Spatial Patterns and Variations of Tornado Damage as Related to Southeastern Appalachian Forests and Terrain from the Franklin County, Virginia EF-3 Tornado

Simple item page
dc.contributor.authorForister, Peter Hardingen
dc.contributor.committeechairResler, Lynn M.en
dc.contributor.committeememberRamseyer, Craig A.en
dc.contributor.committeememberPingel, Thomasen
dc.contributor.committeememberCarroll, David Fredericken
dc.contributor.departmentGeographyen
dc.coverage.countryUnited Statesen
dc.coverage.countyFranklin Countyen
dc.coverage.stateVirginiaen
dc.date.accessioned2022-12-17T07:00:06Zen
dc.date.available2022-12-17T07:00:06Zen
dc.date.issued2021-06-24en
dc.description.abstractStrong tornadoes have impacted the central Appalachian Mountains multiple times in recent years. The topography of this region leads to unique spatial patterns of tornado damage as the tornado vortices pass over ridges in forested areas, and this damage can be detected with vegetation indices derived from remotely sensed imagery. The objectives of this study were to 1) Classify forest damage from the April 19, 2019 EF-3 tornado in Franklin County, VA using remotely-sensed images, 2) Quantify the spatial patterns of forest damage intensity across the path using derived vegetation indices and terrain variables (primarily slope, aspect, elevation, and exposure), and 3) Use regression models to determine if relationships exist among terrain variables along the and forest damage patterns. I generated EVI and NDII vegetation indices from Sentinel-2 imagery and compared the derived damage to the underlying terrain variables. Results revealed that the two vegetation indices were effective for classifying tornado damage, and discrete damage classes aligned well with NWS EF-scale tornado intensity estimations. ANOVA testing suggested that EF-3 equivalent damage was more likely to occur on downslope topography, leeward of the tornado's direction of travel. OLS and geographically weighted regression (GWR) modeling performed poorly, suggesting that an alternative method may be more suitable for modeling, the scale of assessment was inadequate, or that important predictor variables were not captured. Overall, the intensity of the tornado was clearly modified by terrain interactions, and the remote sensing methodology used was effective for reliably identifying and rating damage in forested areas.en
dc.description.abstractgeneralStrong tornadoes have impacted the central Appalachian Mountains multiple times in recent years. The topography of this region leads to unique spatial patterns of tornado damage as the tornado vortices pass over ridges in forested areas, and this damage can be detected with vegetation indices derived from remotely sensed imagery. The objectives of this study were to 1) Classify forest damage from the April 19, 2019 EF-3 tornado in Franklin County, VA using remotely-sensed images, 2) Quantify the spatial patterns of forest damage intensity across the path using derived vegetation indices and terrain variables (primarily slope, aspect, elevation, and exposure), and 3) Use regression models to determine if relationships exist among terrain variables along the and forest damage patterns. I generated EVI and NDII vegetation indices from Sentinel-2 imagery and compared the derived damage to the underlying terrain variables. Results revealed that the two vegetation indices were effective for classifying tornado damage, and discrete damage classes aligned well with NWS EF-scale tornado intensity estimations. ANOVA testing suggested that EF-3 equivalent damage was more likely to occur on downslope topography, leeward of the tornado's direction of travel. OLS and geographically weighted regression (GWR) modeling performed poorly, suggesting that an alternative method may be more suitable for modeling, the scale of assessment was inadequate, or that important predictor variables were not captured. Overall, the intensity of the tornado was clearly modified by terrain interactions, and the remote sensing methodology used was effective for reliably identifying and rating damage in forested areas.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:31367en
dc.identifier.urihttp://hdl.handle.net/10919/112937en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectPhysical geographyen
dc.subjectTornado damageen
dc.subjectVegetation indicesen
dc.subjectSpatial statisticsen
dc.titleSpatial Patterns and Variations of Tornado Damage as Related to Southeastern Appalachian Forests and Terrain from the Franklin County, Virginia EF-3 Tornadoen
dc.typeThesisen
thesis.degree.disciplineGeographyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Forister_PH_T_2021.pdf
Size:
2.42 MB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses