1990-1997

USGS Publications Warehouse

Semenoff-Irving, M.; Howell, J.A.

2005-01-01

The United States Geological Survey Golden Gate Field Station conducted a baseline inventory of terrestrial vertebrates within the Golden Gate National Recreation Area (GGNRA), Marin, San Francisco, and San Mateo Counties, California between 1990 and 1997. We established 456 permanent study plots in 6 major park habitats, including grassland, coastal scrub, riparian woodland, coastal wetland, broad-leaved evergreen forest, and needle-leaved evergreen forest. We tested multiple inventory methods, including live traps, track plate stations, and artificial cover boards, across all years and habitats. In most years, sampling occurred in 3?4 primary sampling sessions between July and September. In 1994, additional sampling occurred in February and May in conjunction with an assessment of Hantavirus exposure in deer mice (Peromyscus maniculatus). Overall, we detected 32 mammal, 14 reptile, and 6 amphibian species during 25,222 trap-nights of effort. The deer mouse?the most abundant species detected--accounted for 67% of total captures. We detected the Federal Endangered salt marsh harvest mouse (Reithrodontomys raviventris) at one coastal wetland plot in 1992. This project represents the first phase in the development of a comprehensive terrestrial vertebrate inventory and monitoring program for GGNRA. This report summarizes data on relative abundance, frequency of occurrence, distribution across habitat types, and trap success for terrestrial vertebrates detected during this 7-year effort. It includes comprehensive descriptions of the inventory methods and sampling strategies employed during this survey and is intended to help guide the park in the implementation of future longterm ecological monitoring programs.

Pilot Inventory of Mammals, Reptiles, and Amphibians, Golden Gate National Recreation Area, California, 1990-1997

USGS Publications Warehouse

Semenoff-Irving, Marcia; Howell, Judd A.

2005-01-01

The United States Geological Survey Golden Gate Field Station conducted a baseline inventory of terrestrial vertebrates within the Golden Gate National Recreation Area (GGNRA), Marin, San Francisco, and San Mateo Counties, California between 1990 and 1997. We established 456 permanent study plots in 6 major park habitats, including grassland, coastal scrub, riparian woodland, coastal wetland, broad-leaved evergreen forest, and needle-leaved evergreen forest. We tested multiple inventory methods, including live traps, track plate stations, and artificial cover boards, across all years and habitats. In most years, sampling occurred in 3-4 primary sampling sessions between July and September. In 1994, additional sampling occurred in February and May in conjunction with an assessment of Hantavirus exposure in deer mice (Peromyscus maniculatus). Overall, we detected 32 mammal, 14 reptile, and 6 amphibian species during 25,222 trap-nights of effort. The deer mouse-the most abundant species detected--accounted for 67% of total captures. We detected the Federal Endangered salt marsh harvest mouse (Reithrodontomys raviventris) at one coastal wetland plot in 1992. This project represents the first phase in the development of a comprehensive terrestrial vertebrate inventory and monitoring program for GGNRA. This report summarizes data on relative abundance, frequency of occurrence, distribution across habitat types, and trap success for terrestrial vertebrates detected during this 7-year effort. It includes comprehensive descriptions of the inventory methods and sampling strategies employed during this survey and is intended to help guide the park in the implementation of future longterm ecological monitoring programs.

Mortality trends and traits of hardwood advance regeneration following seasonal prescribed fires

Treesearch

Patrick Brose; David Van Lear

2003-01-01

Fire ecology studies in eastern hardwood forests generally use traditional, plot-based inventory methods and focus on sprouting stems to detect changes in vegetative composition and structure. Fire intensity often is not quantified or even subjectively classified and, if quantified, is not used in subsequent analysis. Consequently, reported responses of hardwood...

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Herbaceous vegetation in thinned and defoliated forest stands in north central West Virginia

Treesearch

S. L. C. Fosbroke; D. Feicht; R. M. Muzika

1995-01-01

Herbaceous vegetation was inventoried in 1992 and 1993 in eight Appalachian mixed hardwood stands ( 50% basal area/acre in oak species) in north central West Virginia. Vegetation was sampled on 20 6-foot radius plots per stand twice each growing season (once during late spring to sample spring ephemeral...

Carbon stocks and dynamics at different successional stages in an Afromontane tropical forest

NASA Astrophysics Data System (ADS)

Nyirambangutse, Brigitte; Zibera, Etienne; Uwizeye, Félicien K.; Nsabimana, Donat; Bizuru, Elias; Pleijel, Håkan; Uddling, Johan; Wallin, Göran

2017-03-01

As a result of different types of disturbance, forests are a mixture of stands at different stages of ecological succession. Successional stage is likely to influence forest productivity and carbon storage, linking the degree of forest disturbance to the global carbon cycle and climate. Although tropical montane forests are an important part of tropical forest ecosystems (ca. 8 %, elevation > 1000 m a.s.l.), there are still significant knowledge gaps regarding the carbon dynamics and stocks of these forests, and how these differ between early (ES) and late successional (LS) stages. This study examines the carbon (C) stock, relative growth rate (RGR) and net primary production (NPP) of ES and LS forest stands in an Afromontane tropical rainforest using data from inventories of quantitatively important ecosystem compartments in fifteen 0.5 ha plots in Nyungwe National Park in Rwanda. The total C stock was 35 % larger in LS compared to ES plots due to significantly larger above-ground biomass (AGB; 185 and 76 Mg C ha-1 in LS and ES plots), while the soil and root C stock (down to 45 cm depth in the mineral soil) did not significantly differ between the two successional stages (178 and 204 Mg C ha-1 in LS and ES plots). The main reasons for the difference in AGB were that ES trees had significantly lower stature and wood density compared to LS trees. However, ES and LS stands had similar total NPP (canopy, wood and roots of all plots ˜ 9.4 Mg C ha-1) due to counterbalancing effects of differences in AGB (higher in LS stands) and RGR (higher in ES stands). The AGB in the LS plots was considerably higher than the average value reported for old-growth tropical montane forest of south-east Asia and Central and South America at similar elevations and temperatures, and of the same magnitude as in tropical lowland forest of these regions. The results of this study highlight the importance of accounting for disturbance regimes and differences in wood density and allometry of tree species dominating at different successional stages in an attempt to quantify the C stock and sink strength of tropical montane forests and how they may differ among continents.

Can global navigation satellite system signals reveal the ecological attributes of forests?

NASA Astrophysics Data System (ADS)

Liu, Jingbin; Hyyppä, Juha; Yu, Xiaowei; Jaakkola, Anttoni; Liang, Xinlian; Kaartinen, Harri; Kukko, Antero; Zhu, Lingli; Wang, Yunsheng; Hyyppä, Hannu

2016-08-01

Forests have important impacts on the global carbon cycle and climate, and they are also related to a wide range of industrial sectors. Currently, one of the biggest challenges in forestry research is effectively and accurately measuring and monitoring forest variables, as the exploitation potential of forest inventory products largely depends on the accuracy of estimates and on the cost of data collection. A low-cost crowdsourcing solution is needed for forest inventory to collect forest variables. Here, we propose global navigation satellite system (GNSS) signals as a novel type of observables for predicting forest attributes and show the feasibility of utilizing GNSS signals for estimating important attributes of forest plots, including mean tree height, mean diameter at breast height, basal area, stem volume and tree biomass. The prediction accuracies of the proposed technique were better in boreal forest conditions than those of the conventional techniques of 2D remote sensing. More importantly, this technique provides a novel, cost-effective way of collecting large-scale forest measurements in the crowdsourcing context. This technique can be applied by, for example, harvesters or persons hiking or working in forests because GNSS devices are widely used, and the field operation of this technique is simple and does not require professional forestry skills.

Cross-continental comparison of the functional composition and carbon allocation of two altitudinal forest transects in Ecuador and Rwanda.

NASA Astrophysics Data System (ADS)

Verbeeck, Hans; Bauters, Marijn; Bruneel, Stijn; Demol, Miro; Taveirne, Cys; Van Der Heyden, Dries; Kearsley, Elizabeth; Cizungu, Landry; Boeckx, Pascal

2017-04-01

Tropical forests are key actors in the global carbon cycle. Predicting future responses of these forests to global change is challenging, but important for global climate models. However, our current understanding of such responses is limited, due to the complexity of forest ecosystems and the slow dynamics that inherently form these systems. Our understanding of ecosystem ecology and functioning could greatly benefit from experimental setups including strong environmental gradients in the tropics, as found on altitudinal transects. We setup two such transects in both South-America and Central Africa, focussing on shifts in carbon allocation, forest structure, nutrient cycling and functional composition. The Ecuadorian transect has 16 plots (40 by 40 m) and ranges from 400 to 3000 m.a.s.l., and the Rwandan transect has 20 plots (40 by 40 m) from 1500 to 3000 m.a.s.l. All plots were inventoried and canopy, litter and soil were extensively sampled. By a cross-continental comparison of both transects, we will gain insight in how different or alike both tropical forests biomes are in their responses, and how universal the observed altitudinal adaption mechanisms are. This could provide us with vital information of the ecological responses of both biomes to future global change scenarios. Additionally, comparison of nutrient shifts and trait-based functional composition allows us to compare the biogeochemical cycles of African and South-American tropical forests.

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

NASA Astrophysics Data System (ADS)

Liu, Jingbin; Liang, Xinlian; Hyyppä, Juha; Yu, Xiaowei; Lehtomäki, Matti; Pyörälä, Jiri; Zhu, Lingli; Wang, Yunsheng; Chen, Ruizhi

2017-04-01

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.

A comparison of several techniques for imputing tree level data

Treesearch

David Gartner

2002-01-01

As Forest Inventory and Analysis (FIA) changes from periodic surveys to the multipanel annual survey, new analytical methods become available. The current official statistic is the moving average. One alternative is an updated moving average. Several methods of updating plot per acre volume have been discussed previously. However, these methods may not be appropriate...

Selection of stand variables in southern Maine for making volume estimates from aerial photos

Treesearch

Earl J. Rogers; Gene Avery; Roy A. Chapman

1959-01-01

Aerial photographs are used widely in forest inventories. But there is a continuing need for improving the techniques of photo interpretation and making more efficient use of photographs. When the number or intensity of sample ground plots is controlled by airphoto classifications, a reliable stratification of the timber area is a must.

Image-based change estimation for land cover and land use monitoring

Treesearch

Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister

2012-01-01

The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...

Plotview Software For Retrieving Plot-Level Imagery and GIS Data Over The Web

Treesearch

Ken Boss

2001-01-01

The Minnesota Department of Natural Resources Division of Forestry Resource Assessment office has been cooperating with both the Forest Service's FIA and Natural Resource Conservation Services's NRI inventory programs in researching methods to more tightly integrate the two programs. One aspect of these ongoing efforts has been to develop a prototype intranet...

A Study on PolInSAR Coherence Based Regression Analysis of Forest Biomass (BARKOT Reserve Forest India), Using RADARSAT-2 Datasets

NASA Astrophysics Data System (ADS)

Singh, J.; Kumar, S.; Kushwaha, S. P. S.

2015-04-01

Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components

Changes in composition, structure and aboveground biomass over seventy-six years (1930-2006) in the Black Rock Forest, Hudson Highlands, southeastern New York State.

PubMed

Schuster, W S F; Griffin, K L; Roth, H; Turnbull, M H; Whitehead, D; Tissue, D T

2008-04-01

We sought to quantify changes in tree species composition, forest structure and aboveground forest biomass (AGB) over 76 years (1930-2006) in the deciduous Black Rock Forest in southeastern New York, USA. We used data from periodic forest inventories, published floras and a set of eight long-term plots, along with species-specific allometric equations to estimate AGB and carbon content. Between the early 1930s and 2000, three species were extirpated from the forest (American elm (Ulmus americana L.), paper birch (Betula papyrifera Marsh.) and black spruce (Picea mariana (nigra) (Mill.) BSP)) and seven species invaded the forest (non-natives tree-of-heaven (Ailanthus altissima (Mill.) Swingle) and white poplar (Populus alba L.) and native, generally southerly distributed, southern catalpa (Catalpa bignonioides Walt.), cockspur hawthorn (Crataegus crus-galli L.), red mulberry (Morus rubra L.), eastern cottonwood (Populus deltoides Bartr.) and slippery elm (Ulmus rubra Muhl.)). Forest canopy was dominated by red oak and chestnut oak, but the understory tree community changed substantially from mixed oak-maple to red maple-black birch. Density decreased from an average of 1500 to 735 trees ha(-1), whereas basal area doubled from less than 15 m(2) ha(-1) to almost 30 m(2) ha(-1) by 2000. Forest-wide mean AGB from inventory data increased from about 71 Mg ha(-1) in 1930 to about 145 Mg ha(-1) in 1985, and mean AGB on the long-term plots increased from 75 Mg ha(-1) in 1936 to 218 Mg ha(-1) in 1998. Over 76 years, red oak (Quercus rubra L.) canopy trees stored carbon at about twice the rate of similar-sized canopy trees of other species. However, there has been a significant loss of live tree biomass as a result of canopy tree mortality since 1999. Important constraints on long-term biomass increment have included insect outbreaks and droughts.

