Geography Reference
In-Depth Information
0.4
0.4
Poplar
0.3
0.3
0.2
0.2
0.1
0.1
0
0
TM1 TM2 TM3 TM4 TM5 TM7
TM1 TM2 TM3 TM4 TM5 TM7
0.4
0.4
0.3
0.3
Mixed
riparian wood
0.2
0.2
0.1
0.1
0
0
TM1 TM2 TM3 TM4 TM5 TM7
TM1 TM2 TM3 TM4 TM5 TM7
25 May
2 May
23 April
16 April
15 March
21 February
14 June
5 July
29 August
14 September
10 October
30 November
Figure 10.3
(
continued
).
resolutions) the corresponding disturbing factor must
either cover an area 2
2
10.4 From scientists' tools to
managers' choices: what do
we want to know? And how
do we get it?
4 times the size, or introduce an
effective change in a reflectance that is 4 times the size,
or the product of both must be increased by the same
factor 4. Of course, this simplified approach does not take
into account all of the physical factors that influence the
actual radiative transfers. Rather, it simply reminds us
that both the reflectance change and the surface affected
by the change have to be considered in order to detect an
effective modification in the image. Moreover, when the
area affected by a slight change is close to the pixel area,
the probability of detecting it is very low because it is only
by chance that only one single pixel will be affected. The
change will most probably affect several neighbouring
pixels and the modifications in reflectance will then be
too small to detect.
=
Scientific developments in remote sensing and GIS science
provide many useful tools for riparian vegetation studies:
synoptic and repeated data collection, measurement of
numerous biophysical parameters (notably vertical infor-
mation such as tree height or floodplain roughness by
combining optic and LiDAR data) and a broad-scale
monitoring process. However, the utility and accessibility
of these tools is still an open question; which ones are
really useful and can be easily used by river managers and
decision makers?
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