MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall
Snowfall information at the scale of individual particles is rare, difficult to gather, but fundamental for a better understanding of solid precipitation microphysics. In this article we present a dataset (with dedicated software) of in-situ measurements of snow particles in free fall. The dataset i...
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ftpubmed:oai:pubmedcentral.nih.gov:9065139 2023-05-15T14:04:06+02:00 MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall Grazioli, Jacopo Ghiggi, Gionata Billault-Roux, Anne-Claire Berne, Alexis 2022-05-03 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065139/ https://doi.org/10.1038/s41597-022-01269-7 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065139/ http://dx.doi.org/10.1038/s41597-022-01269-7 © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . CC-BY Sci Data Data Descriptor Text 2022 ftpubmed https://doi.org/10.1038/s41597-022-01269-7 2022-05-08T01:13:57Z Snowfall information at the scale of individual particles is rare, difficult to gather, but fundamental for a better understanding of solid precipitation microphysics. In this article we present a dataset (with dedicated software) of in-situ measurements of snow particles in free fall. The dataset includes gray-scale (255 shades) images of snowflakes, co-located surface environmental measurements, a large number of geometrical and textural snowflake descriptors as well as the output of previously published retrieval algorithms. These include: hydrometeor classification, riming degree estimation, identification of melting particles, discrimination of wind-blown snow, as well as estimates of snow particle mass and volume. The measurements were collected in various locations of the Alps, Antarctica and Korea for a total of 2’555’091 snowflake images (or 851’697 image triplets). As the instrument used for data collection was a Multi-Angle Snowflake Camera (MASC), the dataset is named MASCDB. Given the large amount of snowflake images and associated descriptors, MASCDB can be exploited also by the computer vision community for the training and benchmarking of image processing systems. Text Antarc* Antarctica PubMed Central (PMC) Triplets ENVELOPE(-59.750,-59.750,-62.383,-62.383) Scientific Data 9 1 |
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Data Descriptor Grazioli, Jacopo Ghiggi, Gionata Billault-Roux, Anne-Claire Berne, Alexis MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
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Data Descriptor |
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Snowfall information at the scale of individual particles is rare, difficult to gather, but fundamental for a better understanding of solid precipitation microphysics. In this article we present a dataset (with dedicated software) of in-situ measurements of snow particles in free fall. The dataset includes gray-scale (255 shades) images of snowflakes, co-located surface environmental measurements, a large number of geometrical and textural snowflake descriptors as well as the output of previously published retrieval algorithms. These include: hydrometeor classification, riming degree estimation, identification of melting particles, discrimination of wind-blown snow, as well as estimates of snow particle mass and volume. The measurements were collected in various locations of the Alps, Antarctica and Korea for a total of 2’555’091 snowflake images (or 851’697 image triplets). As the instrument used for data collection was a Multi-Angle Snowflake Camera (MASC), the dataset is named MASCDB. Given the large amount of snowflake images and associated descriptors, MASCDB can be exploited also by the computer vision community for the training and benchmarking of image processing systems. |
format |
Text |
author |
Grazioli, Jacopo Ghiggi, Gionata Billault-Roux, Anne-Claire Berne, Alexis |
author_facet |
Grazioli, Jacopo Ghiggi, Gionata Billault-Roux, Anne-Claire Berne, Alexis |
author_sort |
Grazioli, Jacopo |
title |
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
title_short |
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
title_full |
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
title_fullStr |
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
title_full_unstemmed |
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
title_sort |
mascdb, a database of images, descriptors and microphysical properties of individual snowflakes in free fall |
publisher |
Nature Publishing Group UK |
publishDate |
2022 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065139/ https://doi.org/10.1038/s41597-022-01269-7 |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065139/ http://dx.doi.org/10.1038/s41597-022-01269-7 |
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© The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
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