The keys to the kingdom

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I started a new job last week- here I am working on transport and GIS!

As it turns out, both transport and GIS are awesome. But how do you get up to speed really, really quickly?

You ask for help.

Asking for help

Asking for help

In return, I was given the keys to the kingdom - people to follow, blog posts to explore, books to read, offers of help. This community is amazing.

The resources were too good not to share and following Steph Locke’s geospatial lead on this, here’s the summary. I’ve also added a few I found on my own.

Great people to follow

One of the ways I get a good overall view of a topic is by following great people on Twitter. Having a feed that offers me a little new information every day means I’m learning continuously - with context.

The people recommended to me for following include:

Elaine McVey (multiple times)

Civic Angela (who is fighting the patriarchy one spontaneous conference talk at a time AND just graduated!)

Robin Lovelace, who wrote two of the books I’ll link to below. I’m up to Chapter 5 of the microsimulation book and it is an excellent starter’s guide. Highly recommended!

Reka S, who was at this year’s Seattle Unconference and by report an all-round super star.

Oliver Obrien, who tweets about cities

Mark Padgham, bike expert

Michael Sumner, #rstats GIS nice guy who was the first person I ever asked about GIS stuff and came through in spades for a complete twitter stranger. It was my first introduction to what this community can be like.

Belinda Maher, Aussie transport maven.

Alon Levy, transport writer.

Mastodon C, I think he’s/she/they is a cities person?

Jarret Walker, author of human transit.

Packages to explore

gtfsr, a package for doing things with gtfs data. Also, for the record, I found out that gtfs is a type of transport data and does not stand for “go the @#$% to sleep” in this context (language warning on this link!).

stplanr, by Robin Lovelace and Richard Ellison. A package full of useful transport functions and ideas.

RNetlogo for Agent Based Modelling.


Not an R package: The Multi-Agent Transport Simulation MATSim. As far as I can ascertain there is no R wrapper for this Java-based piece of open source magic. We may need to do something about that…

Books to read

Spatial Microsimulation in R by Robin Lovelace. I got through five chapters or so of this already and it’s an excellent starter’s guide.

Geocomputation in R by Lovelace, Nowosad and Muenchow. Forthcoming, but looks fantastic.

Agent-Based Models of Geographical Systems by Heppenstall, Crooks, See and Batty, editors.

Forecasting Urban Travel by Boyce and Williams. This one is not free, but I have a feeling I’m going to get acquainted with it in the future.

Modelling Transport by Ortuzar and Willumsen, ditto.

Handbook of Choice Modelling, again not free. But then the funding to produce these kinds of works has to come from somewhere, right?

Blogs and articles

Todd Schneider on the NYC subway countdown clock

Steve Bennett’s blog

Visualising GTFS data in R by DataFeelings

Not R, but some great Open Cities projects and blogs.

Talks to watch

This talk by Katie Bell on Sydney Buses

Papers largely trapped behind paywalls (sorry!)

These are mostly about choice modelling, which is where I have alot of interest at the moment. A short pay-walled bibliography if you will.

Endogenous treatment of residential location choices in transport and land use models: Introducing the MetroScan framework

Application of irrelevance of state-wise dominated alternatives (ISDA) for identifying candidate processing strategies and behavioural choice rules adopted in best–worst stated preference studies

The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework

Hybrid Route Choice Modeling in Dynamic Traffic Assignment

Stated preference modelling of intra-household decisions: Can you more easily approximate the preference space?

A joint best–worst scaling and stated choice model considering observed and unobserved heterogeneity: An application to residential location choice

What if My Model Assumptions are Wrong? The Impact of Non-standard Behaviour on Choice Model Estimation

Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding

People to thank

I got an amazing list of resources to learn in a very short period of time, because of the help and assistance of the R Community. Thankyou so much to you all!

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