VTechWorks Repository :: Browsing by Author "Prisley, Stephen P."

Browsing by Author "Prisley, Stephen P."

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Acid deposition effects on soil chemistry and forest growth on the Monongahela National Forest
Elias, Patricia Elena (Virginia Tech, 2008-07-28)
Acid deposition (AD) results largely from the combustion of fossil fuels, and has been found to negatively impact forest ecosystems. AD may acidify soils through base cation leaching or Al mobilization, may cause accumulation of nitrates and sulfates in soils, and in some cases has been related to forest decline. The Monongahela National Forest (MNF) lies downwind from many sources of AD pollution, and average deposition pH is around 4.4. Therefore, managers are concerned about the possible deleterious effects of AD on the forest ecosystem. During the 2006 Forest Plan revision, evaluation of site sensitivity to acidification was specifically stated as a step in the Forest's adaptive management process. To meet this management objective, forest practitioners must understand the effects AD has on the forest, prescribe appropriate practices, and be able to monitor for future changes. To address the needs of MNF managers we used Forest Inventory and Analysis (FIA) sites to evaluate forest growth patterns on the Forest and determined the relationship between growth and key indicators of soil acidity. Furthermore, we used those relationships to create a map of site resistance to acidification across the MNF. To further develop a monitoring scheme we assessed two soil sampling protocols and two soil analysis methods for their suitability for monitoring AD-related changes in soil chemistry. Additionally, we evaluated the utility of dendrochronological and foliar sampling as AD-specific monitoring methods. Across all FIA sites on the MNF periodic mean annual volume increment (PMAVI) ranged from -9.5 m³ha⁻¹yr¹ to 11.8 m³ha⁻¹yr¹, suggesting lower-than-expected growth on two-thirds of the sites. Growth was compared to soil indicators of acidity on 30 FIA sites. In the surface horizon, effective base saturation (+), Ca concentration (+), base saturation (+), K concentration (+), Fe concentration (-), Ca/Al molar ratio (+), and Mg/Al molar ratio (+), were correlated with PMAVI (p ≤ 0.1). In the subsurface horizon pH_(w) (+), effective base saturation (+), Al concentration (-), and K concentration (-) were correlated with PMAVI. Site resistance to acidification was mapped based on site parent material, aspect, elevation, soil depth, and soil texture. There was a significant (p ≤ 0.1) positive correlation between PMAVI and a resistance index developed using five soil and site factors. Resistance was also compared with key soil indicators of AD-induced decline on 28 sites across the forest, and pH, effective base saturation, and Al content were found to be the best indicators related to resistance index. Resistance index was used to create a map of the MNF, of which 14% was highly resistant (RI ≥ 0.7), 57% was moderately resistant (0.7 > RI > 0.45) and 29% was slightly resistant (RI ≤ 0.45). The first of our monitoring program evaluations compared soil sampling and analysis methods on 30 FIA plots. Analyses of variance showed that soil pH, effective base saturation, Ca/Al molar ratio, and sum of bases varied significantly with sampling protocol. We also compared lab analyses methods and found that if sampling by horizon, a linear relationship can be used to estimate Ca/Al_SrCl₂ ratio using NH₄Cl extractions. The second monitoring approach evaluated the utility of a northern red oak (Quercus rubra L.) dendrochronology on two FIA plots. This analysis suggests that pollution on the MNF caused a decrease in growth rate during the 50-year period from 1940 to 1990. There were no differences among ring width increment and basal area increment between the two sites. From 1900 to 2007 the two sites showed 58.5% similarity in growth trends, but these could not be attributed to a dissimilar influence of AD. The third monitoring approach evaluated the relationship between foliar and soil chemical indicators. Across FIA plots, nutrient concentrations varied by tree species. The first year results from a potted-seedling study suggest that soil acidity influences growth, and foliar concentrations are related to growth rates. This evaluation of the effects of AD on the MNF can be used to develop adaptive management plans and a monitoring program that will meet the AD-related objectives of the 2006 Forest Management plan.
