Jennifer presented her work on “A computational movement analysis approach for modelling interactions between pairs of moving objects” at the 2017 Geocomputation conference in Leeds, UK. Paul Holloway (UT PhD ’16) also presented his work on “Individual-based modelling of species’ dynamic resource use.”
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Jennifer was back in Europe for a Leiden workshop on Movement: New Sensors, New Data, New Challenges. Lorentz Center (Leiden, The Netherlands), August 21-25, 2017. Jennifer gave a keynote lecture on “Advances & Issues in Spatial Ecology (with applications & implications for Movement pattern analysis and computational movement analysis)”.
We all rented bikes and were able to bike to and from the workshop and to downtown Leiden. The end-of-workshop dinner was on the beach in Katwijk.
I co-organized (along with Harvey Miller and Gil Bohrer from Ohio State) a workshop on Modeling interactions as part of a two workshop series focused on addressing issues in computational movement analysis. The workshops are intended
to draw participants from both the human movement/mobility and animal movement ecology fields.
The interaction workshop was held at UT-Austin Nov. 10-11, 2016. We had about 30 participants and 3 great keynotes from Francesca Cagnacci, Patrick Laube, and Jed Long. More information is here.
The 2nd workshop will be held at Ohio State May 10-11, 2017. More information is here.
A new paper that continues my research on analyzing dynamic interactions using GPS data has just been published. This article employs a null model approach to assess how six currently used dynamic interaction metrics vary in terms of the type and magnitude of interaction they measure. ‘Towards a better understanding of dynamic interaction metrics for wildlife: a null model approach‘ (also see ‘Using spatially explicit simulated data to analyze animal interactions: a case study with brown hyenas in northern Botswana‘). This work will be presented as part of a special Frontiers in GIScience Research session at the ESRI User Conference July 22, 2015.
This research is supported by NSF #1424920.
Dr. Jennifer Miller has received funding from UT’s Center for Identity for a new project that explores how anonymous movement trajectories are based on GPS locations from smartphones. Location data are often released after they have been ‘anonymized’—which means that the trajectory has been stripped of any obvious
identifying information such as name, address, phone number, etc. However, personal points of interest (home, work) can be easily identified by mining trajectory data for movement patterns, and these points of interest are often associated with unique individuals. This project will explore privacy issues associated with smartphone location data using a computational movement analysis framework.
I just received a three year grant to support research on developing a framework for analyzing dynamic interactions between animals using GPS data (NSF #1424920). I’m looking for a graduate student (preferably doctoral) to work on the project starting fall 2015. Student should have a GIScience and/or ecology background and be very comfortable with spatial analysis and modeling. Must have very strong R skills and preferably some python programming experience as well.
If you are a potential graduate student interested in working on this project, please see general information about our graduate program here and more specific information about working with me here.
I presented a paper on ‘A novel framework for analyzing interactions between individuals: a case study using brown hyenas in northern Botswana’ at the International Statistical Ecology Conference. The conference was held July 1-4 on the campus of SupAgro in Montpellier, France.
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I’m co-organizing a workshop on Analysis of Movement Data at the GIScience 2014 conference, Sep. 23 in Vienna. See here for more information.
This project originated as an exploratory study to see how GIScience concepts and methods can be used to analyze and understand movement of and interactions between brown hyenas in Northern Botswana. Correlated random walks were used as a ’null model’ to study movement patterns and interaction rates and several different dynamic interaction metrics were compared. This work was recently published in Transactions in GIS and was supported by a UT Vice President of Research Grant.
