Abstract
Floods may occur in rivers when the flow rate exceeds the capacity of the river channel, particularly at bends or meanders in the waterway. Floods often cause damage to homes and businesses becoming the most prevalent type of disaster in the world and the one with the highest number of events, causing the greatest economic losses, affecting a large number of people. This paper has the objective of mapping and identifying the flooding areas of a selected region in the municipality of Itaqui-RS using remote sensing. In order to do it, we used the Fuzzy ckMeansImage Algorithm to group and to classify the image into similarity clusters. The methodology consists in processing satellite images before and after the flooding occurs. Finally, we discuss the processed images and present the flooded area.
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de Vargas, R.R., Freddo, R., Galafassi, C., Gass, S.L.B., Russini, A., Bedregal, B. (2018). Identifying Pixels Classified Uncertainties ckMeansImage Algorithm. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_36
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DOI: https://doi.org/10.1007/978-3-319-91479-4_36
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