VTechWorks Repository :: Browsing by Author "Campbell, James B. Jr."

Browsing by Author "Campbell, James B. Jr."

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A 1000-year sedimentary record of hurricane, fire, and vegetation history from a coastal lagoon in southwestern Dominican Republic
LeBlanc, Allison Renee (Virginia Tech, 2011-03-24)
Our knowledge of whether hurricanes cause lasting changes in forest composition and the patterns and role of fire in Caribbean dry forests are lacking. This project combines paleoecological and paleotempestological methods to document the disturbance and environmental history of the last 1000 yrs at Laguna Alejandro, situated in the lowland dry forests of arid SW Dominican Republic. I analyzed multiple proxy data sources of a 160 cm coastal lagoon sediment profile. High-resolution (1 cm) sampling for loss-on-ignition and magnetic susceptibility indicated multiple erosion and hurricane events, including a hurricane ~996 cal YBP, and several erosion events and hurricanes between ~321 cal YBP and present day. Pollen analysis documented 32 plant families with most levels dominated by pollen of Fabaceae (legumes), the Urticales order, and Cyperaceae (sedges), though families of upland and montane vegetation are also present ~510-996 cal YBP. All pollen slides contained microscopic charcoal indicating the occurrence of regional or extra-local fires over the last ~1000 yrs. Local fires, as indicated by macroscopic charcoal, occurred before ~434 cal YBP and may be tied to hurricanes, increased moisture in the region (thereby increased fuel and ignition chances), or prehistoric human activities. Pollen spectra representing periods before and after disturbance events were similar and may support the idea of forest resilience, but more samples are needed. Multiple erosion events between ~294 cal YBP and present may be tied to hurricanes or tropical storms and increasing late-Holocene aridity in the region as documented by several studies from the Caribbean.
Accumulated Surfaces & Least-Cost Paths: GIS Modeling for Autonomous Ground Vehicle (AGV) Navigation
Stahl, Christopher Wayne (Virginia Tech, 2005-05-11)
The Geographic Information System (GIS) is a crucial part of any land navigation system. Autonomous ground vehicles should have access to stored geographic data and the ability to manipulate it for routing purposes. Since there is no human interaction involved in operating these vehicles, data that a human driver would use to make decisions must be stored in the GIS. The data which represent the earth's surface become a series of factors and constraints which translate to friction in terms of mobility. Factors need to be weighted appropriately, but require a sensitivity analysis before designating these weights. Constraints do not require any weight because they represent absolute barriers which cannot be traveled upon. All GIS layers are incorporated into the raster environment, so that an accumulated surfaces can be built on which a least-cost path can be located. The sensitivity analysis allows generation of many routes which can be field tested for the appropriate weight selection for each factor. Ultimately, the entire process would select an optimal path and output closely spaced waypoints which the vehicle can follow.
Accuracy Assessment of the National Land Cover Database Impervious Surface dataset for Roanoke, Virginia
Parece, Tammy E.; Campbell, James B. Jr. (2014)
The Multi-Resolution Land Characteristics Consortium (MRLC) developed National Land Cover Database Impervious Surface (NLCD IS) data to identify percent developed imperviousness for the coterminous USA. We present the results of an accuracy assessment on this data for the City of Roanoke, Virginia. First, we performed a classic accuracy assessment using a set of random points generated by GIS, and high resolution aerial photographs (1/2 foot resolution), varying the NLCD IS’ percent imperviousness from 10% to 75% per cell, resulting in an overall accuracy of around 70% for most thresholds. Then a polygon impervious surface dataset was delineated in GIS using the same high resolution aerial photos, and subsequently subdivided into 30 meter by 30 meter pixels matching each cell boundary of the NLCD IS data. A second accuracy assessment was performed on a cell by cell basis, comparing the NLCD IS to this newly created impervious surface dataset. Finally, terrain relief, specifically percent slope created from a 30 meter digital elevation model, was added to the analysis to determine if it impacted the accuracy of the NLCD IS data in the cell by cell assessment.
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.
