the determination of temporal and spatial salinity in tidal rivers is significant in supplying water for agriculture purposes, particularly where there is no controller dam at the downstream. in this research, the coherens model was applied to study the hydraulics of water flow, salinity distribution and transmission at the bahmanshir river. coherens is a 3d multi-purpose hydrodynamic model whi...

geographic information and analysis provide a wide range of data and techniques to monitor and manage natural resources. as an important case, in arid and semi-arid areas, water management is critical for both local governance and citizens. as a result, the estimation of water potential brought by snowmelt runoff and rainfalls seems to be very useful and important for these areas. hydrological ...

Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in statistical methods dedicated to detecting cerebral activation. We propose a new method for modeling the covariance of a stationary spatio-temporal random process and apply this approach to fMRI data analysis. For do...

This paper describes a spatio-temporal configurations building approach, which has been applied to dynamics points in 1-dimensional space. In this approach, a temporal logic, Allen’s time intervals, is crossed with a new spatial logic based on topology called spatial states. These spatial states are derived from topological relationships and a new concept of degenerate topological relationships...

In this paper we define a spatio-temporal model with location dependent parameters to describe temporal variation and spatial nonstationarity. We consider the prediction of observations at unknown locations using known neighbouring observations. Further we propose a local least squares based method to estimate the parameters at unobserved locations. The sampling properties of these estimators a...

We describe current research in temporal, spatial, and spatiotemporal data mining. In these types of data mining, a model of time, space, or space-time plays a nontrivial role. As an example of current research, we describe our MegaMiner prototype software. The DGG-Discover 5.2 module of MegaMiner is based on expected distribution domain generalization graphs (EDDGGs), which allow detailed doma...

An understanding of the dynamic process of urban growth is a prerequisite to the prediction of land-cover change and the support of urban development planning and sustainable growth management. The spatial and temporal complexity inherent in urban growth requires the development of a new simulation approach, which should be process-oriented and have a strong interpretive element. In this paper ...

A central goal in limnology is measurement of physical, biogeochemical, and biological process rates. We can measure process rates from the temporal and spatial patterns they create in a measured variable, and we use 3 approaches for making those measurements: the fixed-site approach for detecting temporal pattern at a location, the snapshot approach for detecting spatial pattern at an instant ...

The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic ...