Exploratory Visual Analysis for Animal Movement Ecology

Slingsby, A. & van Loon, E. (2016). Exploratory Visual Analysis for Animal Movement Ecology. Computer Graphics Forum, 35(3), pp. 471-480. doi: 10.1111/cgf.12923

[img] Text - Accepted Version
Restricted to Repository staff only

Download (14MB) | Request a copy

Abstract

Movement ecologists study animals’ movement to help understand their behaviours and interactions with each other and the environment. Data from GPS loggers are increasingly important for this. These data need to be processed, segmented and summarised for further visual and statistical analysis, often using predefined parameters. Usually, this process is separate from the subsequent visual and statistical analysis, making it difficult for these results to inform the data processing and to help set appropriate scale and thresholds parameters. This paper explores the use of highly interactive visual analytics techniques to close the gap between processing raw data and exploratory visual analysis. Working closely with animal movement ecologists, we produced requirements to enable data characteristics to be determined, initial research questions to be investigated, and the suitability of data for further analysis to be assessed. We design visual encodings and interactions to meet these requirements and provide software that implements them. We demonstrate these techniques with indicative research questions for a number of bird species, provide software, and discuss wider implications for animal movement ecology.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Slingsby, A. & van Loon, E. (2016). Exploratory Visual Analysis for Animal Movement Ecology. Computer Graphics Forum, 35(3), pp. 471-480., which has been published in final form at http://dx.doi.org/10.1111/cgf.12923. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Informatics > giCentre
URI: http://openaccess.city.ac.uk/id/eprint/14159

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics