@InProceedings{AguiarAdSIRuMeSi:2010:MOTiSe,
               author = "Aguiar, Daniel Alves de and Adami, Marcos and SILVA, Wagner 
                         Fernando da and Rudorff, Bernardo Friedrich Theodor and Mello, 
                         M{\'a}rcio Pupin de and Silva, Jo{\~a}o dos Santos Vila da",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Embrapa 
                         Inform{\'a}tica Agropecu{\'a}ria, CNPTIA, Av. Andr{\'e} Toselo, 
                         209, Campinas, SP, 13083-886, Brazil and {} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and Embrapa 
                         Inform{\'a}tica Agropecu{\'a}ria, CNPTIA, Av. Andr{\'e} Toselo, 
                         209, Campinas, SP, 13083-886, Brazil",
                title = "MODIS time series to assess pasture land",
            booktitle = "Proceedings...",
                 year = "2010",
                pages = "2123--2126",
         organization = "International Geoscience and Remote Sensing Symposium, (IGARSS).",
            publisher = "IEEE",
              address = "Piscataway",
                 note = "Setores de Atividade: Agricultura, Pecu{\'a}ria, 
                         Produ{\c{c}}{\~a}o Florestal, Pesca e Aq{\"u}icultura.",
             keywords = "Pasture degradation NDWI, NDVI, spectral mixing model, wavelet 
                         technique.",
             abstract = "Land use conversion is a key factor in the mitigation of GHG 
                         emission. Maximum mitigation can be achieved when degraded pasture 
                         land is converted to biofuel crops. Remote sensing images, and in 
                         particular the MODIS time series data, have a great potential to 
                         asses degraded pasture land. This work has the objective to 
                         identify pasture land and its different levels of degradation in 
                         Mato Grosso do Sul state, Brazil. MODIS time series were used to 
                         obtain vegetation indices and fraction images. The wavelet 
                         technique was applied at various levels of decomposition to 
                         extract the input parameters in the WEKA J48 classifier. Pasture 
                         land was well distinguished from Cerrado. The distinction among 
                         different pasture land presented lower performance with best 
                         results for pasture with invasive plants followed by good pasture. 
                         Pasture land with bare soil patches and termite mounds were not 
                         distinguished from other classes of pasture.",
  conference-location = "Honolulu",
      conference-year = "2010",
                  doi = "10.1109/IGARSS.2010.5649388",
                  url = "http://dx.doi.org/10.1109/IGARSS.2010.5649388",
                 isbn = "978-1-4244-9564-1 and 978-1-4244-9565-8",
                 issn = "2153-6996",
                label = "lattes: 7484071887086439 2 AguiarAdSIRuMeSi:2010:MOTiSe",
             language = "en",
         organisation = "IEEE",
           targetfile = "05649388.pdf",
        urlaccessdate = "11 maio 2024"
}