@InProceedings{QuirinoPaulOlivSilv:2013:EsPrSe,
               author = "Quirino, Dayanna Teodoro and Paula Neto, Hostilio Maia de and 
                         Oliveira, R{\^o}mulo Augusto Juc{\'a} and Silva, Michely 
                         Cristina da",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Estimativa de Precipita{\c{c}}{\~a}o por Sensoriamento Remoto",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "8676--8683",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "It is very important to conduct studies on rainfall variability 
                         due to its influence on social and economic life of the 
                         population. Such studies enable the development of new methods of 
                         work and even greater interaction between national and 
                         international centers for new technologies. The identification and 
                         quantification of precipitation has not been an easy task, because 
                         of its randomness and large spatial and temporal variability. The 
                         main instruments for monitoring precipitation are: rain gauges, 
                         the rain gauges, radars and sensors that operate on board 
                         satellites. In this work we performed a correlation analysis 
                         between precipitation data obtained from Station 
                         Evaporim{\'e}trica First Class located in the School of Agronomy 
                         at the Federal University of Goi{\'a}s - UFG, in the city of 
                         Goi{\^a}nia-GO, with the TRMM satellite data through the 
                         algorithm 3B42_V7. Were calculated for both data sources, the 
                         daily, monthly, seasonal, annual number of days with precipitation 
                         equal to or below 0.1 mm / day and rain at or above 25mm/dia and 
                         their correlations to assess the data sampled from January 2008 to 
                         December 2011. The results of the correlations found indicate an 
                         interdependence, expressing that the data of the samples analyzed 
                         are compatible making TRMM satellite data a reliable alternative 
                         to rainfall information with spatial and temporal quality.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "1297",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GKBK",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GKBK",
           targetfile = "p1297.pdf",
                 type = "Sensoriamento Remoto e Mudan{\c{c}}as Globais",
        urlaccessdate = "04 maio 2024"
}