College of Behavioral & Social Sciences

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Author: search.filters.author.Resop, Jonathan P.

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    Optimization of herbaceous feedstock delivery to a network of supply depots for a biorefinery in the Piedmont, USA
    (Wiley, 2023-09-13) Resop, Jonathan P.; Cundiff, John S.
    The southeastern USA has the potential to be a significant producer of bio-based products; however, research is still needed to demonstrate the most cost-effective feedstock delivery system for this region. A logistic system that has shown promise is one utilizing a network of supply depots. This study calculated the cost to produce a stream of size-reduced herbaceous biomass (i.e., switchgrass) for five theoretical depots in the Piedmont province. Three depots were located in south central Virginia and two in north central North Carolina. A logistics system with a 20-bale handling unit was used for load-out operations at 199 theoretical satellite storage locations (SSLs) within a 48 km radius of each depot location. The distribution of potential production fields and the transportation distance from SSLs to the depots were determined with spatial and network analyses. Based on an analysis of potential land cover available for feedstock production, the annual capacity per depot ranged from 80 839 to 170 830 Mg, resulting in a total annual capacity of 555 195 Mg for all five depots. Cost to deliver feedstock for 24/7 operation, 48 weeks per year ranged from 46.03 to 62.86 USD Mg−1 annual capacity. At the low end, these costs were: SSL operation (22%), truck (29%), receiving facility (26%), and debaling-size-reduction (23%). The principle economy-of-scale factors were the receiving facility and debaling-size-reduction costs. To minimize per-Mg cost, depot capacity should be chosen such that equipment can be operated as close to 80% of design capacity as possible.
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    Drone Laser Scanning for Modeling Riverscape Topography and Vegetation: Comparison with Traditional Aerial Lidar
    (MDPI, 2019-04-12) Resop, Jonathan P.; Lehmann, Laura; Hession, W. Cully
    Lidar remote sensing has been used to survey stream channel and floodplain topography for decades. However, traditional platforms, such as aerial laser scanning (ALS) from an airplane, have limitations including flight altitude and scan angle that prevent the scanner from collecting a complete survey of the riverscape. Drone laser scanning (DLS) or unmanned aerial vehicle (UAV)-based lidar offer ways to scan riverscapes with many potential advantages over ALS. We compared point clouds and lidar data products generated with both DLS and ALS for a small gravel-bed stream, Stroubles Creek, located in Blacksburg, VA. Lidar data points were classified as ground and vegetation, and then rasterized to produce digital terrain models (DTMs) representing the topography and canopy height models (CHMs) representing the vegetation. The results highlighted that the lower-altitude, higher-resolution DLS data were more capable than ALS of providing details of the channel profile as well as detecting small vegetation on the floodplain. The greater detail gained with DLS will provide fluvial researchers with better estimates of the physical properties of riverscape topography and vegetation.
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    Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
    (MDPI, 2021-09-07) Resop, Jonathan P.; Lehmann, Laura; Hession, W. Cully
    Riverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly variable in size and structure, including wetland plants, grasses, shrubs, and trees. This vegetation variability is difficult to precisely measure over large extents with traditional surveying tools. Drone laser scanning (DLS), or UAV-based lidar, has shown potential for measuring topography and vegetation over large extents at a high resolution but has yet to be used to quantify both the temporal and spatial variability of riverscape vegetation. Scans were performed on a reach of Stroubles Creek in Blacksburg, VA, USA six times between 2017 and 2019. Change was calculated both annually and seasonally over the two-year period. Metrics were derived from the lidar scans to represent different aspects of riverscape vegetation: height, roughness, and density. Vegetation was classified as scrub or tree based on the height above ground and 604 trees were manually identified in the riverscape, which grew on average by 0.74 m annually. Trees had greater annual growth and scrub had greater seasonal variability. Height and roughness were better measures of annual growth and density was a better measure of seasonal variability. The results demonstrate the advantage of repeat surveys with high-resolution DLS for detecting seasonal variability in the riverscape environment, including the growth and decay of floodplain vegetation, which is critical information for various hydraulic and ecological applications.
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    Central Control for Optimized Herbaceous Feedstock Delivery to a Biorefinery from Satellite Storage Locations
    (MDPI, 2022-06-17) Resop, Jonathan P.; Cundiff, John S.; Grisso, Robert D.
    The delivery of herbaceous feedstock from satellite storage locations (SSLs) to a biorefinery or preprocessing depot is a logistics problem that must be optimized before a new bioenergy industry can be realized. Both load-out productivity, defined as the loading of 5 × 4 round bales into a 20-bale rack at the SSL, and truck productivity, defined as the hauling of bales from the SSLs to the biorefinery, must be maximized. Productivity (Mg/d) is maximized and cost (USD/Mg) is minimized when approximately the same number the loads is received each day. To achieve this, a central control model is proposed, where a feedstock manager at the biorefinery can dispatch a truck to any SSL where a load will be available when the truck arrives. Simulations of this central control model for different numbers of simultaneous load-out operations were performed using a database of potential production fields within a 50 km radius of a theoretical biorefinery in Gretna, VA. The minimum delivered cost (i.e., load-out plus truck) was achieved with nine load-outs and a fleet of eight trucks. The estimated cost was 11.24 and 11.62 USD/Mg of annual biorefinery capacity (assuming 24/7 operation over 48 wk/y for a total of approximately 150,000 Mg/y) for the load-out and truck, respectively. The two costs were approximately equal, reinforcing the desirability of a central control to maximize the productivity of these two key operations simultaneously.