@Article{NevesKörtFonsEsca:2020:AsTeMa,
               author = "Neves, Alana Kasahara and K{\"o}rting, Thales Sehn and Fonseca, 
                         Leila Maria Garcia and Escada, Maria Isabel Sobral",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Assessment of TerraClass and MapBiomas data on legend and map 
                         agreement for the Brazilian Amazon biome",
              journal = "Acta Amazonica",
                 year = "2020",
               volume = "50",
               number = "2",
                pages = "170--182",
             keywords = "Cobertura da Terra, sistema de classifica{\c{c}}{\~a}o, 
                         Sensoriamento remoto, land cover, classification system.",
             abstract = "Reliable environmental monitoring and evaluation require 
                         high-quality maps of land use and land cover. For the Amazon 
                         biome, the TerraClass and MapBiomas projects apply different 
                         methodologies to create these maps. We evaluated the agreement 
                         between land cover and land use maps generated by TerraClass and 
                         MapBiomas (Collections 2 and 3) for the Brazilian Amazon biome, 
                         from 2004 to 2014. Specifically, we: (1) described both project 
                         legends based on the LCCS (Land Cover Classification System); (2) 
                         analyzed the differences between their classes; and (3) compared 
                         the mapping differences among the Brazilian states that are 
                         totally or partially covered by the Amazon biome. We compared the 
                         classifications with a per-pixel approach and performed an 
                         evaluation based on agreement matrices. The overall agreement 
                         between the projects was 87.4% (TerraClass x MapBiomas 2) and 
                         92.0% (TerraClass x MapBiomas 3). We analyzed methodological 
                         differences to explain the disagreements in class identification. 
                         We conclude that using these maps together without a properly 
                         adapted legend is not recommended for the analysis of land use and 
                         land cover change. Depending on the application, one mapping 
                         system may be more suitable than the other. RESUMO: O 
                         monitoramento e a avalia{\c{c}}{\~a}o ambiental confi{\'a}veis 
                         necessitam mapas de alta qualidade de uso e cobertura da terra. 
                         Para o bioma Amaz{\^o}nia, os projetos TerraClass e MapBiomas 
                         usam diferentes metodologias para criar esses mapas. N{\'o}s 
                         avaliamos a concord{\^a}ncia entre os produtos gerados pelo 
                         TerraClass e pelo MapBiomas (Cole{\c{c}}{\~o}es 2 e 3) para o 
                         bioma Amaz{\^o}nia, de 2004 a 2014. Mais especificamente: (1) 
                         descrevemos as legendas dos projetos com base no LCCS (Land Cover 
                         Classification System); (2) analisamos as diferen{\c{c}}as entre 
                         as classes; e (3) comparamos as diferen{\c{c}}as de mapeamento 
                         entre os estados brasileiros total ou parcialmente 
                         inclu{\'{\i}}dos no bioma Amaz{\^o}nia. As 
                         classifica{\c{c}}{\~o}es foram comparadas em uma abordagem pixel 
                         a pixel e a avalia{\c{c}}{\~a}o foi baseada em matrizes de 
                         concord{\^a}ncia. A concord{\^a}ncia global entre os projetos 
                         foi de 87.4% (TerraClass x MapBiomas 2) e 92.0% (TerraClass x 
                         MapBiomas 3). Analisamos as diferen{\c{c}}as metodol{\'o}gicas 
                         entre os projetos para explicar as discord{\^a}ncias existentes 
                         na identifica{\c{c}}{\~a}o das classes. Concluimos que a 
                         utiliza{\c{c}}{\~a}o dos produtos dos dois projetos de forma 
                         complementar, sem uma apropriada adapta{\c{c}}{\~a}o de 
                         legendas, n{\~a}o {\'e} recomendada para a an{\'a}lise de 
                         mudan{\c{c}}a de uso e cobertura da terra. Dependendo da 
                         aplica{\c{c}}{\~a}o, um sistema de mapeamento pode ser mais 
                         adequado do que o outro.",
                  doi = "10.1590/1809-4392201900981",
                  url = "http://dx.doi.org/10.1590/1809-4392201900981",
                 issn = "0044-5967",
                label = "lattes: 9947670889009026 4 NevesKortFonsEsca:2020:AsTeMa",
             language = "pt",
           targetfile = "neves_assessment.pdf",
        urlaccessdate = "27 abr. 2024"
}