@InProceedings{VelosoDemaCesc:2013:ReCrGr,
               author = "Veloso, Amanda and Demarez, Val{\'e}rie and Ceschia, Eric",
                title = "Retrieving crops Green Area Index from high temporal and spatial 
                         resolution remote sensing data",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "6425--6432",
         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 = "This paper aims at firstly evaluating the correspondence between 
                         Normalized Difference Vegetation Index (NDVI) products from 
                         Formosat-2 (F2) and SPOT sensors and then to perform a comparative 
                         analysis of two methods for retrieving Green Area Index from high 
                         spatial and temporal resolution satellite data (F2 and SPOT). For 
                         this purpose, an empirical approach using NDVI plus field data and 
                         a Neural Network approach using the PROSAIL model are compared 
                         over four different crops: wheat, sunflower, maize and soybean. 
                         The performance of both methods were evaluated and compared with 
                         in-situ direct (destructive) and indirect (hemispherical photos) 
                         measurements. Results suggest better performances for the 
                         empirical approach (Rē, RMSE). Still the physically-based method 
                         leads to good results (Rē, RMSE). The latter seems to be more 
                         promising due to its portability and independence from field 
                         measurements.",
  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 = "391",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GD3M",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GD3M",
           targetfile = "p0391.pdf",
                 type = "Monitoramento e Modelagem Ambiental",
        urlaccessdate = "15 jun. 2024"
}