OSMnx is a Python package for downloading administrative boundary shapes and street networks from OpenStreetMap. It allows you to easily construct, project, visualize, and analyze complex street networks in Python with NetworkX. You can get a city’s or neighborhood’s walking, driving, or biking network with a single line of Python code. Then you can simply visualize cul-de-sacs or one-way streets, plot shortest-path routes, or calculate stats like intersection density, average node connectivity, or betweenness centrality. You can download/cite the paper here.
In a single line of code, OSMnx lets you download, construct, and visualize the street network for, say, Modena Italy:
import osmnx as ox
Continue reading OSMnx: Python for Street Networks
The Department of City and Regional Planning at UC Berkeley has a rather arduous process for advancing to candidacy in the PhD program. It essentially consists of 6 parts:
- Take all the required courses
- Produce an inside field statement – a sort of literature review and synthesis explaining the niche within urban planning in which you will be positioning your dissertation research
- Complete an outside field – sort of like what a minor was in college
- Take an inside field written exam
- Produce a defensible dissertation prospectus
- Take an oral comprehensive exam covering your inside field, your outside field, general planning theory and history, and finally presenting your prospectus.
Whew. Lots to do this year. The good news is I am currently wrapping up my inside field statement and preparing to take the inside field exam. My topic is generally around complexity theory in urban planning. Here is the working abstract from my statement:
Continue reading Urban Complexity and the March Toward Qualifying Exams