@Article{PingDaGaNeWaScBi:2023:AsMaAm,
               author = "Ping, Dazhou and Dalagnol, Ricardo and Galv{\~a}o, L{\^e}nio 
                         Soares and Nelson, Bruce and Wagner, Fabien and Schultz, David M. 
                         M. and Bispo, Polyanna da Concei{\c{c}}{\~a}o",
          affiliation = "{University of Manchester} and {University of Manchester} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas da Amaz{\^o}nia (INPA)} and {University of 
                         California Los Angeles (UCLA)} and {University of Manchester} and 
                         {University of Manchester}",
                title = "Assessing the Magnitude of the Amazonian Forest Blowdowns and 
                         Post-Disturbance Recovery Using Landsat-8 and Time Series of 
                         PlanetScope Satellite Constellation Data",
              journal = "Remote Sensing",
                 year = "2023",
               volume = "15",
               number = "12",
                pages = "e3196",
                month = "June",
             keywords = "blowdowns, tropical forests, spectral mixture model, Google Earth 
                         Engine, PlanetScope NICFI.",
             abstract = "Blowdown events are a major natural disturbance in the central 
                         Amazon Forest, but their impact and subsequent vegetation recovery 
                         have been poorly understood. This study aimed to track 
                         post-disturbance regeneration after blowdown events in the Amazon 
                         Forest. We analyzed 45 blowdown sites identified after September 
                         2020 at Amazonas, Mato Grosso, and Colombia jurisdictions using 
                         Landsat-8 and PlanetScope NICFI satellite imagery. 
                         Non-photosynthetic vegetation (NPV), green vegetation (GV), and 
                         shade fractions were calculated for each image and sensor using 
                         spectral mixture analysis in Google Earth Engine. The results 
                         showed that PlanetScope NICFI data provided more regular and 
                         higher-spatial-resolution observations of blowdown areas than 
                         Landsat-8, allowing for more accurate characterization of 
                         post-disturbance vegetation recovery. Specifically, NICFI data 
                         indicated that just four months after the blowdown event, nearly 
                         half of \& UDelta;NPV, which represents the difference between 
                         the NPV after blowdown and the NPV before blowdown, had 
                         disappeared. \& UDelta;NPV and GV values recovered to 
                         pre-blowdown levels after approximately 15 months of regeneration. 
                         Our findings highlight that the precise timing of blowdown 
                         detection has huge implications on quantification of the magnitude 
                         of damage. Landsat data may miss important changes in signal due 
                         to the difficulty of obtaining regular monthly observations. These 
                         findings provide valuable insights into vegetation recovery 
                         dynamics following blowdown events.",
                  doi = "10.3390/rs15123196",
                  url = "http://dx.doi.org/10.3390/rs15123196",
                 issn = "2072-4292",
             language = "en",
           targetfile = "remotesensing-15-03196.pdf",
        urlaccessdate = "01 maio 2024"
}