Abstract
As remote sensing technologies have become ever more powerful due to the introduction of multi-platforms and multi-sensors, hundreds of terabytes of image data can be made available daily. But in many cases, raw remotely sensed images are not directly useful without further processing. There are more and more needs to aggregate remotely sensed image processing to satisfy the increasing demands of various applications. Remotely sensed image processing services are modular components that are self-contained, self-describing and can be published, located, and invoked across a network to access and process remote sensing data (Onchaga 2004). Remotely sensed image processing services encapsulate all processing functions into services and combine them into a service chain to provide a valueadded service. The various requirements of users can be achieved by combining different existing data and services into a value-added service chain.
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Zhu, Q., Yang, X., Li, H. (2010). Optimal Composition Algorithm Concerned with Response Time for Remotely Sensed Image Processing Services. In: Li, D., Shan, J., Gong, J. (eds) Geospatial Technology for Earth Observation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0050-0_14
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