Mobile Lives

A good idea for Xmas gift.

[image credit: Liam Walsh/The New Yorker, via Arthur Charpentier]

Related quote of the day.

The remains of a ghost town 28 years after Chernobyl

Danny Cooke has used a drone to give a bird's eye view of Pripyat (Ukraine), a beautiful and sad footage of the remains of a ghost town 28 years after the Chernobyl nuclear disaster, which happened in 1986. A great piece of work.

***Soundtrack 'Promise land' by Hannah Miller

Real-time map of 202 transit systems worldwide

The team at geOps have used GTFS feeds to create an incredible real-time map of 202 transit systems around the world (mostly USA and Europe but there are a few cities in Mexico, Australia and Israel). If you zoom in enough you can see the vehicles moving, click on stops and vehicles to get information etc  (via @BrendnCasey).

You can check the map here and read some more information here, in German.

[image credit: geOps nor the University of Freiburg]

Related Links:

• Modeling Transport accessibility with open data
• Accessibility Observatory

What a neuroscientist is doing at Uber

Bradley Voytek writes about what a a neuroscientist is doing at Uber* (ht MR).  In short, Voytek is finding network patterns, mapping different types of users, etc etc (ie data science at its broadest sense).

Some of San Francisco’s Uber Networks

[image credit: Bradley Voytek]

*By now, you should have heard about Uber. If you haven't, I would recommend you to check this Freakonomics episode where they talk about Uber, what it is, its promises to the future of urban transport and some of its controversies. 

Quote of the Day

Man is born free, but everywhere he is checking work-related email.
— Werner Twertzog (@WernerTwertzog) November 23, 2014

Soundtrack for the weekend:

Incorporating Cognitively Perceived Urban Space in Economic Models

Furtado, B. A. (2011). Neighbourhoods in urban economics: incorporating cognitively perceived urban space in economic models. Urban Studies, doi:10.1177/0042098010391288.

Abstract:

This paper proposes that urban economic analysis would benefit from the use of cognitively perceived neighbourhoods, which are discussed within urban studies. Georeferenced data should be aggregated by spatially bounded units that are identifiable by citizens in order to enrich one-dimensional distance as the sole variable to bring urban complexity into economic models. Multivariate analysis is applied to data from Belo Horizonte, Brazil, to formulate four indices, ranked by neighbourhoods that together represent a spatially complex, non-linear influence on urban real estate markets. The results of the indices by neighbourhood are then tested against a traditional specification in an econometrics exercise that does not include the concepts and indices put forward. The definition of neighbourhood used and the empirical results provide a thorough description of urban fabric that can fully and more accurately represent urban influence in economics while avoiding abstract distance measurement.

Urban Picture

[image credit: ?]

Soundtrack:

NASA's high-resolution computer model of CO2 emission

A couple of weeks ago, we wrote a short post about NASA's project to monitor Urban Greenhouse Gas Emissions from Space using a new satellite, the Orbiting Carbon Observatory-2 (OCO-2).

NASA has recently released a new stunning animation using the results of a high-resolution computer model of CO2 emissions on Earth's atmosphere'. (HT Franziska Gaupp, who is working with drought modeling and food supply here at Oxford)

Assorted links

1. Epic Extreme commute: From New Zealand to rural Iceland !(ht Vanessa Nadalin)
   
   
2. The economics of population imbalance
   
   
3. The paradox of Space and Time explained with  8-Bit Philosophy
   
   
4. 7 ways to make your Google Scholar Profile better
   
   
5. The Urban Fabric of English Cities and the Urban Footprint of Scottish Cities
   
   
6. Find Where The Streets Have Your Name, literally
   
   
7. Penguins are being raped by seals. Warning, strong images NSFW (thanks to my poor sick friend Leo Monasterio)
   
   
8. Locations of every photo from International Space Station via Flowing Data

[image credit: Nathan Bergey]

Modeling Transport accessibility with GTFS, OpenStreetMap and OpenTripPlanner Analyst

David Levinson points out to this great presentation by Kevin Webb talking about Modeling Transport accessibility with open data. Kevin and his team at Conveyal combine GTFS data, OpenStreetMap and OpenTripPlanner Analyst to make simple and yet sophisticated analysis of transport accessibility.

I feel very enthusiastic about Kevin's presentation because part of my PhD thesis will be closely connected to some of the questions he raised. In one of my papers, I will analyze the distributional aspects of how the addition of new transport infrastructure/services in Rio de Janeiro (particularity related to mega events) will impact urban accessibility across the metropolitan area. I'll post some updates about my PhD research in the near future as I suffer to make some progress on it.

