I am presenting at the 2015 Conference on Complex Systems tomorrow in Tempe, Arizona. My paper is on methods for assessing the complexity of urban design. If you’re attending the conference, come on by!
Here’s the paper.
Here’s the abstract:
The fall semester begins next week at UC Berkeley. For the third year in a row, Paul Waddell and I will be teaching CP255: Urban Informatics and Visualization, and this is my first year as co-lead instructor.
This masters-level course trains students to analyze urban data, develop indicators, conduct spatial analyses, create data visualizations, and build interactive web maps. To do this, we use the Python programming language, open source analysis and visualization tools, and public data.
This course is designed to provide future city planners with a toolkit of technical skills for quantitative problem solving. We don’t require any prior programming experience – we teach this from the ground up – but we do expect prior knowledge of basic statistics and GIS.
Update, September 2017: I am no longer a Berkeley GSI, but Paul’s class is ongoing. Check out his fantastic teaching materials in his GitHub repo. From my experiences here, I have developed a cycle of course materials, IPython notebooks, and tutorials towards an urban data science course based on Python, available in this GitHub repo.
Hong Kong is a remarkable place. It is the 4th-densest sovereign state or self-governing territory in the world (in 1st place is its neighbor across the delta: Macau). Yet this density is fantastically constrained by the mountains and the sea into narrow, snaking corridors of high-rises wherever the terrain permits. At no time is this unique urban development better seen than at night, when Hong Kong lights up like a carnival.
I took these photos from the top of Victoria Peak on Hong Kong island and from the Tsim Sha Tsui promenade on the Kowloon peninsula, using long exposures of between 3 and 12 seconds.