A project that uses many tools that are taught at the D-Lab, and on which I’m excited to be working with students, focuses on exploring the city of Oakland, CA through spatial data.


Why do I find this interesting?

One project that I’ve been working on with a student (CS major, ERG minor) is the exploration of environmental justice and transportation in the City of Oakland, CA.

It’s really cool to get to know our neighboring city by exploring the multiple data sets available, and then being able to walk through those spots that you’ve seen in your computer, and attest to some of the uncovered insights throughout your project-exploration process. 


The project

In my last blog post I wrote about a cool data set that we’re using related to air quality in Oakland, the Google Air Quality data. Through Working with data to explore Transportation and Society: Part 2, the latest round of work, we’ve been able to match that data with socio-demographic variables, and California’s CalEnviroScreen screening tool (though adapting the index to focus mostly on transportation-related variables). This project has leveraged a tool I’ve written about before: SimplyAnalytics, which is a pretty amazing resource that everyone should check out. 

This effort is allowing us to understand what are some of the characteristic elements of populations that do and do not have access to public transportation. Similarly, it is not clear what attributes do some regions have in terms of their transportation habits and expenditures, which is something we’re quite excited to be learning more about.


Data resources and how the D-Lab can help?

 Although the data in this case has been mostly obtained from open-source databases, we did have to apply to have access to the air quality data set from Google here. As Google’s efforts to expand this line of research grows, the possibility of replicating (and improving!) this type of analysis to other cities is also growing. So do check out their web page.

 Remember that you can alwaysconsult with the staff at the DLab on general data-related issues. The D-Lab also offers workshops on spatial analysis withgeographical information systems (GIS) using tools such as ArcGIS, QGIS, and R, as well as python-based GIS packages (e.g., geopandas).

Moreover, SimplyAnalytics is accessible to the UC Berkeley community if you are on the campus network, but once you’re in, you’ll notice an extraordinary amount of data at high resolution for the entire US.

If you’d like to chat about any of the elements I wrote about above, please reach out to me or any of my colleagues for someconsulting time.


Sergio Castellanos

Sergio is a researcher at the California Institute for Energy & Environment and the Energy and Resources Group, with a background in mechanical engineering (Ph.D.). His research interests are in energy systems modelling, sustainable transportation, energy justice, and analysis of integrated techno-economic models for policy making.