04-07-2019 09:05 PM - edited 04-07-2019 09:15 PM
Hi Community,
I'm new in point cloud data processing. I need bits of help and references about point cloud data:
1. I have .txt point cloud data, how to import it as *.las data into ERDAS IMAGINE ? and what must we do with the *.las data before we process it, is there need to pre-processing steps like optical imagery such as radiometric correction for example, or what steps that *.las data needs before it go to the next processes?
2. I have stockpile *.las data that was visualized into the ERDAS IMAGINE, here it is the picture :
I've calculated for the volume, but there's an unknown projection in the data attributes :
My data doesn't have any projection yet. What steps that I must I do first to add projection to my data so I'm able to know calculated volume in correct units?
3. I've seen *.las data that visualized in the ERDAS IMAGINE seems it meshed with RGB data, so what steps in ERDAS IMAGINE that can make meshed data like that, or the meshed las data with that RGB is from the aerial/terestrial instrument when capturing point cloud data that produced xyz.rgb data?
Thank you and Regards,
Dwima
Solved! Go to Solution.
04-08-2019 05:06 AM
Hi Dwima,
To convert .txt to .las, you can use the Terrain Prep Tool, which is found under the Terrain tab in the IMAGINE ribbon interface. Add the *.txt file as a 3D ASCII xyz data and then use the split or merge functionality to save it in las format.
To add projections/units to las data, start the commands tools found under the Terrain tab in the IMAGINE ribbon interface (Point Could tools group). You will be able to add/change coordinate systems using the tool.
To be able to mesh with RGB information, the point cloud must be encoded with RGB data (from ortho image of teh same area). If you have an RGB image that covers the same areas as the point cloud, you can add the RGB information of the image into the point cloud data using the Color Encode tool (availabel in Terrain tab in the IMAGINE ribbon interface -> Point Could tools group)
Regards, Sam
04-09-2019 12:27 AM - edited 04-09-2019 12:27 AM
Hi, Sam.
Thank you so much, it is very helpful. Your guidances, they're so great! My volume data it's finally doesn't unknown no more.
I know point cloud is better than DEM, but by the way, what makes point cloud is very special and there's no one can deny about it? I think it's because of accuracy, and what tools in ERDAS IMAGINE that can use for DEM volume analysis?
Regards,
Dwima