Comparison of PBIA and GEOBIA Classification Methods in Classifying Turbidity in Reservoirs

Author:

Facco Douglas Stefanello1,Guasselli Laurindo Antonio1,Ruiz Luis Fernando Chimelo2ORCID,Simioni João Paulo Delapasse1,Dick Daiane Gerhardt3

Affiliation:

1. Research Center on Remote Sensing and Meteorology (CEPSRM), Federal University of Rio Grande do Sul (UFRGS), Bento Gonçalves Avenue, 9500, 91501-970, Porto Alegre, Brazil;

2. Superior School of Agriculture “Luiz de Queiroz” (ESALQ) University of Sao Paulo (USP), Pádua Dias Avenue, 11, 13418-900, Piracicaba - SP, Brazil;

3. Hydraulic Research Institute (IPH), Federal University of Rio Grande do Sul (UFRGS), Bento Gonçalves Avenue, 9500, 91501-970, Porto Alegre, Brazil

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Reference132 articles.

1. Acharya TD, Lee DH, Yang IT, Lee JK. 2016. Identification of water bodies in a Landsat 8 OLI image using a J48 decision tree. Sensors. Jul;16(7):1075.

2. Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adeli H. 2018. Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals. Computers in biology and medicine. 1;100:270-8.

3. Alpaydin E, 2014. Introduction to Machine Learning (3rd ed.), The MIT Press, Cambridge, MA.

4. Alsdorf DE, Rodríguez E, Lettenmaier DP. 2007. Measuring surface water from space. Reviews of Geophysics. Jun;45(2).

5. Alves ED, Accioly ID, Cavalcanti Junior ED, Menezes R, da Silva EA, da Silva AB. 2014. Mudanças no uso e na cobertura do solo em uma área piloto da mesorregião agreste de Pernambuco. Geotecnologias: inovações e desenvolvimento: anais. p. 487-493. Simpósio regional de geoprocessamento e sensoriamento remoto. Brasil (SE) Aracaju: UFS.

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