@InProceedings{ParenteSimGuiSilCat:2023:InImSe,
               author = "Parente, Yago Yguara and Sim{\~o}es, Philipe Souza and 
                         Guimar{\~a}es, Ricardo Jos{\'e} de Paula Souza e and Silva, 
                         Christian Nunes da and Catete, Cl{\'{\i}}stenes Pamplona",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Evandro 
                         Chagas} and {Universidade Federal do Par{\'a} (UFPA)} and 
                         {Instituto Evandro Chagas}",
                title = "Integra{\c{c}}{\~a}o de imagens Sentinel-1 e Sentinel-2 para a 
                         classifica{\c{c}}{\~a}o e mapeamento de floesta em parte de 
                         mesorregi{\~a}o sudeste paraense",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155403",
         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 amaz{\^o}nica, Classifica{\c{c}}{\~a}o supervisionada, 
                         Monitoramento ambiental,Amazon rainforest, Supervised 
                         classification, Environmental monitoring.",
             abstract = "A floresta Amaz{\^o}nica vem sofrendo intensamente com o 
                         desmatamento, principalmente nos {\'u}ltimos anos. A 
                         utiliza{\c{c}}{\~a}o de imagens {\'o}pticas integradas com SAR 
                         podem servir como uma excelente ferramenta para o monitoramento da 
                         florestal. O objetivo deste estudo foi determinar a melhor 
                         combina{\c{c}}{\~a}o de imagens {\'o}pticas / SAR para o 
                         mapeamento das {\'a}reas de florestas nativas no bioma 
                         amaz{\^o}nico. A metodologia utilizada nesse estudo consistiu na 
                         classifica{\c{c}}{\~a}o supervisionada de imagens Sentinel 1 e 
                         2, utilizando o classificador Random forest. A 
                         classifica{\c{c}}{\~a}o que usou somente imagens SAR obteve as 
                         menores acur{\'a}cias; as que usaram somente imagens {\'o}pticas 
                         adquiriram acur{\'a}cias maiores; as que fizeram uso da 
                         integra{\c{c}}{\~a}o de dados alcan{\c{c}}aram as maiores 
                         acur{\'a}cias. O uso de imagens SAR ainda se torna valido devido 
                         a capacidade desses sensores em ultrapassar as camadas de nuvens 
                         no per{\'{\i}}odo chuvoso. ABSTRACT: The Amazon rainforest has 
                         been suffering intensely from deforestation, especially in recent 
                         years. The use of optical images integrated with SAR can serve as 
                         an excellent tool for monitoring forest. The objective of this 
                         study was to determine the best combination of optical images / 
                         SAR for mapping native forest areas in the Amazon biome. The 
                         methodology used in this study consisted of the supervised 
                         classification of Sentinel 1 and 2 images, using the Random forest 
                         classifier. The classification that used only SAR images obtained 
                         the lowest accuracy; those that used only optical images acquired 
                         greater accuracy; those that made use of SAR and optical data 
                         integration achieved the highest accuracy. The use of SAR images 
                         still becomes valid due to the ability of these sensors to be able 
                         to pass through the cloud layers, they are of paramount importance 
                         for monitoring during the rainy season.",
  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/493DS4B",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/493DS4B",
           targetfile = "155403.pdf",
                 type = "Degrada{\c{c}}{\~a}o de florestas",
        urlaccessdate = "09 maio 2024"
}