Abstract Augmented reality (AR) is not yet widely used in citizen science (CS). However, the technology offers great potential especially for geographically oriented CS projects. With the help of AR, a participant in a CS project can be guided through the data collection process and thus the technology can contribute to improved data quality. As part of this research, a reusable mobile AR application is developed for use across multiple geographic CS projects. As a use case, the creation of photo series, also called repeat photography, is selected. In a test study, photos were taken over the course of a year using the application. A total of 124 pairs of photos (taken with and without AR) were collected at 13 locations. Visually, it can be recognized that, compared to the reference photo, objects in photos taken without AR assistance are often shifted horizontally or vertically. Using semantic segmentation and the calculation of the intersection over union (IoU), it could be demonstrated that objects in the photos taken with AR have a greater overlap with those in the reference photo. This indicates that data quality can be improved through the use of AR. It can therefore be concluded that the use of AR during spatial data collection can be beneficial for geographically oriented CS projects.
Berger et al. (2026) studied this question.