Canada's Strategic Opportunity: A Sovereign Aerospace Processing Zone
This proposal outlines a Canadian Sovereign Aerospace Processing Zone, with Alberta as the anchor jurisdiction. The concept transforms Alberta into a secure, high-efficiency hub for Earth Observation signal reception, AI-native preprocessing, and interoperable geospatial intelligence generation under sovereign control.
By integrating BigGeo's geospatial architecture into this pipeline, Canada can create a globally competitive capability that transforms raw satellite signals into commercially valuable, AI-ready datasets, while enabling interoperability with real-time terrestrial data from agriculture, infrastructure, logistics, and climate systems.
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by Brent Lane
Alberta as a Global EO Processing Node
Earth Observation Downlink ≠ Internet Dependency
EO satellites transmit directly to regional ground stations - these are bandwidth-constrained edge nodes, not hyperscaler regions. Alberta could serve as a primary ingestion zone, taking in raw EO signals regardless of local fiber limitations.
AI-Native Preprocessing is the New Value Layer
Foundational steps like noise reduction, georeferencing, object tagging, and change detection are compute-intensive and essential before commercial use. This is where the real economic value is created and where Canada can anchor itself in the global EO value chain.
A Closed Sovereign Grid Solves the Fiber Bottleneck
Raw EO signals are processed in a semi-closed, sovereign compute loop. Compressed, enriched outputs can be distributed via CDN partners, regional fiber hubs, BigGeo's sovereign marketplace, or future-forward satellite relays.
Strategic Advantages of Alberta's Location
Regulatory Compliance
Alberta offers a uniquely aligned jurisdiction for compliance with Canadian data residency regulations, Indigenous data sovereignty principles, and GDPR-aligned EO data protection.
ESG Advantages
Local renewable energy access supports green compute objectives for satellite partners and institutional clients, meeting ESG mandates from global EO providers.
Interoperability
BigGeo's geospatial Codex layer enables seamless integration of EO datasets with municipal, industrial, sensor, and geospatial feeds, unlocking applications in agriculture, infrastructure monitoring, resource management, and emergency response.
Addressing Common Rebuttals
More Rebuttals Addressed
Hyperscalers are cheaper
Hyperscalers charge massive egress fees and don't optimize for agentic inference. BigGeo owns the sovereign path from signal to action, skipping the middleman while compressing compute costs and data.
This is just for satellite data
Earth Observation data is the primary input for autonomous systems in agriculture, cities, drones, climate, and logistics. Earth data is the fuel that BigGeo refines into power as a foundation layer.
This isn't generalizable
That's the point. We're mission-specific AI infrastructure built for autonomy, not document summarization. We're not for everything - we're for what's coming as a purpose-built stack.
Final Rebuttals Addressed
Edge AI doesn't need this
All edge agents require spatial context, map data, routes, and regulatory overlays. BigGeo compresses and delivers this at runtime. Even drones need to ask, "Where am I?" We give the answer.
This duplicates what others do
No one combines: sovereign ingest, BigGeo Velocity preprocessing, agentic pipeline compression, onboard expansion, and a resale marketplace. It's not duplication - it's orchestration.
This won't scale
It's already modular and regionally deployable. Each node brings intelligence closer to sensors, agents, and sovereign missions. We scale the brain by growing the network.
Feasibility of Attracting Global EO Providers
EO Providers Already Use Global Third-Party Ground Stations
Most satellite operators don't operate their own ground stations
Edge Preprocessing Is the Next Competitive Frontier
What Canada can offer is AI-native preprocessing
Satellite Operators Are Actively Seeking Green Power
Alberta offers space, land, and modular grid potential
Most satellite operators prioritize reliable signal ingestion, acceptable latency, and regulatory alignment. In this model, location is a function of reliability, power, regulation, and cost - not brand or loyalty. Alberta ticks all these boxes.
Space Alberta: Reinventing Earth Observation
Current EO Flow
Satellite → Signal → Preprocessing → Raster Image → Postprocessing → AI Model Input
Our Approach
Satellite → Signal → Model-Native Representation → Multiple Outputs
Benefits
Faster insights, higher fidelity, multi-modal fusion, lower compute, better interoperability
Most EO infrastructure today treats satellite signals as a step toward imagery - rasterized pixels processed for human interpretation, then laboriously translated back into machine formats for AI analysis. This legacy pipeline is backwards and designed for human consumption, not autonomous reasoning.
