@Article{ChavesPicoSanc:2020:SyRe,
               author = "Chaves, Michel Eust{\'a}quio Dantas and Picoli, Michelle Cristina 
                         Ara{\'u}jo and Sanches, Ieda Del'Arco",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Recent applications of Landsat 8/OLI and Sentinel-2/MSI for land 
                         use and land cover mapping: a systematic review",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "18",
                pages = "e3062",
                month = "Sept.",
                 note = "{Pr{\^e}mio CAPES Elsevier 2023 - ODS 15: Vida terrestre}",
             keywords = "operational land imager, multiSpectral instrument, vegetation 
                         indices, text mining.",
             abstract = "Recent applications of Landsat 8 Operational Land Imager (L8/OLI) 
                         and Sentinel-2 MultiSpectral Instrument (S2/MSI) data for 
                         acquiring information about land use and land cover (LULC) provide 
                         a new perspective in remote sensing data analysis. Jointly, these 
                         sources permit researchers to improve operational classification 
                         and change detection, guiding better reasoning about landscape and 
                         intrinsic processes, as deforestation and agricultural expansion. 
                         However, the results of their applications have not yet been 
                         synthesized in order to provide coherent guidance on the effect of 
                         their applications in different classification processes, as well 
                         as to identify promising approaches and issues which affect 
                         classification performance. In this systematic review, we present 
                         trends, potentialities, challenges, actual gaps, and future 
                         possibilities for the use of L8/OLI and S2/MSI for LULC mapping 
                         and change detection. In particular, we highlight the possibility 
                         of using medium-resolution (Landsat-like, 1030 m) time series and 
                         multispectral optical data provided by the harmonization between 
                         these sensors and data cube architectures for analysis-ready data 
                         that are permeated by publicizations, open data policies, and open 
                         science principles. We also reinforce the potential for exploring 
                         more spectral bands combinations, especially by using the three 
                         Red-edge and the two Near Infrared and Shortwave Infrared bands of 
                         S2/MSI, to calculate vegetation indices more sensitive to 
                         phenological variations that were less frequently applied for a 
                         long time, but have turned on since the S2/MSI mission. 
                         Summarizing peer-reviewed papers can guide the scientific 
                         community to the use of L8/OLI and S2/MSI data, which enable 
                         detailed knowledge on LULC mapping and change detection in 
                         different landscapes, especially in agricultural and natural 
                         vegetation scenarios.",
                  doi = "10.3390/rs12183062",
                  url = "http://dx.doi.org/10.3390/rs12183062",
                 issn = "2072-4292",
             language = "en",
           targetfile = "chaves_recent.pdf",
        urlaccessdate = "27 abr. 2024"
}