2016
DOI: 10.1016/j.pce.2015.12.004
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Land use mapping from CBERS-2 images with open source tools by applying different classification algorithms

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Cited by 9 publications
(5 citation statements)
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“…This algorithm is one of the most used and it is based on a consideration of statistical parameters (average and standard deviation) to calculate the probability of the pixel belonging to a certain class of soil coverage (Sanhouse-García et al, 2016). The classification was performed using the ENVI 4.8 software, through image interpretation and the collection of training samples and accuracy.…”
Section: Methodsmentioning
confidence: 99%
“…This algorithm is one of the most used and it is based on a consideration of statistical parameters (average and standard deviation) to calculate the probability of the pixel belonging to a certain class of soil coverage (Sanhouse-García et al, 2016). The classification was performed using the ENVI 4.8 software, through image interpretation and the collection of training samples and accuracy.…”
Section: Methodsmentioning
confidence: 99%
“…O algoritmo adotado para a classificação da imagem foi o da Máxima Verossimilhança, que considera parâmetros estatísticos para calcular a probabilidade de um pixel pertencer a certa classe de cobertura do solo (Sanhouse-García et al 2016). Foram estabelecidas quatro classes de uso e cobertura da terra: (I) Vegetação Natural, (II) Afloramento Rochoso, (III) Áreas Antropizadas e (IV) Cursos Hídricos, conforme descritos na Tabela 1.…”
Section: Procedimentos Metodológicos: Cobertura E Uso Da Terraunclassified
“…A classificação supervisionada da Janela Amostral foi feita pelo método Maximum Likehood. Este algoritmo é um dos mais usados e é baseado na consideração de parâmetros estatísticos para calcular a probabilidade de um pixel pertencer a certa classe de cobertura da terra (SANHOUSE-GARCIA et al, 2016).…”
Section: Dados E Procedimentos Metodológicosunclassified