Crowdsourcing dust storms in the United States utilizing social media data.

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Title: Crowdsourcing dust storms in the United States utilizing social media data.
Authors: Adegbola, Festus1 (AUTHOR) festusad@buffalo.edu, Crooks, Andrew1 (AUTHOR) atcrooks@buffalo.edu, Evans, Stuart M.1 (AUTHOR) stuartev@buffalo.edu
Source: GeoJournal. Jun2025, Vol. 90 Issue 3, p1-18. 18p.
Abstract: Dust storms and other dust events are natural phenomena characterized by strong winds carrying large amounts of fine particles which have significant environmental and human impacts. However, capturing the occurrence of such phenomena is a challenge. Previous studies have limitations due to available data, especially regarding short-lived, intense dust storms and events that are not captured by observing stations and satellite instruments. In recent years, the advent of social media platforms has provided a unique opportunity to access vast amounts of crowdsourced data. This paper explores the utilization of Flickr and X (Twitter) data to study dust event occurrences within the United States and their correlation with National Weather Service (NWS) advisories. The work ascertains the reliability of using crowdsourced data as a supplementary source for dust events monitoring. Our analysis of Flickr and X indicates that the Southwest region is most susceptible to dust events, with Arizona leading in the highest number of occurrences. On the other hand, the Great Plains show a scarcity of crowdsourced data related to dust events, which can be attributed to the sparsely populated nature of the region. Furthermore, seasonal analysis reveals that dust events are prevalent during the Summer months followed by Spring. These results are consistent with previous traditional studies that did not use social media of dust occurrences in the U.S., and Flickr-identified images of dust events show substantial co-occurrence with regions of NWS dust warnings. This paper highlights the potential of using crowdsourced data for the often overlooked field of dust monitoring that has substantial health and economic impacts. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 185709849
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PubType: Academic Journal
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  Data: Crowdsourcing dust storms in the United States utilizing social media data.
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  Data: <searchLink fieldCode="AR" term="%22Adegbola%2C+Festus%22">Adegbola, Festus</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> festusad@buffalo.edu</i><br /><searchLink fieldCode="AR" term="%22Crooks%2C+Andrew%22">Crooks, Andrew</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> atcrooks@buffalo.edu</i><br /><searchLink fieldCode="AR" term="%22Evans%2C+Stuart+M%2E%22">Evans, Stuart M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> stuartev@buffalo.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22GeoJournal%22">GeoJournal</searchLink>. Jun2025, Vol. 90 Issue 3, p1-18. 18p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Dust storms and other dust events are natural phenomena characterized by strong winds carrying large amounts of fine particles which have significant environmental and human impacts. However, capturing the occurrence of such phenomena is a challenge. Previous studies have limitations due to available data, especially regarding short-lived, intense dust storms and events that are not captured by observing stations and satellite instruments. In recent years, the advent of social media platforms has provided a unique opportunity to access vast amounts of crowdsourced data. This paper explores the utilization of Flickr and X (Twitter) data to study dust event occurrences within the United States and their correlation with National Weather Service (NWS) advisories. The work ascertains the reliability of using crowdsourced data as a supplementary source for dust events monitoring. Our analysis of Flickr and X indicates that the Southwest region is most susceptible to dust events, with Arizona leading in the highest number of occurrences. On the other hand, the Great Plains show a scarcity of crowdsourced data related to dust events, which can be attributed to the sparsely populated nature of the region. Furthermore, seasonal analysis reveals that dust events are prevalent during the Summer months followed by Spring. These results are consistent with previous traditional studies that did not use social media of dust occurrences in the U.S., and Flickr-identified images of dust events show substantial co-occurrence with regions of NWS dust warnings. This paper highlights the potential of using crowdsourced data for the often overlooked field of dust monitoring that has substantial health and economic impacts. [ABSTRACT FROM AUTHOR]
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        Value: 10.1007/s10708-025-11359-9
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        Text: English
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      – TitleFull: Crowdsourcing dust storms in the United States utilizing social media data.
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              Text: Jun2025
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              Y: 2025
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