author = "C{\^a}mara, Gilberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "On the semantics of big Earth observation data for land 
              journal = "Journal of Spatial Information Science",
                 year = "2020",
               volume = "20",
                pages = "21--34",
             keywords = "big data, Earth observation, geospatial semantics, LUCC, land-use 
             abstract = "This paper discusses the challenges of using big Earth observation 
                         data for land classification. The approach taken is to consider 
                         pure data-driven methods to be insufficient to represent 
                         continuous change. I argue for sound theories when working with 
                         big data. After revising existing classification schemes such as 
                         FAO's Land Cover Classification System (LCCS), I conclude that 
                         LCCS and similar proposals cannot capture the complexity of 
                         landscape dynamics. I then investigate concepts that are being 
                         used for analyzing satellite image time series; I show these 
                         concepts to be instances of events. Therefore, for continuous 
                         monitoring of land change, event recognition needs to replace 
                         object identification as the prevailing paradigm. The paper 
                         concludes by showing how event semantics can improve data-driven 
                         methods to fulfil the potential of big data.",
                  doi = "10.5311/JOSIS.2020.20.645",
                  url = "http://dx.doi.org/10.5311/JOSIS.2020.20.645",
                 issn = "1948-660X",
             language = "en",
           targetfile = "camara_semantics.pdf",
        urlaccessdate = "24 jan. 2021"