In: Wagner W„ Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
Figure 6: Segmentation result. The best finding was acquired 
using all Ikonos’ bands. 
Figure 6 shows the 50m buffered Ikonos scene. The riparian 
forest consists of all trees within this buffer. The polygons in 
green are validation data and those in red were obtained with 
MAGIC. 
The MAGIC segmentation result points to a high visual 
correspondence with the validation data like in zoom window (a). 
The MAGIC was able to segment some features like individual 
trees (zoom window (d)). However, some individual features or 
narrow areas were not segmented properly (zoom windows (c) 
and (b)). 
3.2 Biophysical Riparian Forest Modelling Results 
From the initial 70 plots, only 62 were used to obtain the average 
spectral and texture values. The remaining eight plots were 
partially located outside the riparian mask and had to be 
withdrawn. 
The statistical correlations results (adjusted R 2 ) between spectral 
data, textural data and the allometric and structural measurements 
of the plots are presented in Table 7: band 3 indicates that the 
texture features were computed from the red spectral band and 
band 4 the infrared band. The red band is much more related with 
allometric parameters than the infrared band for which only the 
LAI had some success. Basal area and volume obtained the best 
overall results with R 2 =0.61 and R 2 =0.66, respectively. The 
results show better correlations when using an 11x11 pixel 
window for the parameters DBH, Basal Area and Volume. The 
most successful distance between pixels is d=4, which showed 
better results with Basal Area, Volume, DBH and LAI. The best 
mathematical model for each allometric parameter is presented in 
Equation 2 to 8. 
Band 3 
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wll/d3 
0.34 
0.52 
0.50 
0.64 
0.07 
0.32 
0.45 
wll/d4 
0.44 
0.24 
0.61 
0.66 
0.13 
0.33 
0.41 
wl5/d3 
0.39 
0.30 
0.36 
0.42 
0.20 
0.44 
0.46 
wl5/d7 
0.52 
0.29 
0.49 
0.63 
0.04* 
0.34 
0.40 
w20/d4 
0.49 
0.34 
0.52 
0.48 
0.16 
0.20 
0.40 
w30/d3 
0.25 
0.19 
0.21 
0.27 
0.45 
0.39 
0.45 
Band 4 
w30/d4 
0.16 
0.20 
0.19 
0.09 
0.05 
0.41 
0.54 
Table 7: The correlations results for band 3 and 4 (adjusted R 2 
with p test value < 0.05). The left column shows the window 
size (w) and the lag distance between pixels (d). Boxed values 
are significant at p>0.05. 
Height = 64.6 - 0.001 con 90 - 0.00574 enti 35 - 0.0055 asm« 
- 0.0065 ent 90 + 0.00128 idm I35 + 0.00064 coni 35 (2) 
DBH= 184 - 0.0397 ent 90 + 0.0584 B - 0.0662 R 
+ 0.126 cor 0 - 0.0786 cor 135 - 0.0103 asm 90 
+ 0.0037 idm ]3s - 0.005 idm 0 - 0.00246 con 45 (3) 
Basal Area = 0.0569 + 0.000002 asm 135 + 0.000001 IR 
- 0.000004 asm4 5 - 0.000013 ent 45 (4) 
Volume = 80.7 + 0.00304 asm 13s - 0.00555 asm^ 
- 0.0187 ent 45 (5) 
Density = 0.018 - 0.000287 con 90 + 0.000137 con 45 
-0.000190 coi*i 35 + 0.000081 idm« - 0.000531 ent 135 
+ 0.000094 con 135 + 0.000547 ent 45 (6) 
Canopy Openness = - 1129 + 0.214 ent 90 + 0.136 R 
- 0.0865 cor 135 + 0.0137 con 135 + 0.143 asm 90 - 0.101 G (7) 
LAI= 0.556 - 0.00203 R + 0.000573 con 0 - 0.00337 cor 0 
+ 0.000695 idmo - 0.000119 asm 90 + 0.00354 cor 45 (8) 
The direction is not a determining factor in the models and 
none appear to occur predominantly. It is also difficult to 
pinpoint a single co-occurrence measurement that stands out. 
In models with few parameters, the ASM seem to be 
reoccurring (Eq. 4 and 5). Entropy seems to come in second 
place. It is likely that the diversity of measurements is the best 
asset of these models and accounts for their strength. When 
all texture features are analyzed together, it can be verified 
that Second Angular Moment and Entropy are predominant 
for the best results (basal area and volume). These models are 
but indicative of the condition of the riparian forest and are 
probably not directly applicable in another region. However, 
but they can be used regionally to orientate the riparian 
restoration efforts that are currently being undertaken in 
various watersheds of Northern Minas Gerais by the Forest 
Institute of MG.