Friday, May 27, 2016

Commuting hinterland of major UK cities

Alasdair Rae (who has a great blog by the way) has posted a nice short collection of maps comparing the commuting hinterland of some major UK cities.


Tuesday, May 24, 2016

Simulados: agent-based computer simulations

A nice video of the Barcelona Supercomputing Center on the use of agent-based computer simulations to study societies. Via Andy Kirk.



Sunday, May 22, 2016

Spreadsheets

true story

Thursday, May 19, 2016

I'm presenting at UCL next week - Transport legacy and the redistribution of Urban Accessibility

I'm giving a talk at the Bartlett School of Planning UCL next week. Feel free to come by and say hello if you're around.

I will present a case study on the transport legacies of the 2016 Olympic Games in Rio de Janeiro (Brazil) and discuss the distributive aspects of how such developments affect different income groups in terms of their transport accessibility to hospitals, schools and job opportunities. This is one of the papers of my doctoral research, so I'd be glad to get any feedback  if I don't put the audience to sleep 

There is more info about the event here. Thanks Beatriz Mella for the invitation.


Saturday, May 14, 2016

How I feel trying to solve a problem in my research

This is how I've been spending my days lately. #PhDlife





Friday, May 13, 2016

Electric car fact of the day



Thursday, May 12, 2016

Traffic Jam without bottleneck






I guess one could say gridlocks are one of the causes of traffic jam when there is no bottleneck. This video shows a real demonstration of this.  (via ‎Gonçalo Correia)

Wednesday, May 11, 2016

Justice and ethical concerns in Energy decisions

The latest issue of Nature Energy is out. There is an interesting paper that puts together a miscellaneous of concepts from different theories in political philosophy to build an "energy justice framework centred on availability, affordability, due process, transparency and accountability, sustainability, equity and responsibility".


The authors recognize eventual conflicts between these different ideas but I think they don't make it very clear how the ethical framework they propose actually overcomes such conflicts. In any case, it's a good read. 

Thanks Tim Schwanen for the tip.

Tuesday, May 10, 2016

Detecting Spatial Clusters of Flow Data

Tao, R. and Thill, J.-C. (2016), Spatial Cluster Detection in Spatial Flow Data. Geographical Analysis. doi: 10.1111/gean.12100

Abstract:
As a typical form of geographical phenomena, spatial flow events have been widely studied in contexts like migration, daily commuting, and information exchange through telecommunication. Studying the spatial pattern of spatial flow data serves to reveal essential information about the underlying process generating the phenomena. Most methods of global clustering pattern detection and local clusters detection analysis are focused on single-location spatial events or fail to preserve the integrity of spatial flow events. In this research a new spatial statistical approach of detecting clustering (clusters) of flow data that extends the classical local K-function, while maintaining the integrity of flow data was introduced. Through the appropriate measurement of spatial proximity relationships between entire flows, the new method successfully upgraded the classical hot spot detection method to the stage of “hot flow” detection. Spatial proximity of flows was measured by a four-dimensional distance. Several specific aspects of the method were discussed to provide evidence of its robustness and expandability, such as the multiscale issue, relative importance control and adaptive scale detection, using a real dataset of vehicle theft and recovery location pairs in Charlotte, NC.

image credit: Tao, R., & Thill (2016)

Saturday, May 7, 2016

Dumb Ways to Die in Rio

A cute video to celebrate the coming of the Olympic Games this year.

Wednesday, May 4, 2016

Data analytics and visualization at Uber

Here is a neat 3D animated map showing a full day of anonymized Uber trips in Los Angeles. You can also read Nicolas Belmonte on how Uber has been using data analytics and visualization in their work at Uber.





Dragging the cursor over a given radius area reveals distributions of Uber dropoffs in real-time. This is pretty cool. I was wondering if someone would be up for the challenge of building a similar interactive map with Shiny in R.

Dragging the cursor over a given radius area reveals distribution dropoffs in real-time.