www.terrasolid.com

Terrasolid UAVfor DJI L1

Arttu Soininen 06.07.2021

• Game changer in the UAV LIDAR industry• Brings survey grade UAV LIDAR to a whole new

price level

• Nicely integrated package, easy to operate• Very good integration of camera + LIDAR• Quality coloring of LIDAR points

DJI L1

• Bundle which is available for DJI L1 users free of charge until 31.12.2022• Runs on Spatix or MicroStation CAD system• Terrasolid UAV for DJI L1 Spatix package includes:

• TerraScan UAV• TerraModeler UAV• Spatix• License to run these until 31.12.2022 on same computer with DJI Terra

• Terrasolid UAV for DJI L1 MicroStation package includes:• TerraScan UAV• TerraModeler UAV• License to run these until 31.12.2022 on same computer with DJI Terra• You must have MicroStation / PowerDraft / Map PowerView to run this!

Terrasolid UAV for DJI L1

• Free until 31.12.2022 for DJI L1 customers• Normal list prices:

• Purchase price 4 590 euros + 15% maintenance per year• Subscription price 1 530 euros per year

• Terrasolid reserves the right to change pricing and functionality available in packages• We will decide before 31.12.2022 if a different set of functionality and/or different price will serve the

customer base better

• Terrasolid UAV for DJI L1 download packages will appear on our web pages by 15.07.2021

• Terra for Spatix bundle is available for download right now• Includes all software but you need to request for an evalution license

TerraScan UAV & TerraModeler UAV & Spatix

• We improve the software all the time• Regular updates – current TerraScan 021.023 is update 23 during 2021• Next release will come out tomorrow – will have functionality you have seen today

TerraScan UAV & TerraModeler UAV & Spatix

• Tools simplifying DJI L1 data import and processing• One step import dialog• Tool for running normal processing steps using one guided dialog• May add support for other drone systems later on

Drone Processing Wizard

• DJI Terra writes:• Point cloud as LAS file• Trajectory solution as xxxxxxxx_sbet.out• Trajectory accuracy estimates as xxxxxx_smrmsg.out

Drone Processing Wizard – Input Data

Point cloud input file (LAS)

Trajectory solution input file (sbet.out)TerraScan reads corresponding smrmsg.out

• Processing wizard performs typical processing steps which are common for many end products• You run all or some of the wizard steps• You may then continue with end product steps:

• Dedicated tools for powerline processing (vectorize wires, find danger trees, …)• City modeling (building vectorization, texturing with TerraPhoto, …)• Contour production (classify contour keypoints, display contours)• Volume computation (classify model keypoints, create TIN models, compute volumes)• …

Drone Processing Wizard & End Products

• You can decide if you run all automatic steps in one go• Or you can choose to run steps and then check the result before

proceeding• You can always use TerraScan tools to manipulate data at any point

• Classify bad data out at the start or later on• Remove unnecessary data at any point• Perform some Wizard step with different logic if you are not

happy with the result

Drone Processing Wizard

• You can use your own list of classes or let New drone project create default classes

• Don't change classes 1-8 – those are industry standard

• You may choose your own definition for class 9 and higher

Default Point Classes

• Split trajectories so that each flight pass over collection area becomes its own trajectory• Remove short transition segments and delete corresponding laser points

Split Trajectory

• Remove overlapping data so that each xy location has points from one pass only• This:

• Improves accuracy as we remove points with biggest positional issues• Simplifies data as we always have just one image of reality• Reduces data volume

Cut Overlap

• Smoothens surfaces and classifies outliers as noise – eliminates point-to-point noise and makes surfaces prettier

• Can use point color information to recognize vegetation and apply smoothing only to non-vegetation surfaces

Smoothen and Remove Noise

• Optional step for speeding up processing• Applies thinning and classifies many of the points as inactive• We run classification steps only on active points• At the end we copy above ground feature classification to inactive points from closest actively

classified point

Thin Points to Inactive

• Ground classification removes some outliers and runs ground classification• Result is mostly good but some editing is often needed:

• Bridges typically become ground• Ground may have some low points

Classify Ground

• Visualize ground as shaded TIN surface or as contours• Use manual classification tools to classify points out or into the ground• Updates visualization automatically• If terrain is easy, you can do this at the end• If terrain is difficult, you should do this before classifying above ground

Check Ground

● Classifies points to (user can change limits):● 3 – Low vegetation less than 0.3m above ground● 4 – Medium vegetation 0.3 – 2.0m above ground● 5 – High vegetation more than 2.0m above ground

● We have low vegetation everywhere so it does not have much active use● We classify medium and high vegetation further to Car, Tree, Vegetation, Building roof, …

Classify Height from Ground

• Runs grouping (=segmentation) of medium and high vegetation points• Classifies groups using best match principle to 8 possible different classes

Classify Above Ground Features

• Copies above ground feature classification (Building roof, Vegetation, Tree, Pole, ...) to points classified earlier as inactive for speeding up the process

• Needed only if Thin Points to Inactive step was done to speed up the process

Copy Result to Inactive Points

• Copies vegetation classification (Vegetation and Tree) to points classified earlier as noise• Needed only if noise was classified in Smoothen and Remove Noise step• Noise points close to hard surface should remain in Noise class• Vegetation itself is noisy – no reason to discard any points

Copy Result to Noise Points

• 'Urban' data set courtesy of DJI from was used• Has 7 control points on flat surfaces

DJI L1 Vertical Accuracy

Average magnitude

Standard deviation

RMS Average dz(bias)

Raw point cloud 5.86 cm 7.44 cm 6.91 cm -0.54 cm

Cut overlap done 3.97 cm 5.25 cm 5.08 cm -1.46 cm

Smoothing done 3.96 cm 5.29 cm 5.03 cm -1.16 cm

Ground done 4.31 cm 5.35 cm 5.32 cm -1.94 cm

Bias removed 3.93 cm 5.35 cm 4.96 cm -0.04 cm

• We will run regular webinars on DJI L1 processing every 2-4 weeks• Each webinar will introduce some new features or some use case• Next webinar is Checking DJI L1 Lidar Accuracy with Control Points

• Tue 20.07. at 10:00 Helsinki time (GMT +3:00)• Tue 20.07. at 18:00 Helsinki time (GMT +3.00)

• Check www.terrasolid.com for more info and for registration

Upcoming Webinars