PARALLEL PROCESSING ALGORITHMS AND SOFTWARE FOR REMOTE SENSING ARCHIVE DATA IN DISTRIBUTED COMPUTING ENVIRONMENTS
DOI:
https://doi.org/10.5281/zenodo.19364808Abstract
The rapid growth of remote sensing archive data has created significant challenges for efficient processing and analysis. Therefore, this study examines parallel processing algorithms and software solutions within distributed computing environments. In particular, it highlights how data parallelism, task parallelism, and scalable infrastructures enable faster and more efficient handling of large geospatial datasets. As a result, parallel approaches improve processing speed, system scalability, and overall performance, while also addressing the limitations of traditional sequential methods..
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