@InProceedings{BergerRossGaso:2017:AsLeAr,
               author = "Berger, Andres G and Rossini, Pedro R and Gaso, Deborah Viviana",
                title = "Assimilating leaf area index time series into a simple crop growth 
                         model to estimate effective rooting depth and soybean yield",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3073--3077",
         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 = "Soil water holding capacity is the main determinant of soybean 
                         yields in rainfed agriculture in the pampas region. Estimating 
                         water holding capacity is challenging, and the capacity to measure 
                         it over large areas is limited. The main goal of this work is in 
                         advancing in methods to estimate maximum effective root activity 
                         depth (RDMAX) as a proxy for water holding capacity based on 
                         inverse modeling of crop growth, relying on the assumption that it 
                         is the main factor accounting for variations in crop growth. For 
                         that purpose we used a simple model developed by Campbell and Diaz 
                         (1988). The model was inverted to estimate RDMAX, using TOA NDVI 
                         time series (Landsat 7 ETM+ and Landsat 8 OLI) as input while 
                         holding other parameters describing the site and crop fixed (i.e. 
                         planting, emergence and maturity dates, and dry matter water 
                         ratio). The model was also modified to estimate grain yield, 
                         assuming linear increase in harvest index and senescence driven by 
                         nitrogen remobilization from the above ground biomass. The model 
                         was tested at five fields where soybean was grown for six growing 
                         seasons. RDMAX was calibrated obtaining an estimate of RDMAX for 
                         each year and each pixel within a field independently. Comparison 
                         across years and sites suggest that general patterns are estimated 
                         correctly, in particular in normal years (not too wet, not too 
                         dry). The use of a simple model with few parameters to adjust 
                         proved useful in achieving sufficiently reliable and robust 
                         estimates of final RDMAX and grain yield.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59276",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLRQN",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLRQN",
           targetfile = "59276.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "08 maio 2024"
}