In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
E are parameters which depend on canopy type. E is a positive 
value. Parameters C and D are dependent on soil moisture. 
4. RESULTS AND DISCUSSION 
Two dates of LAI maps (July 6 and August 21) were near 
coincident with SAR acquisitions on July 2 (ALOS), July 6 
(RADARSAT-2), July 9 (RADARSAT-2) and August 21 
(TerraSAR). With LAI maps derived from optical data, LAI 
was estimated on a detailed pixel by pixel basis. Defmiens 
software was then used to segment these maps into zones of 
homogeneous LAI for each com and soybean field. These 
homogeneous zones were used as the primary sampling units. 
The average SAR backscatter and the mean LAI for each 
sampling unit were extracted for both com and soybean crops. 
4.1 Correlation analysis between SAR data and LAI 
To quantify the relationship between SAR backscatter and LAI, 
and to assess the sensitivity of SAR frequency and polarization 
to this crop growth parameter, correlation analyses were 
conducted. Scattering from within the crop canopy and the 
subsequent scattering back to the radar sensor is related to the 
physical structure of the scattering elements of the canopy, as 
well as their dielectric properties. Consequently a strong 
correlation between plant variables such as LAI and radar 
return has physical meaning. Table 2 provides the simple 
correlation analysis results for each SAR data set. 
Com 
Soybean 
PALSAR/ALOS 
HH 
0.92 
0.28 
HV 
0.96 
0.26 
RADARSAT-2 FQ20 
HH 
0.72 
0.60 
w 
0.79 
0.73 
HV 
0.79 
0.47 
RADARSAT-2 FQ6 
HH 
0.68 
0.80 
w 
0.72 
0.62 
HV 
0.90 
0.58 
TerraSAR-X 
W 
-0.11 
-0.20 
HV 
0.03 
-0.65 
Table 2. Simple correlation coefficients (r) between SAR data 
and LAI. 
4.1.1 SAR backscatter from com crops 
For com, a strong correlation was found for both L-band and C- 
bands. The highest correlation coefficients (r=0.90—0.96) were 
reported for L-HH and L-HV backscatter and for C-HV 
backscatter from the RADARSAT-2 FQ6 mode. Figure 1 plots 
L-HH, L-HV and C-HV backscatter against com LAI. 
Backscatter at these frequencies and polarizations were strongly 
linearly correlated with LAI. The coefficients of determination 
(R2) were 0.92, 0.85 and 0.80 for HV and HH at L-band and 
HV at C-band, respectively. 
Slightly lower correlations (r=0.68—0.79) were reported for 
com for all C-band linear polarizations at the shallower 
RADARSAT-2 FQ20 mode, as well as for the linear like- 
polarizations (HH,W) at the steeper RADARSAT-2 FQ6 
mode. Backscatter at X-band was poorly correlated with com 
LAI (r < 0.03) regardless of polarization. 
corn 
Figure 1 Correlation between L-HH, L-HV and C-HV (FQ6 
mode) backscatter and com LAI. 
4.1.2 SAR backscatter from soybean crops 
For soybeans, SAR backscatter was only weakly correlated 
with LAI. The highest correlations were reported for the C- 
band data (r=0.58-0.80). Backscatter from L-band and X-band 
had no significant correlation with LAI. Figure 2 illustrates the 
linear relationship between HH, W and HV backscatter at C- 
band (RADARSAT-2 FQ6 mode) and LAI. The best 
correlations were observed for C-HH backscatter (R 2 =0.63). 
Figure 2 Correlation between C-band HH, W and HV 
backscatter (RADARSAT-2 FQ6 mode) and LAI. 
In summary, the lower frequencies such as L- and C-band were 
correlated with LAI, while the higher frequency X-band was 
poorly correlated. These results may be explained by the 
wavelength relative to the size of the crop scattering elements, 
but also by the difference in the canopy penetration. High 
frequency X-band provides little canopy penentration. 
4.2 Water cloud model 
The backscatter signal from vegetated surfaces is affected by 
many factors, including the physical structure of the plants and 
the canopy (biomass, leaf size, stem density, LAI, etc.) as well 
as the surface volumetric moisture of the soil below the canopy. 
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