With the rapid advances of data acquisition techniques, spatio-temporal are becoming increasingly abundant in a diverse array disciplines. Here, we develop regression methodology for analyzing large amounts spatially referenced collected over time, motivated by environmental studies utilizing remotely sensed satellite data. In particular, specify semiparametric autoregressive model without usua...

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-featur...

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov-Malyshev-Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize gener...

Automatic road map updating has been one of the difficult and important research topics in the community of geomatics. An operational road map updating system should include three key components: the generation of a new version of roads, the automatic road change detection/updating and the spatio-temporal modelling of road data. Special considerations have to be given to the spatio-temporal mod...

Environmental air pollution studies fail to consider the fact that air pollution is a spatio-temporal problem. The volume and complexity of the data have created the need to explore various machine learning models, however, those models have advantages and disadvantages when applied to regional air pollution analysis, furthermore, most environmental problems are global distribution problems. Th...

Schema versioning provides a mechanism for handling change in the structure of database systems and has been investigated widely, both in the context of static and temporal databases. With the growing interest in spatial and spatio-temporal data as well as the mechanisms for holding such data, the spatial context within which data is formatted also becomes an issue. This paper presents a genera...

Abstract This paper reports a site-specific spatio-temporal channel model for the suburban slightly NLOS (non-line-of-sight) microcellular environment, based on the field test result of the azimuth-delay spectrum. The parameter extraction scheme of the spatio-temporal channel is briefly reviewed [1, 2], first. Then, the implementation issue of the stochastic spatio-temporal fading simulator is ...

Geospatial image data obtained by satellites and aircraft are increasingly important to a wide range of applications, such as disaster management, climatology, and environmental monitoring. Spatio-temporal aggregations are some of the most important operations over such data. Because of the size of the data and the speed at which it is generated, computing such aggregates over geospatial image ...

Managing moving objects in DSMS has recently been a focus of a relatively intense research. In this paper, we are concerned with data streams containing a location of a moving object at any time instant. Instead of using spatial and time instant data types separately, for representing spatio-temporal characteristics of data streams, we propose a unified approach based on specialized temporal da...

1. MOTIVATION With rapid advancements in computing hardware, tracking devices such as GPS receivers and sensors have become pervasive, generating a large amount of spatio-temporal data, such as measurements of temperature, pressure, air quality, traffic, etc. using sensors, GPS data from mobile phones and data from radars that capture location information about people and other moving objects s...