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AI-Assisted Alignment and Enhancement of Historical Aerial Imagery

Research & Development · Ecology

What it collects

About a place
Anonymized data
  • Historical aerial photographs from the National Air Photo Library (NAPL), capturing land cover, terrain, and landscape features across Canada at various points in time.
Run by
Natural Resources Canada (NRCan)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

Research & DevelopmentEcology

This system uses artificial intelligence to automatically align, enhance resolution, and add colour to historical aerial photographs from the National Air Photo Library. It makes decades of archival imagery accessible for research and allows scientists and planners to study how landscapes have changed over time. The system is used internally by Government of Canada employees and its outputs are not used to make decisions about individual people.

What it collects and what happens to it

Data taken in

About a place
Anonymized data
  • Historical aerial photographs from the National Air Photo Library (NAPL), capturing land cover, terrain, and landscape features across Canada at various points in time.

Processing

Computer Vision
  • Image matching and control point detection algorithms process scanned aerial photographs to identify corresponding features across images for geometric alignment and mosaicking.

What it does

Sensing (Perceptive AI)
Human executes
  • Reads raw scanned aerial photographs and extracts structured geometric and visual information — detecting control points, matching image features, and preparing inputs for downstream mosaicking and enhancement steps.
Deciding (Analytical AI)
Human executes
  • Scores and ranks candidate control point matches and alignment solutions across image pairs during automatic geo-referencing, producing structured spatial assignments without generating new content.
Creating (Generative AI)
Human executes
  • Creates new visual content through super-resolution upscaling and colourization of greyscale historical photographs — producing image data that did not exist in the original scanned source.

Outputs

About a place
Anonymized data
  • Geo-referenced, super-resolution, and colourized aerial image mosaics representing historical land cover and landscape states across Canada, enabling temporal change analysis.
Generated content
Anonymized data
  • AI-generated colourized and super-resolution versions of originally greyscale or low-resolution historical aerial photographs. These are enhanced representations, not original captures.

Run by

Natural Resources Canada (NRCan)
  • Federal department that developed and operates this AI system to process and provide access to historical aerial photography from the National Air Photo Library.

Government of Canada AI Register — 2526-NRCan-RNCan-007

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Processed imagery outputs are available to Government of Canada employees, the primary users of this system, for internal research and analysis purposes.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Algorithmic TransparencyThis system is listed in the Government of Canada Algorithmic Impact Assessment Registry. Members of the public may consult the registry entry. Note that AI use is not currently disclosed to end-users of the imagery products at the point of use.

Risks and safeguards

  • Societal & cultural harmAI-generated colourization and super-resolution are synthetic enhancements that alter the visual character of historical records. There is a risk that enhanced imagery could be mistaken for authentic historical records or misrepresent actual historical land cover, potentially affecting Indigenous land claims, environmental baselines, or historical scholarship.Safeguard: outputs should be clearly labelled as AI-processed and distinguished from original archival photographs; provenance metadata should accompany all distributed imagery.