Fechar
Metadados

@Article{SantosLPPNROPSS:2020:AsVICa,
               author = "Santos, Filippe Lemos Maia and Libonati, Renata and Peres, 
                         Leonardo F. and Pereira, Allan A. and Narcizo, Luiza C. and 
                         Rodrigues, Julia Abrantes and Oom, Duarte and Pereira, Jos{\'e} 
                         M. C. and Schroeder, Wilfrid and Setzer, Alberto Waingort",
          affiliation = "{Universidade Federal do Rio de Janeiro (UFRJ)} and {Universidade 
                         Federal do Rio de Janeiro (UFRJ)} and {Universidade Federal do Rio 
                         de Janeiro (UFRJ)} and {Instituto Federal de Ci{\^e}ncia e 
                         Tecnologia do Sul de Minas} and {Universidade Federal do Rio de 
                         Janeiro (UFRJ)} and {Universidade Federal do Rio de Janeiro 
                         (UFRJ)} and {University of Lisbon} and {University of Lisbon} and 
                         NOAA/NESDIS and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Assessing VIIRS capabilities to improve burned area mapping over 
                         the Brazilian Cerrado",
              journal = "International Journal of Remote Sensing",
                 year = "2020",
               volume = "41",
               number = "21",
                pages = "8300--8327",
                month = "Nov.",
             abstract = "Coarse spatial resolution of remote sensing imagery still hampers 
                         a comprehensive representation of long-term fire patterns at the 
                         regional level, in particular in areas characterized by small and 
                         sparse fire scars. The Visible Infrared Imaging Radiometer Suite 
                         (VIIRS) sensor launched in 2011 upgrades the spatial resolution 
                         (375 m) and gives continuity to the Earth long-term monitoring 
                         initiated by Advanced Very High-Resolution Radiometer (AVHRR) and 
                         Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. 
                         Therefore, aiming to assess VIIRS 375 m imagery capabilities to 
                         improve the accuracy and reliability of fire scars mapping over 
                         the Brazilian Cerrado, we developed a burned area detection 
                         algorithm (VIIRS-SVM) based on machine learning techniques. For 
                         this purpose, the (V, W) burnt index adjusted to VIIRS 
                         near-infrared and middle-infrared channels and the One-Class 
                         Support Vector Machine algorithm were used for burned area 
                         identification. The VIIRS-SVM algorithm was applied over the 
                         Brazilian Cerrado and evaluated against reference scars from 15 
                         Landsat-8 scenes during the fire season of 2015, covering a large 
                         area with substantial variability in terms of fire scars 
                         characteristics. We also performed a comparison with the MCD64A1 
                         collection-6 product over the validation sites. Relying on VIIRS 
                         375 m imagery, the VIIRS-SVM algorithm allows an enhancement of 
                         25% in discrimination of small and medium fire scars (25 to 1000 
                         ha), when compared to the MODIS-derived product. Results have 
                         demonstrated that the enhancement of medium and small fire scars 
                         mapping over the Cerrado is possible using VIIRS sensor 
                         capabilities.",
                  doi = "10.1080/01431161.2020.1771791",
                  url = "http://dx.doi.org/10.1080/01431161.2020.1771791",
                 issn = "0143-1161",
             language = "en",
           targetfile = "santos_assessing.pdf",
        urlaccessdate = "26 jan. 2021"
}


Fechar