scholarly journals Cloud Computing Cloud Computing in Remote Sensing : High Performance Remote Sensing Data Processing in a Big data Environment

2021 ◽  
Vol 16 (6) ◽  
Author(s):  
Yassine Sabri ◽  
Aouad Siham
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Data Processing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Remote Sensing Data ◽  
Cloud Service ◽  
Intermediate Data ◽  
High Level

Multi-area and multi-faceted remote sensing (SAR) datasets are widely used due to the increasing demand for accurate and up-to-date information on resources and the environment for regional and global monitoring. In general, the processing of RS data involves a complex multi-step processing sequence that includes several independent processing steps depending on the type of RS application. The processing of RS data for regional disaster and environmental monitoring is recognized as computationally and data demanding.Recently, by combining cloud computing and HPC technology, we propose a method to efficiently solve these problems by searching for a large-scale RS data processing system suitable for various applications. Real-time on-demand service. The ubiquitous, elastic, and high-level transparency of the cloud computing model makes it possible to run massive RS data management and data processing monitoring dynamic environments in any cloud. via the web interface. Hilbert-based data indexing methods are used to optimally query and access RS images, RS data products, and intermediate data. The core of the cloud service provides a parallel file system of large RS data and an interface for accessing RS data from time to time to improve localization of the data. It collects data and optimizes I/O performance. Our experimental analysis demonstrated the effectiveness of our method platform.

Massive Image Treatment System Based on Cloud Computing Platform

2014 ◽  
Vol 687-691 ◽  
pp. 3733-3737
Author(s):  
Dan Wu ◽  
Ming Quan Zhou ◽  
Rong Fang Bie
Keyword(s):  
Image Processing ◽  
Cloud Computing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Virtual Space ◽  
Image Processing System ◽  
Computing Platform ◽  
Simulation Calculation ◽  
Computer Resources

Massive image processing technology requires high requirements of processor and memory, and it needs to adopt high performance of processor and the large capacity memory. While the single or single core processing and traditional memory can’t satisfy the need of image processing. This paper introduces the cloud computing function into the massive image processing system. Through the cloud computing function it expands the virtual space of the system, saves computer resources and improves the efficiency of image processing. The system processor uses multi-core DSP parallel processor, and develops visualization parameter setting window and output results using VC software settings. Through simulation calculation we get the image processing speed curve and the system image adaptive curve. It provides the technical reference for the design of large-scale image processing system.

scholarly journals The Global Land Surface Satellite (GLASS) Remote Sensing Data Processing System and Products

2013 ◽  
Vol 5 (5) ◽  
pp. 2436-2450 ◽  
Author(s):  
Xiang Zhao ◽  
Shunlin Liang ◽  
Suhong Liu ◽  
Wenping Yuan ◽  
Zhiqiang Xiao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Processing ◽  
Land Surface ◽  
Processing System ◽  
Remote Sensing Data ◽  
Data Processing System ◽  
Sensing Data ◽  
Global Land

scholarly journals Оrganization of Web-Based Environmental Monitoring Service Using Earth Remote Sensing Data and Pipelining Data Processing

2021 ◽  
Vol 7 (1) ◽  
pp. 105-121
Author(s):  
A. Scatkov ◽  
K. Krotov
Keyword(s):  
Remote Sensing ◽  
Data Processing ◽  
Environmental Monitoring ◽  
Processing System ◽  
Remote Sensing Data ◽  
Pipeline System ◽  
Sensing Data ◽  
Functional Scheme ◽  
Architectural Organization ◽  
Data Acquisition And Processing

The article analyzes the types of remote sensing data and methods of their processing, which is implemented in order to identify negative natural phenomena and man-made impacts on the environment on the earth’s surface, their characteristics and distribution conditions. The substantiation of the pipelining remote sensing data processing necessity in Web-oriented services environmental monitoring services is carried out. The article substantiates the architectural organization of Web-oriented services for environmental monitoring services and the functional scheme of the data acquisition and processing system. Based on the analysis of the thematic and POST-thematic data processing methods, the organization of a multistage (pipeline) system for the implementing actions with them that provide versatile environmental monitoring is justified.

Justification of information interaction architecture of remote sensing data processing system

2020 ◽  
Vol 5 ◽  
pp. 141-150
Author(s):  
V. M. Safonov ◽  
◽  
D.A. Pavlov ◽  
A.N. Pavlov
Keyword(s):  
Remote Sensing ◽  
Data Processing ◽  
Decision Maker ◽  
Selection Process ◽  
Processing System ◽  
Remote Sensing Data ◽  
Data Processing System ◽  
Sensing Data ◽  
Production Models ◽  
Information Interaction

Purpose: To fi nd an approach to substantiation of the rational architecture of information interaction of the Earth Remote Sensing Data Processing System. Materials and methods: When conducting research in the fi eld of distributed remote sensing data processing as part of the design of a remote sensing data processing system, it seems necessary to create some digital prototype of it. At the fi rst stage of creating such a “digital double”, the architecture of the information interaction of upper-level elements (services, modules, etc.) should be justifi ed in order to ensure effective and consistent application of the system software components. Results: The article proposes an approach to justifying and choosing the architecture of a software system, which is based on production models of decision maker preferences for describing simple and complex reference situations of the survey, processing of knowledge data using methods of the theory of fuzzy measures and theory of experimental design and checking statements Decision maker for consistency. Conclusions: The proposed approach will signifi cantly increase the degree of formalization and validity of the selection process, which as a result provides the opportunity to increase its automation level.

scholarly journals Framework of cloud web services for processing remote sensing data

2019 ◽  
Vol 75 ◽  
pp. 03001
Author(s):  
Alexey Buchnev ◽  
Pavel Kim ◽  
Valery Pyatkin ◽  
Fedor Pyatkin ◽  
Evgeny Rusin
Keyword(s):  
Remote Sensing ◽  
Web Services ◽  
Data Processing ◽  
Processing System ◽  
Remote Sensing Data ◽  
Functional Modules ◽  
Distributed Network ◽  
Data Processing System ◽  
Earth Remote Sensing ◽  
Sensing Data

We consider a distributed network of cloud web services for processing satellite data, which provides data processing facilities for Earth remote sensing within SaaS model. In fact, this is a set of web services that implement the functional modules of the PlanetaMonitoring remote sensing data processing system.

scholarly journals Construction perspectives of the remote sensing data high-performance processing system

2015 ◽  
Vol 6 (1) ◽  
pp. 121-133 ◽  
Author(s):  
V. Khachumov ◽  
◽  
V. Fralenko ◽  
Chen Guo Xiang ◽  
Zhang Guo Liang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Performance ◽  
Processing System ◽  
Remote Sensing Data ◽  
Sensing Data
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