# Assessing Tornado Impacts in the State of Kentucky with a Focus on Demographics and Roadways Using a GIS-Based Approach

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## Abstract

**:**

## 1. Introduction

## 2. Study Area and Data Collection

#### 2.1. TIGER and ACS Dataset

#### 2.2. Smart Location Calculator Dataset

#### 2.3. H + T Index

#### 2.4. Tornado Incident Dataset

## 3. Methodology

#### 3.1. Density Estimation

#### 3.2. Variable Selection

#### 3.3. Multiscale Geographically Weighted Regression (MGWR)

## 4. Results and Discussions

#### 4.1. Spatial Analysis Results

#### 4.2. Statistical Analysis Results

#### 4.2.1. MGWR Model and Its Performance

#### 4.2.2. Spatial Distribution of Each Variable

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 4.**Risk zone classes of tornado day occurrences within Kentucky between 1950 and 2010 (Blinn, 2012) [16].

**Figure 8.**Distribution of coefficients over Kentucky: (

**a**) intercept, Ac_land, P_WrkAge, and R_PCTLOWWA (percent of low wage workers); (

**b**) D2A_JPHH (jobs per household), SLC_score, vacant_hou, and no_veh_hhs (no vehicle households); (

**c**) median_household_income, ht_ami, t_ami, and residential density; (

**d**) intersection density, P_65, P_5, and P_18.

**Figure 10.**Spatial analysis of t_ami variable: (

**a**) bivariate coloring of t_ami and mean tornado exposure and(

**b**) distribution of significant t_ami coefficients (Numbers in the circles represent the buffers).

**Figure 11.**Spatial analysis of residential density variable: (

**a**) bivariate coloring of residential density and mean tornado exposure and (

**b**) distribution of significant residential density coefficients (Numbers in the circles represent buffers).

**Figure 12.**Spatial analysis of intersection density variable: (

**a**) bivariate coloring of intersection density and mean tornado exposure and (

**b**) distribution of significant intersection density coefficients (Numbers in the circles represent buffers).

**Figure 13.**Spatial analysis of P_65 variable: (

**a**) bivariate coloring of P_65 and mean tornado exposure and (

**b**) distribution of significant P_65 coefficients.

**Figure 14.**Spatial analysis of median household income variable: (

**a**) bivariate coloring of median household income and mean tornado exposure and (

**b**) distribution of significant median household income coefficients (Numbers in circles represent buffers).

TIGER and American Community Surveys (ACS) Dataset | |
---|---|

Variable | Explanation |

Occupied Housing Unit | Number of housing units that are occupied |

Vacant Housing Unit | Number of housing units that are vacant |

No vehicle household | Number of households that have no access to any vehicle |

Median household income | Median household income in the past 12 months (2019) |

Nonwhite pop | Nonwhite population in given CBG |

White pop | White population in given CBG |

Under 5 | Population of people who are under the age of five |

Under 18 | Population of people who are under the age of eighteen |

Pop 65+ | Population of people who are 65 and over |

Total pop | Total population in given CBG |

Smart Location Database (SLD) | |

Variable | Explanation |

SLC Score | Smart location score |

P_WrkAge | Percent of population that is working aged 18 to 64 |

D2a_JpHH | Jobs per household |

D3a | Total road network density |

R_PCTLOWWA(2017) | Percent of low-wage workers in CBG |

Ac_total | Total geometric area (acres) of the CBG |

Housing and Transportation Affordability (H+T) Index | |

Variable | Explanation |

ht_ami | Housing + transportation costs % income for the regional typical household |

t_ami | Transportation costs % income for the regional typical household |

autos_per_hh_ami | Autos per household for the regional typical household |

vmt_per_hh_ami | Annual vehicle miles traveled per household for the regional typical household |

compact_ndx | Compact neighborhood score (0–10) |

res_density | Residential density (households per residential acre) |

intersection_density | Intersection density in square miles |

Variable Name | Explanation | VIF_before | VIF_after |
---|---|---|---|

Ac_total | Total geometric area (acres) of the CBG | 2.63 | 1.92 |

P_WrkAGE | Percent of population that is working aged 18 to 64 years | 2.73 | 2.62 |

