#6367. Anomaly detection for volunteered geographic information: a case study of Safecast data

October 2026publication date
Proposal available till 03-06-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Geography, Planning and Development;
Library and Information Sciences;
Information Systems;
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Abstract:
Volunteered Geographic Information (VGI), defined as geographic information contributed voluntarily by individuals, has grown exponentially with the aid of ubiquitous GPS-enabled technologies. VGI projects have generated a large amount of geographic data, providing a new data source for scientific research. However, many scientists are concerned about the quality of VGI data for research, given the lack of rigorous and systematic quality control procedures. This study contributes to the improvement of quality control procedures by proposing a Cross-Volunteer Referencing Anomaly Detection (CVRAD) method to filter anomalous data, using the crowdsourced Safecast radiation data as a case study. The anomaly detection method is validated using two data sets: (1) an official radiation survey data set collected by the KURAMA car-borne system, (2) a set of anomalous Safecast measurements filtered by Safecast moderators.
Keywords:
Anomaly detection; data quality; participatory sensing; radiation; Volunteered Geographic Information (VGI)

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