Advanced spatial information processes: modeling and application
Zhang, Mingchuan (Virginia Polytechnic Institute and State University, 1985)
Making full use of spatial information is an important problem in information-processing and decision making. In this dissertation, two Bayesian decision theoretic frameworks for context classification are developed which make full use of spatial information. The first framework is a new multispectral image context classification technique which is based on a recursive algorithm for optimal estimation of the state of a two-dimensional discrete Markov Random Field (MRF). The implementation of the recursive algorithm is a form of dynamic programming. The second framework is based on a stochastic relaxation algorithm and Markov-Gibbs Random Fields. The relaxation algorithm constitutes an optimization using annealing. We also discuss how to estimate the Markov Random Field Model parameters, which is a key problem in using MRF in image processing and pattern recognition. The estimation of transition probabilities in a 2-D MRF is converted into two 1-D estimation problems. Then a Space-varying estimation method for transition probabilities is discussed.
Analysis and Reduction of Moire Patterns in Scanned Halftone Pictures
Liu, Xiangdong (Virginia Tech, 1996-05-01)
In this dissertation we provide a comprehensive theory for the formation of a moire pattern in a sampled halftone image. We explore techniques for restoring a sampled halftone image with a moire pattern and techniques for preventing a moire pattern when a halftone picture is scanned. Specifically, we study the frequency, phase, and spatial geometry of a moire pattern. We observe and explain the half period phase reversal phenomenon that a moire pattern may exhibit. As a case study, we examine the moire patterns generated by a commercial scanner. We propose three restoration methods, including a notch filtering method, a simulation method, and a relaxation method. We also describe a moire prevention method, the partial inverse Fourier transform method. Finally, we propose a research agenda for further investigation.
Analysis of Crop Phenology Using Time-Series MODIS Data and Climate Data
Ren, Jie; Campbell, James B. Jr.; Shao, Yang; Thomas, R. Quinn (2014)
Understanding crop phenology is fundamental to agricultural production, management, planning and decision-making. In the continental United States, key phenological stages are strongly influenced by meteorological and climatological conditions. This study used remote sensing satellite data and climate data to determine key phenological states of corn and soybean and evaluated estimates of these phenological parameters. A time series of Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composites from 2001 to 2013 was analyzed with the TIMESAT program to automatically retrieve key phenological stages such as the start of season (emergence), peak (heading) and end of season (maturity). These stages were simulated with 6 hourly temperature data from 1980 to 2013 on the basis of crop model under the Community Land Model (CLM) (version 4.5). With these two methods, planting date, heading date, harvesting date, and length of growing season from 2001 to 2013 were determined and compared. There should be a good correlation between estimates derived from satellites and estimates produced with the climate data based on the crop model.
Analysis of Multiresolution Data fusion Techniques
Carter, Duane B. (Virginia Tech, 1998-03-23)
In recent years, as the availability of remote sensing imagery of varying resolution has increased, merging images of differing spatial resolution has become a significant operation in the field of digital remote sensing. This practice, known as data fusion, is designed to enhance the spatial resolution of multispectral images by merging a relatively coarse-resolution image with a higher resolution panchromatic image of the same geographic area. This study examines properties of fused images and their ability to preserve the spectral integrity of the original image. It analyzes five current data fusion techniques for three complex scenes to assess their performance. The five data fusion models used include one spatial domain model (High-Pass Filter), two algebraic models (Multiplicative and Brovey Transform), and two spectral domain models (Principal Components Transform and Intensity-Hue-Saturation). SPOT data were chosen for both the panchromatic and multispectral data sets. These data sets were chosen for the high spatial resolution of the panchromatic (10 meters) data, the relatively high spectral resolution of the multispectral data, and the low spatial resolution ratio of two to one (2:1). After the application of the data fusion techniques, each merged image was analyzed statistically, graphically, and for increased photointerpretive potential as compared with the original multispectral images. While all of the data fusion models distorted the original multispectral imagery to an extent, both the Intensity-Hue-Saturation Model and the High-Pass Filter model maintained the original qualities of the multispectral imagery to an acceptable level. The High-Pass Filter model, designed to highlight the high frequency spatial information, provided the most noticeable increase in spatial resolution.
