Applying Spatial Video Geonarratives and Physiological Measurements to Explore Perceived Safety in Baton Rouge, Louisiana

Alina Ristea, Michael Leitner, Bernd Resch and Judith Stratmann
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Alina Ristea: Boston Area Research Initiative, School of Public Policy and Urban Affairs, Northeastern University, Boston, MA 02115, USA
Michael Leitner: Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
Bernd Resch: Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
Judith Stratmann: Spatial Information Management, Carinthia University of Applied Sciences, 9524 Villach, Austria

IJERPH, 2021, vol. 18, issue 3, 1-19

Abstract: Spatial crime analysis, together with perceived (crime) safety analysis have tremendously benefitted from Geographic Information Science (GISc) and the application of geospatial technology. This research study discusses a novel methodological approach to document the use of emerging geospatial technologies to explore perceived urban safety from the lenses of fear of crime or crime perception in the city of Baton Rouge, USA. The mixed techniques include a survey, spatial video geonarrative (SVG) in the field with study participants, and the extraction of moments of stress (MOS) from biosensing wristbands. This study enrolled 46 participants who completed geonarratives and MOS detection. A subset of 10 of these geonarratives are presented here. Each participant was driven in a car equipped with audio recording and spatial video along a predefined route while wearing the Empatica E4 wristbands to measure three physiological variables, all of them linked by timestamp. The results show differences in the participants’ sentiments (positive or negative) and MOS in the field based on gender. These mixed-methods are encouraging for finding relationships between actual crime occurrences and the community perceived fear of crime in urban areas.

Keywords: perceived safety; spatial video; geonarrative; moments of stress; mixed-method approach; wearable sensors; spatiotemporal semantic analysis; sentiment analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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