VT0005 In Action: National Forest Biomass Inventory Using Airborne Lidar Sampling

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.

2016-12-01

Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los Angeles through the support of the International Climate Initiative of the German Ministry of Environment, Conservation and Nuclear Security, and the KFW Development Bank.

Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis program, Landsat, and LANDFIRE

USGS Publications Warehouse

Chen, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.

2011-01-01

The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High Plateaus. We also estimated that 8054 Mg AFBC were released from 2.24 km2 burned forest area in the Longston fire. These results demonstrate that an AFBC spatial map and estimated biomass carbon consumption can readily be generated using existing database. The methodology provides a consistent, practical, and inexpensive way for estimating AFBC at 30-m resolution over large areas throughout the United States.

U.S. Forest Greenhouse Gas Impacts of a continued Expansion of E.U. Wood Pellet Demand

NASA Astrophysics Data System (ADS)

Latta, G.; Baker, J.; Ohrel, S. B.

2016-12-01

The United States has ambitious goals of greenhouse gas (GHG) reductions. A portion of these reductions are based on expected contributions from land use, land use change, and forestry (LULUCF). The European Union has similar goals which have resulted in a doubling of wood pellets exported from US ports destined for EU power plants over the last few years. There are potential conflicts between the GHG consequences of this pellet supply and the LULUCF contribution to US GHG goals. This study seeks to inform the discussion by modeling US forest GHG accounts using data measured on a grid of over 150,000 USDA Forest Service, Forest Inventory and Analysis (FIA) forestland plots across the conterminous United States. Empirical yield functions are estimate from plot log volume, biomass and carbon and provide the basis for changes in forest characteristics over time. Demand data based on a spatial database of over 2,000 forest product manufacturing facilities representing 11 intermediate and 13 final solid and pulpwood products. Manufacturing and logging costs are specific to slope, log size, and volume removed along with transportation costs based on fuel prices, FIA plot, and milling locations. The resulting partial spatial equilibrium model of the US forest sector is solved annually for the period 2010 - 2030 with demand shifted by energy prices and macroeconomic indicators from the US EIA's Annual Energy Outlook for a series of potential wood pellet export targets. For each wood pellet export level simulated, figures showing historic and scenario-specific forest products production are generated. Maps of the spatial allocation of both forest harvesting and carbon fluxes are presented at the National level and detail is given in both the US North and Southeast.

African Savanna-Forest Boundary Dynamics: A 20-Year Study

PubMed Central

Cuni-Sanchez, Aida; White, Lee J. T.; Calders, Kim; Jeffery, Kathryn J.; Abernethy, Katharine; Burt, Andrew; Disney, Mathias; Gilpin, Martin; Gomez-Dans, Jose L.; Lewis, Simon L.

2016-01-01

Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, with zero trees ≥10 cm diameter in 1993 and 2013. F1 and F2 forests increased in AGB, mainly as a result of adding recruited stems (F1) and increased Basal Area (F2), whereas F3 and F4 forests did not change substantially in structure, AGB or diversity. Critically, the stability of the F3 stage implies that this stage may be maintained for long periods. Soil carbon was low, and did not show a successional gradient as for AGB and diversity. TLS vertical plant profiles showed distinctive differences amongst the vegetation types, indicating that this technique can improve ecological understanding. We highlight two points: (i) as forest colonises, changes in biodiversity are much slower than changes in forest structure or AGB; and (ii) all forest types store substantial quantities of carbon. Multi-decadal monitoring is likely to be required to assess the speed of transition between vegetation types. PMID:27336632

African Savanna-Forest Boundary Dynamics: A 20-Year Study.

PubMed

Cuni-Sanchez, Aida; White, Lee J T; Calders, Kim; Jeffery, Kathryn J; Abernethy, Katharine; Burt, Andrew; Disney, Mathias; Gilpin, Martin; Gomez-Dans, Jose L; Lewis, Simon L

2016-01-01

Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, with zero trees ≥10 cm diameter in 1993 and 2013. F1 and F2 forests increased in AGB, mainly as a result of adding recruited stems (F1) and increased Basal Area (F2), whereas F3 and F4 forests did not change substantially in structure, AGB or diversity. Critically, the stability of the F3 stage implies that this stage may be maintained for long periods. Soil carbon was low, and did not show a successional gradient as for AGB and diversity. TLS vertical plant profiles showed distinctive differences amongst the vegetation types, indicating that this technique can improve ecological understanding. We highlight two points: (i) as forest colonises, changes in biodiversity are much slower than changes in forest structure or AGB; and (ii) all forest types store substantial quantities of carbon. Multi-decadal monitoring is likely to be required to assess the speed of transition between vegetation types.

Role of sprouts in regeneration of a whole-tree clearcut in central hardwoods of Connecticut

Treesearch

C.W. Martin; L.M. Tritton

1991-01-01

Stump sprouts were the single most important type of regeneration in a central hardwood forest in Connecticut during the first 5 years after whole-tree clearcuttting. Herbs, shrubs, tree seedlings, and stump sprouts were inventoried using stratified permanent plots on a 6-ha watershed during the first, third, and fifth years after harvest.

The urban FIA inventory: plot design, data collection, data flow and processing

Treesearch

Tonya Lister; Mark Majewsky; Mark A. Hatfield; Angie Rowe; Bill Dunning; Chris Edgar; Tom Brandeis

2015-01-01

More than 80 percent of the U.S. population lives in urban areas and tree cover in these areas offers a wide range of environmental benefits including the provision of wildlife habitat, aesthetic appeal and visual barriers, microclimate control, water quality improvement, and air and noise pollution control. Recognizing the importance of urban forests, and with...

Influence of elevation and site productivity on conifer distributions across Alaskan temperate rainforests

Treesearch

John P. Caouette; Ashley E. Steel; Paul E. Hennon; Pat G. Cunningham; Cathy A. Pohl; Barbara A. Schrader

2016-01-01

We investigated the influence of landscape factors on the distribution and life stage stability of coastal tree species near the northern limit of their ranges. Using data from 1465 forest inventory plots, we estimated probability of occurrence and basal area of six common conifer species across three broad latitudinal regions of coastal Alaska. By also comparing...

