@InProceedings{HottCarAntAlvRoc:2015:EsExHu,
               author = "Hott, Marcos Cicarini and Carvalho, Luis Marcelo Tavares de and 
                         Antunes, Mauro Antonio Homem and Alves, Helena Maria Ramos and 
                         Rocha, Wadson Sebasti{\~a}o Duarte da",
                title = "Estimativa de Expoentes de Hurst para s{\'e}ries temporais de 
                         imagens NDVI / MODIS em regi{\~o}es de pastagens da Zona da Mata 
                         de Minas Gerais",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4065--4072",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The Zona da Mata region in Minas Gerais State is configured in a 
                         traditional dairy production chain, whose grasslands have subtle 
                         dynamics in their phenology, and currently there is a strong 
                         concern regarding degradation and vegetative development trends. 
                         The Hurst exponents (H) are a potential tool to describe the 
                         evolution scale of time series, sensitive to short- and long-term 
                         memory. This study was aimed at developing an algorithm in the GIS 
                         that presents reliable results of the Hurst exponents for NDVI 
                         from MODIS imagery, using binary block method applied to R/S 
                         analysis (range rescaled) in the Gretl, an econometrics and time 
                         series software. We produced H values identical to those estimated 
                         H for time series of pixels extracted from the satellite imagery 
                         dataset, processed in the Gretl. In order to estimate and evaluate 
                         the area of occurrence of the H exponents classes for imagery over 
                         time, we performed a processing highlighting the slightly trend of 
                         low sustainability of grasslands (H class 0.52 to 0.65), with 
                         833,768 ha (68.71%), and moderate sustainability or persistence (H 
                         class 0.65 to 0.70), with 162,068 ha. We emphasized the fact that 
                         the estimated class between 0.37 and 0.52 resulted in a 
                         considerable area of grasslands, with about 135,000 ha, possibly 
                         indicating that this region faces remarkable changes, such as 
                         degradation, crop rotation, fallow or others land use changes. 
                         Despite the long processing time to estimate H, we highlight the 
                         usefulness of this methodology for detection of change trends in 
                         the short- and long-term periods.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "802",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4CCS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4CCS",
           targetfile = "p0802.pdf",
                 type = "An{\'a}lise de s{\'e}ries de tempo de imagens de sat{\'e}lite",
        urlaccessdate = "09 maio 2024"
}