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Although the literature provides valuable insight into tornado vulnerability and resilience, there are still research gaps in assessing tornadoes’ impact on communities and transportation infrastructure, especially in the wake of the rapidly changing frequency and strength of tornadoes due to climate change. In this study, we first investigated the relationship between tornado exposure and demographic-, socioeconomic-, and transportation-related factors in our study area, the state of Kentucky. Tornado exposures for each U.S. census block group (CBG) were calculated by utilizing spatial analysis methods such as kernel density estimation and zonal statistics. Tornadoes between 1950 and 2022 were utilized to calculate tornado density values as a surrogate variable for tornado exposure. Since tornado density varies over space, a multiscale geographically weighted regression model was employed to consider spatial heterogeneity over the study region rather than using global regression such as ordinary least squares (OLS). The findings indicated that tornado density varied over the study area. The southwest portion of Kentucky and Jefferson County, which has low residential density, showed high levels of tornado exposure. In addition, relationships between the selected factors and tornado exposure also changed over space. For example, transportation costs as a percentage of income for the regional typical household was found to be strongly associated with tornado exposure in southwest Kentucky, whereas areas close to Jefferson County indicated an opposite association. The second part of this study involves the quantification of the tornado impact on roadways by using two different methods, and results were mapped. Although in both methods the same regions were found to be impacted, the second method highlighted the central CBGs rather than the peripheries. Information gathered by such an investigation can assist authorities in identifying vulnerable regions from both transportation network and community perspectives. From tornado debris handling to community preparedness, this type of work has the potential to inform sustainability-focused plans and policies in the state of Kentucky.
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This content will become publicly available on January 1, 2026
Post-tornado roadway debris detection from satellite images: An integrated GIS and image processing approach
Southeastern United States frequently experience tornadoes, necessitating rapid response and recovery efforts by state and federal agencies. Accurate information about the extent and severity of tornado-induced damage, especially debris volume and locations, is crucial for these efforts. This study, therefore, focuses on post-tornado debris assessment in Leon County, Florida, which was hit by two EF-2 and an EF-1 tornadoes in May 2024. Using satellite imagery from the Planetscope satellite and Geographic Information Systems (GIS), a macro-level evaluation of tornado debris impact was conducted, particularly on roadways and impacted communities. The proposed approach includes an evaluation of the overall post-tornado debris impact across the entire county and its population, and a detailed analysis of debris impact on roadways and its effect on accessibility. Spectral indices from satellite images, specifically the Normalized Difference Vegetation Index (NDVI), were utilized to derive assessment parameters. By comparing NDVI values from pre- and post-tornado images, we analyzed changes in vegetation and debris accumulation along roadway segments leading to possible roadway closures. This integrated method provides critical insights for enhancing disaster response and recovery operations in tornado-prone regions. Findings indicate that high volumes of vegetative debris were present in the south-central parts of the county, which is occupied by the highest population of county residents. The roadway segments in this region also recorded highest debris volumes, which is a critical information for agencies that need to know highly impacted locations. Comparing the results to ground truth damage data, the accuracy recorded was 74%.
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- PAR ID:
- 10572004
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Remote Sensing Applications: Society and Environment
- Volume:
- 37
- Issue:
- C
- ISSN:
- 2352-9385
- Page Range / eLocation ID:
- 101439
- Subject(s) / Keyword(s):
- Tornado debris assessment Normalized vegetation index (NDVI) Satellite imagery Florida Spatial analysis Image processing
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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