dos Santos, Joào Roberto 
  
BIOMASS ESTIMATION OF FOREST AND SAVANNA TRANSITION VEGETATION ZONE BY 
JERS-1 AND SIR-C BACKSCATTER DATA 
Jodo Roberto dos SANTOS', Manfred KEIL’, Luciana Spinelli ARAUJO!, María Silvia PARDI LACRUZ/!, 
Julia Charlotte Marie KRAMER’, Otto KANDLER® 
"National Institute for Space Research — INPE, Brazil 
{jroberto: lucian; lacruz@ltid.inpe.br } 
? German Aerospace Center (DLR), German Remote Sensing Center (DFD) 
? Geographical Institute, University of Mainz, Germany 
Working Group VII/7 
KEY WORDS: Tropical Rain Forest, Savanna, Biomass, Inventory, Microwave Data, Amazonia. 
ABSTRACT 
The inventory and monitoring of transition zones between tropical rain forest and savanna formations in Brazilian 
Amazonia are an essential step for an accurate analysis of global change and biodiversity studies. The objective of this 
study is to analyse the empirical behaviour of the biomass from forest/savanna transition zones referring to backscatter 
signals of JERS-1 and SIR-C images. The complementary objective is to discriminate among vegetation types and to 
map the distribution of its’ biomass using both sensors. The area under study is located in Mato Grosso State (Brazil), at 
the border with Rondónia State, representing a contact zone where typical botanical species of both formations are 
intermingled. The SIR-C and JERS-1 images were georeferenced, based on a bilinear method and the pixel resampling 
was made to get a spatial resolution of 25 m. Comments were made related to the physiognomic-structural details of 
vegetation types and spatial distribution of backscatter at primary forest, tall woodland, savanna woodland, tree and/or 
shrub savanna. The relationship between backscatter and biomass values is based on the analysis of their adequacy into 
a regression model where these variables were adjusted. Using the logarithm regression model, the results show that 
SIR-C data present the highest determination coefficient, specially the Lay band (r^ — 0.8275) when compared to the 
Lun band of JERS-1 data (r” = 0.6791). Considering the same polarization (Ly), the SIR-C data (r — 0.7406) is also 
better than JERS-1 data. The methodological approach used in this study can be very useful to determine the dynamics 
of the biomass, taking into account the settlement of humans that occurred in the contact zones of forest and savanna in 
Amazonia. 
1 INTRODUCTION 
INPE, the Brazilian Institute for Space Research, which is related to the Ministry of Science and Technology (MCT), 
has got the mission to estimate the yearly gross deforestation rate, contributing to the Ministry of Environment (MMA), 
on the deforestation control. Considering a yearly deforestation rate of 17,000 km /year, and that approximately 7596 of 
this amount is located at the so-called “Deforestation Arch”, it is evident that it a higher attention is necessary to control 
those forest/savanna transition areas, where there is the highest concentration of human activities. Besides the clear-cut 
of forest areas, in order to insert them in the agricultural or cattle raising production system of the country, the 
environmental degradation is also due to forest fires and to timber logging activities. All these actions contribute to the 
dynamics of biomass in this region. 
Within this context, the objective of this study is to analyse the behaviour of the biomass at forest/savanna contact 
zones, considering backscatter signals of JERS-1 and SIR-C images. Statistical tests at regression models were used to 
improve the understanding of the empirical relation between field data (biomass) and those derived from radar images. 
The complementary objective of this study is to delineate the vegetation types and to map the distribution of its’ 
biomass using data from both sensor systems. The concept of this study is inserted in the Scientific Cooperation 
Program Brazil-Germany (within the project “Multisensoral Remote Sensing Studies for Rainforest and Landuse 
Monitoring”), where research groups of INPE and DLR are evaluating different sensor products and testing new image 
processing techniques, aiming to use them for the inventory and environmental monitoring in tropical areas. 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000. 377