Call for participation – NSF Workshops on Advancing Movement and Mobility Science

Recent years have witnessed the emergence of interdisciplinary scientific communities focusing on moving objects, motivated by technological advances in location-aware technologies for moving objects data (MOD) collection. In response to these challenges and opportunities, interdisciplinary communities are emerging that focus on the analysis of MOD to in order to provide new insights into complex spatio-temporal systems. However, a schism is also emerging between researchers focusing on human entities (e.g., people, vehicles, commodities) and animal entities (e.g., tigers, pandas, albatrosses, salmon).

A series of two workshops will bring together scholars working on animal movement ecology and human mobility science to generate a nascent interdisciplinary/cross-domain community focusing on the analysis of moving objects.  Specifically, the two workshops will address crucial issues that span both human mobility science and animal movement ecology:

  • Workshop 1: Measuring and interpreting interactions between and among moving objects (November 2016 in Austin, Texas)
  • Workshop 2: Analyzing moving entities within geographic context (May 2017 in Columbus, Ohio).

These workshops are supported by an award from the National Science Foundation (BCS 1560727)

Call for participation – Workshop 1: Measuring and analyzing interactions among mobile entities.   University of Texas-Austin, 10-11 November 2016

Interactions among mobile objects are a second-order but crucial property of movement.  In human mobility, interactions reflect actual or potential social interactions or shared activities, and are often the basis for the formation and maintenance of social networks and social capital.  In animal movement ecology, interactions can range from physical contact to sharing common resources, to simple awareness and are crucial for understanding spatial ecological processes and behaviors such as mating and territoriality, as well as epizootiology.

New advancements in collecting movement/location data enable more and better quality data to be collected, and have resulted in an increasing number of studies on animal or human interaction.  However, there have been few methodological advancements related to improving the ability to analyze and understand interactions. Most of the currently used interaction metrics were developed under a different paradigm of MOD collection (coarser spatial and temporal resolution) and the assumptions the metrics make (such as the way inherent expected values are calculated) are likely inappropriate in many applications to which they are applied.

We invite participation from researchers at any level who are involved in measuring and analyzing interactions among humans and/or animals.  Selected participants will receive travel reimbursement for legitimate expenses ranging from $500-$1000, with priority to students and unfunded scholars.

More information: sites.utexas.edu/interaction.

To be considered, submit the following:

  1. Brief cover letter indicating your intention to participate, and whether partial travel support is required
  2. A 750 word (maximum) abstract of your proposed presentation
  3. If travel support is required, a one to two sentence statement of need.
  4. A short CV (NSF style preferred; two pages maximum)

Please combine all of the above into one document (*.pdf preferred) named with your last name followed by first two initials (ex. MillerJA.pdf) and email as an attachment to Interac.ng0hvbomn4fo6pis@u.box.com.

Due date: 2 September 2016.

Workshop Co-organizers

  • Harvey J. Miller (The Ohio State University)
  • Jennifer A. Miller (University of Texas at Austin)
  • Gil Bohrer (The Ohio State University)

Steering Committee

  • Somayeh Dodge (University of Minnesota)
  • Joni Downs (University of South Florida)
  • Steven Farber (University of Toronto)
  • Wayne Getz (University of California – Berkeley)
  • Trisalyn Nelson (Arizona State University)
  • Kathleen Stewart (University of Maryland)
  • May Yuan (University of Texas – Dallas)

Columbus is one of the top ten cities in the world for GIScience

A recent paper in the International Journal of Geographic Information Science analyzed 12,436 papers published in 20 GIScience journals during the period 2000-2014.  Here is a list of the top ten cities in the world ranked by the number of GIScience papers produced by an author affiliated with that city (usually via a university appointment), with the number of papers published during 2000-2014:

  1. Beijing, CN – 348.8
  2. Wuhan, CN – 196.9
  3. London, UK – 167.2
  4. Enschede, NL – 152.9
  5. Melbourne, AU – 150.8
  6. Hong Kong, CN – 126.9
  7. Columbus, US – 123.5
  8. Santa Barbara, US – 121.5
  9. Zurich, CH – 110.5
  10. Washington, US – 100.4

You can read the full article here: Biljecki, F., 2016. A scientometric analysis of selected GIScience journals. International Journal of Geographicale Information Science, 

Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure

Farber S, O’Kelly M, Miller HJ and Neutens T. (2015) “Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure,” Journal of Transport Geography, 49, 26-38.

Highlights
• Social Interaction Potential (SIP) is extended into a measure of exposure
• We quantify opportunities of within-group and between-group interactions
• The measure is sensitive to the spatial structure of a region, especially daily commuting patterns

Abstract. Recent advances in transportation geography demonstrate the ability to compute a metropolitan scale metric of social interaction opportunities based on the time-geographic concept of joint accessibility. The method we put forward in this article decomposes the social interaction potential (SIP) metric into interactions within and between social groups, such as people of different race, income level, and occupation. This provides a novel metric of exposure, one of the fundamental spatial dimensions of segregation. In particular, the SIP metric is disaggregated into measures of inter-group and intra-group exposure. While activity spaces have been used to measure exposure in the geographic literature, these approaches do not adequately represent the dynamic nature of the target populations. We make the next step by representing both the source and target population groups by space–time prisms, thus more accurately representing spatial and temporal dynamics and constraints. Additionally, decomposition of the SIP metric means that each of the group-wise components of the SIP metric can be represented at zones of residence, workplace, and specific origin–destination pairs. Consequently, the spatial variation in segregation can be explored and hotspots of segregation and integration potential can be identified. The proposed approach is demonstrated for synthetic cities with different population distributions and daily commute flow characteristics, as well as for a case study of the Detroit–Warren–Livonia MSA.

Keywords: Segregation; Social interaction potential (SIP); Exposure; Commuting