Space Alberta: An Intelligence Refinery
From Pixels to Primitives
We don't store images. We store meaning.
From Raster to Representation
Images are just one possible output.
From Fiber to Function
We process locally and distribute lightweight intelligence.
Space Alberta isn't a ground station. It's an intelligence refinery. We create a machine-first spatial layer that renders anything needed - from heatmaps to hazard zones to control signals for agents. Because we operate at the signal layer, we're not constrained by traditional data movement.
Strategic Implications and Outcomes
Precision Agriculture
AI-powered crop monitoring and optimization
Climate Response
Real-time monitoring and prediction systems
Infrastructure
Automated monitoring and maintenance alerts
Disaster Response
Immediate situational awareness and routing
Canada becomes the first nation with a sovereign EO processing zone that isn't just competing on bandwidth - but on how meaning is extracted from orbit. This isn't an image pipeline. It's a spatial intelligence stack, built for the AI economy.
Satellite Data Levels and Intervention Points
Raw Signal (Telemetry/RF)
Raw radio or laser transmission from satellite (bits and waveform, not data). Very hard to access, typically handled by ground stations, defense, or research institutions.
Level 0
Unprocessed instrument data at full resolution. Think: sensor readouts before image creation. Accessible with high-clearance partnerships or open missions.
Level 1
Georeferenced but not yet analyzed imagery (radiometric + geometric corrections done). Public or commercial access possible, depending on provider.
Level 2+
Themed, post-processed products (vegetation index, fire maps, etc.). Widely available.
Feasible Satellite Partnerships
100+
Open Government Missions
Satellites like Sentinel-1/2 and Landsat 8/9 where you can get raw numerical data (radiance, bands, SAR amplitude)
50+
Commercial EO Companies
Providers like Planet, Capella, and ICEYE where you can negotiate access to raw scenes with the right license or contract
20+
CubeSat Partners
Smallsat companies that sometimes allow payload data access through build-your-own sensor partnerships
The most feasible partnerships are with open government missions and commercial EO companies. High-res commercial satellites like Maxar and classified platforms are least feasible as they often don't expose raw data.
BigGeo: The Geospatial Engine for Signal-to-Model Infrastructure
Traditional vs. BigGeo Approach
Traditional EO pipelines prioritize visual rendering over machine usability, requiring massive compute to reverse-engineer meaning from pixels. BigGeo rearchitects the flow from Signal → Model-Native Representation → Multi-Format Output.
Signal-to-Model Pipeline
Instead of preprocessing satellite data into raster images, BigGeo's stack interprets raw signal into structured, geospatially indexed data objects that are machine-readable by default, queryable via spatial SQL or AI APIs, and convertible into multiple formats on demand.
Core Components
BigGeo Codex provides hierarchical, lossless encoding of signal-aligned spatial features. Velocity Engine offers real-time, GPU-accelerated spatial processing. Datalab tracks provenance and access, while BigGeo Functions support complex geospatial operations.
What BigGeo Unlocks for Space Alberta
Space Alberta has a rare window to create sovereign control over the signal → insight pipeline, attract commercial EO providers looking for green, neutral, AI-aligned processing zones, and export not just data, but intelligence-as-infrastructure. BigGeo's architecture turns raw EO signals into a multipurpose geospatial utility layer.
Implementation Roadmap
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1
Ground Station Integration
Partner with CubeSat or EO providers to receive Level 0 signal. This initial phase establishes the physical infrastructure necessary to begin receiving raw satellite data directly in Alberta.
2
Codex Layer Deployment
Begin parsing signals into model-native primitives. This critical step transforms raw data into structured formats optimized for AI processing rather than human visualization.
3
Velocity & Datalab Setup
Process, organize, and route intelligence flows. This infrastructure enables the efficient management and distribution of processed data to various stakeholders and applications.
4
R&D Collaboration
Develop benchmark transformations and cross-sensor pipelines. This research phase refines the system's capabilities and expands its applications across different data types.
5
Marketplace Readiness
Prepare enriched output datasets for resale or licensing. This final phase establishes the commercial framework to monetize the processed intelligence and ensure sustainability.