Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/102591
Author(s): R. Pisani
K. Costa
G. Rosa
D. Pereira
J. Papa
J. M. R. S. Tavares
Title: River sediment yield classification using remote sensing imagery
Issue Date: 2017-03
Abstract: The monitoring of water quality is essencial to the mankind, since we strongly depend on such resource for living and working. The presence of sediments in rivers usually indicates changes in the land use, which can affect the quality of water and the lifetime of hydroelectric power plants. In countries like Brazil, where more than 70% of the energy comes from the water, it is crucial to keep monitoring the sediment yield in rivers and lakes. In this work, we evaluate some stateof- the-art supervised pattern recognition techniques to classify different levels of sediments in Brazilian rivers using satellite images, as well as we make available an annotated dataset composed of two images to foster the related research.
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
URI: https://repositorio-aberto.up.pt/handle/10216/102591
Source: Pattern Recogniton in Remote Sensing (PRRS), 2016 9th IAPR Workshop on
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

Files in This Item:
File Description SizeFormat 
180621.pdfPaper207.01 kBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.