Wrap-up: 2015 AAG Annual Meeting in Chicago

I’m currently sitting at Chicago’s O’Hare airport waiting for my flight back home to Germany. In an attempt to both not forget too much of it too soon and at the same time to keep me awake so I can sleep well on the plane I will now try to craft a wrap-up of my AAG 2015. I’ll start with some details about the sessions I visited and will finish with a more general recap.
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Upcoming Event: 2015 Annual Meeting of the Association of American Geographers (AAG)

While there’s still some time until the 2015 AAG Annual Meeting kicks off in Chicago next spring the deadline for submitting papers is approaching almost here: November 20th, 2014!

As for me, I will present an algorithm I developed as part of my PhD thesis and in the course of my related research of people’s movements in urban areas:

Konstantin Greger, University of Tsukuba
A Spatio-Temporal Betweenness Centrality Measure for the Micro-Scale Estimation of Pedestrian Traffic

The spatio-temporal mobile population estimation approach I introduce here can be used to calculate an index for the pedestrian traffic volume on street segments divided into deliberately chosen time steps. This is especially useful in the spatial context of highly urbanized areas, as it provides the populations in public space as a complementary element to building populations.

This was achieved by employing a graph theory methodology, namely that of betweenness centrality, and extending it by the temporal dimension. This new model was then applied using a number of datasets that provide information about building populations and train station passenger transfers segregated both spatially and by time.

The introduction of the temporal dimension to the estimation of populations in public space allows for a micro-scale analysis of the actual population figures according to the underlying human activities. I believe that this is the most interesting characteristic of the proposed estimation methodology, since for the first time it allows for a reliable estimation of mobile populations even for large study areas with justifiable requirements in terms of both necessary input data and computational expense.

The output result of the spatio-temporal model can be used to visualize the amount of pedestrians on the streets of a chosen study area. While the data do not represent the absolute numbers of pedestrians, they do reflect the traffic volume and allow for a comparison of crowdedness, which can be used for further quantitative analyses, such as population density calculations for certain points in time.

This year I made an effort to not being placed into some random session as has happened to me both in 2012 and 2014 – in 2013 I went all the way and organized my very own session. Therefore I browsed the (admittedly a wee bit confusing) “abstract and session submission console” on the AAG conference website. There I came across an effort by Prof. Diansheng Guo at the University of South Carolina, who proposed a session (or a series thereof?) labeled “Spatial Data Mining and Big Data Analytics”. I was more than happy to receive an almost instantaneous feedback from Prof. Guo, let alone a positive one!

Obviously I don’t have details about the “where and when”s of said session(s) and my presentation, but I will update this article accordingly once the information has become available. The details are:

Paper Session: Spatial Data Mining and Big Data Analytics (2)
Tuesday, 4/21/2015 10:00 AM – 11:40 AM
304 Classroom, University of Chicago Gleacher Center, 3rd Floor

In the meantime, Here’s the general conference information:

2015 AAG Annual Meeting
April 21 – 25, 2015
Hyatt Regency Chicago
http://www.aag.org/cs/annualmeeting

I’m already looking forward to my fourth AAG, and I would be happy to see you there!

Upcoming Event: 2014 Annual Meeting of the Association of American Geographers (AAG)

Readers of my blog know that I have been attending the Annual Meeting of the Association of American Geographers (AAG) for the past two years. While these meetings took place in some of the largest and most international cities in the USA (New York in 2012 and Los Angeles in 2013), the AAG decided to hold the 2014 meeting in Tampa, FL. There’s nothing wrong with this – I love Florida and it should be nice and warm there in early April – but I can’t help but be a little afraid that the city will be more or less overrun by geographers over the course of the conference week. Also, there seem to be mostly two types of accommodation in Tampa: either luxury hotels that break my budget (even at the “discounted conference rate” of USD 199 per night in select hotels) or shady motels far away from the conference venue…

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IGU2013: Spatio-Temporal Analysis of Bicycle Commuting Behavior in the Greater Tokyo Area Using a Micro-Scale Persontrip Database

I just finished my first presentation of the 2013 IGU Regional Conference in Kyoto. In this presentation, co-authored by my academic advisor Prof. Yuji Murayama from the Division for Spatial Information Science at the University of Tsukuba, I talked about some very early findings of one of our most recent research projects analyzing the use of bicycles in the Tokyo Metropolitan Area. We are especially interested if and how the use of bicycles is integrated in routine commuting activities. We are doing this by analyzing a large-scale database of persontrip information.

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Upcoming Event: 2013 Regional Conference of the IGU

From August 4th to 9th 2013 the International Geographic Union (IGU) will hold their 2013 Regional Conference at the International Conference Center in Kyoto. There, at the birthplace of the famous Kyoto Protocol, geographers from all over the world (theoretically – personally I expect a majority of fellows from Asia, hence the “Regional” in the conference name) will gather to discuss, exchange and network for 6 days. The theme of the conference is “Traditional Wisdom and Modern Knowledge for the Earth’s Future”, and what country could be better suited for this dialog between old and new than Japan, where this opposition can be observed everywhere and all the time.

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