What is a DEM, DTM, DSM, or CHM?
Elevation mapping using LiDAR data is quickly becoming the standard for mapping the physical and our built environment. More institutions are placing a greater emphasis on making aerial LiDAR data available to the public in the same way that aerial photography has proliferated in the remote sensing space. This is fantastic news for the geomatics industry. However representing complex LiDAR data sets in a GIS friendly environment can sometimes be a daunting task and it is important for GIS professionals to understand how to effectively use these new tools.
Digital Elevation Models (DEM) in general are not new, nor are they unique to LiDAR collects. Elevation models are often derived from photogrammetric stereoscopy or satellite-based radar platforms. Though the spatial resolution and accuracy allowed by LiDAR collects is often far more precise. Natural Resource Canada’s HRDEM strategy for example relies heavily on previously collected LiDAR.
What are the different types of LiDAR models?
LiDAR DEM (Digital Elevation Model) is any rasterized or TIN surface that represents the elevation points from a given LiDAR point cloud. The elevation values are usually referenced to an orthometric or ellipsoidal height and can reflect any variety of point types. These points may be ground LiDAR returns, rooftops, vegetation, and/or manmade structures.
LiDAR DTM (Digital Terrain Model) is a DEM surface that contains only classified ground or model key points. It is common to see a DTM product referred as a “Bare Earth” DEM, which is simply another term commonly used and is considered an equivalent to a DTM. DTMs are one of the most common and well-known derived products from aerial LiDAR and are common inputs for other LiDAR based analyses such as surface change detection, flood mitigation, flood delineation, contour mapping, mineral exploration, and asset management.
LiDAR DSM (Digital Surface Model) is similar to a DTM but often encompasses more points than just the bare earth. Other surface feature such as vegetation, buildings and manmade structures are included. Rather than using classified points these might also be created using the first return laser pulses from the point cloud. This type of model closer resembles a photogrammetric elevation product.
What if we want to measure absolute heights of our objects?
This classification of surface raster is known as a CHM (Canopy Height Model). A CHM is useful for determining absolute elevation of features where each cell represents the elevation above ground level (AGL) rather than referencing ellipsoidal or orthometric heights. One way a CHM can be generated is by calculating the difference between the DSM and DTM. This process leaves you with the resulting elevations of features above ground. Another way to visualize a CHM is by referencing all LiDAR points above ground. CHMs have an excised role in forestry management and are particularly useful for cataloging forestry health and metrics.
To learn more about LiDAR derived models, or how Leading Edge Geomatics can design the right mapping solutions for your business, contact us today!
Blog Written by Malcolm Elliot, Project Coordinator at Leading Edge Geomatics.