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BRIAR: Biomass Retrieval in Ireland Using Active Remote Sensing (2014-CCRP-MS.17)
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2021-11-23
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Stuart Green, Shafique Martin, Saeid Gharechelou, Fiona Cawkwell and Kevin Black. BRIAR: Biomass Retrieval in Ireland Using Active Remote Sensing. EPA, 2019
Abstract
Biomass Retrieval Using Active Remote
Sensing
Hedgerows are a very significant component of the
Irish landscape. They perform multiple functions,
acting as boundary markers, acting as stock-proof
fencing, supporting bio-diversity and controlling run-off.
They function as reservoirs of above-ground biomass
and their potential as carbon sinks was explored in an
earlier study which found that hedgerows potentially
sequester 0.5–2.7tCO2
/ha/year.
The earlier study used light detection and ranging
(lidar) scanning to build 3D models of hedgerows to
successfully estimate biomass, but at the time the
cost–benefit of doing so was poor. However, this
has since changed with the availability of free lidar
sources and the reduced cost of commissioning/
acquiring lidar data. The purpose of the present study
was to examine the use of another active remote
sensing tool, imaging radar, to estimate biomass in
hedgerows.
The study area around Fermoy in County Cork was
field surveyed using new drone technology to collect
data on a sample of hedgerows from which estimates
of biomass could be drawn. These field estimates were
used with new high-resolution TerraSAR-X Staring
Spotlight (TSX-SS) radar imagery to model hedgerows
directly from radar backscatter.
The study found that hedgerow biomass cannot be
derived directly from radar backscatter. There were
a number of reasons for this, such as the hedgerow
biomass density, with an average of 10kg/m2
, being
above the threshold of saturation for radar in the
X-band frequency range. However, other radar
sensors with lower frequencies, and thus higher
saturation limits, do not have the spatial resolution to
map hedgerows.
An alternative method of investigating hedgerow
structure, and thus inferring biomass, interferometry,
is not successful as the level of coherence between
the observations in our dataset was too low to build
a 3D model (i.e. the backscatter from the hedgerow
changed too much between observations).
A new method that examines the cross-sectional
response of the radar return across a hedgerow was
shown to be successful at modelling the relationship
between the width of the backscatter profile and the
width of the hedgerow. However, this too was sensitive
to the orientation of the hedgerow to the sensor.
Therefore, this study shows that radar data does not
seem to be an appropriate technology for estimating
hedgerow properties in Ireland.
In order to estimate the national stock of hedgerow,
the new Prime2 spatial data storage model (OSI,
2014) was applied in conjunction with developed
maps showing the probability of a field boundary being
a stone wall or a hedgerow, to give a new national
estimate for hedgerow length in Ireland of 689,000km.
This estimate is double the frequently quoted figure
of 300,000km because of a much wider definition of
“hedgerow” used in this report.
Net change in hedgerow length was examined using
the aerial photographic records from 1995, 2005 and
2015, along with county-level survey records, showing
that there has been a net removal of hedgerows
between 1995 and 2015 of between 0.16% and 0.3%
per annum, although the rate is much slower in the
latter half of that period.
As X-band radar seems to be inappropriate for
hedgerow evaluation (especially for the obvious case
of the identification of the complete removal of large
hedgerows, for which it is much more expensive
and time-consuming than the detection of hedgerow
removal using aerial photography), the existing
national lidar surveys from the Geological Survey of
Ireland were examined for their appropriateness for
hedgerow evaluation. A digital canopy model derived
from these data successfully estimated heights (mean
and maximum) in the trial test site, with an r
2
value
of 0.79.