An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery
Bortolot, Zachary Jared (Virginia Tech, 2004-04-23)
Forests have been proposed as a means of reducing atmospheric carbon dioxide levels due to their ability to store carbon as biomass. To quantify the amount of atmospheric carbon sequestered by forests, biomass and density estimates are often needed. This study develops, implements, and tests an individual tree-based algorithm for obtaining forest density and biomass using orthophotographs and small footprint LiDAR imagery. It was designed to work with a range of forests and image types without modification, which is accomplished by using generic properties of trees found in many types of images. Multiple parameters are employed to determine how these generic properties are used. To set these parameters, training data is used in conjunction with an optimization algorithm (a modified Nelder-Mead simplex algorithm or a genetic algorithm). The training data consist of small images in which density and biomass are known. A first test of this technique was performed using 25 circular plots (radius = 15 m) placed in young pine plantations in central Virginia, together with false color othophotograph (spatial resolution = 0.5 m) or small footprint LiDAR (interpolated to 0.5 m) imagery. The highest density prediction accuracies (r2 up to 0.88, RMSE as low as 83 trees / ha) were found for runs where photointerpreted densities were used for training and testing. For tests run using density measurements made on the ground, accuracies were consistency higher for orthophotograph-based results than for LiDAR-based results, and were higher for trees with DBH ≥10cm than for trees with DBH ≥7 cm. Biomass estimates obtained by the algorithm using LiDAR imagery had a lower RMSE (as low as 15.6 t / ha) than most comparable studies. The correlations between the actual and predicted values (r2 up to 0.64) were lower than comparable studies, but were generally highly significant (p ≤ 0.05 or 0.01). In all runs there was no obvious relationship between accuracy and the amount of training data used, but the algorithm was sensitive to which training and testing data were selected. Methods were evaluated for combining predictions made using different parameter sets obtained after training using identical data. It was found that averaging the predictions produced improved results. After training using density estimates from the human photointerpreter, 89% of the trees located by the algorithm corresponded to trees found by the human photointerpreter. A comparison of the two optimization techniques found them to be comparable in speed and effectiveness.
Assessing the Effects of Sea-Level Rise on Piping Plover (Charadrius Melodus) Nesting Habitat, and the Ecology of a Key Mammalian Shorebird Predator, on Assateague Island
Gieder, Katherina Dominique (Virginia Tech, 2015-09-02)
The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands along the U.S. Atlantic Coast and is highly vulnerable to habitat change and predation. We have addressed these two threats by 1) developing and implementing a linked model system that predicts future change to piping plover habitat resulting from sea-level rise and beach management efforts by joining dynamic models of sea-level rise, shoreline change, island geomorphology and piping plover nest habitat suitability, and 2) quantifying occupancy and movement of the red fox (Vulpes vulpes), a key shorebird predator at Assateague Island, Maryland and Virginia. We constructed and tested a model that links changes in geomorphological characteristics to piping plover nesting habitat suitability. We then linked this model to larger scale shoreline change resulting from sea level rise and storms. Using this linked model to forecast future sea-level rise and beach management efforts, we found that modest sea-level rise rates (3 mm and 4.1 mm/yr; similar to current rates) may increase suitable piping plover nesting habitat area in 50-100 years and some beach management strategies (beach nourishment and artificial dune modifications) also influence habitat availability. Our development and implementation of this tool to predict change in piping plover habitat suitability provides a vital starting point for predicting how plover nesting habitat will change in a context of planned human modifications intended to address climate change-related threats. Our findings regarding red fox occupancy and movement complement the use of this model for planning future management actions by providing vital information on the effects of certain predator management activities and habitat use of a key mammalian predator, the red fox, for shorebirds along the U.S. Atlantic Coast. Overall, we found that 1) red fox occupancy was strongly tied to eastern cottontail (Sylvilagus floridanus) trap success, increasing sharply with increased eastern cottontail trap success, 2) red fox occupancy did not change in response to an intensive eradication program, and 3) red foxes in our study area generally moved little between camera stations spaced 300 m from each other, but may move large distances (> 6km) at times, likely to occupy new territory available after lethal control efforts. Our findings have important ramifications for the sustainability of long-term predator removal programs and our understanding of future habitat change on the red fox. For example how vegetation changes affect eastern cottontails, how resulting fluctuations in eastern cottontails affect red fox occupancy, and how consequential changes in red fox occupancy affect plover breeding productivity. Our predictive model combined with these predator findings will allow wildlife managers to better plan and implement effective management actions for piping plovers in response to the multiple stressors of SLR-induced habitat change and predation.
Assessing the Sustainability of Virginia’s Commercial Wood Supply
Prisley, Stephen P. (Virginia Tech. Center for Natural Resources Assessment & Decision Support, 2015-04-15)
This presentation to the Virginia Forestry Summit in April 2015 reports on CENRADS' baseline assessment of the sustainability of Virginia's commercial wood supply.
