multi-pass derived hg, to estimate vegetation canopy height. In
addition, accuracy of single- and multi-pass hg, as an estimate
of vegetation height derived across three incidence angles (NR,
MR, and FR) for five vegetation classes were compared against
in situ measurements of vegetation canopy height. This was
accomplished by a statistical analysis over vegetated land cover
(shrub, deciduous, coniferous, mixed forest, and wetland) of
diverse eco-regions (arid and temperate).
Commercially available X-band InSAR data products are
rapidly being acquired for a large number of countries under the
NEXTMap program and via the Tandem-X global mission, and
so are becoming increasingly available to users. Further
investigation using single-data take data is warranted to aid in
the understanding of potential incidence angle effects in
Astrium spaceborne Tandem-X data, which will have global
coverage by 2015.
The InSAR side-looking geometry created additional errors in
InSAR scattering phase centre height estimates of the single-
data take data, and requires further investigation to better
understand potential reasons for the vegetation canopy height
underestimation at X-HH InSAR. Furthermore, although the X-
HH InSAR NEXTMap scattering phase centre heights are
strongly correlated with field-observed measurements, with the
best accuracies found in the FR, tree heights are underestimated.
Therefore, further calibration of scattering phase centre heights
is required to provide better estimates of InSAR-derived
vegetation canopy heights across all incidence angles.
The Tandem-X (e.g. X-band InSAR from space) mission is
generating a consistent global digital surface model (DSM) with
accuracy equalling or surpassing the HRTI-3 specification (12
m GSD, 10 m LE90%, and 3 m CE90%) for use in a host of
applications (Krieger et al, 2007; Moreira et al, 2004).
Multiple data-takes of these DSM data combined with an
accurate elevation dataset may be used to, for example, derive a
global vegetation canopy height model to improve biomass
estimations to inform the United Nations REDD»- initiative
(Reducing Emissions from Deforestation and Degradation) in
support of climate change mitigation, and to assist forest
management applications.
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