In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B
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(using Chavez’s DOS method) and transformed in reflectance val
ues. The images were also interpolated to a 5 m resolution us
ing the minimum curvature algorithm. It is visually striking to
see that, apart from a few exceptions, the multi-temporal dataset
shows an almost constant shrinking of the lake surfaces and even
the disappearance of one small water body. Figure 5 illustrates
the difference in lake surfaces for the whole period. The triangu
lar area at the bottom of the 1984 image, was part of the eucalyp
tus plantation and is now regenerating.
Figure 5: Comparison of the lakes for the same time of the year
in 1984 (left) and 2009 (right).
Two lake extraction methods were used: 1) threshold of the pos
terior probability of the maximum likelihood classification and
2) threshold of the modified normalized difference water index
(MNDWI). The former approach yielded far superior results in al
most all images. We attribute this result to the presence of aquatic
vegetation and turbidity (for the Formosa lake) mixed with the
water which tends to increase reflectance in the near and mid- in
frared. Figure 6 shows the extreme example of the Formosa lake
which is outside the State Park and suffers from eutrophication
and aquatic vegetation bloom. Figure 6 should also be compared
with the false color image at the top right of Figure 5.
(a) Classification -5m (b) NDWI threshold -5m
Figure 6: Comparison of the contour extraction methods using
classification (a) and MNDWI threshold (b).
By using the posterior probability of a single water class, we
found that there was always an easily identifiable break between
the water and non-water classes that made the selection of a thresh
old very easy. The threshold was applied to all 50 images and
the area of all six lakes computed for every date. The graph in
Figure 7 shows how these areas have changes between 1984 and
2009. Table 2 gives an over view of the shrinking of the six lakes.
The lake areas of 1990 are also indicated for being the record size
for all lakes. While lake “Pista” has completely disappeared since
2000, four other lakes have lost between 59 and 80% of their area.
The lake “Azul” has somewhat retained much more of its origi
nal area (loss of 29%) and it is also the only lake surrounded by
hydromorphic gley soil with a higher clay content.
Since we did not have reliable elevation data at the time of writ
ing, the areas water surfaces could not be associated with precise
Areas
km 2
Pista
Très
Lakes
Meio
Sede
Azul
Formosa
1990
4962
28778
37413
56402
105389
296237
1984
375
14795
32471
39030
92670
291502
2009
0
2928
7228
12243
65829
170409
% loss
100%
80,2%
77,7%
68,6%
29,0%
58,5%
Table 2: Comparison of the areas of all six lakes between 1984
and 2009 with the shrinking expressed in percentage (1990 was
the record year for all lakes).
Figure 7: Graph showing the evolution of the area of all six lakes
for the period 1984-2009.
altimétrie level measurements. These data will be available at the
third quarter of 2010. Using the digital elevation model (DEM)
from the ASTER sensor, and overlaying the contours over it we
were able to estimate the lowering of the water level for the 1984-
2009 period to about 1 meter for the lake “Azul” and to slightly
over 2 meters for the lakes “Sede”, “Meio”, “Très” and “For
mosa”, being outside the State Park. Figure 8 shows the 1984
and 2009 levels on the ASTER DEM profile.
Figure 8: Water level differences between 1984 and 2009 on an
ASTER DEM profile for lake “Formosa”.
The validation of the data was done using the approach described
in section 2.4. Table 3 shows the validation obtained with both
control datasets (GPS and Ikonos image) and with the two meth
ods of comparison (simple comparison of areas and “intersection
-r- union” approach). As expected, the accuracies with the latter
method are slightly lower but since all accuracies but two are well
above 80%, we conclude that both our extraction method and our
geometric correction are within very acceptable boundaries. Fig
ure 9 shows the contours extracted from the Landsat image of
2010 and the GPS survey coutours for three of the lakes.
3.3 Statistical Testing
Spearman’s correlation test was applied to the area series of all
lakes along with the AW data for the same period. The results