TY - JOUR
T1 - The spatiotemporal signature of cherry blossom flowering across Japan revealed via analysis of social network site images
AU - ElQadi, Moataz Medhat
AU - Dyer, Adrian G.
AU - Vlasveld, Carolyn
AU - Dorin, Alan
N1 - Publisher Copyright:
© 2023 Elsevier GmbH
PY - 2023/7
Y1 - 2023/7
N2 - Understanding how changing climatic conditions are impacting flowering plants typically requires intensive effort and expense to sample a local site regularly over long periods of time. The logistics of organising detailed surveys of an extensive area to provide a wider perspective are even more inhibitive. Data on flower bloom patterns across areas stretching hundreds or thousands of kilometres, and with a temporal resolution down to 1 or 2 weeks, is nevertheless very valuable, should it be feasible to collect. To understand the potential for contemporary data to record such flowering patterns, we studied Japan, a country where cherry (Sakura, 桜) flower viewing (Hanami) is a national cultural practice stretching back hundreds of years, and in which contemporary citizens and visitors commonly photograph blossoms to share on social network sites (SNS). We employed the big data this activity creates, within an iEcology framework, by collecting images from the SNS Flickr over the decade 2008–2018. We developed a custom filtering pipeline to validate this extracted data against established databases of historical flowering times. Our results reveal unprecedented detail of the spatiotemporal pattern over which cherry blossoms seasonally sweep from southern to northern Japan during a 12 week period. They also were sufficiently sensitive to reveal a subtle out of peak season bloom. This novel approach and data source therefore provides a simultaneously broad and detailed perspective that communicates the seasonal ecological phenomenon of cherry tree flowering.
AB - Understanding how changing climatic conditions are impacting flowering plants typically requires intensive effort and expense to sample a local site regularly over long periods of time. The logistics of organising detailed surveys of an extensive area to provide a wider perspective are even more inhibitive. Data on flower bloom patterns across areas stretching hundreds or thousands of kilometres, and with a temporal resolution down to 1 or 2 weeks, is nevertheless very valuable, should it be feasible to collect. To understand the potential for contemporary data to record such flowering patterns, we studied Japan, a country where cherry (Sakura, 桜) flower viewing (Hanami) is a national cultural practice stretching back hundreds of years, and in which contemporary citizens and visitors commonly photograph blossoms to share on social network sites (SNS). We employed the big data this activity creates, within an iEcology framework, by collecting images from the SNS Flickr over the decade 2008–2018. We developed a custom filtering pipeline to validate this extracted data against established databases of historical flowering times. Our results reveal unprecedented detail of the spatiotemporal pattern over which cherry blossoms seasonally sweep from southern to northern Japan during a 12 week period. They also were sufficiently sensitive to reveal a subtle out of peak season bloom. This novel approach and data source therefore provides a simultaneously broad and detailed perspective that communicates the seasonal ecological phenomenon of cherry tree flowering.
KW - iEcology
KW - Incidental citizen science
KW - Phenology
KW - Social network site data
KW - Spatiotemporal analysis
UR - http://www.scopus.com/inward/record.url?scp=85162772126&partnerID=8YFLogxK
U2 - 10.1016/j.flora.2023.152311
DO - 10.1016/j.flora.2023.152311
M3 - Article
AN - SCOPUS:85162772126
SN - 0367-2530
VL - 304
JO - Flora
JF - Flora
M1 - 152311
ER -