Canopy Height Model

An example of an object-based approach to generating Canopy Height Models (CHM). The object based approach to CHM generation has advantages over traditional raster CHMs based on LiDAR alone, particularly when leaf-of LiDAR are used. Using a data-fusion object-based approach to land cover mapping leaf-on imagery (A) and leaf-off LiDAR (B) were used to map tree canopy (C). This process overcomes the limitations inherent in the imagery (no clear spectral signature for trees) and the LiDAR (leaf-off returns resulting in tree canopy gaps) to create a highly accurate tree canopy map. The LiDAR (B) and tree canopy (C) are then fed into a second object-based system that creates polygons approximating tree crowns and returns the max (D) and average (E) canopy height using only those LiDAR returns that are actually trees. The result is a vector polygon database that can be easily queried and merged with other vector datasets for subsequent analysis.