Power Lines LiDAR mapping and Offending vegetation detection.QA/QC Power lines analysis and Corridor Mapping. Customized engineering services from LiDAR procesing. PLS-CADD

1. POWER LINES PROCESSING STEPS

2. MAIN PRODUCTS
REPORTS
PLS-CADD
MODELLING
LiDAR
CLASSIFICATION
& NETWORK UPDATE
OFFENDING VEGETATION
DETECTION & GROUND
CLEARANCE ANALYSIS CLOUD SERVICES

3. OUR EXPERIENCE AND BACKGROUND
FLEXIBLE
IN-HOUSE
SOFTWARE
CUSTOMIZED
PRODUCTS
AND SERVICES
BEST QUALITY
COMPETITIVE
PRICING
QA/QC
99,99%
ACCURACY
INTERNATIONAL
EXPERIENCE
+ 85.000 KM
With more than 85.000 km of experience in power line projects, we leverage extensive experience for your
project.
The ability to adapt our own software to provide optimal LiDAR processing solutions enables us to be flexible
to any Client's specific requirements.
This makes us an attractive alternative to traditional fixed flow line LiDAR processing solutions

4. LIDAR PROCESSING STEPS
Delivery of raw LAS files.
Auto classification of raw data
Measure FL and Z errors in overlaps.
Flight line adjustment in Z.
Check and correct errors in XY. Select FL to refly
Intensity image and objects > 3m mask.
2D vector of poles and conductors.
QA of vectors with objects > 3m mask and reference vectors
Check non capture regions
Report non capture regions if necessary
Select Study Data from Total Data Pool and Auto-classify Poles and Conductors
Apply the flight line adjustment.
LAS manual editing.
Roads vectors.
QA of vectors / Ids
Compute PI and ground QA.
QA of LAS classification
Compute and edit patches.
2D vector of crossings.
Prepare vectors to compute offending Vegetation (OV).
Compute OV v1
QA of OV v1
Edit errors detected in OV v1.
Recompute OV v2
Second QA of OV2.
Edit errors detected in OV2.
Compute the OV volume by span
Prepare delivery of Offending Vegetation.
Delivery of Offending Vegetation.
Compute Report Premodeling
QA of Report Premodeling.
Edit errors detected in report pre-modeling.
Insert Roads and MKP in LAS files.
QA of overlaps with other Blocks.
Prepare delivery of the other products.
Delivery of the other products.
2- LiDAR CLASSIFICATION,
QUALITY CONTROL, OFFENDING
VEGETATION AND ERROR
CORRECTION
1- DATA PREPARATION AND
CORRECTION BEFORE
CLASSIFICATION
3- PRE-MODELLING, REPORTS
AND FINAL PRODUCTS
GENERATION
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

5. LIDAR PROCESSING STEPS
Description 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Delivery of raw LAS files.
Auto classification of raw data
Measure FL and Z errors in overlaps.
Flight line adjustment in Z.
Check errors in XY.
Correct errors in XY or select FL to refly.
Intensity image and objects > 3m mask.
2D vector of poles and conductors.
QA of vectors with objects > 3m mask and reference vectors
Check non capture regions
Report non capture regions if necessary
Select Study Data from Total Data Pool and Auto-classify Poles and Conductors
Apply the flight line adjustment.
1- DATA PREPARATION AND CORRECTION BEFORE CLASSIFICATION
6 WORKING DAYS

6. The LiDAR processing team receives raw .las files to begin the processing.
We need a connected network of data before we are able start processing
the depot. Disconnected parts or small parts are not suitable.
We split the project in quadrants when working in large networks or projects
DATA PREPARATION AND CORRECTION
Delivery of raw LAS files

7. - Convert the original LAS files in
ellipsoidal heights to orthometric heights.
- Divide into 1x1 km tiles per flight line for
efficient processing.
- DTM, DSM, intensity images
- LAS only with ground points
- LAS with points > 3m.
- Mask with points > 3m.
DATA PREPARATION AND CORRECTION
Auto processing of raw data

8. Based in the automatic DTM
obtained in the previous point,
algorithms examine height
differences where flight lines
overlap.
DATA PREPARATION AND CORRECTION
Measure Flight Line and height misalignments in overlaps

9. We identify the optimal correction factor to
add to each flight line to minimize the Z
(vertical) small misalignments in the
overlaps.
Any misalignment detected is examined
individually and a flight line adjustment will
be done to achieve the technical
specifications.
Survey points are used for ground truthing.
DATA PREPARATION AND CORRECTION
Flight line adjustment in Z

10. Visually we inspect the
overlaps of flight lines to
detect misalignments in XY.
We examine any variations
and choose between manual
adjustment or re-flying the
affected part.
Rarely are significant issues
identified at this stage but it is
an important QA step
DATA PREPARATION AND CORRECTION
Check errors in XY

