Mapping Emotional Attachment as a Measure of Sense of Place to Identify Coastal Restoration Priority Areas. (January 2022)

• Record Type: Journal Article
• Authors: Hawthorne, Timothy L.; Toohy, Kayla R.; Yang, Bo; Graham, Lain; Lorenzo, Elise M.; Torres, Hannah; McDonald, Morgan; Rivera, Fernando; Bouck, Kirsten; Walters, Linda J.
• Is Part Of: Applied geography. Volume 138(2022)
• Publication Date: 2022-01
• Subjects: Coastal restoration -- Emotional attachment -- Geographic information systems -- Indian river lagoon -- Sense of place; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2021.102608
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: Our applied case study demonstrates how knowledge from community stakeholders about emotional attachment (as a key component of sense of place) can inform and influence future coastal restoration priorities at various scales in the Indian River Lagoon, Florida (USA). We map aggregate measures of emotional attachment from community stakeholders using Geographic Information Systems. We then analyze this human systems level data with kernel density estimation measures at the broader lagoon scale and with inverse distance weighted measures at more localized scales. By connecting these mapped results back to the primary reasons that participants provided for having high or low emotional attachment in a location, we show how varying spatial patterns of emotional attachment as a primary component of sense of place within and across broader geographic regions can be represented, mapped, and visualized to enhance future restoration priorities. We demonstrate how aggregate results gained from community stakeholders can help restoration teams prioritize their science communication and education strategies to align human systems level data with natural systems level data. Highlights: We map aggregate measures of emotional attachment from community stakeholders. We analyze emotional attachment data with KDE measures at a broader scale and with IDW measures at more localized scales. We analyze emotional attachment data with KDE measures at a broader scale and with IDW measures at more localized scale.