An Analysis of Shoreline Change at Little Lagoon, Alabama
Gibson, Glen R. (Virginia Tech, 2006-06-20)
In Alabama, the term "coastal shoreline" applies to the Gulf shoreline and the shorelines of estuaries, bays, and sounds connected to the Gulf of Mexico and subject to its tides. However, Alabama shoreline studies have yet to include Little Lagoon, which has been connected to the Gulf of Mexico for most of the last 200 years, according to historical charts. This study used historical nautical charts, aerial photographs, and LIDAR derived shorelines from 1917 to 2004 to analyze shoreline change on Little Lagoon and its adjacent Gulf shoreline. The high water line was used as the common reference feature, and all shorelines were georeferenced, projected, and digitized in a Geographic In-formation System. Between 1917 and 2001, the Gulf shoreline eroded an average of 40 m over 12.7 km, with some transects eroding almost 120 m while others accreted almost 60 m. The greatest changes to the Gulf shoreline were found near natural inlets, downdrift of jetties, and coincident with nourishment projects. Between 1955 and 1997, Little Lagoon shrank 0.5%, or 51.4 km², from 10,285.9 km² to 10,234.5 km². The greatest changes to Little Lagoon were found on its southern shoreline and near inlets, human development, and hurricane overwash fans. A correlation analysis conducted on the Gulf shoreline and Little Lagoon' s southern shoreline indicated that although weak overall correlation values exist when the entire 12.7 km study area is compared, strong correlation values are obtained in some areas when compared over one kilometer sections. The strongest correlations were found in the same locations as the greatest changes.
Analysis of technological change and relief representation in U.S.G.S. topographic maps
Mahoney, Patricia (Virginia Tech, 1991-01-15)
In 1882, the United States Geological Survey began its National Mappping Program designed to map the nation using a series of several thousand topographic quadrangles. Since that date, the program and the maps themselves have undergone many changes due mainly to technological advances in mapping methods. The use of data collected from historic U.S.G.S. topographic maps in modem day applications necessitates a general knowledge of the potentials and limitations of these data. This study compares representations of terrain features on historic maps compiled using plane table methods with the same features as represented on more accurate modem maps compiled using photogrammetry. Using the modem map as a standard, errors in the old maps were identified and defined using statistical procedures. Measures of closed contour lines recorded the angularity of the line, the length of the line, the area within the contour, the shape of the feature and spatial relationships between contour pairs. The analysis attempts to relate errors to these geometric components of contour lines and to predict the occurrence of error. Due to practices of smoothing and generalization of contour lines in plane table surveys, measures of both angularity and shape were significantly different between older and newer maps. Systematic errors, a consistent displacement of contour lines in a similar direction, were also identified on the historic maps. Based on these results, several suggestions for continuation of the research are given.
Analysis of Viewshed Accuracy with Variable Resolution LIDAR Digital Surface Models and Photogrammetrically-Derived Digital Elevation Models
Miller, Matthew Lowell (Virginia Tech, 2011-10-28)
The analysis of visibility between two points on the earth's terrain is a common use of GIS software. Most commercial GIS software packages include the ability to generate a viewshed, or a map of terrain surrounding a particular location that would be visible to an observer. Viewsheds are often generated using "bare-earth" Digital Elevation Models (DEMs) derived from the process of photogrammetry. More detailed models, known as Digital Surface Models (DSMs), are often generated using Light Detection and Ranging (LIDAR) which uses an airborne laser to scan the terrain. In addition to having greater accuracy than photogrammetric DEMs, LIDAR DSMs include surface features such as buildings and trees. This project used a visibility algorithm to predict visibility between observer and target locations using both photogrammetric DEMs and LIDAR DSMs of varying resolution. A field survey of the locations was conducted to determine the accuracy of the visibility predictions and to gauge the extent to which the presence of surface features in the DSMs affected the accuracy. The use of different resolution terrain models allowed for the analysis of the relationship between accuracy and optimal grid size. Additionally, a series of visibility predictions were made using Monte Carlo methods to add random error to the terrain elevation to estimate the probability of a target's being visible. Finally, the LIDAR DSMs were used to determine the linear distance of terrain along the lines-of-sight between the observer and targets that were obscured by trees or bushes. A logistic regression was performed between that distance and the visibility of the target to determine the extent to which a greater amount of vegetation along the line-of-sight impacted the target's visibility.