11. Any inconsistency detected is
examined individually and points
in error are removed. Usually
these issues are solved removing
the overlaps affected by the
errors.
If appropriate adjustments cannot
be applied to deliver the specified
accuracy, a recommendation is
made to re-fly the affected flight
line.
DATA PREPARATION AND CORRECTION
Correct Errors in XY or Select Flight Line to Re-fly

12. From the corrected LAS files, we prepare
raster layers with the LiDAR intensity. The
intensity image is used in the creation and
QA of the road vectors (every physical
material reflects the laser differently).
We also prepare a raster layer mosaic with
the points that are more than 3m above
ground level. This mask is used for one
stage of the QA of the conductor vectors,
because we can identify easily them in the
image.
DATA PREPARATION AND CORRECTION
Intensity image and objects > 3m mask

13. Using the GIS reference
layers, we generate vector
GIS layers with conductors
and poles for the whole
survey area. A layer is
created for each voltage
on the network.
DATA PREPARATION AND CORRECTION
2D vector of poles and conductors

14. We then conduct a manual
QA check to ensure
consistency between the
vectors created from the
LiDAR data and utility-
supplied reference layers.
DATA PREPARATION AND CORRECTION
QA of vectors with objects > 3m mask and reference vectors

15. Once the conductor
vectors are done, we
identify the regions that
have not been captured
and perform a QA to
confirm their status, and
identify no-fly areas.
The non-captured regions
are reported to the data
capture team to re-fly.
DATA PREPARATION AND CORRECTION
Check Non-Captured Regions

16. Using the 2D vectors, we create new
LAS files containing only the points
inside a buffer from the conductors and
poles. We clip the data set to minimize
the processor time for each
subsequent processing step.
After that we use our custom software
to automate the classification of poles
based in the 2D vectors of poles
obtained previously.
DATA PREPARATION AND CORRECTION
Select Study Data from Total Data Pool and Auto-classify Poles and Conductors

17. Join the LAS files in a
single tile with all the
flight lines.
We prepare the
corrected LAS files and
add the height of each
point to the correction
factor from the
corresponding flight line,
obtained in a previous
step.
Join Flight Lines and Apply the Flight Line Adjustments
DATA PREPARATION AND CORRECTION

18. Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
LAS manual editing.
Roads vectors.
QA of vectors / IDs
Compute PI and ground QA.
QA of LAS classification
Compute and edit patches.
2D vector of crossings.
Prepare vectors to compute offending Vegetation (OV).
Compute OV v1
QA of OV v1
Edit errors detected in OV v1.
Recompute OV v2
Second QA of OV2.
Edit errors detected in OV2.
Compute the OV volume by span
Prepare delivery of Offending Vegetation.
2.- DATA PROCESSING, CLASSIFICATION, ANALYSYS & QC/QA
LIDAR PROCESSING STEPS
10 WORKING DAYS

19. LAS manual editing
Manual editing of the
point cloud to match the
classification table.
DATA PROCESSING, ANALYSYS & QC/QA

20. LAS manual editing
Manual editing of the
point cloud to match the
classification table.
DATA PROCESSING, ANALYSYS & QC/QA

21. Road Vectors
Using the .las files and
intensity image, we prepare
a vector layer of the roads
crossing the network.
DATA PROCESSING, ANALYSYS & QC/QA

22. QA of Vectors/IDs
We assign references to the
digital data of poles and
conductors correlated to the
utility-supplied GIS reference
layers.
Using GIS techniques, we
assign the references
automatically and carry out a
QA and manual editing of the
IDs based on the reference
layers.
DATA PROCESSING, ANALYSYS & QC/QA

23. Compute PI and ground QA
We perform a QA of the ground
classification to confirm that we have
enough points in the ground in all the
regions and that the DTM is correct.
We also run an algorithm to compute
the Points of Intersection (PI).
We derive the X,Y for each PI using
the poles vector layer. The height is
calculated as the average of the
ground points heights in a 1m buffer
from the poles.
DATA PROCESSING, ANALYSYS & QC/QA

24. QA of LAS classification
After the manual
classification, a different
person checks the
consistency of the data and
the correspondence of the
LAS classifications with the
reference layers.
DATA PROCESSING, ANALYSYS & QC/QA

25. 2D vector of crossings
Once the LAS classification
has been QA checked, we
automatically develop a vector
layer with the points that have
been classified as crossings of
any kind.
We check this layer, then
develop manually a separate
vector layer of the crossings
for each voltages.
DATA PROCESSING, ANALYSYS & QC/QA

26. OV Specifications (Issc3 + 0.5 + 5.5)
DATA PROCESSING, ANALYSYS & QC/QA

27. How Our Algorithm Works
DATA PROCESSING, ANALYSYS & QC/QA

28. Prepare vectors to compute offending Vegetation (OV)
Prepare the data to run
the algorithm to detect
the offending vegetation
according to the
specifications.
- Tiles
- Poles
- Conductors
- Classified LAS files
DATA PROCESSING, ANALYSYS & QC/QA

