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Digital Terrain Model (DTM) Extraction from Lidar Point Clouds in densely forested areas JOE ORTIZ

Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

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Page 1: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Digital Terrain Model (DTM) Extraction from Lidar Point Clouds in densely forested areasJOE ORTIZ

Page 2: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Importance of the DTM

Basis for all biomass estimates: need DTM and canopy model Must eliminate spikes. Our data is not typical. Full waveform data – return approximately at peak.

Page 3: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Chose to adapt existing algorithms

Adaptive algorithm for large scale dtm interpolation from lidar data for forestry applications in steep forested terrain, Almasi S. Maguya, Virpi Junttila, Tuomo Kauranne

Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data, Almasi S. Maguya, Virpi Junttila, Tuomo Kauranne

Page 4: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Transforming Lidar point cloud

Translation to move origin.

Rotation by multiplying each coordinate by 3D rotation matrix.

Page 5: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Lidar point cloud

Page 6: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Dividing up the Lidar cloud into tiles

100m

100m

Page 7: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Dividing tiles into cells5m

5m

• Divide tile into cells of minimum size 5m.

• Assign each cell elevation as the minimum elevation of the cloud points inside the cell.

• Gives a grid of 20x20 data points for each 100mx100m tile.

• Apply standard deviation filter to grid of points.

• Gives grid of data points with gaps.

Page 8: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

DTM Extraction from filtered point grid

Page 9: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

DTM of area 300x200m area

Tile size is 100x100m

All tiles chose quadratic fit.

Resolution is 10m in both x and y direction. Defines cell size in DTM.

Page 10: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

DTM of area 300x200m area

Tile size is 60x70m

1 tile chose linear fit. All the others chose quadratic fit.

Resolution is 10m in both x and y direction.

Page 11: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Removing spikes

Spikes appear at edges of tiles usually due to poor extrapolation by the cubic spline interpolation model.

Create DTMs using different tile sizes: ~ 60-120m Take median of elevations of each cell (cell size given by desired

resolution) for each DTM Hopefully produces spikeless final DTM!

Page 12: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Conclusion/ What next?

Algorithm works well on tested areas. Surface is relatively smooth and hopefully will soon be spikeless.

Test over more areas of more complex terrain. Compare to other DTM extraction algorithms. Select best DTM extraction algorithm or combine elements of

several algorithms. Make a biomass estimate!

Page 13: Digital Terrain Model (DTM) Extraction from LiDAR Point Clouds in Densely Forested Areas

Thank you!