“We assume that car use is an incompressible liquid that must be routed somewhere. But it’s more more like a gas that fills whatever space it's given.” Ian Lockwood, HT Taras Grescoe
Structured Procrastination on Cities, Transport Policy, Spatial Analysis, Demography, R
Friday, June 29, 2018
Quote of the Day: induced demand
Thursday, June 28, 2018
8th Anniversary of Urban Demographics Blog!
Just a few days ago, the Urban Demographics blog had its 8th Anniversary. I have reduced the activity in the blog quite a bit over the past year because I moved houses twice (from Oxford to Cambridge the other place, and then from the other place to Brasilia), and also because I've tried to procrastinate less focus on my thesis writing (more news on this soon). Still, this has been a great year, specially because I've had the chance to meet in person a few dozens of people who told me the blog had been actually helpful in pointing out useful study references, data sources etc. Please, feel free to drop me a line with suggestions on how to improve the blog.
Here just a few quick stats that show a summary of the blog over the past year.
- 109 posts, an average of ~2 posts per week
- 37,532 visits, an average of ~104 visits per day (massive drop from the previous year)
- 7,235 followers on Twitter
- 2,959 likes on Facebook
- 416 RSS feed subscribers
The 5 most popular posts:
- How much residential space could you rent with $1,500 in 30 global cities?
- The long-term effect of slavery on inequality today
- Using deep learning and Google Street View to estimate the socioeconomic characteristics of neighborhoods
- Heads up for some useful R packages
- Making a geogif with QGIS
and 10 of my favourite posts:
- Bicycles empower women: evidence from a quasi-experiment in India
- The urban footprint of the largest metropolitan areas of Europe
- Visualizing space-time networks
- Using R to Predict Route Preferences in Bike Sharing
- The health and economic benefits of cycling network expansion in 167 European cities
- Globally consistent estimate of carbon footprints of 189 countries and 13,000 cities
- Why you should always visualize your data
- The creative process lollipop chart
- Political populism and the revenge of the places that don’t matter
- New tool to get population estimates for any user-defined area
Where do readers come from? (164 countries | 4,217 Cities)
- United States (32.9%)
- Brazil (8%)
- United Kingdom (7.4%)
- Canada (3.8%)
- Germany (3.5%)
Thursday, June 21, 2018
On my way to Dar es Salaam
The blog has been quiet lately because I've been trying to finish my PhD thesis I've been saying this for over a year now but here are two quick updates.
The 4th paper of my PhD has been accepted for publication in the Journal of Transport Geography \o/. You can read the pre-print of the study here.
The second update is that I will be in Dar es Salaam next week presenting this paper at a workshop organized by the Volvo Research and Education Foundation (VREF), who also kindly invited me to attend the Mobilize summit organized by ITDP.
I'm very excited to learn about some of the urban development challenges faced by African cities. This will also be a great opportunity to discuss how we can improve research methods to assess the equity impacts of transport policies on people's access to opportunities.
Wednesday, June 13, 2018
Staying away from trouble
When your boss is looking for you to discuss that project report but you just want to finish your PhD thesis. #truestory
image credit: ? via Glaucia Marcondes
Friday, June 8, 2018
Globally consistent estimate of carbon footprints of 189 countries and 13,000 cities
Daniel D Moran et colleagues developed the Global Gridded Model of Carbon Footprints (GGMCF). This model provides a globally consistent and spatially resolved (250m) estimate of carbon footprints in per capita and absolute terms across 189 countries. Their paper got recently accepted for publication (see below) and their data is freely available. Kudos to the team!
Moran, D., Kanemoto, K., Jiborn, M., Wood, R., Többen, J., & Seto, K. (2018). Carbon footprints of 13,000 cities. Environmental Research Letters.
Abstract:
While it is understood that cities generate the majority of carbon emissions, for most cities, towns, and rural areas around the world no carbon footprint (CF) has been estimated. The Gridded Global Model of City Footprints (GGMCF) presented here downscales national CFs into a 250m gridded model using data on population, purchasing power, and existing subnational CF studies from the US, China, EU, and Japan. Studies have shown that CFs are highly concentrated by income, with the top decile of earners driving 30-45% of emissions. Even allowing for significant modeling uncertainties, we find that emissions are similarly concentrated in a small number of cities. The highest emitting 100 urban areas (defined as contiguous population clusters) account for 18% of the global carbon footprint. While many of the cities with the highest footprints are in countries with high carbon footprints, nearly one quarter of the top cities (41 of the top 200) are in countries with relatively low emissions. In these cities population and affluence combine to drive footprints at a scale similar to those of cities in high-income countries. We conclude that concerted action by a limited number of local governments can have a disproportionate impact on global emissions.
credit: Moran et al
Tuesday, June 5, 2018
PolicySpace: agent-based modeling for public policy analysis
I've posted before about the "Humans of Simulated New York", a comprehensive agent-based model (ABM) of city life that is being led by Francis Tseng.
On a similar vein, my colleague from Ipea Bernardo Furtado has been developing the PolicySpace project, an agent-based modelling platform for public policy analysis. According to Furtado:
"PolicySpace is an agent-based model, including families, citizens, residences, businesses, markets, taxes, mobility, and municipalities, that allows “what-if” questions. It is an in silico laboratory, of extremely low relative cost. Yet, it is flexible, adaptable, that anticipates trajectories and, quantitatively, measures horizontal effects across sectors, places and times. The book reviews the literature, explains concepts, and describes the methodology. It details the model, its parameters, and the full process. It validates the proposal and illustrates with applications."
The platform allows for the ex-ante evaluation/simulation of public policy alternatives in a way that takes into account the emergent complexity of the interactions between portions of society and institutions, in space and time. PolicySpace was originally designed for the Brazilian case but it is easily adaptable to other contexts. The code is written in Python, it is open source and the full code is available on Github. The platform is also modular, so it can expanded in a flexible way to gradually incorporate different aspects considered to be relevant for a variety of policy realms. For example, Francis Tseng is further expanding the PolicySpace platform to incorporate public and private urban transportation at fine spatial scale.
Earlier this year, Bernardo published a book where he presents a literature review of ABM and where he introduces, validates and demonstrates applications of PolicySpace. The book PDF is freely available both in English and in Portuguese.
Give Bernardo a shout if you would like to collaborate on the project, use it in your own applications or just give him some feedback. He is co-organizing a special issue on Complexity Science and Public Policy, so some of you might be interested in that as well.
image credit: Francis Tseng and Bernardo Furtado