Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Interactive and Immersive Documentary Methods for Community Resilience & Disaster Reduction

Bibliographic Data

ID12919442
AuthorsTom White (0000-0002-9155-5241, Yale-NUS College, corresponding author)
Year2021
Volume14
Issue1
Pages95-107
Publication date2021-01-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePhotographies (JOURNAL)
Journal identifiersISSN: 1754-0763 • E-ISSN: 1754-0771
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/17540763.2020.1847177
OpenAlexW3137744635
LanguageEN
Citations received2
References cited2

Drawing on field research conducted by Professor Brian McAdoo, an environmental scientist at Yale-NUS College and Tom White, a freelance visual journalist who also teaches part-time at Yale-NUS this paper will explore how methods can be developed for emerging interactive documentary forms might contribute to the ways in which communities increase resilience and reduce losses when meeting the challenge of natural disasters and human-made environmental risks including anthropogenic climate change

Art · Climate change · Community resilience · Disaster risk reduction · Engineering ethics · Environmental ethics · Environmental resource management · Field (mathematics · Geography · Media studies · Meteorology · Natural disaster · Psychological resilience · Resilience (materials science · Sociology · Visual arts · White (mutation · Computer Science · Engineering · Environmental Science · History · Participatory Visual Research Methods · Psychology · Social Psychology · Ecology

  • Degree Video for Virtual Place-Based Research

    Open Access•Jonathan Cinnamon, Lindi Jahiu•Computers Environment and Urban…•2023

  • Enriching Qualitative Inquiry

    Open Access•Matteo Baraldo, Francesca Dolcetti et al.•International Journal of…•2025

Unique citing works2
Citations per year0,67
Citation span2023 - 2025 (3)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae