Transcript Optimizing Laser Scanner Locations using Viewshed Analysis

Optimizing Laser Scanner Locations
using Viewshed Analysis
MEA 592 Final Project
November 20,2009
Jeff Smith
Outline
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Project Purpose
Laser Scanning
Viewshed Analysis
Data
Methodology
Results
Discussion
Conclusion
Project Purpose
• Determine the minimum number of scanner
observation points for complete coverage of
desired area.
• Create a 10cm resolution DEM with the goal
of measuring erosion and deposition by
scanning the area before and after storms.
• Saves time in the field if observation points
are determined ahead of time.
Laser Scanning
• Collects tens of thousands of 3D points (x,y,z) per
second.
• Creates a point cloud from which a DEM can be
derived.
• Rotates 360°
• Specifications for this project:
– Height of Instrument: 1.8m
– Range: 150m
Viewshed Analysis
• A viewshed is determined by an observer’s line of
sight.
• If an observer can “see” a point then it is
considered to be within it’s viewshed.
• For DEMs, viewshed is computed by performing
line of sight analysis from the observation point
to each cell within a given distance.
• Can be used for visual analysis or signal analysis,
i.e. cell phone towers
Line of Sight
• Calculating Line of Sight
– Equation for observation point A and target point B
• tanα = (zB-zA)/dBA
– If for any point C between A and B, αc > α, then B is
not visible.
– If for any point C between A and B, αc < α, then B is
visible
Data – Derivation of DSM
• LiDAR points – multiple returns collected each
with x,y,z coordinates
• Extract first return points for use in
interpolation
• Interpolate first return points to create DSM
• DSM (showing vegetation and other above
bare earth features) used in viewshed
analysis.
Data
• elev_lidrurfirst_1m
– 1m resolution raster DSM (interpolated first return LiDAR
points)
• streets_wake
– vector (street centerlines in Wake County)
• streams
– vector (streams in Wake County)
• All data in NC State Plane Coordinates, Units: Meters
• Spatial Extent: North 220750m, South 220000m, East 639000m, West
638300m
*All data obtained from in-class data
Data
Area of Interest
Methodology
• Steps for performing viewshed analysis
1. Determine coordinates for observation point(s)
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Observation points were determined by visually choosing
points that seemed to be good choices and then adjusted
if needed
2. Get height and range of scanner
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Height of Instrument: 1.8m
Range: 150m
3. Calculate Viewshed
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Determine visible cells by line of sight analysis
4. Derive cumulative viewshed to see overall coverage
of scans
Approach
Work Flow Automation
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Create text file of proposed coordinates
Run Python Script - ViewScript.py
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Creates shell script of GRASS commands
3. Run shell script in GRASS
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Develops viewshed for each set of
coordinates and cumulative viewshed
4. Display raster images
Results
8 viewsheds to reasonably cover area of interest
Results
• Cumulative View – Shows combined coverage of all viewsheds
with varying degrees of overlapping.
Red = Areas of High Multiple Overlap
Green = Area of Single Coverage
Discussion
• Most of the open areas are covered with a few small
gaps of 1-5m. Could readjust or add observation points
to achieve total coverage.
• Trees obviously provide the largest problems.
– DSM derived from LiDAR data assumes trees are
somewhat cylindrical in shape with a constant diameter
from top to bottom
– Scanner coverage under canopy with minimal low
vegetation would probably be better than predicted from
viewshed analysis
• Future Study: Would like to find way to have the
software automatically determine suitable observation
points. At this time, visual determination of points
seems most efficient.
Conclusion
• Process of locating multiple observation points and
running viewshed analysis is time consuming when
done on an individual point basis.
• Task made easier by processing a group of points
simultaneously and running analysis through output
shell script.
• Once settled on suitable observation coordinates we
go to the field…
– Verify quality of locations in the field
– Set georeferenced markers in the ground so the same
points can be occupied at later observation times