Abstract
There is long-standing scientific interest in understanding purposeful movement by animals and humans. Traditionally, collecting data on individual moving entities was difficult and time-consuming, limiting scientific progress. The growth of location-aware and other geospatial technologies for capturing, managing and analyzing moving objects data are shattering these limitations, leading to revolutions in animal movement ecology and human mobility science. Despite parallel transitions towards massive individual-level data collected automatically via sensors, there is little scientific cross-fertilization across the animal and human divide. There are potential synergies from converging these separate domains towards an integrated science of movement. This paper discusses the data-driven revolutions in the animal movement ecology and human mobility science, their contrasting worldviews and, as examples of complementarity, transdisciplinary questions that span both fields. We also identify research challenges that should be met to develop an integrated science of movement trajectories.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 855-876 |
| Number of pages | 22 |
| Journal | International Journal of Geographical Information Science |
| Volume | 33 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 4 2019 |
Bibliographical note
Funding Information:The US National Science Foundation supported the first two workshops (BCS 1560727: Advancing Movement and Mobility Science by Bridging Research on Human Mobility and Animal Movement Ecology). The third workshop was supported by Schloss Dagstuhl?Leibniz Center for Informatics. Gil Bohrer and the editing of Figure 1 were supported in part by US National Science Foundation grants BIO 1823498 and DBI 1564380. Figure 2 is based on research supported by the U.S. National Cancer Institute Obesity Policy Research: Evaluation and Measures program [1R01CA157509-01]. The views in this paper derive in part from three workshops on movement and mobility analytics: i) Measuring and Analyzing Interactions among Mobile Entities (Austin, Texas, USA, 10?11 November 2016); ii) Analyzing Movement and Mobility within Geographic Context (Columbus, Ohio, USA, 11?12 May 2017); iii) From Observations to Prediction of Movement (Seminar 17282, Schloss Dagstuhl, Wadern, Germany, 9?14 July 2017).
Funding Information:
The US National Science Foundation supported the first two workshops (BCS 1560727: Advancing Movement and Mobility Science by Bridging Research on Human Mobility and Animal Movement Ecology). The third workshop was supported by Schloss Dagstuhl – Leibniz Center for Informatics. Gil Bohrer and the editing of Figure 1 were supported in part by US National Science Foundation grants BIO 1823498 and DBI 1564380. Figure 2 is based on research supported by the U.S. National Cancer Institute Obesity Policy Research: Evaluation and Measures program [1R01CA157509-01].
Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Mobility
- mobile objects
- personal movement models