Building data infrastructure for geo-computation by spatial information grid

Huang, Zhenchun; Li, Guoqing; Zeng, Yi

doi:10.1109/gcc.2007.52

Cited by 1 publication

(1 citation statement)

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“…These resources are provided by di®erent provider groups and stored in di®erent nodes, and must be combined to complete user application requirements. In previous online spatial information services, such as SIG [40], the user¯rst chose data, then the system provided on-demand data services for the selected data, such as cutting or mosaicking. In practical applications, these resources should be used and organized comprehensively to form a data service chain À À À call every kind of data source and computing resource, meet users' speci¯c needs, and enable cooperation among distributed resources.…”

Section: Architecture and Componentsmentioning

confidence: 99%

A "Resource Package"-Oriented Approach for Remote Sensing Analysis Modeling — Dust Storm Monitoring Model as Example

Zou

et al. 2014

Int. J. Soft. Eng. Knowl. Eng.

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Now, with the development of intelligent service technology, information provisioning models are changing from simple, single-type models to complex, on-demand models as required. Remote sensing analysis modeling often requires the use of multiple data sources, computer resources, tools, and models, and couples these resources into a work°ow for global change research. Therefore, remote sensing analysis modeling research today faces a critical challenge: the registry, discovery, and allocation of modeling resources are complex, as they are heterogeneous and geographically distributed. This paper proposes a resource package-oriented approach that provides guidelines for remote sensing analysis modeling to increase model sharing and integrating. This uni¯ed wrapping approach can be used to make the management and use of existing resources becoming easy and reusable. Based on this description of construction method, di®erent remote sensing analysis resources can be combined together on-demand. We developed a web environment to compose di®erent remote sensing modeling resources as ondemand processing components, based on the existing work°ow engineering, and use a dust storm monitoring model as an example. Comparative analyses are given to further explain the applications of this hierarchical construction method in the areas of the remote sensing analysis model.

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Section: Architecture and Componentsmentioning

confidence: 99%