Cloud Computing for Remote Sensing


Authors : Arvind Chandrasekaran

Volume/Issue : Volume 8 - 2023, Issue 3 - March

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://bit.ly/3zGnFNb

DOI : https://doi.org/10.5281/zenodo.7809303

Abstract : Multi-faceted remote sensing (SAR) and multiarea datasets are widely adopted because of the up-to-date resource information and global and regional monitoring environment. Remote Sensing (RS) data processing involves a multi-step processing sequence, which includes independent processing steps depending on the RS application type. RS data processing for environmental monitoring and regional disaster is computationally recognized and has data demand. The combination of High-Performance Computing and cloud computing propose an efficient method to solve the problems through large-scale RS data search processing for several applications. The elastic, ubiquitous, and high transparency level of cloud computing enables them to run massive RS data management and monitor the dynamic environments on the cloud through the web interface. The cloud service core provides the parallel file system for large-scale RS data and as an interface to access RS data to improve data localization.

Keywords : Edge Computing; Fog Computing; IoT devices; Multi-faceted and multi-area remote sensing (SAR) datasets; High-Performance Computing; Hilbert-based data indexing.

Multi-faceted remote sensing (SAR) and multiarea datasets are widely adopted because of the up-to-date resource information and global and regional monitoring environment. Remote Sensing (RS) data processing involves a multi-step processing sequence, which includes independent processing steps depending on the RS application type. RS data processing for environmental monitoring and regional disaster is computationally recognized and has data demand. The combination of High-Performance Computing and cloud computing propose an efficient method to solve the problems through large-scale RS data search processing for several applications. The elastic, ubiquitous, and high transparency level of cloud computing enables them to run massive RS data management and monitor the dynamic environments on the cloud through the web interface. The cloud service core provides the parallel file system for large-scale RS data and as an interface to access RS data to improve data localization.

Keywords : Edge Computing; Fog Computing; IoT devices; Multi-faceted and multi-area remote sensing (SAR) datasets; High-Performance Computing; Hilbert-based data indexing.

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