Cubic Transportation Systems’ Post

Topic : city scan

George Mason statistics professor Abolfazl Safikhani applies machine learning tools to predict land use and real estate pricing—potentially disrupting urban planning and real estate. https://lnkd.in/ejteRQfr #UrbanPlanning #RealEstateTech #MachineLearning #DataScience #PredictiveAnalytics #PropertyPrices #DataDrivenDecisions #RealEstateTrends #UrbanDevelopment #StatisticalModeling

📢#CallforPapers 👏A New Special Issue is launched: "Big Data in Urban Land Use Planning" ✍️edited by Prof. Dr. Thomas W. Sanchez and Dr. Soheil Sabri Texas A&M University University of Central Florida 📖Read more at: https://lnkd.in/gpCEtEaj #AI #bigdata #urban #land #Planning

Thanks for the guidance and support from my advisor Andres Sevtsuk. In this review work, we carefully extracted 100+ street attributes that have been proposed through a bunch of urban studies driven by computer vision. For urban design researchers, this paper provides a general overview of how this field is going on with an itemized list. Also, after this review, I am more aware that there are still many gaps between fresh techniques and domain knowledge. It is truly a long journey for me to explore this field. : )

If you're a public transit and/or geospatial data buff, don't miss Milan Janosov, Ph.D.'s latest guide, which explores public transport systems relying on the General Transit Feed Specification.

It’s #WorldTownPlanningDay! Are you interested in the art of town planning in today’s digital era? Take the #TsinghuaOpenCourse “Big Data and City Planning” and learn about the research methods of data technology and application in urban systems and planning designs.

Tomorrow, 6:00pm. Join us for a lecture from Urban Spatial Analytics by Esteban Lopez Ochoa titled “Leveling the Field: Combining Proprietary Micro-Level Data with Machine Learning Methods for Housing Justice Research.” Ochoa, who teaches at the at the University of Texas at San Antonio, will discuss “how property-level gentrification index and code-enforcement bias assessment are two examples of leveraging these new data sources with machine learning and artificial intelligence techniques to level the playing field in data-driven equity advocacy in urban issues.” https://lnkd.in/g7CjPujE

We need to rethink a lot of the institutions in our society and economy, the nation-state being key to that. This graphic by Dark Matter Labs and Indy Johar presents a different view, "seeing the nation as an entangled, interdependent system of flows" Graphic from this article "A New Way Forward: Creating a Framework for Human, Machine and Ecological Transition at a National Scale" https://lnkd.in/ehrd4pUy

Helping identify who benefits from transportation investments is one area where models can help communities and states advance transportation justice. Alta’s Civic Analytics team worked alongside Replica and HEAVY.AI to enrich the National Bridge Database, managed by the Federal Highway Administration (FHWA), with a national catchment vulnerability analysis looking to understand which major bridges in the US are used by low-income travelers. This data was used to create a national critical index for thousands of bridges across the US, where the importance of a bridge to the surrounding community is reflected by more than just the total number of vehicles that use it. https://lnkd.in/grcEEcJc

Did you know that the US has a National Bridge Database that rates the condition of major bridges across the country? I bet you didn't know that "Bridges rated in Poor condition have on average roughly twice as many walking and biking trips as bridges rated in Good condition." This is one of the findings from an analysis completed by my team (Alta's Civic Analytics team) in partnership with Replica and HEAVY.AI. Check out the post below to see more analysis findings and access the interactive dashboard to explore the findings yourself. If you find any surprises during your exploration, I'd be very interested to hear about them!