author = "Diniz, Cesar and Cortinhas, Luiz and Nerino, Gilberto and 
                         Rodrigues, Jhonatan and Sadeck, Lu{\'{\i}}s and Adami, Marcos 
                         and Souza Filho, Pedro Walfir M.",
          affiliation = "{Solved—Solutions in Geoinformation} and {Solved—Solutions in 
                         Geoinformation} and {Solved—Solutions in Geoinformation} and 
                         {Solved—Solutions in Geoinformation} and {Solved—Solutions in 
                         Geoinformation} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade Federal do Par{\'a} (UFPA)}",
                title = "Brazilian mangrove status: three decades of satellite data 
              journal = "Remote Sensing",
                 year = "2019",
               volume = "11",
               number = "7",
                month = "Apr.",
             keywords = "mangroves, machine learning, Google Earth Engine, spectral 
                         indices, Brazil, Landsat.",
             abstract = "Since the 1980s, mangrove cover mapping has become a common 
                         scientific task. However, the systematic and continuous 
                         identification of vegetation cover, whether on a global or 
                         regional scale, demands large storage and processing capacities. 
                         This manuscript presents a Google Earth Engine (GEE)-managed 
                         pipeline to compute the annual status of Brazilian mangroves from 
                         1985 to 2018, along with a new spectral index, the Modular 
                         Mangrove Recognition Index (MMRI), which has been specifically 
                         designed to better discriminate mangrove forests from the 
                         surrounding vegetation. If compared separately, the periods from 
                         1985 to 1998 and 1999 to 2018 show distinct mangrove area trends. 
                         The first period, from 1985 to 1998, shows an upward trend, which 
                         seems to be related more to the uneven distribution of Landsat 
                         data than to a regeneration of Brazilian mangroves. In the second 
                         period, from 1999 to 2018, a trend of mangrove area loss was 
                         registered, reaching up to 2% of the mangrove forest. On a 
                         regional scale, ~85% of Brazils mangrove cover is in the states of 
                         Maranh{\~a}o, Par{\'a}, Amap{\'a} and Bahia. In terms of 
                         persistence, ~75% of the Brazilian mangroves remained unchanged 
                         for two decades or more.",
                  doi = "10.3390/rs11070808",
                  url = "http://dx.doi.org/10.3390/rs11070808",
                 issn = "2072-4292",
             language = "en",
           targetfile = "remotesensing-11-00808.pdf",
        urlaccessdate = "28 nov. 2020"