@InProceedings{BragionGoDaSaOlMoAm:2020:CuAlId,
               author = "Bragion, Gabriel Da Rocha and Gon{\c{c}}alves, Gabriel C. and 
                         Dal'Asta, Ana Paula and Santos, Carolina De Faria and Oliveira, 
                         Lucas Maia De and Monteiro, Ant{\^o}nio Miguel Vieira and Amaral, 
                         Silvana",
          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 {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Traffic Flow at Night: a custom algorithm for identifying basal 
                         nighttime radiance levels of roadways",
            booktitle = "Anais...",
                 year = "2020",
               editor = "Carneiro, Tiago Garcia de Senna (UFOP) and Felgueiras, Carlos 
                         Alberto (INPE)",
                pages = "1--9",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 21. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The recent COVID-19 outbreak drove the attention to methods for 
                         monitoring the flow between settlements, including traffic flow. 
                         Although the remote sensing of nighttime lights is a viable option 
                         to estimate traffic flow derived indicators, changes on radiance 
                         levels at night are not all associated with traffic. This paper 
                         presents the theoretical approach proposed on the development of 
                         an algorithm able to identify spectrally unbiased control samples 
                         for regions of interest (ROI), namely roadway sections. Firstly, 
                         an overview of the algorithm is presented, followed by an 
                         empirical estimation of its time complexity. The results showed 
                         that the algorithm has an O(n) time complexity and that control 
                         samples and ROIs can have similar time series features, indicating 
                         that an analysis without the use of control samples can lead to 
                         biased results.",
  conference-location = "On-line",
      conference-year = "30 nov. a 03 dez. 2020",
                 issn = "2179-4847",
             language = "en",
                  ibi = "8JMKD3MGPDW34P/43PL72H",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/43PL72H",
           targetfile = "p1.pdf",
                 type = "Dados espa{\c{c}}o-temporais",
        urlaccessdate = "28 abr. 2024"
}