In the absence of topography data, DEM is often used in fields like landslide hazard mapping and flood risk assessment. For the first time, our paper with @KalambayTweets provides evidence of its effective use in traffic safety assessment in the mountains.
Excited to share our research just published online in @HeliyonJournal.
I analyzed the factors responsible for non-motorists’ safety perception of autonomous vehicles while adjusting for individual differences. #R#Transportation#AutonomousVehicles
https://t.co/4SfOn3S1eO
🚨🚨🚨New Article Published🚨🚨🚨
If you are interested to know why would drivers state that they did not see peds/bikers before a crash, this is the article to read. Special thanks to my co-authors. #Researchpaper#safety#pedestrians. Full paper https://t.co/1JXyYQe0K8
Congratulations to Diniece Mendes - the first black woman elected to the T&DI Board of Governors! Diniece will begin serving on the Board on Oct 1 and will be T&DI President for FY2026. We know she'll do an amazing job!
https://t.co/rUZmrtX9Tz
#Hacked messages, especially like we just witnessed in #Brookeville, pose major #safety threats to drivers and work crews along roads.
Thank you @JoshRosenthalTV for bringing attention to this issue and inviting me to sit down to talk to you.
@GMU_COS
https://t.co/N3mfIvbJqZ
Wear a helmet or not wear a helmet? 🚲
To answer this question we examined meta studies, lab based research & key methodological papers and here is what we found: 🧵
- helmet while cycling is beneficial (...)
via @SciReports
https://t.co/iHuK32TJIv
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segment-geospatial v0.3.0 is out - segmenting satellite imagery with the Segment Anything Model (SAM).
GitHub: https://t.co/KUOhmJz8hs
Docs: https://t.co/UbkLx9c2l0
Notebook: https://t.co/yWLhWxzT2M
#segmentanything#deeplearning#geopython#geospatial
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Introducing segment-geospatial, A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
GitHub: https://t.co/KUOhmJyArU
Docs: https://t.co/UbkLx9buvs
Notebook: https://t.co/yWLhWxzlde
#segmentanything#deeplearning#geopython
@SciReports – both groups of workers in the sample have a higher probability to cycle more (opportunity to increase commute trips)
– environmentally friendly people and those committed to reducing their CO2 emissions have a higher probability to also cycle more