@Article{TejadaPinellGörgOvanOmet:2020:MaDaGa,
               author = "Tejada Pinell, Graciela and G{\"o}rgens, Eric Bastos and Ovando, 
                         Alex and Ometto, Jean Pierre Henry Balbaud",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)} 
                         and {Centro Nacional de Monitoramento e Alertas de Desastres 
                         Naturais (CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Mapping data gaps to estimate biomass across Brazilian Amazon 
                         forests",
              journal = "Forest Ecosystems",
                 year = "2020",
               volume = "7",
               number = "1",
                pages = "e25",
                month = "Dec.",
             keywords = "Amazon, Tropical forest, Carbon, Aboveground biomass, Data gaps, 
                         REDD+, Environmental factors.",
             abstract = "Background: Tropical forests play a fundamental role in the 
                         provision of diverse ecosystem services, such as biodiversity, 
                         climate and air quality regulation, freshwater provision, carbon 
                         cycling, agricultural support and culture. To understand the role 
                         of forests in the carbon balance, aboveground biomass (AGB) 
                         estimates are needed. Given the importance of Brazilian tropical 
                         forests, there is an urgent need to improve AGB estimates to 
                         support the Brazilian commitments under the United Nations 
                         Framework Convention on Climate Change (UNFCCC). Many AGB maps and 
                         datasets exist, varying in availability, scale and coverage. Thus, 
                         stakeholders, policy makers and scientists must decide which AGB 
                         product, dataset or combination of data to use for their 
                         particular goals. In this study, we assessed the gaps in the 
                         spatial AGB data across the Brazilian Amazon forests not only to 
                         orient the decision makers about the data that are currently 
                         available but also to provide a guide for future initiatives. 
                         Results: We obtained a map of the gaps in the forest AGB spatial 
                         data for the Brazilian Amazon using statistics and differences 
                         between AGB maps and a spatial multicriteria evaluation that 
                         considered the current AGB datasets. The AGB spatial data gap map 
                         represents areas with good coverage of AGB data and, consequently, 
                         the main gaps or priority areas where further biomass assessments 
                         should focus, including the northeast of Amazon State, Amap{\'a} 
                         and northeast of Par{\'a}. Additionally, by quantifying the 
                         variability in both the AGB maps and field data on multiple 
                         environmental factors, we provide valuable elements for 
                         understanding the current AGB data as a function of climate, soil, 
                         vegetation and geomorphology. Conclusions: The map of AGB data 
                         gaps could become a useful tool for policy makers and different 
                         stakeholders working on National Communications, Reducing 
                         Emissions from Deforestation and Degradation (REDD+), or carbon 
                         emissions modeling to prioritize places to implement further AGB 
                         assessments. Only 0.2% of the Amazon biome forest is sampled, and 
                         extensive effort is necessary to improve what we know about the 
                         tropical forest.",
                  doi = "10.1186/s40663-020-00228-1",
                  url = "http://dx.doi.org/10.1186/s40663-020-00228-1",
                 issn = "2095-6355",
             language = "en",
           targetfile = "tejada_mapping.pdf",
        urlaccessdate = "28 abr. 2024"
}