The notion of spatio-temporal multi-granularity is fundamental when modeling objects in GIS applications in that it supports the representation of the temporal evolutions of these objects. Concepts and issues in multi-granular spatio-temporal representations have been widely investigated by the research community. However, despite the large number of theoretical investigations, no comprehensive...

Abstract: This work presents a new approach that aims to characterize the spatio-temporal relationships that exist between geographical objects that are absent or non-existent at the moment of analysis. First, we would like to propose a formal analysis of the spatio-temporal states of presence and existence of a geographical object. We will then use a combination of these states in order to def...

Spatio-temporal events are collected at high levels of detail (LoDs) in many phenomena. Both spatial and temporal characteristics of data can be expressed at different LoDs. Depending on the level of detail, different spatiotemporal patterns can be detected, and in some specific cases spatio-temporal patterns are just detected in some LoDs [1]. It is crucial to model spatio-temporal phenomena h...

We present a method to automatically extract spatio-temporal descriptions of moving objects from synchronized and calibrated multi-view sequences. The object is modeled by a time-varying multi-resolution subdivision surface that is fitted to the image data using spatio-temporal multi-view stereo information, as well as contour constraints. The stereo data is utilized by computing the normalized...

Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and H...

We address a fundamental question concerning spatio-temporal database systems: “What are exactly spatio-temporal queries?” We define spatio-temporal queries to be computable mappings that are also generic, meaning that the result of a query may only depend to a limited extent on the actual internal representation of the spatio-temporal data. Genericity is defined as invariance under groups of g...

A query optimizer requires cost models to calculate the costs of various access plans for a query. An effective method to estimate the number of disk (or page) accesses for spatio-temporal queries has not yet been proposed. The TPR-tree is an efficient index that supports spatio-temporal queries for moving objects. Existing cost models for the spatial index such as the R-tree do not accurately ...

Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains including, climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and Earth sciences. Spatio-temporal data differs from relational data for which computational approaches are developed in the data mining community for multiple decades, in that both spatial and te...

We address a fundamental question concerning spatio-temporal database systems: “What are exactly spatio-temporal queries?” We define spatio-temporal queries to be computable mappings that are also generic, meaning that the result of a query may only depend to a limited extent on the actual internal representation of the spatio-temporal data. Genericity is defined as invariance under groups of g...

Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two f...