Categories
Planning

Off the Grid… and Back Again?

My article “Off the Grid… and Back Again? The Recent Evolution of American Street Network Planning and Design” has been published by the Journal of the American Planning Association and won the 2020 Stough-Johansson Springer Award for best paper. It identifies recent nationwide trends in American street network design, measuring how urban planners abandoned the grid and embraced sprawl over the 20th century, but since 2000 these trends have rebounded, shifting back toward historical design patterns. In this post I discuss these findings and visualizations across the US today as well as over time, then discuss my analysis methods.

Map of where street grids exist today across the US, made with OSMnx and Python

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Categories
Academia

Geospatial Tool Building

My new article “The Right Tools for the Job: The Case for Spatial Science Tool-Building” has been published in Transactions in GIS (free PDF). I originally presented this paper as the 8th annual Transactions in GIS plenary address at the AAG annual meeting last year. I argue that tool-building is an essential but poorly incentivized component of academic geography and social science more broadly. To conduct better science, we need to build better tools. Better tools and data models, spearheaded by academics, can help infuse theory into our field’s quantitative work where it is too often lacking. But if we want better tools, we have to build them. It is not ESRI’s job to satisfy all the theoretical needs of the spatial sciences.

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Categories
Data

OSMnx Summer Wrap-Up

OSMnx underwent a major overhaul this summer, with the development of several new features, improvements, and optimizations. This project concluded yesterday with the release of v0.16.0.

This post briefly summarizes what’s changed since the previous mid-summer updates. It covers the new k shortest paths solver, auto-selecting the first polygon when geocoding, better conversion of graph types, and the new geometries module that lets you flexibly download any OSM geospatial objects as a geopandas GeoDataFrame.

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Categories
Tech

Outlook to Google Calendar Sync

Ah, the travails of academia. Like many universities, USC uses Microsoft Outlook as its email and calendar provider. This presents some integration challenges for those of us, like me, who use Google Calendar everywhere else in life. It’s effectively impossible to sync an Outlook Calendar with a Google Calendar, so I had to juggle between both when trying to schedule anything. Chaos ensues.

So, I created a script to perform an ongoing one-way sync from my USC Microsoft Office 365 Outlook calendar to my personal Google calendar, handling new, updated, and deleted events. I had to develop my own solution because Microsoft/Google inexplicably can’t get their own acts together. For example, you can publish your Outlook calendar’s ICS URL and add it to Google, but it only syncs roughly once per day so you miss any new appointments in the meantime. Microsoft Flow used to work (clumsily) for syncing, but even their official recipes are now broken. So I had to roll my own.

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Categories
Data

What’s New With OSMnx, Part 2

This is a follow-up to last month’s post discussing the many new features, improvements, and optimizations made to OSMnx this summer. As this major improvement project now draws to a close, I will summarize what’s new(er) here. Long story short: there are a bunch of new features and everything in the package has been streamlined and optimized to be easier to use, faster, and more memory efficient.

First off, if you haven’t already, read the previous post about new features including topological intersection consolidation, automatic max speed imputation and travel time calculation, generalized points-of-interest queries, querying OSM by date, and API streamlining. This post covers new changes since then, including improved visualization and plotting, improved graph simplification, the new geocoder module, and other miscellaneous improvements.

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Categories
Data

What’s New with OSMnx, Part 1

There have been some major changes to OSMnx in the past couple months. I’ll review them briefly here, demonstrate some usage examples, then reflect on a couple upcoming improvements on the horizon. First, what’s new:

  • new consolidate_intersections function with topological option
  • new speed module to impute missing street speeds and calculate travel times for all edges
  • generalized POIs module to query with a flexible tags dict
  • you can now query OSM by date
  • you can now save graph as a geopackage file
  • clean up and streamline the OSMnx API
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Categories
Data

New Article on Computational Notebooks

I have a new article out in Region: Journal of the European Regional Science Association, “Urban Street Network Analysis in a Computational Notebook.” It reflects on the use of Jupyter notebooks in applied data science research, pedagogy, and practice, and it uses the OSMnx examples repository as an example.

From the abstract:

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively conduct analytics and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download urban data and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks help introduce methods to new users and help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.

For more, check out the article.

Categories
Academia

AnyConnect VPN on Linux

I run Linux on my school computer, which I brought home to get work done during the stay-at-home order. But when I tried to set up a VPN connection, I was surprised to discover that USC IT didn’t seem to provide a Linux client for Cisco AnyConnect. When I contacted them to ask how to connect, I was informed that “at this time IT doesn’t support Linux.” Shrug emoji.

Fortunately I do support Linux, so if anyone else wants to connect to the USC AnyConnect VPN, here’s how. You could roll your own solution using OpenConnect and a vpnc-script, but that’s complicated. Instead, you can download a current Linux client for Cisco AnyConnect here (you’re welcome). Install it and run it.

You want to connect to sslvpn.usc.edu (the normal vpn.usc.edu server does not work here). To log in, enter your normal USC username and password. For “second password” open your Duo Security app, generate a two-factor code, and enter it here. And ta-da, you’re in.

Linux Cisco AnyConnect VPN client

Categories
Planning

Rental Housing Spot Markets

My new article, “Rental Housing Spot Markets: How Online Information Exchanges Can Supplement Transacted-Rents Data,” with Jake Wegmann and Junfeng Jiao is now published in the Journal of Planning Education and Research (download free PDF).

How much does it cost to rent a typical apartment in your city? Answering this basic housing question can be surprisingly difficult. Consider the case of San Francisco in early 2018.

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Categories
Urban

Housing Search in the Age of Big Data

My article “Housing Search in the Age of Big Data: Smarter Cities or the Same Old Blind Spots?” with Max Besbris, Ariela Schachter, and John Kuk is now published in Housing Policy Debate. We look at the quantity and quality of information in online housing listings and find that they are much higher in White and non-poor neighborhoods than they are in poor, Black, or Latino neighborhoods. Listings in White neighborhoods include more descriptive text and focus on unit and neighborhood amenities, while listings in Black neighborhoods focus more on applicant (dis)qualifications. We discuss what this means for housing markets, filter bubbles, residential sorting and segregation, and housing policy. You can download a free PDF.

Housing search technologies are changing and, as a result, so are housing search behaviors. The most recent American Housing Survey revealed that, for the first time, more urban renters found their current homes through online technology platforms than any other information channel. These technology platforms collect and disseminate user-generated content and construct a virtual agora for users to share information with one another. Because they can provide real-time data about various urban phenomena, housing technology platforms are a key component of the smart cities paradigm.

This paradigm promotes information technology as both a technocratic mode of monitoring cities and a utopian mode of improving urban life through big data. In this context, “big data” typically refers to massive streams of user-generated content resulting from millions or billions of decentralized human actions. Data exhaust from Craigslist and other housing technology platforms offers a good example: optimistically, large corpora of rental listings could provide housing researchers and practitioners with actionable insights for policymaking while also equalizing access to information for otherwise disadvantaged homeseekers. But how good are these platforms at resolving the types of problems that already plague old-fashioned, non-big data? Does this broadcasting of information reduce longstanding geographic and demographic inequalities or do established patterns of segmentation and sorting remain?

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