4,873 research outputs found
Urban Street Network Analysis in a Computational Notebook
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
A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood
OpenStreetMap offers a valuable source of worldwide geospatial data useful to
urban researchers. This study uses the OSMnx software to automatically download
and analyze 27,000 US street networks from OpenStreetMap at metropolitan,
municipal, and neighborhood scales - namely, every US city and town, census
urbanized area, and Zillow-defined neighborhood. It presents empirical findings
on US urban form and street network characteristics, emphasizing measures
relevant to graph theory, transportation, urban design, and morphology such as
structure, connectedness, density, centrality, and resilience. In the past,
street network data acquisition and processing have been challenging and ad
hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently
conduct street network analysis with extremely large sample sizes, with clearly
defined network definitions and extents for reproducibility, and using
nonplanar, directed graphs. These street networks and measures data have been
shared in a public repository for other researchers to use
Rental Housing Spot Markets: How Online Information Exchanges Can Supplement Transacted-Rents Data
Traditional US rental housing data sources such as the American Community Survey and the American Housing Survey report on the transacted market—what existing renters pay each month. They do not explicitly tell us about the spot market—i.e., the asking rents that current homeseekers must pay to acquire housing—though they are routinely used as a proxy. This study compares governmental data to millions of contemporaneous rental listings and finds that asking rents diverge substantially from these most recent estimates. Conventional housing data understate current market conditions and affordability challenges, especially in cities with tight and expensive rental markets
Housing Search in the Age of Big Data: Smarter Cities or the Same Old Blind Spots?
Housing scholars stress the importance of the information environment in shaping housing search behavior and outcomes. Rental listings have increasingly moved online over the past two decades and, in turn, online platforms like Craigslist are now central to the search process. Do these technology platforms serve as information equalizers or do they reflect traditional information inequalities that correlate with neighborhood sociodemographics? We synthesize and extend analyses of millions of US Craigslist rental listings and find they supply significantly different volumes, quality, and types of information in different communities. Technology platforms have the potential to broaden, diversify, and equalize housing search information, but they rely on landlord behavior and, in turn, likely will not reach this potential without a significant redesign or policy intervention. Smart cities advocates hoping to build better cities through technology must critically interrogate technology platforms and big data for systematic biases
Spatial information and the legibility of urban form: Big data in urban morphology
Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, propose designs, compare alternatives, and engage the public. Classic urban form visualizations – from Giambattista Nolli’s ichnographic maps of Rome to Allan Jacobs’s figure-ground diagrams of city streets – have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives
Planarity and Street Network Representation in Urban Form Analysis
Models of street networks underlie research in urban travel behavior,
accessibility, design patterns, and morphology. These models are commonly
defined as planar, meaning they can be represented in two dimensions without
any underpasses or overpasses. However, real-world urban street networks exist
in three-dimensional space and frequently feature grade separation such as
bridges and tunnels: planar simplifications can be useful but they also impact
the results of real-world street network analysis. This study measures the
nonplanarity of drivable and walkable street networks in the centers of 50
cities worldwide, then examines the variation of nonplanarity across a single
city. It develops two new indicators - the Spatial Planarity Ratio and the Edge
Length Ratio - to measure planarity and describe infrastructure and
urbanization. While some street networks are approximately planar, we
empirically quantify how planar models can inconsistently but drastically
misrepresent intersection density, street lengths, routing, and connectivity
Honolulu Rail Transit: International Lessons from Barcelona in Linking Urban Form, Design, and Transportation
The city of Honolulu, Hawaii is currently planning and developing a new rail
transit system. While Honolulu has supportive density and topography for rail
transit, questions remain about its ability to effectively integrate urban
design and accessibility across the system. Every transit trip begins and ends
with a walking trip from origins and to destinations: transportation planning
must account for pedestrian safety, comfort, and access. Ildefons Cerda's 19th
century utopian plan for Barcelona's Eixample district produced a renowned,
livable urban form. The Eixample, with its well-integrated rail transit, serves
as a model of urban design, land use, transportation planning, and
pedestrian-scaled streets working in synergy to produce accessibility. This
study discusses the urban form of Honolulu and the history and planning of its
new rail transit system. Then it reviews the history of Cerda's plan for the
Eixample and discusses its urban form and performance today. Finally it draws
several lessons from Barcelona's urban design, accessibility, and rail transit
planning and critically discusses their applicability to policy and design in
Honolulu. This discussion is situated within wider debates around livable
cities and social justice as it contributes several form and design lessons to
the livability and accessibility literature while identifying potential
concerns with privatization and displacement
Survey and future trends of efficient cryptographic function implementations on GPGPUs
Many standard cryptographic functions are designed to benefit from hardware specific implementations. As a result, there have been a large number of highly efficient ASIC and FPGA hardware based implementations of standard cryptographic functions. Previously, hardware accelerated devices were only available to a limited set of users. General Purpose Graphic Processing Units (GPGPUs) have become a standard consumer item and have demonstrated orders of magnitude performance improvements for general purpose computation, including cryptographic functions. This paper reviews the current and future trends in GPU technology, and examines its potential impact on current cryptographic practice
- …