@Article{NagelNoMaCaBaBo:2022:ImMeMi,
               author = "Nagel, Gustavo Willy and Novo, Evlyn M{\'a}rcia Le{\~a}o de 
                         Moraes and Martins, Vitor Souza and Campos Silva, Jo{\~a}o Vitor 
                         and Barbosa, Cl{\'a}udio Clemente Faria and Bonnet, Marie Paule",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Michigan State 
                         University} and {Norwegian University of Life Science} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Institut 
                         de Recherche pour le D{\'e}veloppement (IRD)}",
                title = "Impacts of meander migration on the Amazon riverine communities 
                         using Landsat time series and cloud computing",
              journal = "Science of the Total Environment",
                 year = "2022",
               volume = "806",
                pages = "e150449",
                month = "Feb.",
             keywords = "Flood pulse, Floodplain, Juru{\'a} River, Remote sensing, 
                         Ribeirinhos.",
             abstract = "River meander migration is a process that maintains biodiverse 
                         riparian ecosystems by producing highly sinuous rivers, and oxbow 
                         lakes. However, although the floodplains support communities with 
                         fish and other practices in the region, meandering rivers can 
                         directly affect the life of local communities. For example, 
                         erosion of river banks promotes the loss of land on community 
                         shores, while sedimentation increases the distance from house to 
                         the river. Therefore, communities living along the Juru{\'a} 
                         River, one of the most sinuous rivers on Earth, are vulnerable to 
                         long-term meander migration. In this study, the river meander 
                         migration was detected by using Landsat 5-8 data from 1984 to 
                         2020. A per-pixel Water Surface Change Detection Algorithm (WSCDA) 
                         was developed to classify regions subject to erosion and 
                         sedimentation processes by applying temporal regressions on the 
                         water index, called Modified Normalized Difference Water Index 
                         (mNDWI). The WSCDA classified the meander migration with omission 
                         and commission errors lower than 13.44% and 7.08%, respectively. 
                         Then, the number of riparian communities was mapped using high 
                         spatial resolution SPOT images. A total of 369 communities with no 
                         road access were identified, the majority of which living in 
                         stable regions (58.8%), followed by sedimentation (26.02%) and 
                         erosion (15.18%) areas. Furthermore, we identified that larger 
                         communities (>20 houses) tend to live in more stable locations 
                         (70%) compared to smaller communities (110 houses) with 55.6%. A 
                         theoretical model was proposed to illustrate the main impacts of 
                         meander migration on the communities, related to Inundation, 
                         Mobility Change, and Food Security. This is the first study 
                         exploring the relationship between meander migration and riverine 
                         communities at watershed-level, and the results support the 
                         identification of vulnerable communities to improve local planning 
                         and floodplain conservation.",
                  doi = "10.1016/j.scitotenv.2021.150449",
                  url = "http://dx.doi.org/10.1016/j.scitotenv.2021.150449",
                 issn = "0048-9697",
             language = "en",
           targetfile = "nagel_impacts_2022.pdf",
        urlaccessdate = "20 maio 2024"
}