The Salford Nature Environments Database (SNED): an open-access database of standardized high-quality pictures from natural environments
2025

The Salford Nature Environments Database: A Resource for Nature Research

Sample size: 801 publication 10 minutes Evidence: high

Author Information

Author(s): Bendall Robert C. A., Royle Sam, Dodds James, Watmough Hugh, Gillman Jamie C., Beevers David, Cassidy Simon, Short Ben, Metcalfe Paige, Lomas Michael J., Graham-Kevan Draco, Gregory Samantha E.

Primary Institution: University of Salford

Hypothesis

The study aims to create a standardized database of natural images to support research on the benefits of nature exposure.

Conclusion

The Salford Nature Environments Database (SNED) provides a comprehensive collection of standardized images that can enhance research into the restorative effects of nature.

Supporting Evidence

  • Nature images were rated significantly higher in positive valence than urban images.
  • Participants rated nature images as evoking lower arousal compared to urban images.
  • Nature images were rated as more pleasant than urban control images.
  • Participants indicated they would feel more at ease in nature environments compared to urban environments.
  • Nature images were rated as more interesting than urban control images.
  • Participants rated nature images as having more to discover than urban images.

Takeaway

This study created a big collection of nature pictures to help scientists understand how being around nature can make us feel better.

Methodology

Participants rated 500 images of natural and urban environments on various properties, including valence, arousal, and approach-avoidance.

Potential Biases

Potential bias in participant demographics as recruitment was skewed towards certain geographical regions.

Limitations

The database may include images that were edited by photographers, and not all images have comprehensive EXIF data.

Participant Demographics

801 participants aged 18-79, with a diverse representation across various geographical regions.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.3758/s13428-024-02556-4

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication