Ontario Lidar Point Cloud With Classification Codes

Ontario's classified point cloud contains elevation and intensity information from airborne topographic lidar sensors. Data is structured into non-overlapping 1 km by 1 km tiles in LAZ format, compiled from multiple acquisition projects. The Government of Ontario maintains this dataset, which was last updated in March 2026.

Use Cases

• Classify ground points from unclassified lidar returns to generate bare earth terrain models.
• Identify water bodies using the water classification code for hydrological mapping and flood risk assessment.
• Filter out high noise and low noise points to improve the accuracy of digital surface models for urban planning.
• Analyze elevation and intensity features across 1 km tiles for regional environmental change detection.

Strengths

• Data is structured into standardized 1 km by 1 km tiles for systematic analysis.
• Points are classified into specific categories including ground, water, and noise for targeted use.

Limitations

• Specifications, accuracy, and sensor parameters vary across the compilation of multiple acquisition projects.
• The dataset's total point count, spatial completeness, and temporal range are not specified.

Provenance

Source

Government of Ontario.

Collection Method

Derived from returns collected by airborne topographic lidar sensors.

Freshness

Last updated March 2026.

Geography

Ontario, Canada.