This post is in response to the question: "Do the scientists find it is
sufficiently accurate to give them measurements at the needed accuracy and at
I will touch on the accuracy question first, and then the costs question.
First, the accuracy question. Tree attributes such as height, dbh (diameter at
breast height), height to live crown, species, age, location, basal area,
volume, biomass growth and leaf area index have been measured in the field in
forest plots for over 100 years. Many of these attributes can be measured
directly using LiDAR data, and some can be inferred from lidar data. Stand
attributes such as age, trees per hectare, mean diameter and height, dominant
height, volume per hectare, form factor, annual increment per hectare and growth
have also been estimated from individual plot data for some time. Again many of
these can be measured from processed LiDAR data. Accuracy, which is usually
estimated by comparing ground data from a series of plots with lidar values,
varies with species, density, topography, lidar equipment. For example, in our
SNAMP project, preliminary analysis shows r2 of 0.78 for tree height, and 0.65
for dbh. A clear technical advantage of lidar is the ability to completely
inventory the forest, instead of collecting a sample of plots that might not be
representative of forest heterogeneity. The derived data products that come from
lidar can easily be used at multiple scales (and resolutions) as direct inputs
to fire models and environmental niche models. The field plot-based approach
requires interpolating between these sampled plots to generate a continuous
Second, the costs question. There is more information on the cost-benefits of
lidar for topographic mapping and construction. For forestry applications,
however, there is less information on the relative costs of lidar vs field
capture. The cost of lidar includes acquisition, field data collection, and
processing, which includes software and hardware as well as personnel. These
can add up. Most comparisons of lidar vs. field alone concentrate on the
technical advantages highlighted above. One exception is Renslow et al. (2000)
who claim that for a typical even-aged, managed forest of 500,000 acres where in
each year, 2% of 10,000 acres (200 acres) are sampled to determine what
management steps are needed, cost savings with lidar would be $15,400 annually.
I think this is overly optimistic, as it only includes 2 weeks for analysis.
Our SNAMP analysis (albeit over a much larger area) takes considerably longer.
So, in proto-conclusion, I think the advantage of lidar is clearly in its
accuracy and coverage, and these outweigh any cost savings that a fast and cheap
field campaign might provide. Still, I will come back to this topic later with
more analysis from our SNAMP project.
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