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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
Image Date Hit Rate Hit Rate
(MSAVI) (NDVI)
19/8/1995 99.93 % 99.91 %
29/11/1995 99.84 % 99.51 %
24/11/1996 99.95 % 99.91 %
15/10/1999 96.69 % 96.07 %
Table 4. Percentage of pixels for which the calculated hue lies
inside the characteristic color interval for the selected class.
Considering all the three color components (hue, value and
chroma) at the same time, the comparison gave the following
results:
Image Date Hit Rate Hit Rate
(MSAVI) (NDVI)
19/8/1995 92.76 % 93.52 %
29/11/1995 93.32 9^ 90.5 %
24/11/1996 89.92 % 85.56 %
15/10/1999 90.44 % 89.77 %
Table 5. Percentage of pixels for which the calculated color
(hue, value and chroma) lies inside the characteristic color
interval for the selected class.
It must be noted that the color interval considered for the
selected class is considered large, with respect to hue it varies
from 2.5YR to 10YR.
In a future application we intend to investigate classes
characterized by smaller color intervals, such as the Latossolos
Vermelhos or Latossolos Vermelho-Amarelo.
6. CONCLUSIONS
The results show a good correlation between NDVI, PAVI and
MSAVI (in that order) and Hue. They also show that Hue can
be predicted with a good level of accuracy directly from the
NOAA images
The low correlation between the color components and
emissivity indicates that unaccounted characteristics of soil
have a larger influence on emissivity than color. As emissivity
has been linked with the structure of soils, maybe other factors,
such as texture, roughness or chemical composition can be
better correlated to emissivity.
A fair correlation has been established between Value and
Vegetation Indices (specially MSAVI, NDVI and PAV], in that
order), and a low correlation between Chroma and Vegetation
Indices. That can be partially explained by the higher influence
moisture has on Value and Chroma than on Hue. The
investigation of soil profile records obtained from EMBRAPA
(from the same Central-West Region of Brazil), shows that a
wet soil sample has usually the same Hue, but lower Value and
Chroma values than a dry sample.
Further tests are currently being made to evaluate the capacity
of prediction of soil degradation processes of the proposed
approach. In the future moisture information should be added to
the models, what we believe will improve the results obtained
by the approach.
223
ACKNOWLEDGMENT
The present work is a part of ECOAIR Project (Digital Image
Processing Technology for Change Detection of Environment
Information), sponsored by CNPq — Brazilian National Council
for Scientific and Technological Development (www.cnpq.br)
and INRIA — Institut National de Recherche en Informatique et
Automatique, France. Authors are very much thankful for their
financial support.
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