Northeastern FIA Tree Taper Study: Current Status and Future Work

Treesearch

James A. Westfall; Charles T. Scott

2005-01-01

The northeastern unit of the Forest Inventory and Analysis program (NE-FIA) is engaged in an ongoing project to develop regionwide tree taper equations. Sampling intensity is based on NE-FIA plot data and is stratified by species, diameter class, and height class. To date, modeling research has been aimed largely at evaluating existing model forms (and hybrids thereof...

Distribution and occupancy of introduced species: a baseline inventory from Phase 3 plots across the country

Treesearch

Bethany K. Schulz; W. Keith Moser

2012-01-01

Invasive plant species have significant negative impacts in many ecosystems and are found in many forests around the world. Although not all introduced species become invasive, there are numerous examples of species escaping cultivation and invading natural ecosystems years or even decades after their initial introduction. Regional distributions of invasive species are...

Rate of value change in New England timber stands

Treesearch

Stanford L. Arner; David A. Gansner; Thomas W. Birch; Thomas W. Birch

1990-01-01

Analyses of remeasured plot data show that between the last two forest inventories of New England, compound rates of value change in timber stands averaged 4.2 percent and ranged from -26 to + 43 percent. Three key characteristics of stand condition (species composition, tree size, and stocking) can be used to estimate economic growth. For example, stands with (1) more...

The spatial distribution of riparian ash: implications for the dispersal of the emerald ash borer

Treesearch

Susan J. Crocker; W. Keith Moser; Mark H. Hansen; Mark D. Nelson

2007-01-01

A pilot study to assess riparian ash connectivity and its implications for emerald ash borer dispersal was conducted in three subbasins in Michigan's Southern Lower Peninsula. Forest Inventory and Analysis data were used to estimate ash biomass. The nineteen percent of plots in riparian physiographic classes contained 40 percent of ash biomass. Connectivity of...

Response of Scots pine stand vitality to changes in environmental factors in Poland, 1991-1995

Treesearch

Jerzy Wawrzoniak

1998-01-01

Vitality inventories of Scots pine stands, the most common species in Poland, have been done since 1991 by using the ICP-Forest methodology. In Scots pine stands older than 40 years, 1,040 observation plots were established. Defoliation was used as the primary indicator of stand vitality. During 1991 to 1995, SO2 and NOx...

Changes in area and ownership of timberland in western Oregon: 1961-86.

Treesearch

Colin D. MacLean

1990-01-01

This report notes the changes in timberland area and in timberland ownership that took place in western Oregon between 1961 and 1986. The data for the report were based on observations and measurements taken during three successive forest inventories of non-Federal lands in western Oregon. Estimates of change were based on repeat measurements of 1,465 permanent plots...

Fusiform-Rust-Hazard Maps for Loblolly and Slash Pines

Treesearch

Robert L. Anderson; Thomas C. McCartney; Noel D. Cost; Hugh Devine; Martin Botkin

1988-01-01

Rust-hazard saps made from Forest Inventory and Analysis plot data show that fusiform rust on slash pine is most common in north-central Florida, in southeastern Georgia, and in areas north of slash pine's natural range. On loblolly pine, the disease is most common in central and southeastern Georgia and in portions of South Carolina. These maps show the general...

Calibration of the STEMS diameter growth model using FIA data

Treesearch

Veronica C. Lessard

2000-01-01

The diameter growth model used in STEMS, the Stand and Tree Evaluation and Modeling System, was originally calibrated using data from permanent growth plots in Minnesota, Wisconsin, and Michigan. Because the model has been applied in predicting growth using Forest Inventory and Analysis (FIA) data, it was appropriate to refit the model to FIA data. The model was...

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

Evaluation of Unmanned Aircraft System (UAS) to Monitor Forest Health Conditions in Alaska

NASA Astrophysics Data System (ADS)

Webley, P. W.; Hatfield, M. C.; Heutte, T. M.; Winton, L. M.

2017-12-01

US Forest Service Alaska Region Forest Health Protection (FHP) and University of Alaska Fairbanks (UAF), Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) are evaluating the capability of Unmanned Aerial Systems (UAS, "drone" informally) to monitor forest health conditions in Alaska's Interior Region. On July 17-20 2017, FHP and ACUASI deployed two different UAS at permanent forest inventory plots managed by the UAF programs Bonanza Creek Long Term Ecological Research (LTER) and Cooperative Alaska Forest Inventory (CAFI). The purpose of the mission was to explore capabilities of UAS for evaluating aspen tree mortality at inaccessible locations and at a scale and precision not generally achievable with currently used ground- or air-based methods. Drawing from experience gained during the initial 2016 campaign, this year emphasized the efficient use of UAS to accomplish practical field research in a variety of realistic situations. The vehicles selected for this years' effort included the DJI Matrice quadcopter with the Zenmuse-X3 camera to quickly capture initial video of the site and tree conditions; followed by the ING Responder (single rotor electric helicopter based on the Gaui X7 airframe) outfitted with a Nikon D810 camera to collect high-resolution stills suitable for construction of orthomosaic models. A total of 12 flights were conducted over the campaign, with two full days dedicated to the Delta Junction Gerstle River Intermediate (GRI) sites and the remaining day at the Bonanza Creek site. In addition to demonstrating the ability of UAS to operate safely and effectively in various canopy conditions, the effort also validated the ability of teams to deliver UAS and scientific payloads into challenging terrain using all-terrain vehicles (ATV) and foot traffic. Analysis of data from the campaign is underway. Because the permanent plots have been recently evaluated it is known that nearly all aspen mortality is caused by an aggressive canker; at some plots up to 70% of aspen stems have canker and most of these trees are dead. Once the imagery is processed the team will statistically calculate the degree of agreement between UAS and ground detection methods. This measure of reliability is necessary to evaluate the usefulness of UAS for the purposes of forest health detection and monitoring.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Pinus albicaulis Engelm. (whitebark pine) in mixed-species stands throughout its US range: Broad-scale indicators of extent and recent decline

Treesearch

Sara A. Goeking; Deborah Kay Izlar

2018-01-01

We used data collected from >1400 plots by a national forest inventory to quantify population-level indicators for a tree species of concern. Whitebark pine (Pinus albicaulis) has recently experienced high mortality throughout its US range, where we assessed the area of land with whitebark pine present, size-class distribution of individual whitebark pine,...

Estimating fine-scale land use change dynamics using an expedient photointerpretation-based method

Treesearch

Tonya Lister; Andrew Lister; Eunice Alexander

2009-01-01

Population growth and urban expansion have resulted in the loss of forest land. With growing concerns about this loss and its implications for global processes and carbon budgets, there is a great need for detailed and reliable land use change data. Currently, the Northern Research Station uses an Annual Inventory design whereby all plots are revisited every 5 years...

