Literature Review on Temporal, Spatial, and Spatiotermpoal Data Models

This paper reviews papers on temporal databases, spatial databases, and spatio-temporal databases

Affine-Invariant Triangulation of Spatio-Temporal Data with an Application to Image Retrieval

In the geometric data model for spatio-temporal data, introduced by Chomicki and Revesz , spatio-temporal data are modelled as a finite collection of triangles that are transformed by time-dependent affinities of the plane. To facilitate querying and animation of spatio-temporal data, we present a normal form for data in the geometric data model. We propose an algorithm for constructing this normal form via a spatio-temporal triangulation of geometric data objects. This triangulation algorithm generates new geometric data objects that partition the given objects both in space and in time. A particular property of the proposed partition is that it is invariant under time-dependent affine transformations, and hence independent of the particular choice of coordinate system used to describe the spatio-temporal data in. We can show that our algorithm works correctly and has a polynomial time complexity (of reasonably low degree in the number of input triangles and the maximal degree of the polynomial functions that describe the transformation functions). We also discuss several possible applications of this spatio-temporal triangulation. The application of our affine-invariant spatial triangulation method to image indexing and retrieval is discussed and an experimental evaluation is given in the context of bird images

Requirements, Definitions and Notations for Spatiotemporal Application Environments

Modeling spatiotemporal applications is a complex task involving intricate issues, such as the representation of objects' position in time, and spatial attributes that change values depending on specific locations in time periods. Due to this complexity, the analysis of users' requirements-as the first phase of an application development methodology-is often neglected, focusing, mainly, on physical design aspects. In this paper, we address the set of spatial, temporal and spatiotemporal concepts as they are drawn from users' needs. The goal is to support the developer's better understanding about spatiotemporal applications, by providing the concepts and the notations needed in such environments; these concepts will, later, be translated into specific constructs and implementation issues. More specifically, space, spatial objects, spatial attributes, fields, time and models of time are presented and then combined to accommodate spatiotemporal peculiarities, resulti..

A Temporal GIS Approach to Characterizing Geographical Dynamics

Temporal GIS research has historically focused on change, motion, and events. This research introduces a framework to represent concepts of fluid kinematics with the emphasis on the concept of flows. General circulation models (GCMs) and other spatially explicit environmental models produce massive time series of geographic fields (e.g. temperature) that call for effective GIS approaches to elicit temporal information embedded in these model outputs. Common temporal GIS approaches with discrete constructs in space and time tend to overlook the spatiotemporal continuity that is fundamental to the understanding of geographic dynamic fields, such as temperature. Common methods of analyzing climatological characteristics center on trend analysis at fixed locations or monitoring meteorological phenomena, such as storm tracks, to evaluate circulation changes. The proposed temporal GIS framework, on the other hand, uses the velocity of virtual particles with fixed climatological values to capture changes in scalar continuous fields. The resulting spatiotemporal distributions of velocity suggest kinematic flows that can be used to recognize features indicative of geographic processes, such as divergence and convergence of isolines. Summative characterizations of these kinematic features highlight the embedded change and motion in these temporal sets of scalar fields and facilitate understanding and comparing model outputs

Formal extension of the relational model for the management of spatial and spatio-temporal data

[Resumen] En los últioms años, se ha realizado un gran esfuerzo investigador en la manipulación de datos especiales y Sistemas de Información Geográfica (SIG). Una clara limitación de las primeras aproximaciones es la falta de integración entre datos geográficos y alfanuméricos. Para resolver esto surge el área de Bases de Datos Espaciales. Los problemas que aparecen en este campo son muchos y complejos. Un primer ejemplo son las peculiaridades de las operaciones espaciales, como el calculo de la intersección espacial de dos superficies. Otro ejemplo es el elegir las estructuras de datos apropiadas (relaciones, capas, etc.) y el conjunto de operaciones adeucado. La combinación con las Bases de Datos Temporales da lugar a las Bases de Datos Espacio-temporales, en las que la inclusión de la dimensión temporal complica más los problemas anteriores. A pesar de la gran cantidad de aproximaciones propuestas, no se ha llegado todavía a una solución satisfactoria. La presente tesis propone una nueva solución que resuelve todos los problemas de modelado de datos espaciales y espacio-temporales resaltados arriba. Parte del trabajo se completó durante el proyecto ""CHOROCRONOS"": A Research Network for Saptiotemporal Database Systems"", financiado por la Unión Europea. El modelo propuesto en la tesis define tres tipos de dato punto, línea y superficie, que encajan perfectamente en la percepción humana. La definición de estos tipos de dato se basa en la definición previa de Quanta Espacial. Las estructuras de datos usadas son las relaciones no anidadas de modelo relacional puro. El conjunto de operaciones relacionales permite alcanzar casi por completo la funcionalidad propuesta en otros modelos. Todas las operaciones han sido definidas en base a un núcleo reducido de operaciones primitvas. Todos los tipos de datos, espaciales, espacio-temporales y convencionales se manipulan de forma uniforme con este conjunto de operaciones