For municipal agencies operating under strict growth boundaries, managing critical right-of-way infrastructure data with a lean team is a constant battle against the clock. The City of Newberg, Oregon was held back by fragmented data, forcing crews to manually spot-check assets and guess which maintenance tasks had actually been completed. This case study reveals how they bypassed a massive logistical bottleneck, using high-resolution street-level imagery and pre-extracted geospatial insights to shift routine assessments from the field to the desktop—all while securing a 2.8x ROI without expanding headcount.
Download the full case study to discover how to:
- Eliminate maintenance blind spots by replacing overlapping vendor timelines with an airtight, objective pavement baseline that removes the guesswork.
- Leverage the power of a digital twin to unlock hidden cross-functional data for tree inventories, alley encroachments, and sidewalk widths from a single week of high-speed collection.
- Automate code compliance workflows using 3D-derived vertical clearances to instantly audit and prioritize tree-trimming routes right from your desk.
- Secure budget transparency by arming committees and managers with clear visual context that grounds high-stakes capital planning decisions.
