Ontario Classified Elevation Point Cloud from Aerial Imagery

Imagery-derived point clouds classify elevation data into categories like ground and low noise. The data is organized into non-overlapping 1 km by 1 km tiles in a compressed format. The Government of Ontario maintains this dataset, with a last recorded update in March 2026.

Use Cases

• Generate bare earth terrain models by filtering for the 'ground' classification code.
• Identify and filter sensor noise or artifacts using the 'low noise' classification label.
• Perform regional land cover analysis by aggregating classification codes across 1 km tiles.
• Create derivative raster products like Digital Elevation Models from the classified point data.

Strengths

• Data is classified into specific categories: unclassified, ground, and low noise.
• Spatial organization into standardized 1 km by 1 km tiles simplifies processing.

Limitations

• The total spatial coverage and point density per tile are unspecified.
• Classification scheme is limited to three codes, lacking detailed land cover categories.

Provenance

Source

Government of Ontario.

Collection Method

Derived from aerial photography.

Time Range

null

Freshness

Last updated March 2026.

Geography

Ontario, Canada.