@InProceedings{BourscheidtBrEaFeDaBa:2023:CáVaÍn,
               author = "Bourscheidt, Vandoir and Breunig, Fabio Marcelo and Earthal, 
                         Daniele Artnt and Ferla, Andressa and Dal Oslo, Janderlei and 
                         Balbinot, Rafaelo",
          affiliation = "{Universidade Federal de S{\~a}o Carlos (UFSCar)} and 
                         {Universidade Federal de Santa Maria (UFSM)} and {Universidade 
                         Federal de Santa Maria (UFSM)} and {Universidade Federal de Santa 
                         Maria (UFSM)} and {Universidade Federal de Santa Maria (UFSM)} and 
                         {Universidade Federal de Santa Maria (UFSM)}",
                title = "C{\'a}lculo das varia{\c{c}}{\~o}es de {\'{\i}}ndices de 
                         vegeta{\c{c}}{\~a}o com cenas Planetscope adquiridas no mesmo 
                         dia e efeito sobre a an{\'a}lise de s{\'e}ries temporais",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155718",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 20. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "floresta, sensoriamento remoto, series temporais, EVI, NDVI, 
                         remote sensing, time series, EVI, NDVI.",
             abstract = "O uso de s{\'e}ries temporais de sensoriamento remoto {\'e} 
                         fundamental para capturar varia{\c{c}}{\~o}es dos fen{\^o}menos 
                         ambientais e das caracter{\'{\i}}sticas fenol{\'o}gicas da 
                         vegeta{\c{c}}{\~a}o. A presen{\c{c}}a de artefatos introduzidos 
                         pelas aquisi{\c{c}}{\~o}es de imagens e hor{\'a}rios distintos 
                         podem afetar as sa{\'{\i}}das dos modelos. Assim, o objetivo do 
                         estudo foi quantificar a amplitude das varia{\c{c}}{\~o}es de 
                         {\'{\i}}ndices de vegeta{\c{c}}{\~a}o associadas a distintos 
                         hor{\'a}rios de aquisi{\c{c}}{\~a}o de dados PlanetScope e seu 
                         efeito sobre as s{\'e}ries temporais. Foram utilizadas 663 
                         imagens de reflect{\^a}ncia de superf{\'{\i}}cie adquiridas 
                         sobre uma floresta subtropical do sul do Brasil, no 
                         per{\'{\i}}odo de 2016 a 2022. O NDVI e EVI foram selecionados 
                         para a an{\'a}lise do efeito da amplitude derivada da hora de 
                         aquisi{\c{c}}{\~a}o da imagem. Os resultados mostraram uma 
                         amplitude m{\'e}dia de 0,040 (±0,006) e 0,035 (±0,010) para o 
                         NDVI e EVI, respectivamente. As varia{\c{c}}{\~o}es observadas 
                         parecem n{\~a}o ter rela{\c{c}}{\~a}o com o hor{\'a}rio de 
                         aquisi{\c{c}}{\~a}o. Por outro lado, elas podem ter impactos 
                         significativos na an{\'a}lise de s{\'e}ries temporais de 
                         produtos de vegeta{\c{c}}{\~a}o. ABSTRACT: The use of remote 
                         sensing time series is essential to capture variations in 
                         environmental and phenological vegetation characteristics. 
                         Artifacts introduced by image acquisitions and different times can 
                         affect the outputs of the models. Thus, the objective of the study 
                         was to quantify the amplitude of variations in vegetation indices 
                         associated with different PlanetScope data acquisition times and 
                         their effect on the time series. We used 663 surface reflectance 
                         images acquired over a subtropical forest in southern Brazil, from 
                         2016 to 2022. The NDVI and EVI were selected to analyze the effect 
                         of the amplitude derived from the time of image acquisition. The 
                         results showed a mean amplitude of 0.040 (±0.006) and 0.035 
                         (±0.010) for NDVI and EVI, respectively. The observed variation 
                         does not seem to be related with the acquisition time. On the 
                         other hand, they may lead to significant impact on vegetation time 
                         series analysis.",
  conference-location = "Florian{\'o}polis",
      conference-year = "02-05 abril 2023",
                 isbn = "978-65-89159-04-9",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/495D2UH",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/495D2UH",
           targetfile = "155718.pdf",
                 type = "An{\'a}lise de s{\'e}ries temporais de imagens de 
                         sat{\'e}lite",
        urlaccessdate = "15 jun. 2024"
}