Quote of the day: Plans

For when you start your PhD: 

"Plans are worthless, but planning is everything" Eisenhower

When you get close to the end of your PhD:

“Everybody has a plan until they get punched in the face.” Mike Tyson

I could say Mike Tyson is my academic hero right now :)

R Links

1. CRAN now has (more than) 10,000 R packages. Here's how to find the ones you need
   
   
2. Predicting gentrification using longitudinal census data, by Ken Steif
   
   
3. How to plot Sex ratios in all countries from Human Mortality Database using R, by Ilya Kashnitsky
   
   
4. ggraph, an R package to plot graph structured data by, Thomas Lin Pedersen
   
   
5. The R community is great. There is a called ggguitar that allows you to create guitar tablature using ggplot2
   
   
6. Using dplyr syntax to query SQL databases, ht mikefc
   
   
7. If you are familiar with R base for data visualization, you will probably like the cartography package to create really nice maps, by Timothée Giraud. Good vignette here, although I still prefer using ggplot2
   
   
8. Finding the most depressing Radiohead song with R, by Charlie Thompson

credit: Charlie Thompson

Analyzing transport accessibility in Sweden, step 1

I've spent a few hours yesterday testing OpenTripPlanner to model transport accessibility by different transport modes in Swedish major metro areas, Stockholm, Gothenburg and Malmo. This is part of a project where I'm collaborating with colleagues from Lund University and K2 - The Swedish Knowledge Centre for Public Transport. Jean Ryan, Anders Wretstrand and I are engaging with the human capabilities approach and conducting a comparative study of transport accessibility of elderly people. Stay tuned.

Latter this year, I will post a detailed step-by-step + code of how I've been conducting accessibility analysis for my PhD and other projects. In short, I estimate travel-time matrices using OpenTripPlanner (I explain how to do this on GitHub). I then process the travel-time matrices with other spatial data in R, mainly using the super fast data.table library and make the plots using ggplot2 and ggmap.

These figures show just some preliminary tests for accessibility by bicycle + public transport. They values are meaningless here but the maps look good, right?

click on the image to enlarge it

Here are a couple of our recent publications related to this topic:

• Ryan, J., Wretstrand, A., & Schmidt, S. M. (2015). Exploring public transport as an element of older persons' mobility: A Capability Approach perspective. Journal of transport geography, 48, 105-114.
  
  


• Pereira, R. H. M., Schwanen, T., & Banister, D. (2017). Distributive justice and equity in transportation. Transport Reviews, 37(2), 170–191.

Urban Picture

"Dramatic Shanghai", by Olivier Symon

On the specification of spatial models

One of best sentences I've read in an academic paper in years:

"Without divine intervention it is generally difficult to know with certainty which (if either) of the two above cases are true"

This is from Fotheringham et al (1998) on the specification of spatial models. I find this quite amusing but I must say this is one of the most well written and accessible articles on spatial econometric models I've come across so far. It's not by chance this paper has become a great reference on the topic with more than 500 citations.

I've only started reading more about spatial models recently. Here are four papers I would recommend to get started on the topic.

• Anselin, L. (2002). Under the hood Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27(3), 247–267.
  
• Fotheringham, A. S., Charlton, M. E., & Brunsdon, C. (1998). Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis. Environment and Planning A, 30(11), 1905–1927.
  
• Florax, R. J. G. M., Folmer, H., & Rey, S. J. (2003). Specification searches in spatial econometrics: the relevance of Hendry’s methodology. Regional Science and Urban Economics, 33(5), 557–579. [thanks Leo Monasterio for the recommendation]
  
• Páez, A., & Scott, D. M. (2005). Spatial statistics for urban analysis: A review of techniques with examples. GeoJournal, 61(1), 53–67.

This paper is particularly relevant to problem raised in the quote above:

• Gibbons, S., & Overman, H. G. (2012). Mostly Pointless Spatial Econometrics?*. Journal of Regional Science, 52(2), 172–191

I just happened to like this plot.

Assorted links

1. Combining satellite imagery and machine learning to predict poverty
   
   
2. Bill Rankin's new work on Mapping Slavery Against US Incarceration
   
   
3. A Review of Temporal Visualizations based on Generalized Space-Time Cube Operation
   
   
4. Charles Darwin was born on this day 208 years ago. All of Darwin's published works are available here.
   
   
5. An extensive list of good blogs and websites on urban- and transport-related topics. ht Kyle Zheng
   
   
6. A 15-min video giving an interesting summary of the largest US health insurance experiment in history - ht Carl Schmertmann
   
   
7. There is an app to crowdsource data on shootings in Rio. Great project by Cecilia Olliveira in face of harsh reality
   
   
8. Can you name a city just by looking at its streets?
   
   
9. Inequality Is Killing The American Dream

Quote of the Day

"My interest is not data, it's the world. And part of world development you can see in numbers. Others, like human rights, empowerment of women, it's very difficult to measure in numbers." 

(Hans Rosling in an interview in 2013)

Thanks Sunniva Sandbukt for bringing this quote to my attention.

Hans Rosling passed away today

"We are extremely sad to announce that Professor Hans Rosling died this morning. Hans suffered from a pancreatic cancer which was diagnosed one year ago. He passed away early Tuesday morning, February 7, 2017, surrounded by his family in Uppsala, Sweden."

This information comes from Gapminder, which Hans was one the founders in 2006.

Hans was incredibly knowledgeable of social and economic dimensions behind population and health issues. He was also and incredible speaker who gave a great contribution to the public understanding of population studies (his Ignorance Project is one of my favorites). Also thanks to the great relevance of the Gapminder project, he became internationally famous because of his TED talks, to the point he became know as the “Mick Jagger" of TED.

I've included below a few links to some of our previous posts on Hans Rosling's work, but he has has many more incredible videos, material out there on the web that will keep a beautiful memory of Hans and his work.

My sentiments to the Rosling's family and close friends.

Some of our posts on Hans Rosling's work.

• The best stats you've ever seen
• Just in case you haven't met him yet
• Is there a demographic divide between rich and poor countries ?
• Quote of the Day: aging
• Where Are the Syrian Refugees Today?

How much of the world is covered by cities? not much

Vinicius Netto asked this question a few days ago. Here is the answer I've found based on a paper by Seto and colleagues.

Proportion of Urban land-cover in km2
0.2% Africa
0.5% S America
0.5% World
0.7% N America
1.2% Asia
2.2% W Europehttps://t.co/qH1aQJrAbG pic.twitter.com/yfKO9Wv6Cz

— Urban Demographics (@UrbanDemog) 22 January 2017

Intro to Spatial Data Science

Seven recorded lectures on Spatial Data Science by Luc Anselin at the University of Chicago (October 2016). It might be of interest to some readers of this blog as well. 

By the way, the Center for Spatial Data Science is also on Twitter.

Urban Picture

Flatland: a beautiful project by the photographer and digital artist Aydın Büyüktaş, who creates Inception-like photos of Turkish Cityscapes (via Colossal).