There are dozens of other thoughts, papers and Links on GTFS and transport accessibility I would like to share here (including the research conducted by Andrew Owen, D. Levinson and other researchers), but I'm sure we will have many more posts to do this in the near future.

Related Links:

• Interactive map about Accessibility to Jobs in NY from the Regional Planning Association 
• Apps that help you get around using GTFS data 
• Hurricane Sandy’s impact on the New York City transit system 
• A set of Python 3.4 tools for processing General Transit Feed Specification (GTFS) data
• How to convert GTFS to GIS shapefiles and KML
• The World Bank, Columbia University and MIT co-organized a workshop on GTFS Data in 2013. The follow-up materials (including notes, slides, codes and videos) can be accessed through this link.

[image credit: Andrew Byrd and OpenTripPlanner Team]

The Evolution of Commute Times in Brazilian Metropolitan Areas (1992-2013)

 shameless self-promotion alert  Tim Schwanen and I published a working paper in 2013 where we analyzed how commute times have evolved in Brazil between 1992 and 2008, with special attention to differences between metropolitan areas, income levels and gender (Portuguese version here). 

The Brazilian newspaper O Globo took our study and made a great work of data visualization a couple of days ago, when they published a much improved and interactive version of Chart #2 in our study. This is their static version of the chart, comparing the evolution of average commute time across Brazilian metropolitan areas between 1992 and 2013. Click here for the interactive version (or here).

[click on the image to enlarge it]

[image credit: Daniel Lima with data from Pereira and Schwanen, 2013]

I would love to make some comments on these findings since we have a marked contrast between different areas, both in terms of trends and levels. I will spare you from reading my typos here, though. In case you are interested, you may read the original publication, here.


Related Links:

• Average Commute Time Worldwide
• Public incentives to private transportation in Brazil

The Reason I am so Inefficient

[image credit: xkcd ]

Postdoc position, LSE and Oxford - Urbanization in Developing Economies

Prof Henry G Overman (LSE) points out to this great opportunity of a Postdoc position to do research on Urbanization in Developing Economies in a joint programme between Serc/LSE and the University of Oxford.

A major joint research programme on urbanisation in developing economies, with particular reference to Africa, has been launched at Oxford's Department of Economics and LSE's Spatial Economics Research Centre with support from the World Bank. Professors Tony Venables, Paul Collier (Oxford) and Vernon Henderson (LSE) are seeking to recruit up to two postdoctoral research economists. This will involve conceptual and econometric work on the overall urbanisation process in developing countries and on the internal development of cities, in particular large African cities. There will be intensive use of satellite data (to classify land use), night lights data, demographic census data, DHS data, survey data, mapping and planning data. The programme offers outstanding opportunities to contribute to cutting edge research in the field, based in two of Europe's leading social science research and training institutions.

What is the city, according to Shakespeare

[via Shoot The Shit]

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Assorted Links

1. Using cellphonedata to map population mobility in the Ebola epidemic 
   
   
2. A race between the world's fastest elevators
   
   
3. A waterfall flowing in the `wrong` direction
   
   
4. Is low fertility really a problem? Population aging, dependency, and consumption. (via Bernardo Queiroz)
   
   
5. Chinese ghost cities: between 2008 and 2012, the total urban area of cities in China expanded by 9,700km, which is the equivalent of 50 cities the size of Wenzhou (via PD Smith)
   
   
6. How to code a cat (nerd alert)
   
   
7. 8,000 glowing balloons trace the Berlin Wall to mark 25 years since its fall (via Gabriella Nunes)

[image credit: kulturprojekte berlin_2014 WEW FU berlin IGB]

Top 10 most populous cities in 2014 and 2030

[image credit: Thompson Reuters, via Pedro Damiao]

Public incentives to private transportation in Brazil

Brazil fact of the day:

The amount of governmental subsidies to private transportation in Brazil totaled R$ 19.38 billion in 2013. This figure is larger than all transport investments for the World Cup (R$ 14.38 billion) and it is almost twice the investments made in public transport in the whole country in the same year (R$ 10.2 billion).

This is from a nice piece published yesterday by Cassia Almeida and her team in O Globo, one the the biggest Brazilian newspapers . You may read the story [in Portuguese] here.

Urban Picture

Great picture by Chris Hadfield (NASA) showing the bright lights of Cairo and hundreds of smaller cities along the Nile river. The lights on the northeast show of Gaza, Tel-Aviv and Jerusalem.

[click on the image to enlarge it]

[image credit: Chris Hadfield/NASA via Leo Mirani]