Moderate-resolution data and gradient nearest neighbor imputation for regional-national risk assessment

Treesearch

Kenneth B. Jr. Pierce; C. Kenneth Brewer; Janet L. Ohmann

2010-01-01

This study was designed to test the feasibility of combining a method designed to populate pixels with inventory plot data at the 30-m scale with a new national predictor data set. The new national predictor data set was developed by the USDA Forest Service Remote Sensing Applications Center (hereafter RSAC) at the 250-m scale. Gradient Nearest Neighbor (GNN)...

Diameter growth models using FIA data from the Northeastern, Southern, and North Central Research Stations

Treesearch

Veronica C. Lessard; Ronald E. McRoberts; Margaret R. Holdaway

2000-01-01

Nonlinear, individual-tree, distance-independent annual diameter growth models are presented for species in two ecoregions defined by R.G. Bailey in the northern Lake States and in parts of the central and southern regions of the U.S. The models were calibrated using Forest Inventory and Analysis (FIA) data from undisturbed plots on land classified as timberland across...

A nonparametric analysis of plot basal area growth using tree based models

Treesearch

G. L. Gadbury; H. K. lyer; H. T. Schreuder; C. Y. Ueng

1997-01-01

Tree based statistical models can be used to investigate data structure and predict future observations. We used nonparametric and nonlinear models to reexamine the data sets on tree growth used by Bechtold et al. (1991) and Ruark et al. (1991). The growth data were collected by Forest Inventory and Analysis (FIA) teams from 1962 to 1972 (4th cycle) and 1972 to 1982 (...

Austin's urban FIA: seamless rural to urban resource monitoring in Texas

Treesearch

Chris Edgar; Burl Carraway

2015-01-01

In 2014 Urban Forest Inventory and Analysis (Urban-FIA) was implemented for the first time ever in Austin, Texas. Work was accelerated and a full complement of plots in the city was measured in six months. In 2015 results are to be released in an FIA report and data made available in a publicly accessible database. In this presentation we discuss the importance of...

Survival of Hardwood Regeneration During Prescribed Fires: The Importance of Root Development and Root Collar Location

Treesearch

Patrick Brose; David Van Lear

2004-01-01

Fire ecology studies in eastern hardwood forests usually use plot-based inventory methods and focus on sprouting stems to detect changes in vegetative composition and structure. Rarely are individual stems studied and stems that fail to sprout are usually ignored. In this study, an individual stem mortality approach was employed. Four hundred fifty stems of eight...

Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

PubMed

Yadav, Bechu K V; Nandy, S

2015-05-01

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

PubMed

Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

2014-12-01

The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce rates of deforestation and forest degradation, logging inventories offer a promising source of data to support mechanisms such as the United Nations REDD + (Reducing Emissions from Tropical Deforestation and Degradation) program.

Long-term monitoring of diversity and structure of two stands of an Atlantic Tropical Forest

PubMed Central

Carvalho, Warley Augusto Caldas; Santos, Rubens Manoel; Gastauer, Markus; Garcia, Paulo Oswaldo; Fontes, Marco Aurélio Leite; Coelho, Polyanne Aparecida; Moreira, Aline Martins; Menino, Gisele Cristina Oliveira; Oliveira-Filho, Ary Teixeira

2017-01-01

Abstract Background This study aimed to report the long-term monitoring of diversity and structure of the tree community in a protected semideciduous Atlantic Forest in the South of Minas Gerais State, Southeast Brazil. The study was conducted in two stands (B and C), each with 26 and 38 10 m x 30 m plots. Censuses of stand B were conducted in 2000, 2005 and 2011, and stand C in 2001, 2006 and 2011. In both stands, the most abundant and important species for biomass accumulation over the inventories were trees larger than 20 cm of diameter, which characterize advanced successional stage within the forest. New information The two surveyed stands within the studied forest presented differences in structure, diversity and species richness over the time. PMID:28848371

Long-term monitoring of diversity and structure of two stands of an Atlantic Tropical Forest.

PubMed

Diniz, Écio Souza; Carvalho, Warley Augusto Caldas; Santos, Rubens Manoel; Gastauer, Markus; Garcia, Paulo Oswaldo; Fontes, Marco Aurélio Leite; Coelho, Polyanne Aparecida; Moreira, Aline Martins; Menino, Gisele Cristina Oliveira; Oliveira-Filho, Ary Teixeira

2017-01-01

This study aimed to report the long-term monitoring of diversity and structure of the tree community in a protected semideciduous Atlantic Forest in the South of Minas Gerais State, Southeast Brazil. The study was conducted in two stands (B and C), each with 26 and 38 10 m x 30 m plots. Censuses of stand B were conducted in 2000, 2005 and 2011, and stand C in 2001, 2006 and 2011. In both stands, the most abundant and important species for biomass accumulation over the inventories were trees larger than 20 cm of diameter, which characterize advanced successional stage within the forest. The two surveyed stands within the studied forest presented differences in structure, diversity and species richness over the time.

Evaluating sustainability: a method for assessing vegetation change in southern Missouri, U.S.A.: 1820-2003

Treesearch

W. Keith Moser; Mark H. Hansen; Mark A. Hatfield; Timothy A. Nigh

2006-01-01

The General Land Office of the United States of America surveyed the state of Missouri during the first half of the 1800s. Frequently relying on witness trees to mark corners of surveyed units, surveyors also recorded other trees situated on or near the survey lines. Using plot-level data from inventories conducted by the U.S. Forest Service, Northern Research Station...

Creating a fuels baseline and establishing fire frequency relationships to develop a landscape management strategy at the Savannah River Site

Treesearch

Bernard R. Parresol; Dan Shea; Roger Ottmar

2006-01-01

The Savannah River Site is a Department of Energy Nuclear Defense Facility and a National Environmental Research Park located in the upper coastal plain of South Carolina. Prescribed burning is conducted on 15,000 to 20,000 ac annually. We modified standard forest inventory methods to incorporate a complete assessment of fuel components on 622 plots, assessing coarse...

A comparison of two estimates of standard error for a ratio-of-means estimator for a mapped-plot sample design in southeast Alaska.

Treesearch

Willem W.S. van Hees

2002-01-01

Comparisons of estimated standard error for a ratio-of-means (ROM) estimator are presented for forest resource inventories conducted in southeast Alaska between 1995 and 2000. Estimated standard errors for the ROM were generated by using a traditional variance estimator and also approximated by bootstrap methods. Estimates of standard error generated by both...

The Impact of Afforestation on the Carbon Stocks of Mineral Soils Across the Republic of Ireland.

