Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic systems. In geographic information systems, analysis and modeling at pre-defined spatial and temporal scales may miss critical relationships in other scales. Previous studies have investigated the uses of the triangle model as a multi-scale framework in analyzing temporal data. This article demonstrates the utilities of the triangle model and pyramid model for multi-scale spatial analysis through real-world analytical tasks and discusses the potential of developing a unified modeling framework that integrates the two models
Process-based spatio-temporal component models simulate real world processes, using encapsulated pro...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...
Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic system...
The representations of space and time are fundamental issues in GIScience. In prevalent GIS and anal...
The representations of space and time are fundamental issues in GIScience. In prevalent GIS and anal...
Many disciplines are faced with the problem of handling time-series data. This study introduces an i...
This paper introduces an innovative representation of time series data, namely, the Continuous Trian...
Most of the discussion in the CIS community is concerned at the highest level with the support of ma...
When studying geographical phenomena, different levels of spatial and temporal granularity often hav...
<p>An MSSpDES model of the system under consideration is constructed and simulated to generate time ...
To support analysis and modelling of large amounts of spatio-temporal data having the form of spatia...
Presented at the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information ...
Multiple granularities provide an essential support for extracting significant knowledge from spatio...
Thesis (Ph.D.)--University of Washington, 2018Across scientific disciplines, an ever-growing proport...
Process-based spatio-temporal component models simulate real world processes, using encapsulated pro...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...
Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic system...
The representations of space and time are fundamental issues in GIScience. In prevalent GIS and anal...
The representations of space and time are fundamental issues in GIScience. In prevalent GIS and anal...
Many disciplines are faced with the problem of handling time-series data. This study introduces an i...
This paper introduces an innovative representation of time series data, namely, the Continuous Trian...
Most of the discussion in the CIS community is concerned at the highest level with the support of ma...
When studying geographical phenomena, different levels of spatial and temporal granularity often hav...
<p>An MSSpDES model of the system under consideration is constructed and simulated to generate time ...
To support analysis and modelling of large amounts of spatio-temporal data having the form of spatia...
Presented at the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information ...
Multiple granularities provide an essential support for extracting significant knowledge from spatio...
Thesis (Ph.D.)--University of Washington, 2018Across scientific disciplines, an ever-growing proport...
Process-based spatio-temporal component models simulate real world processes, using encapsulated pro...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...
This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt t...