26 November 2018 San Rafael HailPixel Survey Data and Analysis

Published: 1 September 2019| Version 4 | DOI: 10.17632/6j4g52fv3m.4
Joshua Soderholm


The following collection is used to demonstrate the HailPixel survey technique as part of an AGU GRL publication. The following is an abstract for this paper: A new technique, named "HailPixel," is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger than population sizes from existing sensors (e.g., a hail pad). Comparison with a co-located hail pad for an Argentinan hailstorm event demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hailfall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution. The dataset contains the DEM and orthomosaic imagery, processing reports, final location of hail centroids, final measurements of hail major and minor axis, subset offsets and hail pad data. For more information applying the subset offsets to calculate the true position of the hail centroids please see the paper.



Applied Meteorology, Optical Remote Sensing