@Article{SilveiraCuGaWiArSc:2021:MoAbBi,
               author = "Silveira, Eduarda Martiniano de Oliveira and Cunha, Luiza Imbroisi 
                         Ferraz and Galv{\~a}o, L{\^e}nio Soares and Withney, Kieran 
                         Daniel and Arcebi J{\'u}nior, Fausto Weimar and Scolforo, 
                         Jos{\'e} Roberto Soares",
          affiliation = "{Universidade Federal de Lavras (UFLA)} and {Universidade Federal 
                         de Lavras (UFLA)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Lancaster University} and {Universidade Federal de 
                         Lavras (UFLA)} and {Universidade Federal de Lavras (UFLA)}",
                title = "Modelling aboveground biomass in forest remnants of the Brazilian 
                         Atlantic Forest using remote sensing, environmental and 
                         terrain-related data",
              journal = "Geocarto International",
                 year = "2021",
               volume = "36",
               number = "3",
                pages = "281--298",
             keywords = "AGB, random forest, spatial distribution, Rio Doce.",
             abstract = "The Brazilian Atlantic Forest, one of the most threatened tropical 
                         regions in the world, exhibits high levels of terrestrial 
                         aboveground biomass (AGB). We propose a random forest approach to 
                         model, map and assess whether public lands provide protection for 
                         AGB in the Rio Doce watershed, one of the most important 
                         watercourses of the Atlantic Forest biome. We used 188 field plots 
                         and individual and hybrid features from remote sensing, 
                         environmental and terrain-related data. The hybrid model improved 
                         the AGB prediction by reducing the root mean square error to 33.43 
                         Mg/ha and increasing the coefficient of determination (R2) to 
                         0.57. The total estimated AGB was 178,967,656.73 Mg, ranging from 
                         20.40 to 167.72 Mg/ha following the seasonal precipitation pattern 
                         and anthropogenic disturbance effects. Only 5.76% of the total AGB 
                         was located on public protected lands, totalling 10,305,501 Mg, 
                         while most of the remaining AGB were located on private 
                         properties.",
                  doi = "10.1080/10106049.2019.1594394",
                  url = "http://dx.doi.org/10.1080/10106049.2019.1594394",
                 issn = "1010-6049",
             language = "en",
           targetfile = "silveira_modelling.pdf",
        urlaccessdate = "09 maio 2024"
}