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

Coleman L. Little, Elizabeth E. Perry, Jessica P. Fefer, Matthew T. J. Brownlee and Ryan L. Sharp
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Coleman L. Little: Department of Parks, Recreation, and Tourism Management, Clemson University, 263 Lehotsky Hall, Clemson, SC 29634, USA
Elizabeth E. Perry: Department of Parks, Recreation, and Tourism Management, Clemson University, 263 Lehotsky Hall, Clemson, SC 29634, USA
Jessica P. Fefer: Horticulture and Natural Resources Department, Kansas State University, 2021 Throckmorton, Manhattan, KS 66506, USA
Matthew T. J. Brownlee: Department of Parks, Recreation, and Tourism Management, Clemson University, 263 Lehotsky Hall, Clemson, SC 29634, USA
Ryan L. Sharp: Horticulture and Natural Resources Department, Kansas State University, 2021 Throckmorton, Manhattan, KS 66506, USA

Data, 2020, vol. 5, issue 2, 1-19

Abstract: 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 ( n = 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.

Keywords: automated image coding; data collection methods; interdisciplinary learning theory; research methods; systematic literature review; visitor use management (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2020
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