author = "Maciel, Adeline Marinho and Vinhas, L{\'u}bia and C{\^a}mara, 
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "The spatiotemporal interval logic formalism for reasoning about 
                         land use change",
                 year = "2016",
         organization = "Workshop de Computa{\c{c}}{\~a}o Aplicada, 16. (WORCAP)",
             abstract = "This work presents a spatiotemporal interval logic formalism and 
                         shows how to use it for reasoning about land use change using big 
                         Earth observation data. Extending the ideas from Allens interval 
                         temporal logic, we introduce predicates holds(o, p, t) and 
                         occur(o, p, Te) to build a general framework to reason about 
                         events. Events can be defined as complete entities on their 
                         respective time intervals and their lifetime is limited while 
                         objects persist in time, with a defined begin and end. Since 
                         events are intrinsically related to the objects they modify, a 
                         geospatial event formalism should specify not only what happens, 
                         but also which objects are affected by such changes. The main 
                         contribution of this work is a spatiotemporal interval logic that 
                         includes geospatial objects explicitly. The formalism proposed and 
                         predicates extended from Allens ideas can model and capture 
                         changes using big Earth observation data, and also allows 
                         reasoning about land use trajectories in regional or global areas. 
                         Spatiotemporal interval logic describe data types and their 
                         operations in a formalism improves our ability to extract 
                         information from large remote sensing data sets. In an experiment 
                         performed in an tropical forest area, our proposed spatiotemporal 
                         interval logic framework was able to discover some events related 
                         the land use change caused by soybeans in Amazonia.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP",
      conference-year = "25-26 out.",
             language = "en",
        urlaccessdate = "27 jan. 2021"