Spatio-temporal data analysis plays an important role in many scientific applications like environmental epidemiology and public health. Our approach STARS (SpatioTemporal dAtabase system Realized with Shore) integrates spatio-temporal aspects in the persistent object system SHORE [1]. STARS provides an object oriented query language to formulate spatio-temporal queries which can be processed b...

We present regional model simulations of the dust emission events during the Bodélé Dust Experiment (BoDEx) that was carried out in February and March 2005 in Chad. A box model version of the dust emission model is used to test different input parameters for the emission model, and to compare the dust emissions computed with observed wind speeds to those calculated with wind speeds from the reg...

Spatio-temporal extensions to the classical optical ow technique are presented. A novel optical ow estimator is derived capable of incorporating spatio-temporal motion models by iteratively rening initial motion estimates. These initial estimates may be derived from motion in previous frames using a spatio-temporal processing architecture, or from block matching or feature matching techniques. ...

Animals flexibly change their locomotion triggered by an identical stimulus depending on the environmental context and behavioral state. This indicates that additional sensory inputs in different modality from the stimulus triggering the escape response affect the neuronal circuit governing that behavior. However, how the spatio-temporal relationships between these two stimuli effect a behavior...

Weather conditions at the time of wildfire front arrival strongly influence fire behavior and effects, yet few methods exist for estimating weather more spatio-temporally resolved than coarse-grain (e.g., 4 km) daily averages. When a advances rapidly are heterogeneous over space time, greater spatio-temporal precision is required to accurately link observed effects. To identify on effects acros...

s of Talks ______________________________________________________________ 7 What are spatioTemporal Databases ___________________________________________________8 CHOROCHRONOS: A Research Network for Spatio-temporal Database Systems (TMR Programme) ______8 Requirements of Traffic Telematics to Spatial and Temporal Databases _______________________________9 Ontology-Based Map Integration _______...

Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of object...

Abstract. As wind energy increases its share of total electricity generation and integration into the power system becomes more challenging, accurately representing spatio-temporal variability in data crucial. Wind fluctuations impact systems, e.g. planning, vulnerability to storm shutdowns, available voltage stability support. To analyse such their dependencies, time series speeds at an hourly...

• An enhanced wind power scenario generation and evaluation method is proposed. A non-separable covariance function incorporated to capture spatial temporal correlations. more accurate parameter estimation with fluctuation-based clustering New indices from the perspective of system operators are introduced. Short-term scenarios significantly affect economic efficiency stochastic scheduling. In ...