R_PCTLOWWA | Percent of low-wage workers in CBG | 1.94 | 1.56 |

D2a_JpHH | Jobs per household | 1.11 | 1.04 |

D3a | Total road network density | 11.58 | - |

SLC Score | SLC Score | 2.71 | 2.23 |

occ_hou | Number of occupied housing units | 10.73 | - |

vacant_hou | Number of vacant housing units | 1.22 | 1.16 |

no_veh_hhs | No vehicle household | 1.98 | 1.61 |

median_household_income | Median household income | 3.32 | 2.31 |

total_pop | Total population | 11.1 | - |

ht_ami | Housing+ transportation costs % income for the regional typical household | 5.16 | 4.71 |

t_ami | Transportation costs % income for the regional typical household | 8.72 | 6.71 |

autos_per_hh | Autos per household | 14.25 | - |

vmt_per_hh | Annual vehicle miles traveled per household | 18.71 | - |

compact_nd | Compactness index | 11.01 | - |

res_density | Residential density | 1.75 | 1.72 |

intersection_density | Intersection density | 6.75 | 2.42 |

P_65 | Percentage of people who are older than 65 | 3.3 | 2.69 |

P_5 | Percentage of people who are younger than 5 | 1.49 | 1.47 |

P_18 | Percentage of people who are younger than 18 | 3.16 | 3.05 |

P_nwhite | Percentage of nonwhite population | >1000 | - |

P_white | Percentage of white population | >1000 | - |

Explanatory Variables | Explanation | Mean | Standard Deviation | Min | Median | Max | |
---|---|---|---|---|---|---|---|

A | Intercept | - | −0.062 | 0.779 | −1.565 | −0.111 | 1.992 |

Ac_total | Total geometric area (acres) of the CBG | 0.012 | 0.071 | −0.228 | 0.016 | 0.250 | |

P_WrkAge | Percent of population that is working aged 18 to 64 years | 0.007 | 0.034 | −0.246 | 0.012 | 0.181 | |

R_PCTLOWWA | Percent of low-wage workers in CBG | 0.018 | 0.047 | −0.284 | 0.021 | 0.160 | |

D2a_JpHH | Jobs per household | 0.001 | 0.002 | −0.001 | 0.001 | 0.028 | |

SLC Score | SLC score | 0.035 | 0.077 | −0.236 | 0.034 | 0.211 | |

vacant_hou | Number of vacant housing units | −0.014 | 0.041 | −0.227 | −0.005 | 0.089 | |

no_veh_hhs | No vehicle household | −0.010 | 0.019 | −0.023 | −0.018 | 0.071 | |

median_household_income | Median household income | 0.067 | 0.109 | −0.133 | 0.036 | 0.319 | |

ht_ami | Housing+ transportation costs % income for the regional typical household | 0.049 | 0.098 | −0.278 | 0.070 | 0.372 | |

t_ami | Transportation costs % income for the regional typical household | −0.188 | 0.333 | −0.920 | −0.131 | 0.474 | |

res_density | Residential density | 0.002 | 0.116 | −0.443 | 0.008 | 0.445 | |

intersection_density | Intersection density | 0.005 | 0.063 | −0.363 | −0.020 | 0.380 | |

P_65 | Percentage of people who are older than 65 | 0.009 | 0.029 | −0.087 | 0.011 | 0.115 | |

P_5 | Percentage of people who are younger than 5 | −0.004 | 0.025 | −0.141 | −0.003 | 0.152 | |

P_18 | Percentage of people who are younger than 18 | −0.007 | 0.004 | −0.029 | −0.006 | −0.003 | |

