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Pasolli_TU1_TO3.4.pptx
1.
2.
3.
4.
5.
Mountain landscape (Alpine
area)
6.
7.
Estimation of vegetation
biomass (forest)
8.
Investigation on the
influence of soil and vegetation parameters in connection to natural hazard in Alpine regions.
9.
10.
11.
flood and landslide
prediction
12.
13.
sensitivityof microwave signals
on different target properties (moisture content, roughness, vegetation, land use)
14.
15.
16.
17.
18.
Land use
19.
20.
21.
DEM geocoded, filtered
(Frost 7x7)
22.
23.
NDVI map extracted
from MODIS Terra images (pixel size 250 m)
24.
25.
26.
27.
28.
29.
Polarimetric backscattering coefficients
30.
Polarimetric Combinations: Span
(HH+HV+2HV), Polarization Ratio (HH/VV) and Linear Depolarization Ratio (HV/VV)
31.
Polarimetric phase difference
(PPD) and interferometric coherence
32.
Polarimetric Decompositions
33.
H/A/αdecomposition
34.
Generalpurposefeatureextractiontechniques
35.
36.
37.
RetrievalAlgorithmSettings:
38.
SVR withGaussian RBF
kernelfunction
39.
Hyper-parametersranges: 10-3 <
γ < 103 , 10-3< C < 103 , 10-3 < ε < 10
40.
Multi-objectives model selection
according to RMSE and R2 quality metrics
41.
Performance assessment on
17 independent test reference samples according to:
42.
Root Mean Squared
Error (RMSE)
43.
Determination coefficient (R2)
44.
45.
Generation ofsoilmoisturecontentmapsassociatedwith RADARSAT
2 SAR imagestimeseriesacquiredduringsummer 2010
46.
47.
48.
49.
50.
51.
52.
53.
54.
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