29. Using our custom in-house
software, we apply the algorithms
to the data set of this depot,
automatically and precisely
generating a new LAS file with the
offending vegetation classified
according the specifications.
For each voltage, we also
generate a vector layer of
polygons showing the extension of
the OV and the minimum 3D
distance.
Compute OV V1
DATA PROCESSING, ANALYSYS & QC/QA

30. QA of OV v1
The results are validated
against the specification.
We have internal software to
automatically zoom to each
polygon ensuring that we
check all the polygons to
confirm each one is offending
vegetation and not an error in
the .las classification.
DATA PROCESSING, ANALYSYS & QC/QA

31. Edit Errors Detected in OV v1
Manual correction of
any misclassified
points.
DATA PROCESSING, ANALYSYS & QC/QA

32. Recompute OV v2
Once the errors detected
have been corrected, we
reapply the algorithms to the
dataset of this block,
automatically generating a
second version of the .las files
with the offending vegetation
and the vectors for each
voltage.
DATA PROCESSING, ANALYSYS & QC/QA

33. QA of OV v2
We check the conformance
of the result of the OV v2 to
the specifications, paying
particular attention to the
classes with more risk and
small polygons that could
correspond to single points
that are noise in the LAS
files.
Manual correction of any
misclassified points.
DATA PROCESSING, ANALYSYS & QC/QA

34. Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Delivery of Offending Vegetation.
Compute Report Premodelling
QA of Report Premodelling.
Edit errors detected in report pre-modelling.
Insert Roads and MKP in LAS files.
QA of overlaps with other Blocks.
Prepare delivery of the other products.
Delivery of the other products.
3.- Rest of products and final delivery
LIDAR PROCESSING STEPS
8 WORKING DAYS

35. Report Pre-Modelling Specifications
QA, REPORTS & DELIVERIES

36. Compute Report Pre-modelling
Automatically measure the ground
clearances between the ground/road
surface and the conductor using the
LiDAR data at ambient conditions for
each different voltage and circuit
present on the network, resulting in a
vector layer with the results.
It also indicates clearances to other
circuits within the same span
(attached) and circuits located on
unattached structures.
QA, REPORTS & DELIVERIES

37. QA of Report Premodelling
Check the conformance of
the result to the
specifications.
We have internal software to
automatically zoom to each
clearance measurement,
ensuring that we check all
the points to confirm that the
measurement is accurate
QA, REPORTS & DELIVERIES

38. QA of Report Premodelling
QA, REPORTS & DELIVERIES

39. Edit errors detected in report pre-modelling
Manual correction of
errors in LiDAR
classification.
QA, REPORTS & DELIVERIES

40. Insert Roads and MKP in LAS files
Finally, we compute the
Model Key Points (MKP)
from the ground points and
we use the road vectors to
automatically reclassify the
ground points inside the
road polygons from ground
class to the ground in roads.
QA, REPORTS & DELIVERIES

41. QA of overlaps with other Blocks
To prepare the delivery of
the LAS files, we check
the consistency with
overlapping depots to
ensure continuity in the
classification of the LAS
files and in the height
adjustment.
QA, REPORTS & DELIVERIES

42. Prepare delivery
We export the data to the different formats as requested in the specifications
and merge with the data previously delivered.
QA, REPORTS & DELIVERIES

43. POINTSTREES
CLASSIFICATION
DEACTIVATION
INSERT SUPPORTSECTIONS
CREATION
LINE AT 50º
LINE AT 75ºRE-INSERTING
TREES
PLS-CADD MODELLING
OTHER LIDAR PROCESSING STEPS

44. OFFENDING VEGETATION ANALYSIS AND TREE FALL BY SPECIES
OTHER LIDAR PROCESSING STEPS
Offending vegetation detection and tree
fall analysis by species. Estimations for
X years period.
• Offending vegetation distances and
classes
• Ground clearances and distances
among wires.
• Risk simulation for forestry species.
• Tree fall risk for different species

45. FFCC AND CORRIDOR MAPPING FOR VEGETATION AND RISK DETECTION
OTHER LIDAR PROCESSING STEPS
Safety parameters modification and
new algorithms generation for the
analysis of railway and road
infrastructures.
• Safety distances to the ground.
• Tree fall risk for flat areas but
also for irregular areas and big
slopes.
• Other potential risks

46. CLOUD & ONLINE SOLUTIONS
ONLINE PROJECTS, CLOUD SERVERS AND GEO-LINKS FOR POWER LINES
LiDAR DATA SERVERS
GIS WEB PORTALS
ONLINE GIS PROJECTS & TOOLS
GEO-LINK CLOUD SERVICES

47. ONLINE DATA MANAGEMENT AND PUBLICATION
LiDAR DATA SERVER & WEB PORTALS
LiDAR, Raster & Vector
Web Portal customization
Online tools, 3D and more
Content Manager
SEE VIDEO ONLINE

48. CLOUD SERVICES
GEO-LINKS CLOUD
DOWNLOAD PDF ONLINE HERE