Baseline Analysis of Virginia’s Commercial Wood Supply
Prisley, Stephen P. (Virginia Tech. Center for Natural Resources Assessment and Decision Support, 2015-02)
Baseline information is crucial for planning and policymaking regarding our forest resources. CeNRADS has conducted a “Tier I” forest resource assessment for the Commonwealth of Virginia. A Tier I assessment is based upon the most fundamental and readily available public data. This assessment uses recent inventory data from the US Forest Service, 2011 land cover data from US Geological Survey, ownership data from the Virginia Department of Conservation and Recreation, and soils, terrain, and population data from various agencies. In addition, harvest notification records from the Virginia Department of Forestry are used to characterize the areas within Virginia that have experienced harvests within the last 5 years. These data are collated and analyzed to determine the forest resource potentially available for harvest, and how recent harvest levels compare to forest growth as reported by the forest inventory.
Biogeochemistry of Carbon on Disturbed Forest Landscapes
Amichev, Beyhan Y. (Virginia Tech, 2007-04-11)
Carbon accreditation of forest development projects is essential for sequestering atmospheric CO2 under the provisions of the Kyoto Protocol. The carbon sequestration potential of surface coal-mined lands is not well known. The purpose of this work was to determine how to measure carbon sequestration and estimate the additional amount that could be sequestered using different reforestation methods compared to the common practice of establishing grasslands. I developed a thermal oxidation technique for differentiating sequestered soil carbon from inorganic and fossilized carbon found at high levels in mine soils along with a geospatial and statistical protocol for carbon monitoring and accounting. I used existing tree, litter, and soil carbon data for 14 mined and 8 adjacent, non-mined forests in the Midwestern and Eastern coal regions to determine, and model sequestered carbon across the spectrum of site index and stand age in pine, mixed, and hardwood forest stands. Finally, I developed the framework of a decision support system consisting of the first iteration of a dynamic model to predict carbon sequestration for a 60-year period for three forest types (white pine, hybrid poplar, and native hardwoods) at three levels of management intensity: low (weed control), medium (weed control and tillage) and high (weed control, tillage, and fertilization). On average, the highest amount of ecosystem carbon on mined land was sequestered by pine stands (148 Mg ha-1), followed by hardwood (130 Mg ha-1) and mixed stands (118 Mg ha-1). Non-mined hardwood stands contained 210 Mg C ha-1, which was about 62% higher than the average of all mined stands. After 60 years, the net carbon in ecosystem components, wood products, and landfills ranged from 20 to 235 Mg ha-1 among all scenarios. The highest net amount of carbon was estimated under mixed hardwood vegetation established by the highest intensity treatment. Under this scenario, a surface-mined land of average site quality would sequester net carbon stock at 235 Mg C ha-1, at a rate of 3.9 Mg C ha-1 yr-1, which was 100% greater than a grassland scenario. Reforestation is a logical choice for mined land reclamation if carbon sequestration is a management objective.
Build-Out Analysis as a Planning Tool With a Demonstration for Roanoke County, Virginia
Zirkle, Mary A. (Virginia Tech, 2003-04-18)
The objectives of this paper are to explain what build-out analysis is and how localities can integrate it into their planning regimen. In addition, I will demonstrate a build-out analysis tailored to Roanoke County, Virginia, in order to calculate the fiscal impact of its current zoning ordinance at complete build-out. I conclude with recommendations for Roanoke County, other uses of build-out analysis and conclusions about this tool. The purpose of a build-out analysis is to show a locality what land is available for development, how much development can occur and at what densities, and what consequences may result when complete build-out of available land occurs according to the zoning ordinance. A build-out analysis can reflect changes in the zoning ordinance to illustrate the effects of those changes on future resources. A build-out analysis can also help quantify the costs of growth. Original build-out analyses were done by hand and relied on mathematical formulas. Now, build-out analyses are becoming more popular, feasible and dynamic with advances in computers and developments in geographic information system (GIS) software. While mathematical formulas still produce the quantitative measures of build out, GIS can provide visual representation and spatial specificity, as well as some of the quantitative measures. The first part of this paper describes the process of conducting a build-out analysis. The second part uses a modified process to illustrate how to tailor build-out analysis to a real location. This location is Roanoke County, which is experiencing growth demands in its low- to medium-density residential zoning districts. It appears from my analysis that Roanoke County can withstand another century of growth in these zoning districts before it reaches build-out, if the smallest lot sizes are applied. If larger lots are used, build-out will occur faster. From my analysis, it appears that small-lot zoning would cost the County more initially but may ultimately preserve more of the things that citizens value, as described in the goals of the 1998 Community Plan. Measures need to be taken at present to prepare for the growth allowed by the Countyâ s 1992 Zoning Ordinance.
