November 1, 2014

Accessibility Analysis with Python and OpenTripPlanner

Walking time to the nearest grocery store for all Census blocks in Chicago.

OpenTripPlanner is a great bit of software for both customer-facing tools and analysis. Until recently, it had the capability to perform batch queries, calculating an origin-destination matrix or an aggregate measure of accessibility. Configuring this functionality, however, was somewhat awkward, as it used a verbose XML format that was more suited to allowing developers to configure application components than as a user-facing interface (and I say that having been one of the last defenders of this approach on the OTP mailing list).

October 20, 2014

Using GeoTools with Multiple User Accounts

I have a situation where I have multiple GeoTools applications being run on a server by different users. I was having a lot of issues with exceptions about not being able to decode CRS codes, even though I was sure I had the gt-epsg-hsql file included in my JAR, and had set up Maven correctly to include the dependency.

It turns out the issue was that the gt-epsg-hsql extracts its hsql database of projections to Geotools in the system temporary directory, and if there are multiple geotools apps running as different users, the first one to start gets the directory, and the remaining ones crash because they don’t have permissions to access it.

August 10, 2014

Running RStudio Server on Amazon EC2

R is a great environment for statistical computing; I’ve used it in a number of projects. RStudio is hands-down the best IDE for R (there is even less debate here than there is about emacs being the best editor). Sometimes, though, I find that I need to run analyses that require more computing power than my personal computer can provide (especially since my desktop is currently in storage in California and I’m in Illinois with a circa-2007 netbook with 2GB of RAM).

May 1, 2014

Predicting the Popularity of Bicycle Sharing Stations: An Accessibility-Based Approach

I presented a paper about modeling the popularity of bikesharing stations at the California Geographical Society 2014 annual meeting in Los Angeles. I calculated accessibility measures to jobs and residents using Census and OpenStreetMap data and the open-source OpenTripPlanner network analysis suite. I used those as independent variables in regressions to try to explain the popularity of bikesharing stations. I used bikeshare popularity data from Washington, DC, San Francisco, and Minneapolis–St. Paul. The main goal of the modeling is to build models of station popularity that can be transferred from one city to another, and thus used as planning tools for new bikeshare systems.

April 24, 2014

Identifying Patterns in Bikeshare Trip Making

Bay Area Bike Share has recently released their trip history data; the data file contains the origin station, end station, time and date, and user type (day-pass or subscriber) for all the trips taken on the system since its inauguration on August 29, 2013. For another project, I had calculated accessibility measures for each bikeshare station in the Bay Area Bike Share system (using the beta OpenTripPlanner transportation analysis suite; see this post and the attached paper). I wondered if there were different types of trips represented by different accessibility footprints (e.g., trips that have high job accessibility at one end but not the other may be commute trips).

March 26, 2014

Overanalyzing Board Games: Network Analysis and Pandemic

I like board games, and one of my favorites is Pandemic. The game consists of a board (pictured above) with a world map on it, with various cities highlighted, and a network between the cities. Disease breaks out randomly in the cities at the start of the game (using the shuffled infection deck) and then progresses using the same deck. Players cooperatively attempt to quell disease by moving between cities and treating disease. On each turn, players draw city cards; by collecting five of a particular color, they can cure a disease. Additional cards are drawn each turn from the infection deck to infect additional cities. Periodically, there are ’epidemics’ in which the cards for the cities that have already been drawn are returned to the top of the infection deck. If a city is infected three times without being treated, and there is an additional infection, an ‘outbreak’ occurs and all of the cities connected to that city are infected.

February 22, 2014

Visual Correlation Matrices

Correlation matrices show up often in papers and anywhere data is being analyzed. They are useful because they succinctly summarize the observed relationships between a set of variables; this also makes them very good for exploratory data analysis.

However, correlation matrices by themselves are still a bit difficult to interpret, as they are simply numbers. For example, here is the output of the R cor() function. There’s a lot of useful information there, but it’s still a bit difficult to interpret.

December 28, 2013

Schelling's Segregation Model in JavaScript

Schelling’s segregation model is an interesting model of neighborhood dynamics developed by the economist Thomas C. Schelling. It’s an agent based model, in which agents of two groups (which could be based on income, political affiliation, race, &c.) are placed on a grid. There is some threshold for what percentage of an agent’s neighbors must be of the same group for it to be happy. For instance, agents might want 30% of their neighbors to be of the same group. If they are not happy, they move. This continues until all agents are happy.

December 14, 2013

Analyzing the Effects of Space and Time on Bikeshare Use

Bikeshare systems have been taking off in the US of late. One of the first of these systems, Capital Bikeshare in Washington, DC, has been in operation since 2010. The automated bikeshare stations generate a wealth of information; the start and end stations and times of each trip are recorded, and are available to the public in anonymous form. This project used the approximately 4.5 million trips taken on the system from the fourth quarter of 2010 until the second quarter of 2013.

June 20, 2013

Microaccessibility with OpenTripPlanner

Analysis of accessibility is generally undertaken in large regions, such as metropolitan areas or entire countries. Frequently it also uses macro temporal scales, as in before-and-after analysis. This analysis instead looks at micro scales, both spatial and temporal. The study area is the University of California, Santa Barbara campus and the adjoining student community of Isla Vista.

I analyzed accessibility at every hour of a typical week, so that accessibility can be compared at different times of day and on different days. This has been done before, looking at accessibility at different times of day (page 8) in the Los Angeles area. I used tighter temporal scales (one hour instead of four chunks) and also analyzed accessibility over the entire week to allow the discernment of weekly cycles.