Application of Ancillary Data In Post-Classification to Improve Forest Area Estimates In A Landsat TM Scene
Holoviak, Brent Matthew (Virginia Tech, 2002-07-15)
In order to produce a more current inventory of forest estimates along with change estimates, the Forest Inventory Analysis (FIA) program has moved to an annual system in which 20% of the permanent plots in a state are surveyed. The previous system sampled permanent plots in 10-year intervals by sampling states sequentially in a cycle (Wayman 2001, USDA FIA). The move to an annual assessment has introduced the use satellite technology to produce forest estimates. Wayman et al (2001) researched the effectiveness of satellite technology in relation to aerial photo-interpretation, finding the satellite method to do an adequate job, but reporting over-estimations of forest area. This research extends the satellite method a step further, introducing the use of ancillary data in post-classification. The US Forest Service has well-defined definitions of forest and nonforest land-use in its (FIA) program. Using these definitions as parameters, post-classification techniques were developed to improve forest area estimates from the initial spectral classification. A goal of the study was to determine the accuracy of using readily available ancillary data. US Census data, TIGER street files, and local tax parcel data were used. An Urban Mask was created based on population density to mask out Forested pixels in a classified image. Logistic Regression was used to see if population density, street density, and land value were good predictors of forest/nonforest pixels. Research was also conducted on accuracy when using contiguity filters. The current filter used by the Virginia Department of Forestry (VDoF) was compared to functions available in ERDAS Imagine. These filters were applied as part of the post-classification techniques. Results show there was no significant difference in map accuracies at the 95% confidence interval using the ancillary data with filters in a post-classification sort. However, the use of ancillary data had liabilities depending on the resolution of the data and its application in overlay.
Application of Spatial Analysis in the Incidence of the Gall Midge in Jamaican Hot Pepper Production
Williams, Ryan Williams (Virginia Tech, 2001-05-30)
Jamaican farmers are experiencing constraints to hot pepper (Capsicum chinense) export production due to a quarantine pest -- the gall midge (Contarinia lycopersici; Prodiplosis longifila). There is a threat of gall midge introduction into the United States, where the insect pest is not known to occur. This research tests the significance of a range of variables to gall midge incidence. The purpose was to explain the spatial patterns that result from the relationships between gall midge incidence in hot pepper production and production methods and/or environmental conditions. There were three components to the sample of 47 farm visits: the interview, the hot pepper sampling, and the measurements of physical and locational attributes. Producers responded to questions about production methods, marketing, and quarantine issues. The percent of infested fruits per plot was calculated. GPS was used to record farm location. Using ArcView, environmental and climatic datasets were overlaid with farm locations and their attributes. Multiple regression was used to measure significance of variables to gall midge incidence. Cluster analyses were used to demonstrate the spatial patterns of the variability of gall midge incidence and its associated variables. There was significant effect on incidence by farm elevation, observance of pesticide-use recommendations, producer awareness of pre-clearance fumigation, and the use of intercropping in hot pepper production.
Application of Spectral Change Detection Techniques to Identify Forest Harvesting Using Landsat TM Data
Chambers, Samuel David (Virginia Tech, 2002-07-11)
The main objective of this study was to determine the spectral change technique best suited to detect complete forest harvests (clearcuts) in the Southern United States. In the pursuit of this objective eight existing change detection techniques were quantitatively evaluated and a hybrid method was also developed. Secondary objectives were to determine the impact of atmospheric corrections applied before the change detection, and the affect post-processing methods to eliminate small groups of misclassified pixels ("salt and pepper" effect) had on accuracy. Landsat TM imagery of Louisa County, Virginia was acquired on anniversary dates in both 1996 and 1998 (Path 16, Row 34), clipped to the study area boundary, and registered to one another. Previous to the change detection exercise, two levels of atmospheric corrections were applied to the imagery separately to produce three data sets. The three data sets were evaluated to determine what level of pre-processing is necessary for harvest change detection. In addition, eight change detection techniques were evaluated: 1) the 345 TM band differencing, 2) 35 TM band differencing, 3) NDVI differencing, 4) principal component 1 differencing, 5) selection of a change band in a multitemporal PCA, 6) tasseled cap brightness differencing, 7) tasseled cap greenness differencing, and 8) univariate differencing using TM band 7. A hybrid method that used the results from the eight previous techniques was developed. After performing the change detection, majority filters using window sizes of 3x3 pixels, 5x5 pixels, and 7x7 pixels were applied to the change maps to determine how eliminating small groups of misclassified pixels would affect accuracies. Accuracy assessments of the binary (harvested or not harvested) change maps were used to evaluate the accuracies of the various methods described using 256 validation points collected by the Virginia Department of Forestry. The atmospheric corrections did not seem to significantly benefit the change detection techniques, and in some cases actually degraded accuracies. Of the eight techniques applied to the original dataset, univariate differencing using TM band 7 performed the best with a 90.63% overall accuracy, while Tasseled Cap Greenness returned the worst result with an overall accuracy of 78.91%. Principal component 1 differencing and 35 differencing also performed well. The hybrid approach returned good results, but at its best returned an overall accuracy of 90.63%, matching the TM band 7 method. The majority filters using the 3x3 and 5x5 window sizes increased the accuracy in many cases, while the majority filter using the 7x7 window size degraded overall accuracy.
