Qloud performance improvement
Over the past months a number of QINSy modules have been optimized to meet the demands of mobile laser scanning with (multiple) high resolution laser scanners.
The fast increase in DTM to handle with QLOUD required further optimization in data handling and processing. It turned out that not only software changes improved the performance of QLOUD, but also the hardware used proved to be an important factor.
In general notebooks have 5200 rpm HDD. Using an external (USB 2.0) 7200 rpm HDD to work from already gives a noticeable performance improvement.
The use of Solid State Drives (SSD)gives a further boost to the performance of QLOUD. QPS tested QLOUD on a Corsair 256GB SSD. The performance (e.g. import, export, cleaning etc.) of QLOUD is at least 2x faster when using these types of drives.
The import of ASCII and QPD have been optimized for performance making use of lately developed routines. On average the import of point data is now 2 times faster with normal HDD and when using SSD it is up to 4 times faster.
The same improvement is achieved during manual editing and when running the automated cleaning profiles. Export to ASCII points is now up to 6 times faster.
We were able to find the bug which caused 'hanging' of QLOUD sometimes when trying to load too many points in the 3D view.
Two important tools have been added recently to QLOUD
- TIN Decimation. Based on the TIN model the number of valid DTM points can be reduced dramatically without losing resolution. The reduction criteria are based on the height difference between connected points and maximum distance allowed between points. The operator has full control over the parameters. The result TIN will keep resolution where required (slopes, outcrops, objects etc.) and reduced resolution on relatively flat areas.
This will also give a boost to the cleaning performance when cleaning profiles are carried out on less data.
- Measuring slant ranges between two DTM points in 3D display.