The Hunt for Missing Tornadoes: Using Satellite Imagery to Detect and Document Historical Tornado Damage in Canadian Forests

Abstract

Historical tornado events from 1982-2020 were documented within Canada’s forested regions using high-resolution satellite imagery. Tornado forest disturbances were identified using a three-step process: 1) detecting; 2) assessing; and 3) dating e ach event. A grid of 120 km x 120 km boxes was created covering Canada (excluding the extreme north). Of the 484 boxes, 367 were manually searched. Once a long, narrow region of tree damage was detected, it was first cross-referenced with known tornado databases to ensure it was a unique event. Once events were classified as either tornadic or downburst, the coordinates of the start, worst damage and end locations were documented, as well as the direction of motion, damage indicators, degree of damage, estimated maximum wind speed, and F/EF rating. In total, 231 previously unknown tornadoes were identified. In Ontario, 103 events were discovered, followed by 98 in Quebec, 9 in Manitoba, 6 in Saskatchewan, 9 in Alberta, 5 in British Columbia and 1 in New Brunswick. The largest number of discovered tornadoes occurred in 2015, while the largest number of strong F2 tornadoes occurred in 2005. Most of the discovered tornadoes occurred in July for both F/EF1 and F/EF2 ratings. Most tornado tracks had widths between 200-400 m, and more than 50% of the tornadoes had a path length less than 10 km. Of all the events discovered, 125 events could be fully dated, while 19 were dated only by month, 41 only by year, and 46 remained undated.

Using Deep Learning and Advanced Image Processing for the Automated Estimation of Tornado-Induced Treefall

“…One of the principal challenges lies in pinpointing tornado locations in sparsely populated areas. In addressing this challenge, researchers conducted a comprehensive analysis of satellite imagery data, utilizing various techniques to accurately detect the location and path information of tornado damage [15].…”