TY - JOUR
AB - The article contains all poster abstracts from the Wildland Fire track of the 2013 Society of American Foresters National Convention. Geospatial Technologies Jingjing Liang a Corresponding author (jiliang@mail.wvu.edu). b West Virginia University, Division of Forestry and Natural Resources, Morgantown, WV 26506. Mapping Large-Scale Forest Dynamics: A Geospatial Approach 107 Digital maps of forest dynamics are emerging as useful research and management tools. As a key issue to address in developing digital maps of forest dynamics, spatial autocorrelation has been distinguished into “true” and “false” gradients. Previous ecological models are mostly focused on either “true” or “false” gradient, and little has been studied to simultaneously account for both gradients in a single model. The main objective of this study was to incorporate both gradients of spatial autocorrelation in a deterministic geospatial model to provide improved accuracy and reliability in future digital maps of forest dynamics. The mapping was based on two underlying assumptions—unit homogeneity and intrinsic stationarity. This study shows that when the factors causing the spatial nonstationarity have been accounted for, forest states could become a stationary process. A prototype geospatial model was developed for the Alaska boreal forest to study current and future stockings across the region. With areas of the highest basal area increment rate projected to cluster along the major rivers and the lowest near the four major urban developments in Alaska, it was hypothesized that moisture limitation and inappropriate human interference were the main factors affecting the stocking rates. These results could be of unprecedented value, especially for the majority of Alaska boreal region where little information is available. Rick Odom Mark Ford Stephen Prisley a Corresponding author (rhodom@vt.edu). b Virginia Tech, Charlottesville, VA 22901. c USGS Fish & Wildlife Coop Research Unit, Virginia Tech, Blacksburg, VA 24061. d Virginia Tech, Blacksburg, VA 24061. Simulating Extent of Forest Ecoregions under Future Climate Scenarios 383 To better understand the potential impact of climate change on military installations in the continental US, the extent of current and future ecoregions were mapped using the Holdridge Life Zone system for three climate change scenarios using an ensemble approach. Relative change in climate variables was summarized for over 600 military installations and included in a vulnerability index being developed for military installations. A conceptual approach for large-scale simulation of forest ecosystem change at specific installations using the LANDIS-II modeling environment is also described. James Jeuck Christopher Hopkins Dennis Hazel Robert Bardon a Corresponding author (jajeuck@ncsu.edu). b North Carolina State University Extension Forestry, Raleigh, NC 29695. c North Carolina State University, Durham, NC 27705. Geospatial Leveraging of FIA Data for Assessing Woody Biomass Potential in North Carolina 419 NCSU Extension Forestry has conducted over 50 detailed biomass supply assessments supporting prospective projects on behalf of bio-energy industries and economic developers. These analyses leverage data from numerous sources and scales for gross woody biomass, drain, and net woody biomass distributed spatially across timberland. Described here are details of NCSU FiberAnalytics processing techniques for two levels of woody biomass supply assessment offered to clients. The first level results in state-wide, coarse-resolution, gradient maps of net supply based on client feedstock preferences. These are derived from net supply-distance curve coefficients generated through a series of neighborhood functions performed on net supply maps. Web-hosting interactive assessment enables potential industries, policy developers or others to explore scenarios across the state. The second level of supply assessment is performed for clients with identified site locations. For each identified site, supply areas are developed for specified haul distances using road networks. All forms of potential woody biomass are applied to timberland distributed (derived from satellite imagery) throughout each supply area, summed, and used to develop supply curves. Estimated demand from facility-specific demand regions for existing and potential competitors are subtracted yielding accurately portrayed net supply based on distance and feedstock type. Jin Hyung Lee Gregg Cassidy a Corresponding author (jin_hyung_lee@brown.edu). b Brown University, Providence, RI 02912. c Rhode Island Department of Environmental Management, Providence, RI 02908. Application of GIS to Assess Potential Forest Legacy Program Projects 429 Rhode Island's Forest Legacy Area (FLA) includes a large portion of the State's rural area. Geospatial information system (GIS) data was used to develop a map to assist the Rhode Island Forest Legacy Committee to identify focus areas within the FLA to prioritize land protection activities. The United States Forest Service (USFS) lists the social, ecological, and economic attributes as deemed important for the Forest Legacy Program (FLP), ranks all projects submitted by how many of these attributes each project meets and accepts projects based on their rank and the president's budget. A map was created by inputting data for key attributes used to determine which projects are selected for funding. By doing so, the model map was able to 1) highlight areas within the state's FLA where the State ought to focus its efforts and 2) predict whether a proposed project would rank highly and therefore, predict the potential of a project being funded. These capabilities demonstrate the map's ability to be used as a tool for decision makers in assessing potential projects for the FLP. Through the use of such a map, decision makers can more effectively and more efficiently utilize resources to protect meaningful forestland. Matthew Wade