Full text: XIXth congress (Part B7,1)

  
Araujo, Luciana Spinelli 
  
  
w61*30' w61°25° w61° 20° w61° 157 w61° 10° w61° 05” w 61° 00” 
: : n02* 50" 
LEGEND 
Ell Primary Forest 
108.74 - 181.15 ton/ha 
id Secondary Forest 
14.64 - 79.96 ton/ha 
Savanna 
4.23 - 10.73 ton/ha 
n02° 40° ES Pasture 
n02^45 PB n 02*45* 
  
n 02? 40 
  
Bare Soil 
Bl water 
Bl Unclassified 
n02°35 n02°35° 
Cartographic Base: Sheet MI-53/DSG 
Projection: UTM-SAD/69 
; n02°30? A 
w61°30° w61°25° w61° 20° w61°15° w61° 10° w 61*05* w 61? 00" N 
  
  
  
  
Figure 4. Distribution of vegetation cover in the forest and savanna contact zone derived from synthetic SAVI image 
obtained by the ICM classifier algorithm. 
5 CONCLUSIONS 
The SAVI model presents a reasonable performance in the characterization of forested and non-forested areas. 
However, this performance is not significant in the intra-class analysis, with a similarity in the space of spectral 
attributes, mentioning for example, the park savanna and grass/shrub savanna. Taking into account that there is an 
increase on density of forest cover, with greater structural and biomass complexity, the characterization of intra-classes 
using synthetic SAVI image is also difficult. This may be explained by the saturation limit of this vegetation index for a 
certain level of forest canopy closure, where due to the roughness of canopy, there is a higher shade proportion, which 
influences in the intra-pixel response. Actually, it is confirmed that in the relationship between biomass and SAVI 
values, there is not a direct linear behavior with the increase of values from one of these variables, after a certain limit. 
In a synoptic view, the synthetic SAVI image can be accepted for a initially approach in the spatial distribution of 
vegetation cover types and their corresponding biomass, in this region of forest and savanna contact zone. However, 
new digital processing techniques must be searched especially for identifying new parameters to constitute the 
vegetation indices, in order to make the optical image an effective tool for forest inventory in tropical regions. 
ACKNOWLEDGMENTS 
This project was conduced with the financial support by Fundacáo de Amparo à Pesquisa do Estado de Sáo Paulo- 
FAPESP (process number 1997/0943-8). The authors acknowledge CNPq (process 300677/91, 300808/94-1, 
380597/99-3) and CPAF-RR/EMBRAPA. 
REFERENCES 
Araujo, L.S., 1999. Análise da cobertura vegetal e biomassa nas áreas de contato floresta/savanna a partir de dados 
TM/Landsat e JERS-1. Instituto Nacional de Pesquisas Espaciais - INPE, Sáo José dos Campos. 120 p. Dissertaçäo de 
Mestrado em Sensoriamento Remoto. 
Araujo, L.S.; Santos, J.R.; Freitas, C.C.; Xaud, H.A.M., 1999. The use of microwave and optical data for estimating 
aerial biomass of the savanna and forest formations at Roraima State, Brazil. IGARSS'99 — Remote Sensing of the 
System Earth: A Challenge of the 21* Century. [CD-ROM]. IEEE 1999 International Geoscience and Remote Sensing 
Symposium. June 28th—July 2th, 1999. Hamburg, Germany. 
  
80 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.
	        
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