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The Influence of Coastal Saltmarsh Vegetation on LiDAR Elevation Measurement Accuracy


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Davidson, AM (2010) The Influence of Coastal Saltmarsh Vegetation on LiDAR Elevation Measurement Accuracy. Research Master thesis, University of Tasmania.

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The recent availability of airborne LiDAR data covering the most populated areas of
Tasmania’s coastal zone has stimulated considerable interest in its potential for a
range of applications including land use planning, ecosystem research, coastal
development policy and building codes, emergency response planning, and
communications, particularly given the heightened awareness of impending climate
change and sea level rise impacts on the coastal zone. Acquired for the Climate
Futures for Tasmania project, the data provides high accuracy, high resolution
elevation measurement not previously available in broad-scale terrestrial elevation
data. A stated vertical accuracy of ± 25 cm makes the data better suited to detailed
assessments and decision making than alternative large area digital terrain datasets.

However, the levels of accuracy stated in LiDAR data specifications usually apply to
best-case vertical accuracy assessments for open, level terrain. Interference from
above-ground features such as vegetation is known to reduce the reliability of LiDAR
elevation measurements. In particular, low-lying, dense vegetation cover poses
significant challenges for automated and semi-automated vegetation filters and
elevation correction algorithms. Existing approaches to the separation of ground from above-ground LiDAR returns have not been universally successful due to the
constraints of sensor system hardware capabilities, ineffective data filtering
techniques, and the inability of laser pulses to fully penetrate closed canopy
vegetation. The Climate Futures for Tasmania data provides evidence of the
misclassification of laser returns due to sensor system and data processing

The broad aims of this study were to apply ground truthing to quantify the influence of low saltmarsh vegetation on the quality of Climate Futures for Tasmania data, to
investigate a method for separating ground and low vegetation returns to improve
ground elevation estimation, and to construct digital elevation, canopy surface and
canopy height models using separated ground and vegetation returns.

Results from the study concluded that the classified point data and digital elevation
model provided to the Climate Futures for Tasmania project contained statistically
significant elevation errors for the areas tested. For vegetated terrain, strong linear relationships between surveyed and LiDAR elevations were not evident. The
approach adopted to separate ground and vegetation returns was not effective in
significantly improving the accuracy of digital elevation modelling over the saltmarsh
platform. While vegetation-related elevation error was significant for each vegetation
group assessed, no significant difference was detected between groups. The
variability of vegetation height and structure within the marsh, combined with
uncertainty in the geolocation of the LiDAR footprint, were identified as primary
impediments to a more reliable assessment of vegetation influences on LiDAR
accuracy. Upward bias in LiDAR ground elevation coupled with a reduction in
vegetation height measurement due to laser infiltration of the upper canopy resulted
in a significant underestimation of vegetation height.

Item Type: Thesis (Research Master)
Date Deposited: 08 Dec 2010 00:11
Last Modified: 11 Mar 2016 05:53
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