@Article{FerreiraCamaMont:2014:ObEv,
               author = "Ferreira, Karine Reis and Camara, Gilberto and Monteiro, 
                         Ant{\^o}nio Miguel Vieira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "An algebra for spatiotemporal data: From observations to events",
              journal = "Transactions in GIS",
                 year = "2014",
               volume = "18",
               number = "2",
                pages = "253--269",
                month = "Apr.",
             keywords = "algebra, spatiotemporal data, geospatial.",
             abstract = "Recent technological advances in geospatial data gathering have 
                         created massive data sets with better spatial and temporal 
                         resolution than ever before. These large spatiotemporal data sets 
                         have motivated a challenge for Geoinformatics: how to model 
                         changes and design good quality software. Many existing 
                         spatiotemporal data models represent how objects and fields evolve 
                         over time. However, to properly capture changes, it is also 
                         necessary to describe events. As a contribution to this research, 
                         this article presents an algebra for spatiotemporal data. Algebras 
                         give formal specifications at a high-level abstraction, 
                         independently of programming languages. This helps to develop 
                         reliable and expressive applications. Our algebra specifies three 
                         data types as generic abstractions built on real-world 
                         observations: time series, trajectory and coverage. Based on these 
                         abstractions, it defines object and event types. The proposed data 
                         types and functions can model and capture changes in a large range 
                         of applications, including locationbased services, environmental 
                         monitoring, public health, and natural disasters.",
                  doi = "10.1111/tgis.12030",
                  url = "http://dx.doi.org/10.1111/tgis.12030",
                 issn = "1361-1682",
                label = "self-archiving-INPE-MCTI-GOV-BR",
             language = "en",
           targetfile = "tgis12030.pdf",
        urlaccessdate = "27 abr. 2024"
}