@InProceedings{BrandãoGregManj:2017:GeToSp,
               author = "Brand{\~a}o, Ziany Neiva and Grego, Celia Regina and Manjolin, 
                         Rodolfo Correa",
                title = "Geoestatistical tools and spectral measurements from AWiFs data 
                         for evaluation of N and P contents in cotton leaves",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2408--2415",
         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 = "Satellite images and geostatistics are useful tools to assess the 
                         nutritional status of plants, and thus, understanding the 
                         variability of cotton yield in farmers'' fields. The resulting 
                         kriged maps provide a unique opportunity to overcome both spatial 
                         and temporal scaling challenges and understanding the factors that 
                         led to crop yield. To support decisions on improving cotton yield, 
                         this study combines the conventional statistic analysis, spatial 
                         regression modeling of georreferenced data and AWiFs'' vegetations 
                         indices assessment. The experiments were carried out in a 47.4 ha 
                         commercial field of Goi{\'a}s state, Brazil. Multispectral 
                         satellite images at 56 m spatial resolution were collected in a 
                         rainfed cotton field in two dates, on 04/01/2011 and 04/10/2012, 
                         from AWiFS sensor during the flowering cotton stage. Measures of 
                         leaf nitrogen (N) and phosphorus (P) contents were determined over 
                         previously georreferenced central points of 70 plots, each one 
                         measuring 80X80 m. Data were analyzed using descriptive statistics 
                         and geostatistical analyses by building and setting semivariograms 
                         and kriging interpolation. Best correlation was found between IVs 
                         and nitrogen contents of cotton leaves. Results indicated that 
                         NDVI, MSAVI and SAVI were the best indices to estimate P contents 
                         at cotton peak flowering. Identifications of spatial differences 
                         were possible using geostatistical methods with remote sensing 
                         data obtained from medium resolution satellite images, allowing to 
                         identify distinct nutritional needs and growth status of canopy to 
                         cotton plants.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59423",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLQH2",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLQH2",
           targetfile = "59423.pdf",
                 type = "Agricultura e silvicultura",
        urlaccessdate = "27 abr. 2024"
}