Insights

Federal agencies sit on some of the world’s most powerful data assets: massive collections of satellite imagery, airborne surveys, and dense lidar point clouds. Yet a persistent bottleneck stands between this data and the critical missions it is meant to support.

Before a research or defense team can train a machine learning (ML) model or process a massive imagery archive, they must obtain a secure cloud environment that meets strict agency compliance guidelines. Depending on existing infrastructure and approvals, this administrative hurdle can delay critical projects by weeks — or even months.

To solve this challenge, Woolpert Digital Innovations and Mile Two have joined forces. By pairing Woolpert’s deep geospatial data science and Google Cloud expertise with Mile Two’s automated CloudLab provisioning platform, we are helping federal agencies bypass the bottleneck and deploy compliant geospatial AI in minutes.

The Compliance Hurdle: Securing Cloud Resources Without the Wait

Providing high-compute cloud resources — especially Graphics Processing Units (GPUs) for heavy AI/ML training and distributed storage for vast imagery archives — is a massive undertaking for federal IT teams. Administrators must configure cloud projects, manage granular user access, and strictly enforce security controls to meet:

• Department of Defense (DoD) Impact Levels (IL2, IL4, IL5)
• FedRAMP high authorizations
• CMMC obligations

Mile Two’s CloudLab automates this heavy lifting. Operating within established, governed frameworks, CloudLab allows authorized users to self-provision secure Google Cloud resources with approved policies pre-applied.

Proven in the Field: Deployed at the Air Force Research Laboratory, CloudLab has enabled researchers to provision approved computing environments, complete with GPUs, in minutes instead of months.

Intelligence at Scale: Woolpert’s Geospatial and AI Toolkit

Once CloudLab establishes the secure environment, analysts can immediately leverage Woolpert’s advanced geospatial workflows. Key capabilities include:

• Google Earth Engine at Scale: Seamlessly analyzing satellite archives (like Sentinel and PlanetScope) to detect geographic changes over time — essential for flood damage assessments or environmental monitoring.
• 3D Lidar and ML: Classifying complex three-dimensional point clouds. Woolpert utilizes advanced model architectures (such as Pointcept and Superpoint Transformers) for semantic segmentation to automatically identify buildings, vegetation, and ground terrain.
• Efficient Point Cloud Handling: Implementing tools like Entwine Point Tiles to stream and analyze specific geographic sections of massive lidar datasets without needing to download or process the entire collection.
• Gemini Enterprise Agent Platform: Utilizing Google Cloud’s premier AI platform to rapidly build, train, and deploy mission-ready models.

Tactical Scenario: Post-Flood Disaster Response

To see this partnership in action, consider a DoD data science team tasked with assessing infrastructure damage at a major military installation following severe flooding:

1. Minutes to Access: The team requests a secure Google Cloud environment via CloudLab, immediately gaining access to a compliant, high-compute sandbox.
2. Rapid Change Detection: Analysts run Google Earth Engine workflows to compare pre- and post-flood imagery, isolating corridors with high water pooling.
3. Targeted 3D Analysis: The team pulls high-resolution lidar data for those specific corridors using Entwine Point Tiles. Woolpert’s classified ML models segment the terrain, flagging collapsed structures and blocked supply routes.
4. Secure Scaling: If the analysis transitions from unclassified training to sensitive mission data, the workflow seamlessly moves from an IL2 environment to an authorized IL4 or IL5 environment.

The Bottom Line: Repeatable, Reusable Efficiency

Federal agencies shouldn’t have to reinvent the wheel for every project. By standardizing cloud provisioning, IT administrators save valuable time, security posture is tightly maintained, and research teams can focus entirely on generating insights.

Furthermore, the data workflows and ML models developed for one mission — be it installation monitoring, wildfire tracking, or coastal erosion — can be easily adapted and reused, driving down costs and preparation times across the entire agency.

Key Takeaway: If your agency’s geospatial AI initiatives are stalled by infrastructure delay, it’s time to transition to automated, compliant cloud provisioning. Start with a focused pilot program to measure how rapidly your team can go from raw satellite data to actionable mission intelligence.

Let’s Accelerate Your Mission

Ready to put secure, compliant geospatial AI into the hands of your researchers? Contact the Woolpert Digital Innovations and Mile Two teams today to request a joint consultation and discover how CloudLab can transform your agency’s workflows.

• Mile Two: email [email protected] or call (937) 262-7213
• Woolpert Digital Innovations: email [email protected]