We often work with our fix wing drones (e-bee) in very dense tropical forest areas between 200 ha and 5000 ha. We fly at 100-120m high and have an Overlap of 80%-85% and 70% Sidelap. We need the altitude curves between 25-50cm equidistance (hydrology projects). What represents the DTM and the resulting curves, the tree crowns or the ground? We work with at least 5 GCP and 3 Checkpoints. But often we have so dense forests, where the camera (Canon PS110, Canon SX260, Sony WX500 und Sequoia) does not look at the ground. The questions: If we only have closed forest and the forests are hilly or in the mountains, and the GCP can only be placed at the edge zones of the forests, what represents the DTM.
If the same situation is flat forests, what represents the DTM. If the forest has a “hole” where the GCPs are placed, what does the DTM represent? Or in other Words, is the DTM consistent in all three situations? How would you obtain consistent data of elevation working with drones in dense tropical forest.
What do you recommend for these situations in order to obtain consistent high-altitude data.
Then the final question: If we compare the DSM with the DTM in these situations, can we derive the tree height from it?
To make it easier we chose to answer your questions independently. Please find our answers below:
1. As general guidelines for areas with forest and dense vegetation we know from experience that a Ground Sampling Distance (GSD) of at least 10cm/pixel gives better results for reconstruction. The flight plan is usually a grid pattern with at least 85% frontal overlap and at least 70% side overlap.
For future projects, we would recommend not to place the GCPs exactly at the edges of the area, as they will only be visible in few images. When you acquire your GCPs another decision factor is their position which should be placed evenly on the landscape to minimise the error in Scale and Orientation. That being said if you have different small areas with low vegetation within the forest it would be recommended to consider them for positioning your GCPs.
3. The DTM generation it is based on Semiautomatic Approach, takes the Raster DSM (Digital Surface Model) as an input, computes a classification mask that represents the terrain / objects and generates the Raster DTM (Digital Terrain Model). That being said the DTM is void of tree, building, objects etc…
Due to the smoothing nature of the DTM generation algorithm we do not recommend to derive the height of the trees by subtracting the DTM from DSM.
5. Pix4D Desktop can produce contour lines with an elevation interval between 0.001 to 10000. You can find more information on contour line in the following article: https://support.pix4d.com/hc/en-us/articles/202560639
6. An easier way to deal with hilly terrain is to launch from the highpoint on your site, or adjust your consistent flight altitude so the difference between the UAV and the terrain will be constant. You can find more information regarding image acquisition plan for terrain with height variations please see the article: [https://support.pix4d.com/hc/en-us/articles/20465620
The DTM that is being generated is very wrong in altitude and shape comparing to the sharp DSM model. I need the DTM model as accurate as possible, just with the trees and buildings removed.Â
Is there a way to make DTM sharper and correct in height ?
At the moment as the DTM generation is semiautomatic we cannot manipulate the classification.
However It is possible to remove an object by editing the point cloud. In this case you can select the features (trees, grass etc…), assign them to the Deleted point group and then process step 3. Deleted points will not be taken into account and instead of generating the DSM during step 3, you will manually generate a DTM of higher resolution, in which the ground will be more visible. The contour lines can be exported directly from DSM hence the heights will be much closer to the real values.
What are the things that need to be considered to have good DTM and DSM maps from the pix4D?
We have been collecting visual images from our farms at different times in the growing season to see changes in crop heights. For this, we generated DTM and DSM maps along with their Orthomosaics. We used AgRGB template of the pix4D. We came up with pretty odd DTM/DSM maps. The reason is this: when the ground is bare, the DSM values are in the range of 281 - 322. This is close to the existing DEM data for this field. But, for the same field, it came to 280 - 309 when the ground are covered with tall plants. It is kind of odd to see lower DSM values in the later part of the growing season instead of observing higher values.
Is this something other people are encountering as well? Or do I need to select another template for this purpose? Thanks.
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