How vegetation should affect your LiDAR Vs photogrammetry decision

by Measure Australia

The decision of whether to capture LiDAR point cloud or photogrammetry will be based on a few factors as discussed before. We’ll dive into one aspect here, which relates to vegetation and how vegetation should affect the platform decision.

As a recap, photogrammetry interprets 2D raster images to provide reliable information about physical objects such as dimensions, volume and position.

LiDAR uses millions of individual geo-tagged laser returns to generate a point cloud of the area being scanned, with GPS aligned points. Those millions of location-known laser points combine to form a 3D map.

Photogrammetric techniques will be used to find, for example, a tree’s height and width from photos. Professional platforms and experienced technicians can deliver quite accurate results with these techniques. A ground map can similarly be inferred, in a process that is closer to artform than science. The photogrammetric source files contain no direct information of the obscured ground.

Fun story – our technicians competed to see who could get the most accurate pole height from the same source images. They were all impressive, and the prize went to the technician 2 mm out on a 3425mm pole, which is accuracy of 0.058%!
This was insanely awesome, and they insist it was 100% skill.

LiDAR will get point returns from the tree, leaves and so on to make an accurate model of the outside of the tree – but it will also, if captured by a decent pilot, capture points around, through and under the canopy. Quality processing will tag the trees, shrubs and other vegetation. With this processed LiDAR map, users will be able to toggle viewing a map with or without vegetation.


Example: stripping vegetation from assets under management

The following example is from a Measure Australia project focusing on the linear asset - the power lines, poles and associated infrastructure - in a suburban environment. 


mcapture deliv07
LiDAR - view from above of mapped area


Region with all elements including vegetation
LiDAR - view of a focal portion of the mapped area, including tagged vegetation, linear asset power lines and surface


LiDAR - mapped area stripped of vegetation
LiDAR - mapped area digitally stripped of vegetation, structures, etc, to show powerlines and surface


LiDAR - mapped area stripped of linear asset power lines, to show DSM digital surface model
LiDAR - mapped area stripped of vegetation, structures, power lines, and all other elements to show surface only


Where very dense vegetation exists technicians may have only a few ground points per square metre – but frankly, this is more points than ground surveyors use, and reasonable ground models can be extrapolated. Compared to photogrammetry it will be significantly more based in fact.


Blog - point cloud - close up of foliage
Blog - point cloud - close up of foliage


Where accurate ground mapping is required, such as for building or mine stripping, LiDAR is generally indicated. Photogrammetry may suffice if there’s little or no ground vegetation – but it will still be less accurate. This depends on the circumstances and projected map use. And if your data capture operator only offers photogrammetry, please do consult with an operator that offers both LiDAR and photogrammetry before you make that decision!

There’s a less common use for tagged LiDAR vegetation point clouds, being the study of the vegetation as opposed to the more common removal of vegetation so that the surface or terrain can be more clearly viewed. The extraction of vegetation point sets from the LiDAR cloud enables this as much as it enables the converse – the accuracy of these analyses will be determined by the aptitude of the original LiDAR capture and the specificity and precision of LiDAR processing. A paper referenced in this post discusses that Chinese researchers proposed that ‘tridimensional green biomass’ be used to monitor urban greening. Tridimensional green biomass was described as the ‘living vegetation volume’ LVV which is either the tree crown volume or the volume of the branches. The approach apparently gained traction in China and despite calls for additional research determined that LiDAR was a more accurate and superior than previous methods. The original research is referenced below, for those wishing to explore further.

Questions to ask:
  1. What is the expected use of the map?

  2. How dense is the vegetation?

  3. Does the vegetation create an opaque level or canopy, or will LiDAR gain some coverage to the ground?

  4. What is the budget?

These questions will enable a credible data collection expert to advise the most appropriate method for the project.