NASA Astrophysics Data System (ADS)

Wellock, M.; Laperle, C.; Kiely, G.; Reidy, B.; Duffy, C.; Tobin, B.

2009-04-01

At the beginning of the twentieth century forests accounted for only 1% of the total Irish land cover (Pilcher & Mac an tSaoir, 1995). However, due to the efforts of successive governments there has been rapid afforestation since the 1960s resulting in a 10.0% forest land cover as of 2007 (The Department of Agriculture, Fisheries, and Food, 2007). A large proportion of this afforestation took place after the mid-1980s and was fueled by government grant incentive schemes targeted at private landowners (Renou & Farrell 2005). Consequently, 54% of forests are less than 20 years old (Byrne, 2006). This specific land use change provides an opportunity for Ireland to meet international obligations set forth by the United Nations Framework Convention on Climate Change (UNFCCC, 1992). These obligations include the limitation of greenhouse gas emissions to 13% above 1990 levels. In order to promote accountability for these commitments, the UNFCCC treaty and the Kyoto Protocol (Kyoto Protocol, 1997) mandate signatories to publish greenhouse gas (GHG) emissions inventories for both greenhouse gas sources and removals by sinks. Article 3.3 of the Kyoto Protocol allows changes in C stocks due to afforestation, reforestation, and deforestation since 1990 to be used to offset inventory emissions. Therefore, due to the rapid rate of afforestation and its increased carbon sequestration since 1990, Ireland has the potential to significantly offset GHG emissions. There is little known as to the impacts of afforestation on the carbon stocks in soils over time, and even less known about the impact on Irish soils. The FORESTC project aims to analyse this impact by undertaking a nationwide study using a method similar to that of the paired plot method in Davis and Condron, 2002. The study will examine 42 forest sites across Ireland selected randomly from the National Forest Inventory (National Forest Inventory, 2007). These 42 sites will be grouped based on the forest type which includes conifer, broadleaf, and mixed (broadleaf and conifer) and soil type: brown earth, podzol, brown podzolic, gley and brown earth. The paired plot method involves selecting a second site that represents the same soil type and physical characteristics as the forest site. The only difference between the two sites should be the current land-use of the pair site, which should represent the pre-afforestation land-use of the forest site. Each forest site and its pair site will be sampled in the top 30 cm of soil for bulk density and organic carbon %, while litter and F/H layer samples will be taken and analysed for carbon. This data should provide an analysis of the carbon stocks of the soil and litter of both the forest site and its pair site allowing for comparison and thus the impact of afforestation on carbon stocks. References. Byrne, K.A., & Milne, R. (2006). Carbon stocks and sequestration in plantation forests in the Republic of Ireland. Forestry, 79, no. 4: 361. Davis, M.R., & Condron, L.M. (2002). Impact of grassland afforestation on soil carbon in New Zealand: a review of paired-site studies. Australian Journal of Soil Research, 40, no. 4: 675-690. Kyoto Protocol. 1997 Kyoto Protocol to the United Nations Framework Convention on Climate Change. FCCC/CP/1997/7/Add.1, Decision 1/CP.3, Annex 7. UN. National Forest Inventory: NFI Methodology. (2007). Forest Service, The Department of Agriculture, Fisheries, and Food, Wexford, Ireland. Pilcher, J.R. & Mac an tSaoir, S. (1995). Wood, Trees and Forests in Ireland. (Royal Irish Academy, Dublin. Renou, F. & Farrell, E.P. (2005). Reclaiming peatlands for forestry: the Irish experience. In: Stanturf, J.A. and Madsen, P.A. (eds.). Restoration of boreal and temperate forests. CRC Press, Boca Raton. p.541-557. UNFCCC. 1992 United Nations Framework Convention on Climate Change. Palais des Nations, Geneva. http://www.unfccc.de/index.html

Legume abundance along successional and rainfall gradients in Neotropical forests.

PubMed

Gei, Maga; Rozendaal, Danaë M A; Poorter, Lourens; Bongers, Frans; Sprent, Janet I; Garner, Mira D; Aide, T Mitchell; Andrade, José Luis; Balvanera, Patricia; Becknell, Justin M; Brancalion, Pedro H S; Cabral, George A L; César, Ricardo Gomes; Chazdon, Robin L; Cole, Rebecca J; Colletta, Gabriel Dalla; de Jong, Ben; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan Manuel; Durán, Sandra M; do Espírito Santo, Mário Marcos; Fernandes, G Wilson; Nunes, Yule Roberta Ferreira; Finegan, Bryan; Moser, Vanessa Granda; Hall, Jefferson S; Hernández-Stefanoni, José Luis; Junqueira, André B; Kennard, Deborah; Lebrija-Trejos, Edwin; Letcher, Susan G; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Meave, Jorge A; Menge, Duncan N L; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Ostertag, Rebecca; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Reich, Peter B; Reyes-García, Casandra; Rodríguez-Velázquez, Jorge; Romero-Pérez, I Eunice; Sanaphre-Villanueva, Lucía; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; de Almeida, Arlete Silva; Almeida-Cortez, Jarcilene S; Silver, Whendee; de Souza Moreno, Vanessa; Sullivan, Benjamin W; Swenson, Nathan G; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria das Dores Magalhães; Vester, Hans F M; Vieira, Ima Célia Guimarães; Zimmerman, Jess K; Powers, Jennifer S

2018-05-28

The nutrient demands of regrowing tropical forests are partly satisfied by nitrogen-fixing legume trees, but our understanding of the abundance of those species is biased towards wet tropical regions. Here we show how the abundance of Leguminosae is affected by both recovery from disturbance and large-scale rainfall gradients through a synthesis of forest inventory plots from a network of 42 Neotropical forest chronosequences. During the first three decades of natural forest regeneration, legume basal area is twice as high in dry compared with wet secondary forests. The tremendous ecological success of legumes in recently disturbed, water-limited forests is likely to be related to both their reduced leaflet size and ability to fix N 2 , which together enhance legume drought tolerance and water-use efficiency. Earth system models should incorporate these large-scale successional and climatic patterns of legume dominance to provide more accurate estimates of the maximum potential for natural nitrogen fixation across tropical forests.

Tree allometry and improved estimation of carbon stocks and balance in tropical forests.

PubMed

Chave, J; Andalo, C; Brown, S; Cairns, M A; Chambers, J Q; Eamus, D; Fölster, H; Fromard, F; Higuchi, N; Kira, T; Lescure, J-P; Nelson, B W; Ogawa, H; Puig, H; Riéra, B; Yamakura, T

2005-08-01

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.

Effect of tree thinning and litter removal on the radiocesium (Cs-134, 137) discharge rates in the Kawauchi forest plantation (Fukushima Prefecture, northern Japan)

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel; Onda, Yuichi; Takahashi, Junko; Kato, Hiroaki; Hisadome, Keigo

2016-04-01

On 11 March 2011 a 9.0 earthquake and the resulting tsunami occurred in central-eastern Japan triggering, one day after, the Fukushima Dai-ichi nuclear power plant (DNPP) accident. Despite the bulk of radionuclides (ca. 80%) were transported offshore and out over the Pacific Ocean, significant wet and dry deposits of those radionuclides occurred mainly in the Fukushima Prefecture and in a minor way in the Miyagi, Tochigi, Gunma and Ibaraki Prefectures. As a consequence and among other radionuclides, a total of 511,000 TBq of I-131, 13,500 TBq of Cs-134 and 13,600 TBq of Cs-137 were released into the atmosphere and the ocean, contaminating cultivated soils, rivers, settlements and forested areas. This accident caused severe environmental and economic damages. Several decontamination practices have done, including tree thinning and litter removal within the forests and tree plantations. In this study we analysed the effect of eight different management practices on the radiocesium (Cs-134 and Cs-137) discharge rates during 20 months (May'2013 - Dec'2014) in a Japanese cedar (Cryptomeria japonica) plantation (stand age of 57 years), located in a hillslope near the Kawauchi village, Fukushima Prefecture, northern Japan. This study area (37⁰ 20' 04" N, 140⁰ 53' 13.5" E) is located 16 km southwestern from the DNPP and within the evacuation area. The soils are Andosols. Ten runoff plots (5 x 2 meters) were installed and measurements started on May 2013. Two plots remained without any treatment as control plots and the other eight plots represented the following management practices: Mng1) Litter removal + clear-cutting (no sheet); Mng2) Litter removal + clear-cutting (no sheet); Mng3) Litter removal + clear-cutting (no sheet); Mng4) Litter removal; Mng5) Thinning (logged area); Mng6) Thinning (under remnant trees); Mng7) Litter removal + thinning (logged area); Mng8) Litter removal + thinning (under remnant trees). Each plot had a gauging station and sediment samples were collected every three weeks. Litter removal and tree thinning were done twice. The minimum of ground and vegetation coverages occurred in May and June 2013 and between February and April 2014. The maximum coverages appeared in September-October 2013 and between July and September 2014. The radioactivities of Cs-134 and Cs-137 were determined in the soil and litter fractions by gamma-ray spectrometry. Emissions were measured using a high purity n-type Ge coaxial detector coupled to an amplified and multichannel analyser at the CRiED laboratory of the University of Tsukuba. The activity concentration (Bq / kg) of Cs-134 and Cs-137 were calculated as well as the inventory (Bq / m2) and daily inventory (Bq / m2 day) of Cs-137. A total of 70 correlations were analysed: between the dry weight of the leaf and soil and the corresponding activity of Cs-134 and Cs-137 as well as between the total movement and total daily movement of leaf and soil and the inventory and daily inventory of Cs-137. The amount of soil and caesium movement in the experimental slopes was considerably decreased in the year 2014 than in 2013 due to the vegetation recovery after the operations in each plot.

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

NASA Technical Reports Server (NTRS)

Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus;

Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar

NASA Astrophysics Data System (ADS)

Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.

2017-12-01

Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.

Do trees fall downhill? Relationship between treefall direction and slope-aspect and wind in eight old-growth oak stands in the central hardwood forest

Treesearch

James S. Rentch

2011-01-01

This study examined the relationship between direction of treefall and slope-aspect, and prevailing wind in eight old-growth stands where single-tree canopy gaps characterize the dominant disturbance regime. All live and downed trees were inventoried in 0.45-ha sample plots. To determine crown asymmetry, crown sizes of live trees were measured along two perpendicular...

Estimating root collar diameter growth for multi-stem western woodland tree species on remeasured forest inventory and analysis plots

Treesearch

Michael T. Thompson; Maggie. Toone

2012-01-01

Tree diameter growth models are widely used in many forestry applications, often to predict tree size at a future point in time. Also, there are instances where projections of past diameters are needed. An individual tree model has been developed to estimate diameter growth of multi-stem woodland tree species where the diameter is measured at root collar. The model was...

Effects of species composition and site factors on the severity of beech bark disease in western Massachusetts and the White Mountains of New Hampshire: a preliminary report

Treesearch

Mark J. Twery; W.A. Patterson

1983-01-01

The extent of beech bark disease was examined on permanent inventory plots in western Massachusetts and on Bartlett Experimental Forest in New Hampshire. The amount of disease-caused defect was correlated with a reduction in the proportion of beech in a stand. Sites on lower slopes and with greater abundance of hemlock contained more defective beech.

Estimation of tropical forest canopy temperatures, thermal response numbers, and evapotranspiration using an aircraft-based thermal sensor

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Lieberman, Diana; Lieberman, Milton; Hartshorn, Gary S.; Peralta, Rodolfo

1990-01-01

Thermal infrared Multispectral Scanner (TIMS) data were collected at a resolution of 5 to 10 m from a tropical rain forest over an elevation gradient from 35 to 2700 m in the Braulio Carrillo National Park in Costa Rica. Flight lines were repeated with a 15 to 30 minute time difference for measurement of forest canopy thermal response over time. Concurrent radiosonde measurements of atmospheric profiles of air temperature and moisture provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Techniques for using calibrated aircraft-based thermal scanner data to examine tropical forest canopy thermal properties are described. Forest canopy temperature changes over time assessed between repeated, duplicated flight lines were combined with estimates of surface radiative energy measurements from towers above the forest canopy to determine temperature spatial variability, calculate Thermal Response Numbers (TRN), and estimate evapotranspiration along the elevation gradient from selected one hectare forest inventory plots.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios

PubMed Central

Coulston, John W.; Wear, David N.