An approach to studying soil-landscape relationships in Virginia
Stolt, Mark H. (Virginia Tech, 1990)
Various methods and techniques were used to examine soil-landscape relationships for residual and colluvial soils of Virginia. Soil micromorphology indicated that although some BC and C horizons in the field appeared structureless, evidence of pedogenic process was observed. These were designated as either BCt, BC, or CB horizons depending on the amount of oriented clay and the rates of change with depth of clay, DCB extractable Fe, and sand contents. Soil variability was examined for the overall study, as well as within toposequences, pedons, and individual horizons. Most of the overall variability was attributed to differences between study sites or between horizons, with minimal amounts due to landscape position. Substantial lateral variability occurred within horizons indicating a strong need for subsampling within horizons of the same pedon. Lithologic discontinuities were found to be difficult to recognize without obvious field evidence. Reconstruction analysis was used to examine soil and saprolite formation. Summit and backslope soils were found to be essentially the same in both morphology and degree of profile development. Sand weathering and clay eluviation/illuviation were the major soil forming processes occurring within these soils. Footslope soils were less developed than associated summit and backslope soils, with both depositional and pedologic processes contributing to soil formation and development. Thickness of saprolite was found to decrease. from the summit to the footslope. Thicker saprolite at the summit was apparently related to the greater stability of the summit position compared to the backslope and footslopes. A bucket auger was modified to obtain undisturbed samples of deep saprolite for reconstruction analysis. Saprolite reconstruction indicated that between 20 and 36 % of the mass of the partially weathered rock, which is the precursor to saprolite, is lost during saprolite formation. Most of these losses were either Al or Si. Initial soil formation was shown to occur at a faster rate than saprolite formation, but after substantial profile development, soil formation is reduced to a rate below that of saprolite formation, and saprolite accumulates below the solum. Reconstruction analysis was found to be a valuable tool in studying soil-landscape relationships.
The Asian Tiger Mosquito (Aedes albopictus): Spatial, Ecological, and Human Implications in Southeast Virginia
Ratigan, Christopher William (Virginia Tech, 2000-01-28)
The overall theme that drove my research was the concern for public health and its possible compromise due to the colonization of large areas of the United States by the disease-vectoring Aedes albopictus. The main objective is to determine the elements that make an environment conducive to Aedes albopictus populations. Specifically, the objective of this research is to identify the socio-economic impact of Aedes albopictus on residents in the Hampton Roads area in southeast Virginia and determine if there is an identifiable environment in which A. albopictus could be found. Data were collected at the Census block group level (demographic variables) and at the single household level (survey and physical-cultural variables). The variables were then correlated (Pearson) and the results were analyzed. Only variables that were less than (.1) significance were examined. The following physical-cultural variables were found to be associated with the reduction of A. albopictus activity: having a sea breeze, being near an oceanfront, cutting the grass frequently, and keeping the overall neatness of a property high. Secondary variables that are related to the decrease in A. albopictus populations are sunny yards, yards with no containers that can hold water, and yards that contain coniferous trees versus deciduous trees. The primary socio-economic variables that can signify an environment with high A. albopictus activity are: lower house value and median rent value, lower levels of education, and a lower median income level. Other demographic variables that help determine the size of an A. albopictus population are (in order of significance): ethnicity (white or black), poverty/unemployed, owner/renter occupied, and the year a house was built. These secondary variables increase A. albopictus numbers if the following trends exist: high percent of persons in poverty and unemployed, higher percent of renter occupied homes, and older houses.