The Cartographic Representation of Language: Understanding language map construction and visualizing language diversity
Luebbering, Candice Rae (Virginia Tech, 2011-03-23)
Language maps provide illustrations of linguistic and cultural diversity and distribution, appearing in outlets ranging from textbooks and news articles to websites and wall maps. They are valuable visual aids that accompany discussions of our cultural climate. Despite the prevalent use of language maps as educational tools, little recent research addresses the difficult task of map construction for this fluid cultural characteristic. The display and analysis capabilities of current geographic information systems (GIS) provide a new opportunity for revisiting and challenging the issues of language mapping. In an effort to renew language mapping research and explore the potential of GIS, this dissertation is composed of three studies that collectively present a progressive work on language mapping. The first study summarizes the language mapping literature, addressing the difficulties and limitations of assigning language to space before describing contemporary language mapping projects as well as future research possibilities with current technology. In an effort to identify common language mapping practices, the second study is a map survey documenting the cartographic characteristics of existing language maps. The survey not only consistently categorizes language map symbology, it also captures unique strategies observed for handling locations with linguistic plurality as well as representing language data uncertainty. A new typology of language map symbology is compiled based on the map survey results. Finally, the third study specifically addresses two gaps in the language mapping literature: the issue of visualizing linguistic diversity and the scarcity of GIS applications in language mapping research. The study uses census data for the Washington, D.C. Metropolitan Statistical Area to explore visualization possibilities for representing the linguistic diversity. After recreating mapping strategies already in use for showing linguistic diversity, the study applies an existing statistic (a linguistic diversity index) as a new mapping variable to generate a new visualization type: a linguistic diversity surface. The overall goal of this dissertation is to provide the impetus for continued language mapping research and contribute to the understanding and creation of language maps in education, research, politics, and other venues.
Center for Natural Resources Assessment and Decision Support (CENRADS) Quarterly Report, January 2015
Prisley, Stephen P. (Virginia Tech. Center for Natural Resources Assessment and Decision Support, 2015-01)
This quarterly report for the Center for Natural Resources Assessment and Decision Support (CENRADS) provides updates on current research and future projects at the Center.
Cheetah of the Serengeti Plains: A home range analysis
Laver, Peter Norman (Virginia Tech, 2005-11-11)
Cheetah (Acinonyx jubatus) persist under continued conservation threat in small populations mostly in protected areas in an historically reduced geographic range. Home range, a useful trait for threat assessment, species reintroduction, and population estimation, is plastic in cheetah with sizes ranging from 40 km2 to over 1000 km2 depending on location. Previous home range estimates for cheetah used the minimum convex polygon (MCP), assuming asymptotic home ranges and MCP insensitivity to sample size. They reported metrics of home range size and overlap based on only outline methods. I use 6 481 observations of 240 female and 315 male cheetah from > 60 matrilines over 25 years in the Serengeti Plains to investigate lifetime, core, yearly, and seasonal range size with kernel density estimation. I investigate autocorrelation using time to statistical independence of locations. I confront the assumption of asymptotic home ranges by testing the traditional and multiscaled home range predictions and provide a novel method for determining kernel asymptotes. I challenge the notion of Serengeti cheetah as a migratory carnivore with analyses of site fidelity and objectively defined core ranges. I assess year to year and seasonal location shifts, showing that yearly shifting lessens as females age. I provide quantitative evidence for philopatry in female- and juvenile dispersal in male cheetah of the Serengeti Plains. I use simple overlap metrics to show that overlap in lifetime and core ranges is greater in related than unrelated female pairs. I use multi-response permutation procedures (MRPP) to show that overlap in unrelated female pairs varies with season. I use correlation of utilization distributions to show that avoidance is apparent only in unrelated pairs of females. My results call into question previous MCP estimates of cheetah home range size, and provide guidance for future sampling of cheetah locations. My home range results will guide management of this imperiled species and my methodological findings may be general and applicable to a wide range of taxa.
