Full text: XVIIIth Congress (Part B7)

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Slope Steepness (S) were integrated to form the Natural 
Erosion Potential (NEP) for the area under study and they 
were divided into three levels : low, medium and high. 
The integration of A (soil loss suitability) and At 
(tolerable index) data, allowed the discrimination of areas 
under erosion process (EP) and areas without erosion and 
areas of high erosion risks on the timeframe 1988 - 1994. 
Table 2 presents the quantitative results of critical areas 
and non-critical areas and it is possible verify that for the 
year 1994 there is an increase of critical area (58.6796 to 
65.98). 
  
Classes 1988 1994 
Area (ha) | Area (%) | Area (ha) | Area (%) 
  
  
Critical Areas 5616.57 58.67] 6316.56 65.98 
  
Non- Critical 3956.90 41.33] 3256.91 34.02 
  
  
  
  
  
  
Areas 
  
  
and land 
such as 
(L) and 
Table 2 - Quantitative assessment of areas submitted to 
erosion processes in 1988 and 1994. 
This fact is associated mainly to the reduction of 
reforestation and natural vegetation areas as well as to the 
increase of areas planted with summer crops and pasture 
that present lower soil erosion protection when compared 
to reforestation and natural vegetation areas. 
The analysis of the NEP and EP maps for the two dates 
shows that the class with high NEP coincides with areas 
of high erosion risks, although there are areas that present 
high NEP but without erosion risks due to the presence of 
natural vegetation and reforestation. The EP maps allows 
the verification of the influence of land use changes on 
the erosion process and shows the importance of this kind 
of information as an input for environmental and 
agricultural planning of watersheds. 
4. CONCLUSIONS 
This study shows that, for small watersheds it is possible 
to monitor soil erosion processes using the USLE model 
and geoprocessing techniques. The temporal analysis of 
these areas submitted to erosion risks shows that the most 
critical areas are mainly associated with summer and 
perennial crops, growing in incompatible conditions to 
the land use capability of these areas. 
5. REFERENCES 
Bertoni, J.; Lombardi Neto, F., 1985. Conservacáo do 
solo. Piracicaba, Livroceres, 285p. 
Bocco, G.; Valenzuela, C.R., 1988. Integration of GIS 
and image processing in soil erosion studies using 
ILWIS. ITC Journal, (4): 309-319. 
239 
Castro, A.G., 1992. Técnicas de sensoriamento remoto e 
sistemas de informagdo geográfica no estudo integrado 
de bacias hidrográficas. Msc. Thesis, INPE, Sáo José dos 
Campos, Brazil. 94p. 
Donzeli, P.L.; Valerio Filho, M.; Pinto, S.A.F.; Nogueira, 
F.P.; Rotta, C.L.; Lombardi Neto, F., 1992. Técnicas de 
sensoriamento remoto aplicadas ao diagnóstico básico 
para planejamento e monitoramento de microbacias 
hidrográficas. Campinas, Brazil, Instituto Agronómico de 
Campinas. Documentos IAC (29), 91-119. 
Mellerowicz, K.T.; Rees, T.L.; Chow, T.L.; Ghanem, I.., 
1994. Soil conservation planning at the watershed level 
using the Universal Soil Loss Equation with GIS and 
microcomputer technologies: a case study. Journal of Soil 
Water Conservation, 49(2): 194-200. 
Olson, K.R.; Lal, R.; Norton, L.D., 1994. Evaluation of 
methods to study erosion-productivity relationships. 
Journal of Soil and Water Conservation, 49(6): 586-590. 
Pinto, S.A.F., 1991. Sensoriamento remoto e integracáo 
de dados aplicados no estudo da erosáo dos solos: 
contribuicáo metodológica. Doctor Thesis, Sáo Paulo. 
Universidade de Sáo Paulo, Brazil 122p. 
Valerio Filho, M.; Donzeli, P.L.; Pinto, S.A.F., 1993. 
Remote sensing and data integration to evaluate the 
potential soil erosion and land capability. In: 
International Symposium on Remote Sensing and Global 
Environmental Change, Graz, Austria, (2) 678-685. 
Ventura, S.J.; Chrisman, N.R.; Connors, K.; Gurda, R.F.; 
Martin, R.W., 1988. A land information system for soil 
erosion control planning. Journal of Soil and Water 
Conservation, 43(3): 230-233. 
Wischmeier, W.H.; Smith, D.D., 1978. Predicting rainfall 
erosion losses - a guide to conservation planning. 
Agriculture Handbook, 537, U.S. Department of 
Agriculture, Washington, 58p. 
Zhou,Q., 1989. A method for integrating remote sensing 
and geographic information systems. Photogrammetric 
Engineering and Remote Sensing, Falls Church, 
55(5):591-596. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996 
 
	        
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