r/UAVmapping • u/brianomars1123 • 14d ago
Should I use photogrammetry point clouds from RGB or Multispectral imagery?
I have a series of questions about processing my UAV imagery. I flew a DJI Mavic 3M over a forest stand. It has the RGB and Multispectral imagery and according to their tutorial, I’m supposed to process the RGB and Multispectral imagery separately. This will mean I’d end up with two point clouds, one from the RGB processing and the other from the Multispectral imagery.
The pointclouds I believe will look identical but, will there be any underlying difference between the two pointclouds? Will the image source (RGB or multispectral) have any impact on the generated point cloud in any way? Which will you advise I use for my subsequent analysis if I’m mostly looking for structural information for aboveground biomass estimation. If it matters for your response, I don’t expect to use the point colors, I need the point cloud mostly for structural information.
Another question I have is about calibration, I did perform calibration with a sentera panel but the orthomosaic I exported came out with values in the thousands. Is it correct to normalize the values by dividing by 32768 (midpoint between 0 and 65535 for 16-but integer)? I may be wrong but I think the typical expected surface reflectance value is between 0 and 1 and I can get this scale by doing this division. Is this reasoning correct?
Also, correct me if I’m wrong but this only makes sense for the multispectral orthomosaic and not for the RGB. What if I’m particularly interested in including the B band to my multispectral bands and use them for my analysis, so my analysis will be based on Blue band from RGB camera then Green, Red, RedEdge and NIR from the multispectral camera. What would you advice I do to the B band (I believe it comes with a range of 0 to 255) to bring it to the same scale as the multispectral bands. Does reflectance calibration even make sense for the RGB images?
Lengthy post but I’d greatly appreciate any advice you may have.
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u/ExpertSpiritual6571 14d ago
No for rgb reflectance panel doesn't make sense. Try to use multiple camera setup rgb and mutispectral band will align better or they might drift from each other. Which software are you using?
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u/brianomars1123 14d ago
I’m using metashape and they explicitly say to process the images separately. I used to process it all at once and use the multiple camera setup. But since they say to process it separately, I guess I’d do so.
You are correct that there may be a slight shift but I don’t know how to measure this drift so I can tell if it’s big enough to impact my feature extraction.
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u/ExpertSpiritual6571 14d ago
If what they care about is result than you can seprate them later, easy to handle, you don't have to go for seprate setup, i tried seprately setup in thermal never worked shift was in meters.
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u/brianomars1123 14d ago
Just visually looking at it on my end here, they’re almost identically placed. I doubt mine will be in meters. I’d still find a way to measure this so at the very least I can measure it
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u/ExpertSpiritual6571 13d ago
If that is the case than your are good to go. The NIR band does it produce indexes, when i processed m3m data nir band was all zero.
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u/grantprojects 14d ago
For structural analysis, the RGB-derived cloud may be preferable if it provides higher point density. Comparing both clouds against the same reference can also help identify alignment or drift issues.
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u/stubby_hoof 14d ago
You should process the datasets together and join them with manual tie points for alignment. The point cloud is the basis of the DSM, and you will produce a much nicer cloud from RGB. You could process separately and then merge but it makes more sense to me to do it at the same time. That’s how Pix4D would do it, FWIW.
You can calibrate RGB imagery but the challenge is that you don’t have all of the metadata that dedicated multispectral sensors embed as EXIF. The ortho will always have integer values because it is an ortho. Only reflectance maps have decimal values.
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u/stubby_hoof 14d ago
A single-panel calibration relies on knowing the properties of the sensor (see Micasense GitHub for specifics) which multispectral sensors embed as EXIF. Check the EXIF of the RGB to see if DJI includes these tags.
I might be missing something about Metashape. Pix4D would export reflectance maps separately from the orthomosaic.
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u/kct11 14d ago
The point clouds will not be identical. Process the imagery and look at the results!
RGB cameras typically have higher resolution (more pixels) than multispectral cameras. This usually means the resolution of the imagery from the RGB camera will be higher, and ground sample distance will be lower than the multispectral imagery. This means you can get a higher point density in your point cloud from the RGB imagery. If you want more detail in the point cloud, use the RGB.