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Sep 4, 2022 at 0:35 comment added Arthur_Morgan Thank you will try your suggestion :)
Sep 3, 2022 at 18:43 comment added JRR This sound overly complex. You could simply use you lascatalog with files from different folders. It is not a problem. You can also retile in 1x1 km tiles with custom name convention. Both options are better than one big 100 GB file
Sep 3, 2022 at 18:38 comment added Arthur_Morgan So first I will stitch them all up to have a single file for the county, then clip cities out of it one by one. And then from cities I will extract parks and other areas of interest.
Sep 3, 2022 at 18:35 comment added Arthur_Morgan true, but the problem is that ESRI gave us height normalized LAS files for our county. And ESRI put the files into 4 folders, only one of those folders is for 1 city out of 31 other cities. The rest of the LAS files were put under folders SectionNE, SectionNW and SectionS respectively. On top of that ESRI used their own naming convention so I have no idea what's the location of a tile by reading the filename. I also don't know how ESRI did the tiling. Hence basically I am stiching them up to extract ROIs for cities, parks and conservation areas.
Sep 3, 2022 at 11:35 history edited JRR CC BY-SA 4.0
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Sep 3, 2022 at 10:23 history edited JRR CC BY-SA 4.0
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Sep 3, 2022 at 10:21 comment added JRR Yes, but the file will be so big that it will take a significant amount of time. You must create a spatial index to perform spatial query in a reasonable time-frame. Merging 110 file into a single one is a bad idea in all aspect actually.
Sep 2, 2022 at 20:25 comment added Arthur_Morgan Thank you for the detailed answer. Since, the output file would be too big to load into R. Can I clip an ROI from it by just using readLAScatalog?
Sep 2, 2022 at 18:43 vote accept Arthur_Morgan
Sep 2, 2022 at 17:42 history answered JRR CC BY-SA 4.0