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The relationship between biodiversity loss and the impacts on ecosystem services of tropical forests, in face of the ongoing
global climate change needs to be better quantified. In this work, we considered the concept of Ecosystem Integrity (IE),
which represents the connection of biodiversity with the ability of ecosystems to sustain the processes of self organization.
Bayesian Networks (BBN-Bayesian Belief Network) can provide metrics for the generation of ecosystem integrity index, from
the training of probabilistic relationships of evidence obtained through field data, Remote sensing data and GIS. The objective of
this work is to present the methodological approach and the results of IE mapping, elaborated at the regional scale for different
patterns of phyto-ecologic landscape of the Brazilian Amazon. The modeling was based on learning from the parameters (datadriven
model) through the use of the Expectation Maximization algorithm. For the validation of this probabilistic model, an
evaluation was carried out in controlled areas, with field observation and comparison with the IE model based on knowledge
(knowledge driven), prepared by experts.
Biography
Margareth Simoes is a senior researcher at Embrapa where is the coordinator of several Projects on Geomatics for Environmental and Agriculture Planning.
From 2010-2012 she was a researcher at Embrapa LabEx Europe Program, where was responsible for the research area of Agriculture Sustainability and Natural
Resources, coordinating projects and international articulations in Europe. By that time, she was a research fellow at la Maison de la Télédétection (UMR TETIS
Territoires, Environnement, Télédétection et Information Spatiale). She is also professor at the Department of Computer Engineering and thesis supervisor at the
Post graduate (Ph.D.) Course on Environment at Rio de Janeiro State University, Brazil.
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