Advance in the timing of the annual migration of the brown-veined white butterfly through Johannesburg, South Africa, over the period 1914–2020

Perspective and review: how to develop our understanding of temporal changes in the relationship between people and the landscape under societal and climate change in Northeast Asia?

“…In an analysis of Instagram and Flickr data, which mainly consist of images, we can examine the spatio-temporal distribution of a wide variety of people's interests, such as foods, tourism, butterfly migration, flowering phenology, and recreational activities, by referring to the attribute information of the shooting date and geolocation (Stafford et al, 2010;Yoshimura and Hiura, 2017;Song et al, 2020;ElQadi et al, 2021;Fitchett et al, 2022;ElQadi et al, 2023;Shin et al, 2024a). Similarly, in an analysis of YouTube videos and other data, we can study people's interests and records in a wide range of topics (Michelsen et al, 2016;Dylewski et al, 2017;Lewis and Park, 2018;Sbragaglia et al, 2022;Vins et al, 2022;Herrera et al, 2023;Shin et al, 2024a).…”

“…However, given the almost ubiquitous nature of smartphones and the Internet in the modern world, the analysis of human communication in cyberspace is a useful approach to remove the interpretability gap in our understanding based on field work alone. Second, this approach provides data on the spatio-temporal distribution of phenology (Kotani et al, 2021;Shin et al, 2022a;2022d;Fitchett et al, 2022), which can be estimated from the seasonality of people's interests in foods, events, and recreation (i.e., cultural ecosystem services), as well as ground-truth data for disasters (e.g., Fohringer et al, 2015;Khan et al, 2022) to enhance our understanding based on satellite observations. The potential of spatial analysis utilizing social sensing data is found in, for example, detecting landscape value (van Zanten et al, 2016) and users' mobility patterns in urban (Soliman et al, 2017).…”