Single photon mode lidar

[Paski]

Hi all.

I follow this forum, not as thoroughly I'd like, and I can´t remenber and/or I can´t find some topic about this. 

We are from Navarra's Government, Spain, and in a few lapse of time we will have the data from a fligth made with a single photon mode lidar. Although we will recive some derived products as DTM or DSM, also we will have "unclassified" data. 

We have some questions:  

How Lastools works with these data? 

Are Lastools capable to extract similar data outputs as working with linear mode lidar? 

And..... you are free to share your related point of view about this.

Thanks in advance

Roberto Pascual

Cartography Section

Navarra's Government

[Martin Isenburg]

Hello Roberto.

you seem to be talking about the Single Photon LiDAR (SPL) system from SigmaSpace / Leica / Hexagon if I am not mistaken. I have not yet seen the raw data from SPL systems but I hear that LAStools has been successful in processing the LiDAR from other "experimental" LiDAR systems that are producing much noisier data than traditional linear LiDAR.systems. I do not know how similar SPL is to Geiger mode LiDAR but based on some Geiger mode LiDAR data sets I have seen the data is a bit reminiscent of dense-matching photogrammetry with much less to no penetration of vegetation in contrast to linear LiDAR systems. The other similarity between Geiger mode LiDAR and image-based methods is that the delivered points are not really the "raw" data but derived from multiple observations. Is that similar or different for SPL? Maybe someone who is a specialist with Single Photon LiDAR (SPL) systems could chime in here.

Either way ... the many modules in LAStools will usually be able to create the processing workflow you desire. Just look at the various pipelines described in these blog articles how well LAStools is able to handle point clouds from dense-matching photogrammetry that are also not generated by linear mode LiDAR:

https://rapidlasso.com/2017/07/04/removing-excessive-low-noise-from-dense-matching-point-clouds/

https://rapidlasso.com/2017/06/13/integrating-external-ground-points-in-forests-to-improve-dtm-from-dense-matching-photogrammetry/

https://rapidlasso.com/2016/11/22/creating-a-better-dtm-from-photogrammetic-points-by-avoiding-shadows/

https://rapidlasso.com/2015/10/07/removing-low-noise-from-semi-global-matching-points/

https://rapidlasso.com/2015/09/21/creating-dtms-from-dense-matched-points-of-uav-imagery-from-senseflys-ebee/

https://rapidlasso.com/2014/08/25/processing-large-dense-matching-point-clouds/

https://rapidlasso.com/2014/06/13/dtm-from-dense-matching-points/

Easiest may be you wait for the data and try it out or share a link to some of the raw SPL data in this forum. I am sure there are a few curious minds who would like to see such data.

Regards,

Martin @rapidlasso

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[Paski]

Yes, Martin, you are not mistaken in all of you say. SPL system from SigmaSpace / Leica / Hexagon, noisy data, less penetration (but we have a nominal density of 14 points per m2), not so "raw" data (they passed a previous software), and the easy way is to share some data (we are not a LiDAR data proccesing especialists).

In order to this last, we will select some sample areas of our varied geography and let them in our FTP. There, you will be free to download, apply software and share your commnents. We also have a previous traditional LiDAR of 1 point per m2 and you could compare.

When we have the selected data I'll send to this forum the links.

Thank you

Roberto Pascual

Cartography Section

Navarra's Government

[Paski]

Hi all again.

We have put for free download in our ftp site (ftp://ftp.cartografia.navarra.es/) some samples of de Single Photon LiDAR fligth. Data are zipped in 1.4 laz format.

In the LiDAR folder you have a subfolder (ftp://ftp.cartografia.navarra.es/5_LIDAR/5_4_2017_ZONAS_DE_MUESTRA/) with 5 sample of different and representative areas: Dense forest and Badlands, Reforestation forest, Riverside, Crops and water areas and Urban area.

Data are automatically clasified so erroneus calsification is possible, and have a lot of noise, it seems that it’s snowing, but sometimes noise carries information, as power lines for example.

Also you have a “_leeme_LiDAR_muestra” document (equal to “readme_LiDAR_demo”) where we explain some important info to take into account. Document is in Spanish but I think that usual translators work well.

Now only have data from the south part of our territory, the drier, continental, and less forested area in Navarra. We hope that in a few weeks we will have all territory (about 10000 km²) with more varied geography and big and dense forest areas.

When we have all our data uploaded we will tell you.

We will be very garteful with your comments about all you discover.

Good luck and thanks in advance. 

[Olsen, Richard (RC) (CIV)]

First comment/question:

Is there a file that describes the data – in particular the sensor – and how it was flown (aircraft, altitude, etc).    Was this the Sigma Space (Hexagon);  Harris, or some other?

Processing steps so far ?   In particular, any filtering that has been done already?

 

rco

 

RC Olsen

Naval Postgraduate School

--

[Paski]

Sorry for delay, 

About the sensor SPL100 you have a pdf in FTP site and more info in Sigma Space Web. Aircratf was a Beechcraft B200 King Air.

Flight alttittude is about 13000 feet and was adjusted with 100 calibration fields. Data are the flight pass without filtering, only an automatic classification until level 18 (noise) as standard. Points of overlaped areas are separated in levels from 20 to 28, where 28 is the same of 18, and 0 as 20, 1 as 21, etc, but for overlapped areas. Water is not classified. This separation is an specificatión of the National Geography Institute of Spain.

I think this is all.

Thank you.

Roberto

[Agnieszka Ptak]

Hello,

have You checked that data with GCP?  Is this already georeferenced?

BR

[Paski]

Yes, 100 control or calibration fields with 16 points each one in a grid of 4 x 4 meters, around 1600 ground points. These for 10000 square kilometers of territory.

Data are in EPSG 25830 and elipsoidal altittudes, GRS80.

Roberto