@InProceedings{RuizAlmeLace:2023:CoClCo,
               author = "Ruiz, Paulo Roberto da Silva and Almeida, Cl{\'a}udia Maria de 
                         and Lacerda, Camila Souza dos Anjos",
          affiliation = "{Faculdade de Tecnologia (FATEC)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and Instituto Federal de 
                         Educa{\c{c}}{\~a}o, Ci{\^e}ncia e Tecnologia do Sul de Minas 
                         Gerais (IFSULDEMINAS)",
                title = "Compara{\c{c}}{\~a}o de classifica{\c{c}}{\~o}es da cobertura 
                         urbana usando redes neurais a partir de cenas Worldview-2 e 
                         Worldview-3",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155468",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 20. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "minera{\c{c}}{\~a}o de dados, redes neurais, 
                         classifica{\c{c}}{\~a}o da cobertura urbana, data mining, neural 
                         networks, urban land cover classification.",
             abstract = "Este estudo tem como objetivo comparar classifica{\c{c}}{\~o}es 
                         de cobertura do solo urbano de sensores orbitais com diferentes 
                         resolu{\c{c}}{\~o}es espaciais e espectrais. Um deles {\'e} o 
                         WorldView- 2 (WV-2), com 0,5 m de resolu{\c{c}}{\~a}o espacial e 
                         8 bandas multiespectrais, e o outro {\'e} o WorldView-3 (WV-3), 
                         que possui 16 bandas multiespectrais e resolu{\c{c}}{\~a}o 
                         espacial de 0,31 m. As classifica{\c{c}}{\~o}es foram realizadas 
                         em duas cenas, cobrindo um transecto dentro do campus da 
                         Universidade Estadual de Campinas, S{\~a}o Paulo. Para cada 
                         conjunto de dados, foram realizadas classifica{\c{c}}{\~o}es 
                         aplicando o algoritmo Multilayer Perceptron, definindo-se 38 e 42 
                         classes de cobertura do solo, respectivamente para o WV-2 e WV-3. 
                         As classifica{\c{c}}{\~o}es obtiveram acur{\'a}cias muito 
                         semelhantes, apresentando {\'{\i}}ndice Kappa superiores a 0,77 
                         e exatid{\~a}o global acima de 75%, com os melhores 
                         {\'{\i}}ndices pertencendo ao WV-3. Dessa forma, conclui-se que 
                         o melhor refinamento espacial e espectral do WV-3 contribuiu para 
                         a obten{\c{c}}{\~a}o de melhores resultados. ABSTRACT: This 
                         study aims to compare urban land cover classifications from 
                         orbital sensors with different spatial and spectral resolutions. 
                         One of them is WorldView-2 (WV-2), with 0.5 m of spatial 
                         resolution and 8 multispectral bands, and the other one is 
                         WorldView-3 (WV-3), which has 16 multispectral bands and 0.31 m of 
                         spatial resolution. The classifications were performed in two 
                         scenes, extending over a transect inside the campus of the State 
                         University of Campinas, S{\~a}o Paulo. For each data set, 
                         classifications were performed by applying the Multilayer 
                         Perceptron algorithm, comprising 38 and 42 land cover classes, 
                         respectively for WV-2 and WV-3. The classifications obtained very 
                         similar accuracies, with Kappa index above 0.77 and overall 
                         accuracy higher than 75%, with the best indices belonging to the 
                         WV-3. Thus, we conclude that the better spatial and spectral 
                         refinement of the WV-3 contributed to obtain the best results.",
  conference-location = "Florian{\'o}polis",
      conference-year = "02-05 abril 2023",
                 isbn = "978-65-89159-04-9",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/4936P65",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/4936P65",
           targetfile = "155468.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "28 abr. 2024"
}