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Sounds Like a Better Plan: USA Transportation Noise, Revised and Updated

ArcGIS

The Living Atlas of the World just updated the tiled, hosted image service featuring transportation noise, from the USDOT.

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ILA Evo: Meta’s journey to reimagine fiber optic in-line amplifier sites

Engineering at Meta

Minimizing concrete (avoid cost and time to transport, form, tie rebar, pour, and cure concrete). Because ILAs are unmanned, allow the building to run hotter: e.g., increase temperature set points from typical 22C (72F) to >35C (95F); most optical transport kit is GR-63-CORE NEBS-3 compliant and able to run continuously at 40C (104F).

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Esri at GIS-T: Discover Innovative Solutions for Transportation

ArcGIS

A highly anticipated event for transportation professionals. Read about Esri's presence at the conference.

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Driving into the future of electric transportation

databricks

Rivian chose to modernize its data infrastructure on the Databricks Data Intelligence Platform, giving it the ability to unify all of its data into a common view for downstream analytics and machine learning.

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Unlocking the Power of Geospatial Data for Insights

Snowflake

This example requires you to layer three sets of data: country boundaries, transportation routes and locations (EV chargers in this example), but you could easily substitute the transportation routes and EV charger locations with two other sets of location data in your organization.

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Mapping walkability to LA28 Olympic venues: A transit accessibility analysis using ArcGIS Pro

ArcGIS

To do this, we added the World Transit Stops layer and applied the following SQL query: SQL query on World Transit Stop esri_contributor = 'Metrolink' Or esri_contributor = 'LA Metro' SQL query on World Transit Stops Living Atlas layer to display only Los Angeles public transportation.

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Top 5 GeoSpatial Data Science Project Ideas for Practice

ProjectPro

Transport Demand Modelling If you have ever used Google maps to reach a destination place then this project idea will be easier to understand. In this project, the goal is to use the geospatial information of vehicles on road to estimate the transport demand. You can use the neural network algorithm to evaluate the demand.