Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Master of Engineering Science

Program

Civil and Environmental Engineering

Supervisor

Kopp, Gregory A.

Abstract

There are numerous tornadoes that occur each year in Canada. However, many of them occur in Canada’s croplands, which means they cannot be classified because the Enhanced Fujita (EF) scale is a damage-based assessment which relies on the tornado hitting damage indicators whose wind loads have been well-documented, which currently does not include crops. Not knowing the true intensities of these tornadoes results in an inaccurate tornado climatology for the Prairie regions of Canada (Alberta, Saskatchewan, and Manitoba). Therefore, the goal of this paper is to better understand Canada’s tornado climatology by developing a method to use a Normalized Difference Vegetation Index (NDVI) from multispectral satellite imagery to assess characteristics of a tornado such as path length, path width, and intensity. To accomplish this, multispectral satellite imagery collected by the Northern Tornadoes Project of all Canadian tornadoes across the Prairie regions of Canada between 2017-2023 was analyzed. The results indicate that the methodology is able to easily identify damage caused by EF4 and EF5 tornadoes, occasionally able to identify damage caused by EF2 and EF3 tornadoes, and unable to identify damage from EF0 and EF1 tornadoes. Additionally, a weak relationship between the observed maximum width of crop damage and the maximum width of the tornado was identified. Finally, it was noted that solely looking at crop damage, it is difficult to determine the full path of a tornado due to fluctuations of tornado intensity and land cover.

Summary for Lay Audience

There are numerous tornadoes that occur each year in Canada. However, many of them occur in Canada’s croplands, which means they are unable to be classified. This is because the current Enhanced Fujita (EF) scale has no damage indicator for crops. Not knowing the true number and intensities of these tornadoes results in inaccurate tornadic risk assessments for certain areas of Canada. Therefore, the goal of this paper is to better understand Canada’s tornado climatology by developing a method to empirically define the amount of damage in crops / low-lying vegetation and relate it to the EF-scale rating of a tornado through the use of remote sensing (satellite imagery) in the visible and near-infrared spectrum. To accomplish this, this thesis looked at tornadoes across the prairie regions of Canada between 2017 – 2023 using satellite imagery collected from the Northern Tornadoes Project. This satellite imagery was analyzed in ArcGIS Pro to empirically define the damage in low-lying vegetated areas from the percent change in plant health via the usage of a Normalized Difference Vegetation Index (NDVI). The results indicate that NDVI is easily able to detect EF3 and higher damage, and less consistently able to detect EF2 damage, and unable to detect EF1 and lower damage. The NDVI results were compared to the wind speed given by the traditional EF-scale assessment by correlating the peak decrease in plant health to nearby proven damage indicators from structures and trees. However, no clear relation was observed between these values. Despite this, a simple method was created using NDVI to identify damage to crops and low-lying vegetation. As a result, NDVI can detect EF2+ damage and will be useful in future events where only crops were damaged to understand the intensity of a tornado.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Available for download on Saturday, May 31, 2025

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