Virginia Tech GIS and Remote Sensing Research Symposium

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https://hdl.handle.net/10919/88978

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2012 OGIS Symposium Program
McGee, John; Wynne, Randolph H.; Shao, Yang (2012-04-13)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 13, 2012.
2013 OGIS Symposium Program
McGee, John; Wynne, Randolph H.; Shao, Yang (2013-04-19)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 19, 2013.
2014 OGIS Symposium Program
McGee, John; Wynne, Randolph H.; Thomas, Valerie A. (2014-04-04)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 4, 2014.
2015 OGIS Symposium List of Poster Presentations
McGee, John (2015-04-10)
List of student posters and web map app presentations from the symposium held on April 10, 2015.
2015 OGIS Symposium Program
McGee, John; Wynne, Randolph H. (2015-04-10)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 10, 2015.
2016 OGIS Symposium Program
McGee, John; Wynne, Randolph H. (2016-04-08)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 8, 2016.
2017 OGIS and Virginia GIS Conference List of Poster Presentations
McGee, John (2017-04-06)
List of student posters and web map app presentations from the conference held on April 6, 2017.
2018 OGIS Symposium Program
McGee, John; Wynne, Randolph H. (2018-04-20)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 20, 2018.
2019 OGIS Symposium Program
McGee, John; Wynne, Randolph H. (2019-04-26)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 26, 2019.
2021 GIS and Remote Sensing Research Symposium
(2021-04-30)
Schedule for the Virginia Tech GIS and Remote Sensing Symposium, held on April 30, 2021.
Assessing Seasonal Changes of Spatial Complexity in Riverscapes using Drone-Based Laser Scanning
Aquilina, Charles A.; Hession, W. Cully; Lehman, Laura; Resop, Jonathan P. (Virginia Tech, 2019-04-26)
Light detection and ranging (lidar) is a form of remote sensing using laser pulses to measure distances. Recent advancement in lidar technology has made units small enough to mount on drones, which makes high-quality data more accessible. Recent studies have utilized drone-based photogrammetry to measure characteristics of streams and rivers, as well as their associated riparian areas. These areas have been referred to as riverscapes. The physical characteristics of riverscapes are traditionally difficult to measure due to ever-changing characteristics across space and time. Drone-based laser scanning (DLS), is uniquely positioned to measure changing physical characteristics as it allows for increased temporal (daily, monthly, seasonal flights) and spatial (more than 400 pts/m2 at 30-m flight elevation) resolutions. It has more upfront costs compared to photogrammetry, as a DLS system (large drone and lidar) is vastly more expensive than a small drone with a digital camera payload. However, lidar can penetrate through vegetation, allowing for high-quality ground data, as well as vegetation points, which is a limitation of photogrammetry. One use of this ground and vegetation data is to analyze small changes of the topography to estimate complexity (an important habitat variable), as well as obstructions to flow such as vegetation. These obstructions to flow result in increased roughness, which is an important metric in biological studies and hydraulic modeling. In previous studies, estimating roughness was limited to visual observations or back-calculating from flow measurements, which can be time consuming and does not produce continuous spatial data. Using DLS-derived ground and vegetation, we will monitor small changes in vegetation and topography over the course of the stream both longitudinally, laterally, and through time. We will test various methods of computing roughness from detailed lidar point clouds to determine roughness. Some possibilities estimating roughness and complexity include the standard deviation of the elevation change, the variation between maximum and minimum elevations in a pixel, slope variability, surface roughness factors, and others. These values can be compared to a calibrated 2D hydraulic flood modeling (HEC-RAS), DLS has the potential to change the way we map and understand spatial complexity and habitat characteristics of riverscapes.
Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States
Ritz, Alison; Thomas, Valerie A.; Wynne, Randolph H. (Virginia Tech, 2021-04-30)
Remote sensing offers many advantages to previous forest measurements, such as limiting costs and time in the field. Light detection and ranging (lidar) has been shown to enable accurate estimates of forest height. Lidar does produce precise measurements for ground elevation and forest height, where and when it is available. However, it is expensive to collect and does not have wall-to-wall coverage in the United States. In this study, we estimated height using the National Agricultural Imagery Program (NAIP) photogrammetric point clouds to create a predicted height map for managed loblolly pine stands in the southeastern United States. Recent studies have investigated the ability of digital aerial photogrammetry (DAP), and more specifically NAIP, as an alternative to lidar as a means of estimating forest height due to its lower costs, frequency of acquisition, and wall-to-wall coverage across the United States. Field-collected canopy height for 534 plots in Virginia and North Carolina were regressed against distributional metrics derived from NAIP and lidar point clouds. The best regression model for predicted pine height used the 90th percentile of height (P90), predicted pine height = 1.09(P90) – 0.43. The adjusted R^2 is 0.93 and the RMSE is 1.44 m. This model is being used to produce a 5 x 5 m canopy height model for all pine stands across Virginia, North Carolina, and Tennessee. NAIP-derived point clouds are thus a viable means of predicting canopy height in southern pines.
Assessment of the diurnal relationship of photochemical reflectance index to forest light use efficiency by accounting for sunlit and shaded foliage
Williams, Paige Tatum; Harding, David J.; Thomas, Valerie A.; Wynne, Randolph H.; Ranson, Kenneth J.; Huemmrich, Karl F.; Middleton, Elizabeth; Campbell, Petya K. (Virginia Tech, 2021-04-30)
Gross Primary Productivity (GPP) is the amount of carbon fixed during photosynthesis by all producers in the ecosystem. GPP is dependent on light use efficiency (LUE), photosynthetically active radiation (PAR), and fraction of absorbed PAR (fPAR). To estimate light use efficiency (LUE), which is dependent on the exposure of leaves to photosynthetically active radiation (PAR), the photochemical reflectance index (PRI) is calculated using 531 nm and 570 nm wavelengths. Our team has examined the sensitivity of forest canopy PRI to canopy shadows using airborne hyperspectral data acquired in eastern North Carolina. A bounding box for this study was placed adjacent to a flux tower in a loblolly pine stand to evaluate the variability of LUE derived from the reflectance data acquired in the morning, midday and afternoon, and compare LUE estimates to the flux tower observations. We compute PRI values for the sunlit and shadowed parts of the canopy determined by thresholding a 2 m panchromatic image produced by averaging wavelength bands from 525 nm to 600 nm. We show that PRI for the sunlit canopy is substantially lower than for the shadowed components at all times of day, leading to an overestimate of LUE when using whole-canopy reflectance. Implications for estimating GPP using PRI reflectance as a surrogate for LUE is examined by comparing to the flux tower derivation of GPP. This work is being done to refine measurement requirements for a diurnal constellation concept, the Structure and Function of Ecosystems (SAFE).
Attribute Standardization of Car Crashes and Its Potential Uses
Mitchell, Allison; Hamilton, Lonnie III; Newman, Joseph (Virginia Tech, 2019-04-26)
The primary focus of our research endeavor centers around standardizing the spatial attributes of police-reported crash records in the Commonwealth of Virginia. The Center for Geospatial Information Technology at Virginia Tech (CGIT) is working in support of the Virginia Department of Motor Vehicles Highway Safety Office’s mission to improve public safety. This data will be used by highway safety officials to identify particularly dangerous intersections and road segments across the commonwealth. We evaluated the crash factors and characteristics present in the dataset to better understand the potential that geospatial techniques can provide to the highway safety community. We elected to analyze crashes involving the black bear (Ursus Americanus) to see what observation could be made. To start, it was necessary to define the criteria to identify crashes involving bears. This was initially done manually by using an SQL request to obtain all records from 2018 crash data where the word ‘bear’ is referenced in the officer’s narrative. From there, we conducted a manual sort of the remaining data to help craft future, more efficient SQL requests for other years Once all records involving bears have been found, the data will be rendered in ArcGIS. Some exploratory analyses we plan on conducting involve identifying routes with high incidences of bear-related crashes, overlaying the crashes with known Wildlife Urban Interfaces (zones where housing density >6.17 housing units/km2 and vegetation cover >50%), and overlaying the crashes with the known habitats of the black bear in the commonwealth to observe if and how they may differ.