Coarse Woody Debris in Industrially Managed Pinus taeda Plantations of the Southeastern United States
Pittman, Judd R. (Virginia Tech, 2005-07-15)
Coarse woody debris (CWD) plays an influential role in forested ecosystems by adding organic matter to soils, stabilizing the soil environment, providing wildlife habitat, preventing soil erosion, providing seedling establishment habitat, and involvement in the nutrient cycle. Most CWD research has been conducted in old-growth and unmanaged, second-growth forests. However, less is understood about CWD in intensively managed ecosystems, such as industrialized southern pine plantations. The objectives of this study were to determine the climatic and ecological factors that affect the decomposition rate of CWD, to predict the decomposition rate, specific gravity, and time since death (TSD) using multiple linear regression in industrial loblolly pine (Pinus taeda L.) plantations in the southeastern United States. The study sites for this project were part of a long-term, loblolly pine thinning study maintained by the Loblolly Pine Growth and Yield Research Cooperative at Virginia Tech. Measurements included piece size, position, and decay class. Samples of CWD were collected and analyzed to determine their mass and density. Decomposition rate of CWD was significantly different across position classes and decay classes: disk decomposition rates were significantly negatively correlated with disk diameter, large and small end piece diameter, estimated disk height, and disk dry weight. Average annual precipitation and average annual temperature were not significantly correlated with CWD disk decomposition rate.
Community Based Backyard Conservation for Wildlife in Loudoun County Virginia's Evergreen Rural Village- A Planned Residential Development
Kordella, Lesley Ann (Virginia Tech, 2005-04-15)
Centex Homes initiated the development of a wildlife management plan for Evergreen Rural Village, a planned residential development in Loudoun County, Virginia. The county's landscape has changed from rural to suburban in the past decade, prompting the need to integrate natural resource management into land planning processes. Centex Homes partnered with Virginia Tech to develop a long term management plan for wildlife living in and around the property that incorporates community outreach and resident education. Specific recommendations in this plan incorporate habitat enhancement projects designed for a 148-acre lot donated to Loudoun County Parks and Recreation Department and community outreach activities. The plan also specifies recommendations for managing buffer areas that exist within the perimeters of large "conservancy lots" of Evergreen, which measure approximately 20 acres to 108 acres, and consist of limited agricultural use. Lastly, the management plan includes recommendations for the design of small scale habitat enhancement projects for central village lots and low impact development sites. The management plan relies on the participation of community members to become environmental stewards of their own backyards and natural space. Recommendations from this management plan are designed for a wildlife management based covenant for the Home Owners Association.
A Comparison of GIS Approaches to Slope Instability Zonation in the Central Blue Ridge Mountains of Virginia
Galang, Jeffrey (Virginia Tech, 2004-10-22)
To aid in forest management, various approaches using Geographic Information Systems (GIS) have been used to identify the spatial distributions of relative slope instability. This study presents a systematic evaluation of three common slope instability modeling approaches applied in the Blue Ridge Mountains of Virginia. The modeling approaches include the Qualitative Map Combination, Bivariate Statistical Analysis, and the Shallow Landsliding Stability (SHALSTAB) model. Historically, the qualitative nature of the first model has led to the use of more quantitative statistical models and more deterministic physically-based models such as SHALSTAB. Although numerous studies have been performed utilizing each approach in various regions of the world, only a few comparisons of these approaches have been done in order to assess whether the quantitative and deterministic models result in better identification of instability. The goal of this study is to provide an assessment of relative model behavior and error potential in order to ascertain which model may be the most effective at identifying slope instability in a forest management context. The models are developed using both 10-meter and 30-meter elevation data and outputs are standardized and classified into instability classes (e.g. low instability to high instability). The outputs are compared with cross-tabulation tables based on the area (m²) assigned to each instability class and validated using known locations of debris flows. In addition, an assessment of the effects of varying source data (i.e. 10-meter vs. 30-meter) is performed. Among all models and using either resolution data, the Qualitative Map Combination correctly identifies the most debris flows. In addition, the Qualitative Map Combination is the best model in terms of correctly identifying debris flows while minimizing the classification of high instability in areas not affected by debris flows. The statistical model only performs well when using 10-meter data while SHALSTAB only performs well using 30-meter data. Overall, 30-meter elevation data predicts the location of debris flows better than 10-meter data due to the inclusion of more area into higher instability classes. Of the models, the statistical approach is the least sensitive to variations in source elevation data.
