Ontario Lidar-Derived Digital Surface Model for Land Feature Analysis

Lidar-derived raster data provides the first reflective surface, including treetops, rooftops, and ground features. The dataset is organized into 1 km by 1 km non-overlapping tiles compiled from multiple acquisition projects. It is produced by the Government of Ontario and was last updated in March 2026.

Use Cases

• Model urban canopy height and coverage by analyzing the first reflective surface values representing treetops.
• Assess building footprint and rooftop characteristics for solar potential analysis using DSM values.
• Identify and map artificial structures like telephone poles and towers from elevated surface features.
• Analyze terrain and ground surface elevation in areas with sparse vegetative cover.
• Support flood risk modeling by integrating ground surface data from the DSM with other hydrological layers.

Strengths

• Data is compiled from multiple lidar acquisition projects, providing broad coverage.
• Raster tiles are provided in a standardized 1 km by 1 km format for systematic analysis.

Limitations

• Specifications, parameters, and sensors vary between the source lidar projects, leading to potential inconsistencies.
• The dataset's exact spatial and temporal coverage is not specified, limiting reproducibility for specific areas or times.

Provenance

Source

Government of Ontario

Collection Method

Derived from classified lidar point clouds from multiple acquisition projects.

Freshness

Last updated in March 2026, indicating active maintenance.

Geography

Province of Ontario, Canada.