Articles | Volume 13, issue 2
Research article
 | Highlight paper
17 Feb 2020
Research article | Highlight paper |  | 17 Feb 2020

Quantifying hail size distributions from the sky – application of drone aerial photogrammetry

Joshua S. Soderholm, Matthew R. Kumjian, Nicholas McCarthy, Paula Maldonado, and Minzheng Wang


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Mirena Feist-Polner on behalf of the Authors (09 Jan 2020)  Author's response    Manuscript
ED: Publish as is (10 Jan 2020) by Brian Kahn
AR by Joshua Soderholm on behalf of the Authors (17 Jan 2020)  Author's response    Manuscript
Short summary
Collecting measurements of hail size and shape is difficult due to the infrequent and dangerous nature of hailstorms. To improve upon this, a new technique called HailPixel is introduced for measuring hail using aerial imagery collected by a drone. A combination of machine learning and computer vision methods is used to extract the shape of thousands of hailstones from the aerial imagery. The improved statistics from the much larger HailPixel dataset show significant benefits.