Fechar
Metadados

@InProceedings{SoaresBVUNLKF:2020:PhPaSa,
               author = "Soares, Anderson Reis and Bendini, Hugo do Nascimento and Vaz, 
                         Daiane Vieira and Uehara, Tatiana Dias Tardelli and Neves, Alana 
                         Kasahara and Lechler, Sarah and K{\"o}rting, Thales Sehn and 
                         Fonseca, Leila Maria Garcia",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {University of Muenster} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Stmetrics: a phython package for satellite image time-series 
                         featrue extraction",
                 year = "2020",
         organization = "IEEE International Geoscience and Remote Sensing Symposium 
                         (IGARSS)",
             keywords = "time-series, python, multi-temporal features, remote sensing.",
             abstract = "Producing reliable land use and land cover maps to support the 
                         deployment and operation of public policies is a necessity, 
                         especially when environmental management and economic development 
                         are considered. To increase the accuracy of these maps, satellite 
                         image time-series have been used, as they allow the understanding 
                         of land cover dynamics through the time. This paper presents the 
                         stmetrics, a python package that provides the extraction of 
                         state-of-the-art time-series features. These features can be used 
                         for remote sensing time-series image classification and analysis. 
                         stmetrics aims to be an easy-to-use package. The package is 
                         available under the GNU GPL software license, and the full source 
                         code is available for download at: 
                         github.com/andersonreisoares/stmetrics.",
  conference-location = "Virtual Symposium",
      conference-year = "26 Sept. - 02 Oct.",
             language = "en",
           targetfile = "soares_stmetrics.pdf",
        urlaccessdate = "20 jan. 2021"
}


Fechar