B | Statistic | GWR | MGWR | ||||

R-Squared | 0.926 | 0.936 | |||||

Adjusted R-Squared | 0.911 | 0.929 | |||||

AICc | 1668.870 | 927.527 | |||||

Sigma-Squared | 0.089 | 0.071 | |||||

Sigma-Squared MLE | 0.074 | 0.064 | |||||

Effective Degrees of Freedom | 2637.060 | 2855.330 |

Explanatory Variables | Explanation | Bandwidth (% of Extent) | Significance (% of Features) | Effective Number of Parameters | Adjusted Value of Alpha | Adjusted Critical Value of Pseudo-t Statistics |
---|---|---|---|---|---|---|

Intercept | - | 38.41 (8.75) | 2446 (77.80) | 19.42 | 0.0026 | 3.0172 |

Ac_total | Total geometric area (acres) of the CBG | 38.41 (8.75) | 357 (11.35) | 23.93 | 0.0021 | 3.0801 |

P_WrkAge | Percent of population that is working aged 18 to 64 years | 38.41 (8.75) | 59 (1.88) | 25.41 | 0.0020 | 3.0979 |

R_PCTLOWWA | Percent of low-wage workers in CBG | 38.41(8.75) | 309 (9.83) | 24.2 | 0.0021 | 3.0833 |

D2a_JpHH | Jobs per household | 285.97 (65.15) | 0 (0.00) | 1.02 | 0.0490 | 1.9698 |

SLC Score | SLC score | 38.41 (8.75) | 818 (26.02) | 21.47 | 0.0023 | 3.0475 |

vacant_hou | Number of vacant housing units | 38.41 (8.75) | 319 (10.15) | 24.03 | 0.0021 | 3.0813 |

no_veh_hhs | No vehicle household | 141.50 (32.23) | 797 (25.35) | 2.58 | 0.0194 | 2.3392 |

median_household_income | Median household income | 38.41 (8.75) | 1030 (32.76) | 22.03 | 0.0023 | 3.0553 |

ht_ami | Housing + transportation costs % income for the regional typical household | 38.41 (8.75) | 1062 (33.78) | 21.10 | 0.0024 | 3.0423 |

t_ami | Transportation costs % income for the regional typical household | 38.41 (8.75) | 2025 (64.41) | 16.58 | 0.0030 | 2.9688 |

res_density | Residential density | 38.41 (8.75) | 289 (9.19) | 15.3 | 0.0033 | 2.9439 |

intersection_density | Intersection density | 38.41 (8.75) | 110 (3.50) | 18.44 | 0.0027 | 3.0013 |

P_65 | Percentage of people who are older than 65 | 38.41 (8.75) | 2 (0.06) | 25.19 | 0.0020 | 3.0954 |

P_5 | Percentage of people who are younger than 5 | 38.41 (8.75) | 32 (1.02) | 26.52 | 0.0019 | 3.1106 |

P_18 | Percentage of people who are younger than 18 | 213.73 (48.69) | 1 (0.03) | 1.43 | 0.0351 | 2.1086 |

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## Share and Cite

**MDPI and ACS Style**

Kaya, M.B.; Alisan, O.; Karaer, A.; Ozguven, E.E.
Assessing Tornado Impacts in the State of Kentucky with a Focus on Demographics and Roadways Using a GIS-Based Approach. *Sustainability* **2024**, *16*, 1180.
https://doi.org/10.3390/su16031180

**AMA Style**

Kaya MB, Alisan O, Karaer A, Ozguven EE.
Assessing Tornado Impacts in the State of Kentucky with a Focus on Demographics and Roadways Using a GIS-Based Approach. *Sustainability*. 2024; 16(3):1180.
https://doi.org/10.3390/su16031180

**Chicago/Turabian Style**

Kaya, Mehmet Burak, Onur Alisan, Alican Karaer, and Eren Erman Ozguven.
2024. "Assessing Tornado Impacts in the State of Kentucky with a Focus on Demographics and Roadways Using a GIS-Based Approach" *Sustainability* 16, no. 3: 1180.
https://doi.org/10.3390/su16031180