@InProceedings{MacielVinh:2017:CaStMu,
               author = "Maciel, Adeline Marinho and Vinhas, Lubia",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Time series classification using features extraction to 
                         identification of land use and land cover: A case study in the 
                         municipality of Itaqui, South Region of Brazil",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4429--4436",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "One of the main applications in remote sensing is the analysis and 
                         classification of land cover and land use. Sensors, such as MODIS, 
                         are have been largely used for monitoring land cover change due to 
                         its high temporal resolution. Although several studies perform 
                         time series classification by features extracting or similarities 
                         measures to verify annual usage patterns and land cover, a little 
                         has been explored about the extraction of information by focal 
                         neighborhood operation and different sub-intervals of a time 
                         series whole. In order to explore the use of different features 
                         extracted of annual time series, for sub-intervals and focal 
                         neighborhood to identify patterns of land use and land cover, this 
                         work takes the use of statistical measures already extracted in 
                         the context of annual time series and presents an approach to 
                         information extraction for sub-intervals of year and focal 
                         neighborhood to characterise temporal patterns. To demonstrate the 
                         applicability of this study an experiments were conducted to 
                         classify of time series of land use and land cover using EVI MODIS 
                         sensor data, using Random Forest algorithm, where resulted in the 
                         creation of temporal maps identifying temporal patterns.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59305",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM352",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM352",
           targetfile = "59305.pdf",
                 type = "An{\'a}lise de s{\'e}ries temporais de imagens de 
                         sat{\'e}lite",
        urlaccessdate = "27 abr. 2024"
}