**5. Conclusions**

The studies herein presented summarize innovative approaches in the use of spaceborne LHH SAR images such as the ones acquired by the JERS-1 SAR satellite, aiming for the development of an environmental sensitivity index to oil spills adequate for the fluvial variations of Central Amazonia, with an initial application for half of the hydrologic cycle. The JERS-1 SAR mosaics correspond to the low water season (September–October 1995) and the subsequent high water season (May–June 1996).

The USTC algorithm enabled the construction of thematic maps to meet the computational requirements of engineering applications that demand the expeditious identification of flooded area maps. In this work, four classes of interest were considered: water, flooded vegetation, upland forest, and flooded forest.

The risk analysis method using linguistic if-then rules derived from expert knowledge and data statistics proved to be an efficient method for remapping 16 landscape change classes. Consequently, this approach could illustrate the potential risks in the fluvial transportation of oil in environments subject to intense seasonal variations in the water level, such as in the Central Amazon.

The procedure based on symbolic fuzzy modeling performed as expected is that it identified the boundaries of landscape change classes using TESI values. Such an approach considered the radiometric centers pertaining to the 16 landscape change classes defined by backscatter values of dry and flooded JERS-1 SAR mosaics.

Finally, the watershed technique satisfactorily represented the seasonality of the flooding process in the study area, as an aid to the determination of the fluvial sensitivity to oil spills in the Coari region. The achieved results offer a new perspective for the elaboration of products using the SRTM DEM in conjunction with the mathematical morphology and the study of water-level time series in the Amazon region.

## **Acknowledgements**

The authors thank the Brazil's National Agency of Petroleum, Natural Gas and Biofuels (ANP), National Council for Scientific and Technological Development (CNPq), Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), and Federal University of Rio de Janeiro (UFRJ) for their support in the development of this research.

**79**

**Author details**

Luiz Landau<sup>1</sup>

Patricia Mamede da Silva1

(UFRJ), Rio de Janeiro, Brazil

provided the original work is properly cited.

*Overview of Hydrological Dynamics and Geomorphological Aspects of the Amazon Region…*

\*, Fernando Pellon de Miranda1

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and Alexandre Gonçalves Evsukoff 1,2

\*Address all correspondence to: patmamed@lamce.coppe.ufrj.br

1 Laboratory for Computational Methods in Engineering (LAMCE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil

2 Technology Transfer Nucleus (NTT), Federal University of Rio de Janeiro

, Carlos Henrique Beisl1

,

*DOI: http://dx.doi.org/10.5772/intechopen.86592*

*Overview of Hydrological Dynamics and Geomorphological Aspects of the Amazon Region… DOI: http://dx.doi.org/10.5772/intechopen.86592*
