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Transport Poverty and Accessibility Workshop, organized by the the European Commission Joint Research Centre (JRC.C6 Transport Networks team) The workshop will also be streamed live for all online participants Dates: 10-11 June 2026 Registration: joint-research-centre.ec.europa.eu/events/trans...
Transport Poverty and Accessibility Workshop, organized by the the European Commission Joint Research Centre (JRC.C6 Transport Networks team) The workshop will also be streamed live for all online participants Dates: 10-11 June 2026 Registration: joint-research-centre.ec.europa.eu/events/trans...
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Rafael H. M. Pereira 🚡 Urban Demographics
Rafael H. M. Pereira 🚡 Urban Demographics
Table with all the data sets available here github.com/ipeaGIT/geob...
1mo
We've built a #targets pipeline in #rstats to generate all data sets of #geobr v2.0.0. It's almost ready. It looks beautiful, doesn't it ? Install the dev version of geobr 📦v2.0.0 in R github.com/ipeaGIT/geobr Full pipepline Vs Only the targets
Great dashboard implementation our methodology from @cep-lse.bsky.social @bsoeberlin.bsky.social research to illustrate microgeographic property prices and rents in Germany by @tagesspiegel.de. Try clicking on your postcode. 😀 interaktiv.tagesspiegel.de/lab/der-inte...
1mo
3d
github.com
Easy access to official spatial data sets of Brazil in R and Python - ipeaGIT/geobr
GitHub - ipeaGIT/geobr: Easy access to official spatial data sets of Brazil in R and Python
Rafael H. M. Pereira 🚡 Urban Demographics
Rafael H. M. Pereira 🚡 Urban Demographics
Chuffed to give one of the keynote presentations at the fantastic two-day Transport Poverty and Accessibility Workshop organised by the Joint Research Centre of the European Commission today. I will talk about how people map transport poverty in space in practice (abstract below)
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» arrow-extendr « now supports geoarrow 🌏 Use geoarrow types from anywhere in your 🦀 Rust-powered R packages 🐇📦 👈🏼 Centroid using geoarrow + extendr 👉🏼 called from R compared to {sf} #rust #rstats
Gabriel M Ahlfeldt
STREET: Simulation Transport for Realistic Engineering Education and Training STREET, short for Simulating Transportation for Realistic Engineering Education and Training, is a set of web-based simulation modules built to improve teaching in undergraduate units that cover travel demand modelling,…
In Boston for @netsciconf.bsky.social. See you on Friday 11:15 for session PS 3.6 Mobility, Spatial & Urban Networks 3 The urban impact of algorithmic navigation D. Pedreschi lnkd.in/dAG-v4PF The urban impact of AI: modelling feedback loops in location-based recsys L. Pappalardo lnkd.in/dR4JjCCQ
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STREET, short for Simulating Transportation for Realistic Engineering Education and Training, is a set of web-based simulation modules built to improve teaching in undergraduate units that cover travel demand modelling, geometric design, traffic flow, and traffic signal control. This project was originally funded by NSF and hosted at the University of Minnesota, but had been taken down in a website reorganisation.
transportist.org
STREET: Simulation Transport for Realistic Engineering Education and Training
Luca Pappalardo
Giulio Mattioli
Josiah
Access door-to-door: An intercity efficiency and distributional analysis of the costs of travel by plane, train, and automobile
1mo
dlvr.it
Recently published: * Yu L., Li, M., Dai, Z., Cui, M., and Levinson, D. (2026) Access door-to-door: An intercity efficiency and distributional analysis of the costs of travel by plane, train, and automobile. Transport Policy. Volume 184, August 2026, 104188 [doi] Existing studies typically evaluate air travel accessibility by examining either air network performance or ground access to airports in isolation. This paper offers a complementary perspective by assessing the national air travel accessibility through a door-to-door framework and comparing it against multiple modes of intercity transport. We compare four scenarios: air-only, railway-only, highway-only, and an optimal-mode scenario. The first three rely exclusively on a single mode for intercity trips, whereas the optimal-mode scenario selects the lowest-cost option among air, rail, and direct driving for each origin–destination pair. The results show that air travel provides higher accessibility and more balanced spatial equity than rail or highway travel at higher cost thresholds. Air travel also delivers clear advantages in regions with significant geographical constraints, where land-based transport infrastructure is limited. Although the optimal-mode scenario generally enhances spatial equity, it reduces within-group equity in regions characterized either by highly developed urban cores (e.g., the Yangtze River Delta in East China) or by significant geographic constraints (e.g., the peninsula areas of Northeast China). Figure 9: Difference in accessibility among three scenarios (air-only, railway-only, and highway-only) based on the cost-weighted accessibility metrics.
Access door-to-door: An intercity efficiency and distributional analysis of the costs of travel by plane, train, and automobile
David M Levinson ⁂
David M Levinson ⁂