A Comparison of Spatial Interpolation Techniques for Determining Shoaling Rates of the Atlantic Ocean Channel
Sterling, David L. (Virginia Tech, 2003-05-08)
The United States of Army Corp of Engineers (USACE) closely monitors the changing depths of navigation channels throughout the U.S. and Western Europe. The main issue with their surveying methodology is that the USACE surveys in linear cross sections, perpendicular to the channel direction. Depending on the channel length and width, these cross sections are spaced 100 - 400 feet apart, which produces large unmapped areas within each cross section of a survey. Using a variety of spatial interpolation methods, depths of these unmapped areas were produced. The choice of spatial interpolator varied upon which method adequately produced surfaces from large hydrographic survey data sets with the lowest amount of prediction error. The data used for this research consisted of multibeam and singlebeam surveys. These surveys were taken in a systematic manner of linear cross-sections that produced tens of thousands of data points. Nine interpolation techniques (inverse distance weighting, completely regularized spline, spline with tension, thin plate spline, multiquadratic spline, inverse multiquadratic spline, ordinary kriging, simple kriging, and universal kriging) were compared for their ability to accurately produce bathymetric surfaces of navigation channels. Each interpolation method was tested for effectiveness in determining depths at "unknown" areas. The level of accuracy was tested through validation and cross validation of training and test data sets for a particular hydrographic survey. By using interpolation, grid surfaces were created at 15, 30, 60, and 90-meter resolution for each survey of the study site, the Atlantic Ocean Channel. These surfaces are used to produce shoaling amounts, which are taken in the form of volumes (yd.³). Because the Atlantic Ocean Channel is a large channel with a small gradual change in depth, a comparison of grid resolution was conducted to determine what difference, if any, exists between the calculated volumes from varying grid resolutions. Also, a comparison of TIN model volume calculations was compared to grid volume estimates. Volumes are used to determine the amount of shoaling and at what rate shoaling is occurring in a navigation channel. Shoaling in each channel was calculated for the entire channel length. Volumes from varying grid resolutions were produced from the Atlantic Ocean Channel over a seven-year period from 1994-2001. Using randomly arranged test and training datasets, spline with tension and thin plate spline produced the mean total error when interpolating using singlebeam and multibeam hydrographic data respectively. Thin plate spline and simple kriging produced the lowest mean total error in full cross validation testing of entire singlebeam and multibeam hydrographic datasets respectively. Volume analysis of varying grid resolution indicates that finer grid resolution provides volume estimates comparable to TIN modeling, the USACE's technique for determining sediment volume estimates. The coarser the resolution, the less similar the volume estimates are in comparison to TIN modeling. All grid resolutions indicate that the Atlantic Ocean Channel is shoaling. Using a plan depth of 53 feet, TIN modeling displayed an annual average increase of 928,985 cubic yards of sediment from 1994 - 2001.
Comparison of Techniques for Estimation of Forest Soil Carbon
Amichev, Beyhan Y. (Virginia Tech, 2004-05-06)
Soil organic carbon represents the largest constituent of the global C pool and carbon budgets are studied by researchers and modelers in C cycling, global climate change, and soil quality studies. Pedon and soil interpretation record databases are used with soil and ecological maps to estimate regional SOC even though these databases are rarely complete for surface litter and mineral subsurface horizons. The first main objective of the project is to improve the ability to produce soil organic carbon estimates from existing spatial soils datasets, such as STATSGO. All records in the STATSGO Layer table that were incomplete or appeared to be incorrectly filled with a null or zero value were considered invalid. Data sorting procedures and texture lookup tables were used to identify exiting correct (valid) data entries that were used to substitute invalid records. STATSGO soil property data were grouped by soil order, MLRA, layer number, and texture to produce replacement values for all invalid data used to calculate mass SOC. Grouping criteria was specific to each variable and was based on texture designations. The resulting filled and unfilled tables were used with procedures assuming Normal and Lognormal distribution of parameters in order to analyze variation of mass SOC estimates caused by using different computation techniques. We estimated mass SOC to 2 m in Maine and Minnesota using filled and unfilled STATSGO data tables. Up to 54% of the records in Maine and up to 80% of the records in Minnesota contained null or zero values (mostly in fields related to rock fragments) that were replaced. After filling, the database resulted in 1.5 times higher area-weighted SOC. SOC calculated using the Normal distribution assumption were 1.2 to 1.5 