In this article, I will attempt to give an overview of how we combine Drone and LiDAR survey data, via point clouds and other means. Everyone has a different method of doing this, depending on the software at their disposal, but this is the process that works best for us.
Why combine the data?
There are a number of reasons a project requires a combination of Drone and LiDAR point cloud data. In our case, we use a terrestrial LiDAR unit along with aerial photogrammetry. Sometimes, the shape and height of an object means we cannot get the LiDAR device to scan the top of the target. In other cases, the area is too large to simply survey with a terrestrial LiDAR unit.
An example project is a recent project to scan an old farm and it’s surrounding landscape. The farm was in disrepair and needed internal and external surveying. As it was built on a glacial drumlin, the surrounding area also needed to be included. Our method was to survey the buildings with the terrestrial LiDAR scanner and then combine this with a point cloud created from an aerial survey.
This point cloud would then be used as a guide to draw a detailed Autocad Revit model including the topography and buildings.
Drawbacks of this method
The main drawback of this method is that we are combining two datasets with differing point cloud densities. The terrestrial LiDAR survey has a point cloud density in the thousands per square meter, whereas the drone photogrammetric survey has a density of nearer the hundreds. This is not generally a problem if we understand that the two methods have different uses.
It is also tough aligning two point clouds created with different hardware and algorithms. This is where accurate GNSS survey data becomes essential.
The importance of GPS and Control Points.
The importance of using accurate GPS co-ordinates and ground control points / targets cannot be understated here. If you have a wide range of effectively placed targets that are visible in both the drone survey and the LiDAR point cloud, it makes combining the two datasets immeasurably easier. There will be errors and there will be a slight difference in figures, but the more accurate you GPS control points are, the lower the error rate, ensuring the resulting combined dataset is still within accuracy limits.
We use a combination of a Trimble R8 GPS unit and the Trimble Catalyst to survey our ground control points and targets. By scanning the outside of a building and moving along a path to the inside of a building (where GNSS is sometimes not possible) we are still able to get very accurate GNSS locations on the resulting point cloud. Our drone has a built in GNSS unit (c. 1m accuracy), which is then tightened up using measured ground control points in post-processing. We generally get GNSS accuracy in the sub- 2cm range but can get sub- 1cm for projects that require it.
Post-Processing the Survey Data
This step is determined by the type of project we have and what the resulting output is. In many cases, we will use the drone photogrammetry to provide and overall topographical dataset on which we combine the LiDAR point clouds main target. This is done by specialist software that can statistically align the point clouds, creating a single output. Sometimes multiple scans and point clouds need to be stitched together to provide an output suitable to requirements. It is not a simple process, but good planning usually mitigates any major issues.
To combine Drone and LiDAR survey data from different surveying methods can be done, but it needs planning. It’s not suitable for all projects, but can come in useful if you have access to the equipment required. Highly accurate GNSSS data is essential, as is the placement of ground control points and targets. For some projects, aerial LiDAR combined with terrestrial LiDAR would be a better method. It really depends on the requirements of the project and what outputs are needed.
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