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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Coleman L. Little & Elizabeth E. Perry & Jessica P. Fefer & Matthew T. J. Brownlee & Ryan L. Sharp, 2020. "An Interdisciplinary Review of Camera Image Collection and Analysis Techniques, with Considerations for Environmental Conservation Social Science," Data, MDPI, vol. 5(2), pages 1-19, June.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:2:p:51-:d:368253
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    References listed on IDEAS

    as
    1. Feng-Ping An, 2019. "Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model," Complexity, Hindawi, vol. 2019, pages 1-16, October.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
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