Grounding Big Data on Climate-Induced Human Mobility

Bibliographic Data

ID4490944
AuthorsIngrid Boas (0000-0001-7842-5883), Ruben Dahm (0000-0002-8667-3358), David Wrathall (0000-0003-1085-6534)
Year2020
Volume110
Issue1-2
Pages195-209
Publication date2020-01-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGeographical Review (JOURNAL)
Journal identifiersISSN: 0016-7428 • E-ISSN: 1931-0846
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1111/gere.12355
OpenAlexW2926557868
LanguageEN
Citations received11
References cited23

How can site-based fieldwork support big-data research? We reflect on this question by sharing our experiences in combining on-site fieldwork with an existing big-data analysis using call-detail records (CDR), which detected anomalous population flows in Bangladesh during cyclone Mahasen. In the original study of the CDR, this mobility was hypothesized to reflect late evacuations from homes. We discuss how site-based fieldwork enabled us to discover that the detected patterns in our area of study reflected something different: the movement of fishers seeking to protect their trawlers located at harbor areas. Moreover, the fieldwork, in conjunction with remote sensing shoreline evolution data, allowed us to identify and study high-risk behaviors of immobility that the CDR analysis was not able to detect. In sharing our findings, we are reflective of our own endeavor to optimally combine qualitative and big-data methods. While mistakes were made and challenges had to be overcome, insights were gained on how a combined methodology makes research well-grounded, reflective, and more interactive

Big data · Cartography · Computer security · Data mining · Data science · Geography · Population · Sociology · Climate Change, Adaptation, Migration · Computer Science · Disaster Management and Resilience · Human Mobility and Location-Based Analysis