Thursday, February 18, 2016

Call for Papers: GeoSocial: Social Media and GIScience

GeoSocial: Social Media and GIScience

A GIScience 2016 Workshop

September 27th, Montreal, Canada

This day-long workshop aims to serve as a platform to discuss and showcase the complex issues associated with the analysis of social media contributions in the context of GIScience.

Spanning spatial footprints, social networks, and sociocultural themes, such data can support a variety of applications, ranging from disaster response and environmental monitoring to health informatics and digital citizenship. Given their variations in accuracy, the complex patterns of participation, and the constantly increasing data volumes, analyzing such data in a meaningful, reliable, and timely manner is a substantial challenge. The objective of this workshop is to showcase on-going research in the GIScience community on the analysis of social media content and thus support the emergence of a cohesive research agenda in our community.

We invite submissions of short papers (1,500-2,000 words) that present research related to the workshop theme. Examples of topics of particular interest include:
  • Theoretical/conceptual issues in linking social media with GIScience.
  • Accuracy and reliability issues associated with the analysis of social media content.
  • Analysis of the spatial and spatiotemporal patterns of social networks.
  • Geocoding methods and engines for social media messages.
  • GeoSocial Analytic software and tool development.
  • Visualization of multi-thematic geosocial content.
  • Computational challenges associated with the big data nature of such information.
  • Social multimedia: images and videos.
  • Applications and case studies. 

Workshop Format:

  • This full day workshop will comprise presentations of research based on short paper submissions, as well as a break-out group session will be held in the afternoon, followed by a plenary synthesis session, addressing a “GeoSocial Research Agenda”. 



Tuesday, February 16, 2016

Pedestrian Modeling Examples

Readers might know that we like pedestrian models here. So in keeping with the theme of NetLogo models and the use of GIS below are two simple pedestrian models. In the first model (shown in the movie below), agents just exit the room, taking the shortest path (calculated via a cost surface). The idea behind this first model is to highlight how changing the width of the exit (i.e. the door) can impact on the evacuation time (the model can be downloaded from here).

In the second model (shown in the movie below and the code is here) we show a more complicated configuration based on a floor plan that has been first converted from a CAD file to a Shapefile  before being converted into a raster where each cell is 50cm by 50cm that can then be used in the NetLogo model (coming soon there will be a bunch of tutorials on how we do this).

From CAD File (A) to Shapefile (B) to Raster (C)

In this model, agents like in the simple model above, walk to the exit. In essence, one could consider this as a fire evacuation scenario. The agents are assumed to walk to the nearest exit, analogous to following exit signage. Similar to the first example, user can explore what happens if an additional exit is added.

More information about the models (and the code) can be found over at Geospatial Computational Social Science.

Call For Papers: Rethinking the ABCs

Readers of the blog might be interested in a workshop being organized by Daniel Brown, Eun-Kyeong Kim, Liliana Perez, and Raja Sengupta entitled:

Rethinking the ABCs: Agent-Based Models and Complexity Science in the age of Big Data, CyberGIS, and Sensor networks

September 27th, 2016 in Montreal, Canada

To quote from the call:

"A broad scope of concepts and methodologies from complexity science – including Agent-Based Models, Cellular Automata, network theory, chaos theory, and scaling relations – has contributed to a better understanding of spatial/temporal dynamics of complex geographic patterns and process.

Recent advances in computational technologies such as Big Data, Cloud Computing and CyberGIS platforms, and Sensor Networks (i.e. the Internet of Things) provides both new opportunities and raises new challenges for ABM and complexity theory research within GIScience. Challenges include parameterization of complex models with volumes of georeferenced data being generated, scale model applications to realistic simulations over broader geographic extents, explore the challenges in their deployment across large networks to take advantage of increased computational power, and validate their output using real-time data, as well as measure the impact of the simulation on knowledge, information and decision-making both locally and globally via the world wide web.

The scope of this workshop is to explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era."

More information about the workshop can be found at