times higher than those using the Lognormal transformation. SOC maps using the filled tables had more logical geographic SOC distribution than those using unfilled tables. The USDA Forest Service collects and maintains detailed inventory data for the condition and trends of all forested lands in the United States. A wide range of researchers and landowners use the resulting Forest Inventory and Analysis (FIA) database for analytical and decision making tasks. FIA data is available to the public in transformed or aggregate format in order to ensure confidentiality of data suppliers. The second main objective of this project was to compute SOC (kg m-2) results by FIA forest type and forest type group for three depth categories (25 cm, 1 m, and 2 m) at a regional scale for the 48 contiguous United States. There were four sets of results derived from the filled STATSGO and FIA datasets for each depth class by region: (1) SOC computed by the Lognormal distribution approach for (1a) all soil orders, (1b) without Histosols; and (2) SOC computed by the Normal distribution approach for (2a) all soil orders, (2b) without Histosols. Two spatial forest cover datasets were relevant to this project, FIA and AVHRR. We investigated the effects of FIA inventory data masking for Maine and Minnesota, such as plot coordinates rounding to the nearest 100 arc-second, and the use of 1 km resolution satellite-derived forest cover classes from AVHRR data, on SOC estimates to 2 m by forest type group. SOC estimates by soil mapping unit were derived from fixed STATSGO database tables and were computed by the Lognormal distribution approach including all soil orders. The methods in this study can be used for a variety of ecological and resource inventory assessments and the automated procedures can be easily updated and improved for future uses. The procedures in this study point out areas that could benefit the most during future revisions of STATSGO. The resulting SOC maps are dynamic and can be rapidly redrawn using GIS whenever STATSGO spatial or tabular data undergo updating. Use of pedon data to define representative values for all properties in all STATSGO layers and correlation of STATSGO layers to soil horizons will lead to vast improvement of the STATSGO Layer table and promote its use for mass SOC estimation over large regions.
A Computer Simulation Model for Predicting the Impacts of Log Truck Turn-Time on Timber Harvesting System Productivity
Barrett, Scott M. (Virginia Tech, 2001-01-18)
A computer simulation model was developed to represent a logging contractor's harvesting and trucking system of wood delivery from the contractor's in-woods landing to the receiving mill. The Log Trucking System Simulation model (LTSS) focuses on the impacts to logging contractors as changes in truck turn times cause an imbalance between harvesting and trucking systems. The model was designed to serve as a practical tool that can illustrate the magnitude of cost and productivity changes as the delivery capacity of the contractor's trucking system changes. The model was used to perform incremental analyses using an example contractor's costs and production rates to illustrate the nature of impacts associated with changes in the contractor's trucking system. These analyses indicated that the primary impact of increased turn times occurs when increased delivery time decreases the number of loads per day the contractor's trucking system can deliver. When increased delivery times cause the trucking system to limit harvesting production, total costs per delivered ton increase. In cases where trucking significantly limits system production, total costs per delivered ton would decrease if additional trucks were added. The model allows the user to simulate a harvest with up to eight products trucked to different receiving mills. The LTSS model can be utilized without extensive data input requirements and serves as a user friendly tool for predicting cost and productivity changes in a logging contractor's harvesting and trucking system based on changes in truck delivery times.
Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake
Cooner, Austin Jeffrey (Virginia Tech, 2016-12-19)
Remote sensing continues to be an invaluable tool in earthquake damage assessments and emergency response. This study evaluates the effectiveness of multilayer feedforward neural networks, radial basis neural networks, and Random Forests in detecting earthquake damage caused by the 2010 Port-au-Prince, Haiti 7.0 moment magnitude (Mw) event. Additionally, textural and structural features including entropy, dissimilarity, Laplacian of Gaussian, and rectangular fit are investigated as key variables for high spatial resolution imagery classification. Our findings show that each of the algorithms achieved nearly a 90% kernel density match using the United Nations Operational Satellite Applications Programme (UNITAR/UNOSAT) dataset as validation. The multilayer feedforward network was able to achieve an error rate below 40% in detecting damaged buildings. Spatial features of texture and structure were far more important in algorithmic classification than spectral information, highlighting the potential for future implementation of machine learning algorithms which use panchromatic or pansharpened imagery alone.
Developing a Topographic Model to Predict the Northern Hardwood Forest Type within Carolina Northern Flying Squirrel (Glaucomys sabrinus coloratus) Recovery Areas of the Southern Appalachians
Evans, Andrew M.; Odom, Richard H.; Resler, Lynn M.; Ford, W. Mark; Prisley, Stephen P. (Hindawi, 2014-08-28)
The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Our study related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrain variables analyzed included elevation, aspect, slope gradient, site curvature, and topographic exposure. We used an information-theoretic approach to assess seven models based on associations noted in existing literature as well as an inclusive global model. Our results indicate that, on a regional scale, elevation, aspect, and topographic exposure index (TEI) are significant predictors of the presence of the northern hardwood forest type in the southern Appalachians. Our elevation + TEI model was the best approximating model (the lowest AICc score) for predicting northern hardwood forest type correctly classifying approximately 78% of our sample points. We then used these data to create region-wide predictive maps of the distribution of the northern hardwood forest type within CNFS recovery areas.
Development and assessment of remotely derived variables in current southern pine beetle (Dendroctonus frontalis Zimm.) hazard mapping in North Carolina, USA
Moan, Jason Edward (Virginia Tech, 2008-07-24)
The southern pine beetle (SPB) (Dendroctonus frontalis Zimm.) is one of the most destructive forest insect pests in the southeastern United States and has historically had a large impact on the forests of North Carolina. Many characteristics of a forest can contribute to SPB susceptibility including stand density, growth rate, age, soil type, and position on the landscape. This work was undertaken in an effort to assist and improve on the current federal SPB hazard modeling being conducted for North Carolina by the USDA Forest Service – Forest Health Protection's Forest Health Technology Enterprise Team (FHTET). In our study, predictive SPB susceptibility models were developed for each physiographic region in North Carolina using two variables not currently included in the FHTET modeling, mean stand age and the in-stand percentage of sawtimber-sized pines. These variables were obtained from USDA Forest Service – Forest Inventory and Analysis (FIA) data and North Carolina Forest Service historical SPB records creating a dataset of both infested and non-infested stands and the models were developed using the CART® classification tree approach. Two model-derived age classes (older than and younger than 22 years) were identified on the landscape using current Landsat 5 Thematic Mapper (TM) imagery chronosequences of disturbance index (DI) â transformed scenes to identify stand-replacing disturbances, resulting in a kappa statistic of 0.6364 for the younger than 22 year age class and 0.7778 for the older than 22 years age class. A kappa value of 1 is ideal. The CART® modeling effort produced valid models in all three physiographic regions of North Carolina, though the complexity of the piedmont model makes it impractical for use in the field. The dependent variable in the classification tree was presence or absence of SPB outbreak and the test sample error percentages were similar across regions, with errors ranging between 23.76 - 34.95 percent. Overall prediction success, based on the software's internal cross-validation procedure, was likewise comparable across the regions with 72.28 - 89.56 percent correctly predicted. Based on our modeling, stand age and percent sawtimber should be included in future FHTET SPB hazard modeling efforts for the coastal plain and mountains, respectively. Age classes can be reasonably estimated using Landsat or other multispectral imagery.
Diameter Distributions of Juvenile Stands of Loblolly Pine (Pinus taeda L.) with Different Planting Densities
Bullock, Bronson P. (Virginia Tech, 2002-02-08)
Diameter distributions of juvenile loblolly pine (Pinus taeda L.) with different planting densities were characterized utilizing a two-parameter Weibull distribution. Trend analysis was employed to describe the effects of planting density, age, relative spacing, and rectangularity on the estimated diameter distributions for juvenile loblolly pine. A reparameterization of the two-parameter Weibull distribution was sought to reduce the dispersion of the estimated shape parameter. Methods that quantify the amount of inter-tree spatial dependency in a particular stand were applied. Empirical semivariograms were derived for each plot over all ages to enable spatial trend recognition. Moran's I and Geary's C coefficients were estimated for ground-line diameters from ages 2 to 5, and for breast height diameters from ages 5 to 11. Though there was no discernable trend in the presence of significant spatial autocorrelation with planting density, an initial negative trend with age was present, but leveled off by age 5. A conditional autoregressive model was utilized to evaluate the amount of spatial influence stems in a stand have on one another. The occurrence of significant spatial influences was positively associated with age through age 8, the trend then leveled off; no recognizable trend was detected with planting density. These indices help to describe stand dynamics that are influenced by the spatial distribution of stems. Models to predict the parameters of the two-parameter Weibull distribution were developed to aid in forecasting and simulation of juvenile loblolly pine. Simulations were conducted where a spatial dependency was imposed on the diameters within a stand. The spatial structure simulation enables accurate representations of stem characteristics when simulating forest stands that include spatially-explicit information.

Browsing by Author "Prisley, Stephen P."

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