Assessing and Evaluating Recreation Resource Impacts: Spatial Analytical Approaches
Leung, Yu-Fai (Virginia Tech, 1998-02-09)
It is generally recognized that the magnitude of recreation resource impacts should be judged by their severity and spatial qualities, including extent, distribution, and association. Previous investigations, however, have primarily focused on assessing the severity of impacts, with limited examination of spatial qualities. The goal of this dissertation was to expand our understanding of the spatial dimension of recreation resource impacts and their assessment and evaluation. Two empirical data sets collected from a comprehensive recreation impact assessment and monitoring project in Great Smoky Mountains National Park provided the basis for the analyses. Three spatial issues were examined and presented as three papers, designed for journal submission. The purpose of the first paper was to improve our understanding of the dimensional structure and spatial patterns of camping impacts by means of multivariate analyses and mapping. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: land disturbance, soil and groundcover damage, and tree-related damage. Cluster analysis yielded three distinctive campsite types that characterize both the intensity and areal extent of camping impacts. Spatial patterns and site attributes of these three campsite types and an additional group of primitive campsites were illustrated and discussed. The purpose of the second paper was to examine the influence of sampling interval on the accuracy of selected trail impact indicator estimates for the widely applied systematic point sampling method. A resampling-simulation method was developed and applied. Simulation results indicated that using systematic point sampling for estimating lineal extent of trail impact problems can achieve an excellent level of accuracy at sampling intervals of less than 100 m, and a reasonably good level of accuracy at intervals between 100 and 500 m. The magnitude of accuracy loss could be higher when the directions of loss are not considered. The responses of accuracy loss on frequency of occurrence estimates to increasing sampling intervals were consistent across impact types, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling using an interval of less than 500 m can be an appropriate method for estimating the lineal extent, but not for estimating occurrence of trail impacts. Further investigations are called for to examine the generalizability of these results to other areas. The purpose of the third paper was to expand the scope of indices used for evaluating recreation resource impacts. Two specific objectives were to synthesize the recreation ecology and recreation resource management literature on the use of spatial indicators and indices, and to propose and apply selected spatial indices that are mostly lacking in the literature. Three spatial indices primarily adapted from the geography and ecology literature were proposed for application in recreation impact evaluation. Application results demonstrated that the Lorenz curve and associated Gini coefficient, and the linear nearest-neighbor analysis and associated LR ratio were effective in quantifying the spatial distribution patterns of trail impacts at landscape and trail scales, respectively. Application results of the third index, the impact association index, were less promising and require further refinements. Management implications and future directions of research were discussed in light of the findings of this dissertation. As the field of recreation ecology is emerging, this dissertation has demonstrated: (1) the value of recreation impact assessment and monitoring programs in providing data for examining the spatial dimension of impacts, and (2) the utility of spatial analytical approaches in understanding recreation impact assessment and evaluation.
