UrbanFootprint

🎉 Please join us in welcoming our new Technical Project Manager,
Hannah McNeill to UrbanFootprint! 👋 Welcome Hannah! We're excited to have you on the team.

How can we create an equitable future for all? How do we overcome barriers like income and race? How do we identify and address EV charging deserts? Click the link to explore these questions. https://hubs.ly/Q01WkRzr0

Three Keys to an Equitable EV Future | UrbanFootprint Managing equitable EV deployment is complex, but with the right data and insights, planners can make better decisions more quickly.

🌟🎉 Starting the New Year with a Bang! 🎉🌟

We're thrilled to announce that UrbanFootprint has been named to the GovTech 100 list for the FOURTH consecutive year by Government Technology!

Our commitment to driving data insights and innovation across the U.S. has never been stronger. This past year, our data science team rolled out proprietary climate models that connect risk exposure with community and built environment data, covering the entire nation.

We are proud to work with a wide variety of government agencies that leverage the breadth of our data insights and analysis capabilities, as well as leading finance, real estate, and energy companies that rely on UrbanFootprint to analyze risk and prioritize investments.

Thank you to our incredible team and partners who make this possible year after year!

As we step into this new year, expect more innovations aimed at enhancing your experience with UrbanFootprint. Here's to continuous improvement and impact at scale! 🌍💡

🚀Join us on Thursday at AGU23 to see Madeline Jones present UrbanFootprint’s Enhanced Earthquake Hazard Model!

Understanding earthquake hazard on a national scale is critical for businesses, governments, and institutions to be able to proactively manage risks, protect assets, and ensure sustainable development amidst evolving environmental challenges.

📊 The Challenge:
The USGS offers 8 soil-specific earthquake hazard maps, but lacks a consistent nationwide dataset. This forces national-scale analysis to rely on a single map/soil type, potentially compromising accuracy.

🌐 The Solution:
This custom data product combines the USGS data with a CONUS-wide machine learning-derived Vs30 dataset.

🔑 What sets it apart?

🌎 Nationwide coverage - no longer assuming a single site class for all of CONUS
🔬Unprecedented accuracy - no more underreporting earthquake risk
💡Understanding impacts - intersect with parcel-level data for a clear picture of what and who is at risk.

Don't miss this opportunity to stay ahead in earthquake hazard assessment, and better safeguard your assets. Join us at AGU23 or comment 👇 to learn more!