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The operational processing of remote sensing data usually requires high-performance radiative transfer model (RTM) simulations.
As a result, the operational processing of remote sensing image time series requires preliminary correction steps, such as the detection of clouds and the correction for atmospheric effects.
The rapid processing of remote sensing (RS) images is essential in many large-scale real-time monitoring, such as meteorological monitoring and natural disaster warning.
Due to the extensive requirements of resources and manual workload, Pasher et al. suggested (semi) automated processing of remote sensing imagery to advance their approach for assessing the urban tree canopy or to provide general rapid re-assessments.
While the resolution has improved, the amount of remote sensing image data and the redundant information is also increasing, and it is not conducive to the processing of remote sensing image.
Two major design decisions were full automation of the discovery, retrieval and processing of remote sensing data from multiple sources, and making the system easily modifiable in response to changes in data availability and user needs.
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Sea-land segmentation is a key step for the information processing of ocean remote sensing images.
Also, the considerable amount of computer processing of the remote sensing imagery in regard to positional and spectral distortions requires a revision process which can integrate other maps and ancillary data in order to produce a sound analysis of the spatial pattern.
For each slot, there are two types of PTE's, local and remote PTE's for the processing of local and remote blocks, respectively.
When it does need to assign a data block to a remote slot, ECT chooses a block on the local disk of the slot that has the maximum Remaining Local Processing Time (RLPT) to further reduce the amount of remote processing.
From this point on until the end of the map phase, the majority of the data blocks would be processed by remote slots, and large amount of remote processing causes the sharp rise of the Hadoop trace.
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