Hierarchical multistep remote sensing classification enhances land use mapping accuracy in anthropogenically modified landscapes

Abstract: This study addresses the challenge of accurately classifying land use and land cover (LULC) changes in landscapes influenced by anthropogenic activities. By leveraging multi-temporal satellite imagery and a hierarchical multistep classification approach, we enhance the differentiation of L...

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Publié dans:Boletim de Ciências Geodésicas Boletim de Ciências Geodésicas, Volume: 32, Article number: e2026001, Published: 13 MAR 2026
Auteurs principaux: Domingues, Getulio Fonseca, Silva, Marcos Vinícius de Campos Meneses e, Oliveira, Sofia Corradi, Nero, Marcelo Antônio, Elmiro, Marcos Antônio Timbó, Macedo, Diego Rodrigues, Amaral, Cibele Hummel do
Format: Article
Langue:English
Publié: Universidade Federal do Paraná 2026
Sujets:
Remote sensing
Spectral indices
Landscape monitoring
Classification accuracy
Accès en ligne:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1982-21702026000100602&lng=en&tlng=en
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http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1982-21702026000100602&lng=en&tlng=en

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