Canopy Height Model

A Canopy Height Model (CHM) is a raster dataset representing the height of vegetation and other above-ground features relative to the bare earth surface. It is typically computed by subtracting a Digital Terrain Model (DTM, representing the ground surface) from a Digital Surface Model (DSM, representing the top of the canopy and structures): CHM = DSM - DTM. The resulting values represent the actual height of vegetation at each pixel location. Data sources and generationCHMs are most commonly derived from airborne LiDARLiDARLight Detection and Ranging (LiDAR) is a remote sensing technology that measures distances using laser pulses to crea... data, which provides both canopy-top returns (for the DSM) and ground returns penetrating through vegetation gaps (for the DTM). Photogrammetric point clouds from stereo satellite imagerySatellite ImagerySatellite imagery consists of photographs and data captured by Earth observation satellites orbiting the planet. Thes... (e.g., WorldView) and drone-based Structure from Motion can also generate CHMs, though they cannot penetrate dense canopy like LiDAR. NASA's GEDI spaceborne LiDAR mission provides global canopy height samples from the International Space Station. ApplicationsCHMs support forest inventory and timber volume estimation, carbon stock and biomass calculation for climate reporting, individual tree crown detection and species classification, wildlife habitat assessment, urban tree canopy mapping for shade and air quality analysis, and obstacle clearance planning for aviation and telecommunications. Canopy Height Models are a fundamental forestry and ecological data product that quantifies vegetation structure across landscapes. As global LiDAR coverage expands and spaceborne LiDAR missions multiply, CHMs are becoming increasingly important for carbon accounting and forest management at regional to global scales.