@InProceedings{OliveiraHernBispTeix:2019:PrÁgCa,
               author = "Oliveira, Daniela Ara{\'u}jo de and Hernandez, Fernando Braz 
                         Tangerino and Bispo, Regiane de Carvalho and Teixeira, Antonio 
                         Heriberto de Castro",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and {Universidade 
                         Estadual Paulista (UNESP)} and {Universidade Estadual Paulista 
                         (UNESP)} and {Empresa Brasileira de Pesquisa Agropecu{\'a}ria 
                         (EMBRAPA)}",
                title = "Produtividade da {\'a}gua em cana-de-a{\c{c}}{\'u}car irrigada 
                         e n{\~a}o irrigada utilizando imagens do sat{\'e}lite Landsat 
                         8",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "1183--1186",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Biomassa, evapotranspira{\c{c}}{\~a}o, Saccharum officinarum, 
                         sensoriamento remoto, Biomass, evapotranspiration, Saccharum 
                         officinarum, remote sensing.",
             abstract = "A cultura da cana-de-a{\c{c}}{\'u}car tem grande 
                         import{\^a}ncia econ{\^o}mica para a regi{\~a}o Noroeste 
                         Paulista. Assim, este trabalho avaliou os componentes da 
                         produtividade da {\'a}gua na cultura da 
                         cana-de-a{\c{c}}{\'u}car em condi{\c{c}}{\~o}es irrigada e 
                         n{\~a}o irrigada, a partir de imagens do sat{\'e}lite Landsat 8, 
                         utilizando o algoritmo SAFER (Simple Algorithm for 
                         Evapotranspiration Retrieving) na safra 2016/2017, sendo 
                         calculadas a evapotranspira{\c{c}}{\~a}o (ET), a biomassa (BIO) 
                         e a produtividade da {\'a}gua (PA). Os maiores valores de ET 
                         foram encontrados nos meses de fevereiro e mar{\c{c}}o, tanto no 
                         cultivo irrigado, quanto no de sequeiro, com m{\'e}dias de 2,13 e 
                         2,06 mm dia-1, respectivamente. A varia{\c{c}}{\~a}o espacial de 
                         BIO ficou entre 2,53 e 93,5 Kg ha-1 dia-1 para a {\'a}rea com 
                         irriga{\c{c}}{\~a}o e 1,92 a 90,5 Kg ha-1 dia-1 na cana-de 
                         a{\c{c}}{\'u}car sequeiro, resultando nas maiores m{\'e}dias de 
                         PA de 5,52 Kg m-3 na {\'a}rea irrigada e 5,06 Kg m-3 na {\'a}rea 
                         sem irriga{\c{c}}{\~a}o. ABSTRACT: The sugar cane crop has a 
                         huge economic importance in the Northwest region of S{\~a}o 
                         Paulo. Thus this work evaluated the water productivitys components 
                         in the sugar cane crop in irrigated and non-irrigated conditions, 
                         through images from the Landsat 8 satellite using the SAFER 
                         (Simple Algorithm For Evapotranspiration Retrieving) algorithm in 
                         the 2016/2017 harvest, calculating the evapotranspiration (ET), 
                         biomass (BIO) and water productivity (AP). The highest ET values 
                         were found in February and March, in the irrigated crop as well as 
                         the rainfed one, with averages of 2.13 and 2.06 mm day-1 
                         respectively. The BIOs special range fell between 2.53 and 93.5 kg 
                         ha-1 day-1 for the irrigated area and between 1.92 and 90.5 kg 
                         ha-1 day-1 for the non-irrigated sugar cane, resulting in the 
                         highest PAs average of 5.52 kg m-3 for the irrigated area and 5.06 
                         kg m-3 for the non-irrigated one.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U9SKSB",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U9SKSB",
           targetfile = "97841.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "30 abr. 2024"
}