An Interdisciplinary Review of Camera Image Collection and Analysis Techniques, with Considerations for Environmental Conservation Social Science

• Main Authors: Coleman L. Little, Elizabeth E. Perry, Jessica P. Fefer, Matthew T. J. Brownlee, Ryan L. Sharp
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Data
• Subjects: automated image coding; data collection methods; interdisciplinary learning theory; research methods; systematic literature review; visitor use management
• Online Access: https://www.mdpi.com/2306-5729/5/2/51

Camera-based data collection and image analysis are integral methods in many research disciplines. However, few studies are specifically dedicated to trends in these methods or opportunities for interdisciplinary learning. In this systematic literature review, we analyze published sources (<i>n</i> = 391) to synthesize camera use patterns and image collection and analysis techniques across research disciplines. We frame this inquiry with interdisciplinary learning theory to identify cross-disciplinary approaches and guiding principles. Within this, we explicitly focus on trends within and applicability to environmental conservation social science (ECSS). We suggest six guiding principles for standardized, collaborative approaches to camera usage and image analysis in research. Our analysis suggests that ECSS may offer inspiration for novel combinations of data collection, standardization tactics, and detailed presentations of findings and limitations. ECSS can correspondingly incorporate more image analysis tactics from other disciplines, especially in regard to automated image coding of pertinent attributes.