David Kulhavy Daniel Unger I-Kuai Hung a Stephen F. Austin State University, Arthur Temple College of Forestry and Agriculture, Nacogdoches, TX 75962. b Corresponding author (unger@sfasu.edu). Evaluating Tree Height Using Pictometry Hyperspatial Imagery Versus Traditional Measurements 438 Trees within Nacogdoches, Texas were measured for height using Pictometry hyperspatial imagery at 4-inch spatial resolution. Trees measured included baldcypress located on LaNana Creek as part of a hybrid analysis study. Baldcypress, Taxodium distichum, was planted along La Nana Creek, Nacogdoches, Texas, for erosion control and as a test bank for growth of the species genotypes. Each tree was located with GPS and entered into the GIS database in the Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University. Actual tree height, measured using a height pole in 0.1-inch increments, was compared to tree height measured onscreen using Pictometry hyperspatial 4-inch spatial digital imagery. Remotely sensed tree height using Pictometry digital imagery was within 2.5 percent of actual height. Results indicate that hyperspatial digital imagery is an effective and cost effective method to measure tree height in lieu of in situ measurements. David Dyson John Gilbert a Corresponding author (dsdyson@fs.fed.us). b USDA Forest Service, Escambia Experimental Forest, Brewton, AL 36426. c Auburn University, School of Forestry and Wildlife Sciences, Longleaf Pine Stand Dynamics Laboratory, Auburn, AL 36849. Improving Forest Research and Management Using Geospatial Technology: GIS at the Escambia 450 Geographic Information Systems (GIS) are a vital part of forest management that allow managers to organize, view, analyze, and interpret data with a spatial reference. Examples include information such as species, age, volume, and management practices for individual forest stands. Originally designed and maintained at the drafting table, advancements in computing and Global Positioning System (GPS) technology have greatly increased the capabilities and power of GIS. Spatial data for the Escambia Experimental Forest dates back to the forest's establishment in 1947 as “pencil and paper” maps showing all the spatial information related to forest management and research locations. As technology has advanced, these maps and spatial data have been digitized and incorporated with GPS data to create a dynamic GIS database, which provides many applications useful for both managers and scientists. With today's GIS, spatial data is more secure (stored in multiple locations), more available (can be accessed remotely), and more efficient (requires less space and time to maintain). GIS technology has also helped improve forest management by providing a mapping tool with increased precision and accuracy and a method to analyze effects of management activities and determine current and future needs. Matthew Holt a Corresponding author (mholt5@utk.edu). b University of Tennessee, Knoxville, TN 37920. Multivariate Analysis of Forest Type Classifications in Tennessee 501 The goal of this study is to identify forest type classifications for areas in Tennessee using Continuous Forest Inventory (CFI) and Geographic Information Systems (GIS). As acreage increases, assigning appropriate sampling intensities becomes more difficult and costly. The ability to stratify based on known forest compositions can save time and money while producing better estimates of current and future inventories. The use of stratified sampling often increases sampling efficiency, but it requires accurate classification of different strata. The study tested ESRI's multivariate spatial statistical analysis tool's ability to stratify using multiple layers including aerial imagery and topography. The factors chosen to identify unsupervised classes were: slope, aspect, distance from drainage, elevation, soil type, and moisture. Supervised locations were created using CFI data and aerial imagery. The results of the analysis were mapped and compared to collected CFI land type classifications from permanent plots established across the study area. Future results will be used to calculate growth models for species in mixed hardwood forest across multiple physiographic land types in Tennessee. Kristen Brubaker Laura Leites Sarah Johnson Josh Brinks a Corresponding author (brubaker@hws.edu). b Hobart and William Smith Colleges, Geneva, NY 14456. c Penn State University, University Park, PA 16802. d The Nature Conservancy Pennsylvania, Harrisburg, PA 17110. Estimating Canopy Height of Deciduous Forests at a Regional Scale with Leaf-Off, Low-Density LiDAR 521 As we strive towards a more accurate understanding and quantification of carbon pools in forested ecosystems, the development of landscape scale maps of forest characteristics is essential to establish baselines and monitor change. LiDAR (Light Detection and Ranging) is increasingly being used to improve our understanding of forested ecosystems on a broad spatial scale, although obtaining data can be expensive and time consuming. We evaluated the effectiveness of using freely available low point density, leaf off LiDAR collected for the entire state of Pennsylvania, to create an accurate state-wide dominant/co-dominant canopy height model for the State Forests in Pennsylvania. We tested several methodologies using a ground truthed inventory dataset with over 1400 sample points. The canopy height model we created was accurate to about 10% of the field measured dominant/co-dominant tree height for each plot, with a RMSE of approximately 2 m across all site and forest variables. Factors that affected the accuracy of the canopy height model included tree density, slope, and percent evergreen cover. Copyright © 2014 Society of American Foresters
TI - Abstract
JF - Journal of Forestry
DO - 10.1093/jof/112.1.161
DA - 2014-01-01
UR - https://www.deepdyve.com/lp/springer-journals/abstract-m0IqUXBCqP
SP - 161
EP - 163
VL - 112
IS - 1
DP - DeepDyve
ER -