Ok, so this may be a more advanced topic than normally found on this forum. But I am struggling to classify the point clouds generated with the UAV. After Pix4D, after Agisoft or others you are left with an unclassified point cloud If I want to classify the buildings, vegetation, and ground points so I can then generate a DTM. How is everyone doing this? What software have you used, what settings?
The main problem I have found is that most point cloud manipulation software is designed for LiDAR, and LiDAR has one thing we do not have, multiple returns. So for them clasifying the ground is a matter of getting the last return and then just cleaning up the buildings. But most of these don't work so well with the point clouds from Pix4D, Agisoft, etc... I have tried LASTools, ESRI, and recently DTMaster. Any other suggestions? or suggestions on the settings to use?
Replies
hello, do you have tutorial this method? thanks
IronDOME said:
do you have tutorial or ways how to make dtm from UAV data? thanks
IronDOME said:
Hi Jaime
Have you had any luck with this? Global mapper as suggested by few, is quite useful in some cases, but some cases it has issues. Like you said, there are a few parameters to set, and I did this by try and error finally I got an excellent DTM. So I assumed my parameters would work for every situation, it turns out to be wrong. Right now I have some data from another project once again I'm going through try and error to see what I come up with. I have tried without success using LASTools, there is very clear explanation on how to use it and since it is sort of "free" application you can't get much support or be hard on getting support. I tried to contact the developer Dr. Martin and his reply wasn't so clear to me so I gave up. The one problem with these developers, they tend to think users will have same level of understanding as them hence they may provide with explanation on how to do things, but may not be clear to you as an end user who is trying to learn it as new product.
See images from my DSM and finally the DTM I processed with Global Mapper. I have included the Orthophoto to give you a clue of how the area looks like.
Follow this link to my Public Dropbox folder.
https://www.dropbox.com/sh/rxhrgaznnup3ioh/AAB3qDvhBOIq3PgGGyja6sHv...
Another vote for Global Mapper
Not only for lidar classification, but also great imagery rectification options and much much more.
Kudos mate!
Hi Jaime, I used CANUPO recently to classify a fiber optic cable in a lidar scene and it worked great. Haven't tried it on UAV SfM yet but I imagine it would do pretty well.
You might want to try Global Mapper as well. It is a GIS program but you can purchase the LiDAR module and classify point clouds, automated and manual, and also export raster and vector DTM data. Global Mapper is about $400 and the LIDAR module is also about $400. I use this to classify data collected from an eBee and think it's great for the price and they have great tech support.
I tried it but I did not have very good results so I did not purchase it, the price seems steep and I did not give me very good results. I found a couple of articles that seem promising, I will have to try them out:
http://rapidlasso.com/2015/09/21/creating-dtms-from-dense-matched-p...
and
http://rapidlasso.com/2014/06/13/dtm-from-dense-matching-points/
I think the key point from this is "not too much vegitation" lol! I live in British Columbia... Lidar, d'oh!
Processing/classifying Point Cloud data requires knowing how to use the software and experience regardless of the software being used. Vegetation is why people use LiDAR because you will likely get points on the ground. LiDAR is an active sensor which emits a pulse and then receives it with the time and angle used to determine where the point is in real space. Creating point clouds from photos is not LiDAR that is why vegetation is a problem and why Photogrammetry (an older technology) is being supplanted by LiDAR. Using photos requires the same point on the "ground" to appear in at least two photos shot from different angles so that a stereo image can be created to determine the Z value of the point. Orthorectification of a single photo is required to determine the point's X and Y position.
Multiple returns do provide more information that can be derived from the data but is not required to determine the ground surface. Even with multiple returns the last return is not always on the actual ground. So it is not as simple as saying if I have all last returns I have the ground surface, You would have every solid object in that surface as well including roof tops, water towers, heavy vegetation, etc.
Point cloud classification software regardless of the vendor takes an investment of time to learn how to use them. No vendor has the "one button push" and produce a ground surface solution. They all have some semi automatic tools to help classify points but they all require manual cleanup for good results.
-
1
-
2
-
3
-
4
of 4 Next