GeoComputation 2009 [chapter]

Yong Xue, Forrest M. Hoffman, Dingsheng Liu
2009 Lecture Notes in Computer Science  
The tremendous computing requirements of today's algorithms and the high costs of high-performance supercomputers drive us to share computing resources. The emerging computational Grid technologies are expected to make feasible the creation of a computational environment handling many PetaBytes of distributed data, tens of thousands of heterogeneous computing resources, and thousands of simultaneous users from multiple research institutions (Giovanni et al. . GeoComputation is about using
more » ... s different types of geographical and environmental data and developing relevant tools within the overall context of a computational scientific approach. It is concerned with new computational techniques, algorithms, and paradigms that are dependent upon and can take advantage of Grid Computing. It includes spatial data analysis, dynamic modeling, simulation, space-time dynamics and visualization and virtual reality. This conference will offer presentations from a variety of sources, both local, national and international and will enable you to network with others working in similar fields. Grid computing technology is a new method for processing remotely sensed data. Jianwen Ai et al. in their paper "Grid Workflow Modeling for Remote Sensing Retrieval Service with Tight Coupling" discusses some application cases based on Grid computing for Geo-sciences and the application limit of Grid in remote sensing, and provides a method for Grid Workflow modeling for remote sensing. Tight-coupling remote sensing algorithms cannot be scheduled by a Grid platform directly. Therefore, we need an interactive graphical tool to present the executing relationships of algorithms and to generate automatically the corresponding submitted description files for a Grid platform. Image resampling, which is frequently used in remote sensing processing procedures, is a time-consuming task. Parallel computing is an effective way to speed up
doi:10.1007/978-3-642-01973-9_38 fatcat:tafxqi442vhqhj2uiw44gidtdm