Assessing annual urban change and its impacts on evapotranspiration
Wan, Heng (Virginia Tech, 2020-06-19)
Land Use Land Cover Change (LULCC) is a major component of global environmental change, which could result in huge impacts on biodiversity, water yield and quality, climate, soil condition, food security and human welfare. Of all the LULCC types, urbanization is considered to be the most impactful one. Monitoring past and current urbanization processes could provide valuable information for ecosystem services evaluation and policy-making. The National Land Cover Database (NLCD) provides land use land cover data covering the entire United States, and it is widely used as land use land cover data input in numerous environmental models. One major drawback of NLCD is that it is updated every five years, which makes it unsatisfactory for some models requiring land use land cover data with a higher temporal resolution. This dissertation integrated a rich time series of Landsat imagery and NLCD to achieve annual urban change mapping in the Washington D.C. metropolitan area by using time series data change point detection methods. Three different time series change point detection methods were tested and compared to find out the optimal one. One major limitation of using the above time series change point detection method for annual urban mapping is that it relies heavily on NLCD, thus the method is not applicable to near-real time monitoring of urban change. To achieve the near real-time urban change identification, this research applied machine learning-based classification models, including random forest and Artificial Neural Networks (ANN), to automatically detect urban changes by using a rich time series of Landsat imagery as inputs. Urban growth could result in a higher probability of flooding by reducing infiltration and evapotranspiration (ET). ET plays an important role in stormwater mitigation and flood reduction, thus assessing the changes of ET under different urban growth scenarios could yield valuable information for urban planners and policy makers. In this study, spatial-explicit annual ET data at 30-m resolution was generated for Virginia Beach by integrating daily ET data derived from METRIC model and Landsat imagery. Annual ET rates across different major land cover types were compared, and the results indicated that converting forests to urban could result in a huge deduction in ET, thus increasing flood probability. Furthermore, we developed statistical models to explain spatial ET variation using high resolution (1m) land cover data. The results showed that annual ET will increase with the increase of the canopy cover, and it would decrease with the increase of impervious cover and water table depth.
Assessing Coastal Plain Wetland Composition using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery
Pantaleoni, Eva (Virginia Tech, 2007-05-03)
Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. In this study, we used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185υm). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classs of the study locations, we generated a Classification and Regression Tree (CART) model and a Multinomial Logistic Regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while the overall accuracy of the logit model was 76.7%. Although the CART producer's accuracy (correct category classification) of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%), we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a sub-pixel analysis of the ASTER images to establish canopy cover of forested wetlands. The canopy cover ranged from 0 to 225 m2. We used visble-near-infrared ASTER bands, Delta Normalized Difference Vegetation Index, and a Tasselled Cap transformation in an ordinary linear regression (OLS) model. The model achieved an adjusted-R2 of 0.69 and an RMSE of 2.73% when the canopy cover is less than 16%. For higher canopy cover values, the adjusted-R2 was 0.4 and the RMSE was19.79%. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type.
Assessing the Impacts of Balsam Woolly Adelgid (Adelges Piceae Ratz.) and Anthropogenic Disturbance on the Stand Structure and Mortality of Fraser Fir (Abies Fraseri (Pursh) Poir.) in the Black Mountains, North Carolina
McManamay, Rachel Harris (Virginia Tech, 2009-05-06)
Over the past several decades, naturally occurring populations of Fraser fir (Abies fraseri) in the Black Mountains of North Carolina have been heavily impacted by both direct and indirect anthropogenic disturbances, including logging and logging- associated fires, and high mortality rates due to the introduction of the exotic insect, balsam woolly adelgid (BWA) (Adelges piceae). The decline in Fraser fir is particularly concern because it serves as a foundation species within the spruce-fir forests of the Southern Appalachian Mountains. Our objectives for this research were to 1) use current stand structure to infer whether Fraser fir trees are experiencing a cycle of regeneration-mortality that will lead to eventual decline of the population, 2) determine what role, if any, the site-specific geographic variables of slope, elevation, aspect, and land use history have on stand structure, mortality, and BWA infestation level, and 3) analyze repeat aerial photography to examine broad trends of spruce-fir forest cover change caused by anthropogenic disturbance and the BWA. In order to understand stand structure, mortality, and infestation levels, we conducted detailed field surveys of Fraser fir trees throughout the Black Mountains using 44, fixed-radius circular sampling plots. These plots were placed throughout a series of aspects, elevations, and disturbance types in order to understand geographic variability among these variables. An analysis of 4 repeat aerial photographs and corroborating ground photographs revealed broad spatio-temporal trends of spruce-fir regeneration and mortality from 1954 to 2006. Our results indicate that Fraser fir stands at higher elevations are currently in a state of recovery; whereas stands at lower elevations appear to be more susceptible to BWA-induced mortality. Changes in forest cover area from 1954 to 2006 were influenced greatly by direct and indirect anthropogenic disturbance. Our results call attention to the significant impact that direct and indirect anthropogenic disturbance has had on Fraser fir stand structure, but also provide evidence for the ability of an imperiled ecosystem to recover from high rates of insect caused mortality.

Browsing by Author "Campbell, James B. Jr."

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