2017-01-01

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and identified the indicator and dominant species associated with each. Cluster typologies in two levels of a hierarchy of forest assemblages, with 29 and 147 groups respectively, were supported by diagnostic criteria. Groups in these two levels of the hierarchy were labeled based on the top indicator species in each, and ranged widely in size. For example, in the 29-cluster typology, the sugar maple-red maple assemblage contained the largest number of plots (30,068), while the butternut-sweet birch and sourwood-scarlet oak assemblages were both smallest (6 plots each). We provide a case-study demonstration of the utility of the typology for informing forest climate change impact assessment. For five assemblages in the 29-cluster typology, we used existing projections of changes in importance value (IV) for the dominant species under one low and one high climate change scenario to assess impacts to the assemblages. Results ranged widely for each scenario by the end of the century, with each showing an average decrease in IV for dominant species in some assemblages, including the balsam fir-quaking aspen assemblage, and an average increase for others, like the green ash-American elm assemblage. Future work should assess adaptive capacity of these forest assemblages and investigate local population- and community-level dynamics in places where dominant species may be impacted. This typology will be ideal for monitoring, assessing, and projecting changes to forest communities within the emerging framework of macrosystems ecology, which emphasizes hierarchies and broad extents. PMID:28877258

Structural and climatic determinants of demographic rates of Scots pine forests across the Iberian Peninsula.

PubMed

Vilà-Cabrera, Albert; Martínez-Vilalta, Jordi; Vayreda, Jordi; Retana, Javier

2011-06-01

The demographic rates of tree species typically show large spatial variation across their range. Understanding the environmental factors underlying this variation is a key topic in forest ecology, with far-reaching management implications. Scots pine (Pinus sylvestris L.) covers large areas of the Northern Hemisphere, the Iberian Peninsula being its southwestern distribution limit. In recent decades, an increase in severe droughts and a densification of forests as a result of changes in forest uses have occurred in this region. Our aim was to use climate and stand structure data to explain mortality and growth patterns of Scots pine forests across the Iberian Peninsula. We used data from 2392 plots dominated by Scots pine, sampled for the National Forest Inventory of Spain. Plots were sampled from 1986 to 1996 (IFN2) and were resampled from 1997 to 2007 (IFN3), allowing for the calculation of growth and mortality rates. We fitted linear models to assess the response of growth and mortality rates to the spatial variability of climate, climatic anomalies, and forest structure. Over the period of approximately 10 years between the IFN2 and IFN3, the amount of standing dead trees increased 11-fold. Higher mortality rates were related to dryness, and growth was reduced with increasing dryness and temperature, but results also suggested that effects of climatic stressors were not restricted to dry sites only. Forest structure was strongly related to demographic rates, suggesting that stand development and competition are the main factors associated with demography. In the case of mortality, forest structure interacted with climate, suggesting that competition for water resources induces tree mortality in dry sites. A slight negative relationship was found between mortality and growth, indicating that both rates are likely to be affected by the same stress factors. Additionally, regeneration tended to be lower in plots with higher mortality. Taken together, our results suggest a large-scale self-thinning related to the recent densification of Scots pine forests. This process appears to be enhanced by dry conditions and may lead to a mismatch in forest turnover. Forest management may be an essential adaptive tool under the drier conditions predicted by most climate models.

Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

NASA Technical Reports Server (NTRS)

Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

Beneath the veil: Plant growth form influences the strength of species richness-productivity relationships in forests

USGS Publications Warehouse

Oberle, B.; Grace, J.B.; Chase, J.M.

2009-01-01

Aim: Species richness has been observed to increase with productivity at large spatial scales, though the strength of this relationship varies among functional groups. In forests, canopy trees shade understorey plants, and for this reason we hypothesize that species richness of canopy trees will depend on macroclimate, while species richness of shorter growth forms will additionally be affected by shading from the canopy. In this study we test for differences in species richness-productivity relationships (SRPRs) among growth forms (canopy trees, shrubs, herbaceous species) in small forest plots. Location: We analysed 231 plots ranging from 34.0?? to 48.3?? N latitude and from 75.0?? to 124.2?? W longitude in the United States. Methods: We analysed data collected by the USDA Forest Inventory and Analysis program for plant species richness partitioned into different growth forms, in small plots. We used actual evapotranspiration as a macroclimatic estimate of regional productivity and calculated the area of light-blocking tissue in the immediate area surrounding plots for an estimate of the intensity of local shading. We estimated and compared SRPRs for different partitions of the species richness dataset using generalized linear models and we incorporated the possible indirect effects of shading using a structural equation model. Results: Canopy tree species richness increased strongly with regional productivity, while local shading primarily explained the variation in herbaceous plant richness. Shrub species richness was related to both regional productivity and local shading. Main conclusions: The relationship between total forest plant species richness and productivity at large scales belies strong effects of local interactions. Counter to the pattern for overall richness, we found that understorey herbaceous plant species richness does not respond to regional productivity gradients, and instead is strongly influenced by canopy density, while shrub species richness is under multivariate control. ?? 2009 Blackwell Publishing.

Benefits of a strategic national forest inventory to science and society: the USDA Forest Service Forest Inventory and Analysis program

Treesearch

J. D. Shaw

2006-01-01

Benefits of a strategic national forest inventory to science and society: the USDA Forest Service Forest Inventory and Analysis program. Forest Inventory and Analysis, previously known as Forest Survey, is one of the oldest research and development programs in the USDA Forest Service. Statistically-based inventory efforts that started in Scandinavian countries in the...

Large-Scale Mixed Temperate Forest Mapping at the Single Tree Level using Airborne Laser Scanning

NASA Astrophysics Data System (ADS)

Scholl, V.; Morsdorf, F.; Ginzler, C.; Schaepman, M. E.

2017-12-01

Monitoring vegetation on a single tree level is critical to understand and model a variety of processes, functions, and changes in forest systems. Remote sensing technologies are increasingly utilized to complement and upscale the field-based measurements of forest inventories. Airborne laser scanning (ALS) systems provide valuable information in the vertical dimension for effective vegetation structure mapping. Although many algorithms exist to extract single tree segments from forest scans, they are often tuned to perform well in homogeneous coniferous or deciduous areas and are not successful in mixed forests. Other methods are too computationally expensive to apply operationally. The aim of this study was to develop a single tree detection workflow using leaf-off ALS data for the canton of Aargau in Switzerland. Aargau covers an area of over 1,400km2 and features mixed forests with various development stages and topography. Forest type was classified using random forests to guide local parameter selection. Canopy height model-based treetop maxima were detected and maintained based on the relationship between tree height and window size, used as a proxy to crown diameter. Watershed segmentation was used to generate crown polygons surrounding each maximum. The location, height, and crown dimensions of single trees were derived from the ALS returns within each polygon. Validation was performed through comparison with field measurements and extrapolated estimates from long-term monitoring plots of the Swiss National Forest Inventory within the framework of the Swiss Federal Institute for Forest, Snow, and Landscape Research. This method shows promise for robust, large-scale single tree detection in mixed forests. The single tree data will aid ecological studies as well as forest management practices. Figure description: Height-normalized ALS point cloud data (top) and resulting single tree segments (bottom) on the Laegeren mountain in Switzerland.