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es, 
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and 
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of 
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oil 
and 
  
Hi = 0.55. In a consistent way and as 
expected, the spectral response decreased 
from the higher to lower levels of iron 
oxide. The results were darker tones for 
LR and lighter tones for AQ. 
In the case of Hi, the dominant 
factor was the level of moisture for the 
absorption of the infrared radiation. In 
terms of our purely visual 
interpretations of the images, we were 
able to distinguish with confidence the 
LR, LE, and LV soils. The AQ soils were 
confused with the more sandy areas of LV 
soils. PV soils could not be 
distinguished, possibly because of their 
low representation in the study area. 
These results are comparable to 
those of other authors who compared soil 
maps from field work and spectral data: 
Cipra et alii (1980), Lund et ^ alii 
(1980), Harrison and Johnson (1982) and 
Agbu and Nizeyiama (1991). Of note, 
however, is that this current study is 
conducted with completely different soils 
and conditions, being tropical soils in 
Brazil. 
CONCLUSIONS 
For the study area, the presented 
methodology permits us to make the 
following conclusions: 
1.The employed mathematical 
models of JM distances and ISOMIX were 
sensitive and effective for the data 
analyses of these tropical soils. 
2. For areas of exposed soils, 
their spectral character was of extreme 
usefulness for the improvement of the 
quality and precision of the final map. 
3.The methodology shows that it 
is not only possible to redefine the 
limits of the soil units, but also the 
detection and delimitation of associated 
soil units. 
4, The authors believe that the 
high degree of discrimination obtained 
permits the suggestion that the 
methodology is valid for application in 
areas with soils that are more similar to 
each other than are those in the study 
area. 
BIBLIOGRAPHY 
AGBU, P.A.; NIZEYAIAMA, E. 1991. 
Comparisons between spectral mapping 
units derived from SPOT image texture 
and field soil map units. 
Photogrammetric Engineering and Remote 
Sensing, 57:397-405. 
ANDRADE, L.A. 1985 Critérios de seleçäo 
de atributos visando a escolha dos 
quatro canais mais significativos do 
Thematic Mapper. In: 122 Congresso 
Brasileiro de Cartografia, Anais, 
Brasilia - Brazil, Vol 1, pp. 205-226. 
BAUNGARDNER, M.F.; KRISTOF, S.J.; 
JOHANSEN, A.L.; ZACHARY, A.L. 1970. 
Effets of organic matter on the 
multispectral properties of soils. 
301 
Indiana Academy of Sciences, 79:413- 
422. 
BENDAT, J.S.; PIERSOL, A.G, 1986. Randon 
data analysis and measurement 
procedures. John Wiley, N.York, 304p. 
CIPRA, J.E.; FRANZMEIER, D.P.; BRAVER, 
M.E. and BOYD, R.K. 1980. Comparison 
of multispectral measurements from 
some nonvegetated soils using Landsat 
digital data and a spectro radiometer. 
Soil Sci. Soc. Am. J., 44:80-84. 
COLEMAN, T.L.; MONTGOMERY, OL. 1987. 
Soil moisture, organic matter and iron 
content effect on the spectral 
characteristics of selected vertisols 
and alfisols in Alabama. 
Photogrammetric Engineering and Remote 
Sensing, 53:1659-1663. 
CURI, P. 1982. Análise Multivariada. Int. 
Biociencias - UNESP, Botucatu - SP, 64 
P. 
EVERITT, J.H.; ESCOBAR, D.E.;  ALANIZ, 
M.A. and DAVIS, M. 1989. Using 
multispectral video imagery for 
detecting soil surface conditions. 
Photogrammetric Engineering and Remote 
Sensing, 55:467-471. 
HARALICK, R.M.; SHAMUGAN, K.S. 1974. 
Combined spectral and spatial 
processing of  Erts imagery data. 
Remote Sensing of Environment, 3:3-13. 
HARRISON, W.D. and JOHNSON, M.E. 1982. 
Improving mapping unit  delineation 
accuracy using Landsat MSS spectral 
maps. In: Proc. Western Region Tech. 
Work Planning Conf. Nat. Coop. Soil 
Survey, SCS, Washington, D.C., pp. 
112-128. 
IGC - INSTITUTO GEOGRÁFICO E CARTOGRÁFICO 
1982. Mapa Geológico do Estado de Säo 
Paulo. Sáo Paulo, SEPLAN. 
LUND, L.J.; WEISMILLER, R.A.; KRISTOF, 
S.J.; KIRSCHNER, F.R. and HARRISON, 
N.D. 1980. Development of spectral 
mapas for soil-vegetation mapping in 
the Big Desert Area, Idaho. In: Proc. 
Sixth Ann. Symp. on Machine Processing 
of Remotely  Sensed Data. Lab. for 
Application of Remote Sensing. Purdue 
Univ. ,West Lafayette, Indiana, pp. 84- 
96. 
MONTGOMERY, O.L.; BAUNGARDNER, M.F. 1974. 
The effects of the physical and 
chemical properties of soils on the 
spectral reflectance of soils. LARS 
Information Note. Pardue University, 
West Lafayette - USA, 36 p. 
MONTGOMERY,  O.L.;  BAUNGARDNER,  M.F.; 
WEISSMILLER, R.A. 1976. An 
investigation of the relationship 
between spectral reflectance and 
chemical physical ^ and genetic 
characteristic of soils. LARS 
Information Note. Pardue University, 
West Lafayette - USA, 147 p. 
OLIVEIRA, J.B.; MENK, J.R.F.; BARBIERI, 
J.L.;  ROTTA, C.L.;  TREMOCOLDI,  W. 
1982. Levantamento pedológico 
semidetalhado do Estado de Sáo Paulo - 
Quadrícula de Araras. IAC, Campinas - 
SP, 180 p. 
PAGE, N.R. 1974. Estimation of organic 
matter in Atlantic coastal plain soils 
with color-diference meter. Agronomy 
Journal, 66:652—653. 
PARADELLA, W.R. 1984. 
critérios de  selegáo de 
Avaliaçäo de 
atributos