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The fields of application of spatio-temporal systems, i.e., systems that must operate with time-varying spatial properties, are vast and heterogeneous. Since it would be difficult to treat such diversity as a whole, we introduce a classification for spatio-temporal systems based on the properties of the represented objects. Building on this classification, we also claim that features of some complex objects can be derived from those of simpler ones, suggesting an evolutionary approach, starting with the study of simple objects and progressing by enriching them with new features. This paper focuses on the definition of a data model for representation of moving points. The model is based on the decomposition of the trajectory of moving points into sections. The movement within each section of a trajectory is described by a variability function. Since, for most systems, it is not possible to store the exact knowledge about the movement of a mobile, the answers to queries may be imprecise. We propose two additional approaches to deal with imprecision, the superset and the subset semantics, based on a maximum value for the variability function, and a smooth technique to integrate them in the model. Finally, we analyse some functional aspects of the implementation of the data model on a Relational Database Management System (RDBMS) and outline some directions for future research.

Geographical Information Systems were originally intended to deal with snapshots representing a single state of some reality but there axe more and more applications requiring the representation and querying of time-varying information. This work addresses the representation of moving objects on GIS.The continuous nature of movement raises problems for representation in information systems due to the limited capacity of storage systems and the inherently discrete nature of measurement instruments. The stored information has therefore to be partial and does not allow an exact inference of the real-world object's behavior. To cope with this, query operations must take uncertainty into consideration in their semantics in order to give accurate answers to the users.The paper proposes a set of operations to be included in a GIS or a spatial database to make it able to answer queries on the spatio-temporal behavior of moving objects. The operations have been selected according to the requirements of real applications and their semantics with respect to uncertainty is specified. A collection of examples from a case study is included to illustrate the expressiveness of the proposed operations.

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This paper deals with the application of satellite images to characterize some aspects of the circulation dynamics of the Tinto-Odiel estuary using turbidity patterns as ‘natural tracers’. 15 images (Landsat TM and Spot HRV) were processed to provide synoptic, instantaneous views of the circulation patterns under different environmental conditions. In addition, a comparison was made between results of oceanographic field work, using biplanes and fluorescent tracers, and satellite image turbidity patterns used as ‘ground truth’ data for specific hydroclimatic situations. This approach allowed (1) the identification and mapping of dynamic processes of interest during a theoretical tidal cycle, (2) the elaboration of additional information on the ‘flow schemes’ at the mouth of the estuary with improved spatial and temporal resolution, and (3) the supply of basic data to improve the knowledge of exchange processes between estuarine and coastal waters. The results of this study are considered to be useful for the management of the estuarine system