Beaver-driven dynamics of a peatland ecotone: Identification of landscape features with Lidar and geomorphon analysis
Swift, Troy P.; Kennedy, Lisa M. (Virginia Tech, 2021-04-30)
Beaver are renowned for their role as ecosystem engineers. Their ponds and vegetation consumption can greatly alter local hydrology and ratios of meadow to woodland. Beavers also actively buffer their environments against drought and wildfire susceptibility, and influence important climate parameters like carbon retention and methanogenesis (Rozhkova-Timina et al. 2018). This investigation focuses on beaver impacts on the boreal peatland ecotones enmeshing Cranberry Glades Botanical Area (~300 ha, ~1000 masl), a National Natural Landmark in mountainous West Virginia. Beaver activity has been suggested (Stine et al. 2011) to have an important role in the formation and maintenance of peatland conditions at Cranberry Glades. Using Lidar, geomorphon analysis, and aerial imagery, we were able to identify and reconstruct shifting hydrological patterns associated with beaver dams and ponds. The three-year interval worked well, allowing time for widespread changes in beaver infrastructure while conserving utility of reference imagery. Future work will include analysis of the most recent beaver activity, refinement of classification workflows, generation of more accurate physical models using drone-acquired Lidar and better ground filtering, and more complete incorporation of historical imagery.
Comparing UAS and Pole Photogrammetry for Monitoring Beach Erosion
Gonzales, Jack; Pingel, Thomas (Virginia Tech, 2021-04-30)
Sandy beaches are vulnerable to extreme erosion, especially during hurricanes and other extreme storms, as well as gradual seasonal erosion cycles. Left unchecked, coastal erosion can put people, homes, and other infrastructure at risk. To effectively manage beach resources, coastal managers must have a reliable means of surveying the beach to monitor erosion and accretion. Traditionally, these surveys have used standard ground-based survey methods, but advancements in remote sensing technology have given surveyors new tools to monitor erosion. Structure from Motion (SfM) photogrammetry presents an inexpensive, fast, and reliable method for routine beach surveying. Typically, SfM utilizes photos taken by unmanned aerial systems (UAS), but weather conditions and government regulations can make flying difficult or impossible, especially around crowded areas popular with beachgoers. Photos taken from a tall pole on a mobile platform can also be used for SfM, eliminated the challenges posed by weather and UAS regulations. This poster compares UAS SfM and “photogrammetry on a stick” (POAS) for monitoring beach erosion. Three surveys were conducted on a barrier Island in South Carolina, at monthly intervals, using both UAS SfM and POAS. Both techniques show promise, but POAS is more difficult to generate quality reconstructions from, while UAS provides a faster, smoother workflow.
Digital Transformation: Possibilities for a Geo-Enabled Campus
Miller, Geri (Virginia Tech, 2019-04-26)
A Geo-enabled Campus is a campus where everyone is empowered with access to geospatial tools, data, and technologies, embracing all aspects of a campus’ teaching, research, and administration. There are a lot of possibilities to achieve a Geo-enabled campus, given the massive digital transformation we are experiencing. Digital transformation means using technology to fundamentally change what we do, and today there are many technology trends which influence our actions. Some trends, like Drones and AI, are enablers of major transformation because the power of disruption is in the hands of the user/implementer. Others like Smart Cities and Autonomous Vehicles will have impacts on us that are beyond the control of any one person, organization or society. These trends are powerful, analytics driven, and location aware. These trends have influenced the development of geospatial technology and have increased the potential for truly geoenabling a campus in many ways, from curriculum and learning, to research, to campus operations.
Effect of establishment fertilization on leaf area development of loblolly pine plantation stands in the southeastern United States
House, Matt (Virginia Tech, 2021-04-30)
Loblolly pine plantations in the southeastern United States are some of the most intensively managed forest plantations in the world. Within intensive management one common practice is fertilizing a stand/site at establishment. The objective of this study was to investigate the effect of establishment fertilization on the leaf area development of loblolly pine planation stands across time. Sub-objectives included comparison of fertilized stands with stands that had no intervention and examination of whether identifying fertilized stands and no intervention stands could be applied across the landscape. To account for the size of the study area and different landscape types (elevation and proximity to a coast) the study area was also stratified by hardiness zone. Additionally, the study was stratified by soil type, specifically CRIFF (Cooperative Research in Forest Fertilization) groupings. Leaf area index (LAI) is a meaningful biophysical parameter and an important functional and structural element of a plantation stand. The Landsat satellite missions provides plantation managers and scientists a way to estimate LAI over time. Google Earth Engine (GEE) provides the ability to leverage the Landsat archive to obtain LAI estimates over large areas and through time. Stand boundaries were buffered inwards 30m to minimize mixed pixels and to match the spatial resolution of Landsat. LAI was computed (using: SR * 0.3329155 - 0.00212) to create trajectories of mean Stand LAI over time for analysis.
Effects of Clearing Linear Features through Forest Patches in WV and VA
Moore, Sierra; Klopfer, Scott D. (Virginia Tech, 2021-04-30)
Recent pipeline construction through predominantly forested mountain areas presents many concerns for environmentalists. Impacts from construction are often measured in total area of forest removal, but this may not capture the extent of change to the landscape. Other effects, such as increased fragmentation and edge go unmeasured. We examined changes to the forest landscape resulting from the Mountain Valley Pipeline; a recently constructed corridor that runs through West Virginia and Virginia. We identified affected forest patches using the 2016 National Land Cover Dataset and analyzed both pre- and post-construction patch characteristics. The total area of forest removed was 1,182.57 ha, (0.03%). The total core forest decreased by 5,781.33 ha (2.7%). The number of forest patches increased from 242 to 667, with an average of 2.9 new patches per original patch. The edge density increased 5.4% between pre and post pipeline (0.0059 m/ha to 0.0062 m/ha). Area/Perimeter ratio increased between pre and post construction (0.049 to 0.2524). Our results demonstrate that area, alone, is insufficient to determine the total impacts of linear construction on forest in the study area, particularly since the loss of core forest and increasing edge have well-documented impacts to ecological processes.
The Effects of Land Cover Change on the Spatial Distribution of Lyme Disease in Northern Virginia Since 2005
Stevenson, Megan N.; Kolivras, Korine N. (Virginia Tech, 2019-04-26)
Lyme disease has been a growing problem in the United States over the last few decades, and is currently the most common vector-borne disease in the country. This research evaluates the land cover within specified counties of northern Virginia to find a correlation between forest fragmentation, suburbanization, and cases of human Lyme disease; as has been demonstrated in other Lyme endemic regions in the United States. Few studies have focused specifically on northern Virginia when considering the impacts of land cover change on Lyme disease. Discovered through the use of GIS and Geospatial Modelling Environment softwares, the cluster of Lyme disease cases in northern Virginia could be attributed to the forest fragmentation within the study region, which creates an ideal habitat for black-legged ticks and allows for an increase in Lyme disease transfer from vector to humans. The goal is for the research findings to be applicable to other regions with similar land cover types. Regions with similar characteristics would then be able to recognize the potential risk of human Lyme disease and implement ways to reduce the Lyme disease risk associated with suburban development. The purpose of this study is to answer the following research questions: 1) How has the spatial distribution of Lyme disease in Northern Virginia changed since 2005 with respect to land cover? 2) Which suburban communities are more at risk for Lyme disease when considering their land cover types and the increasing spatial distribution of Lyme disease?

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