An On-Demand Service for Managing and Analyzing Arctic Sea Ice High Spatial Resolution Imagery
An On-Demand Service for Managing and Analyzing Arctic Sea Ice High Spatial Resolution Imagery
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DOI：
10.3390/data5020039
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发表时间：
2020-04
期刊：
影响因子：
2.6
通讯作者：
D. Sha;X. Miao;Mengchao Xu;C. Yang;H. Xie;Alberto M. Mestas-Nuñez;Yun Li;Qian Liu;Jingchao Yang
中科院分区：
文献类型：
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作者：
D. Sha;X. Miao;Mengchao Xu;C. Yang;H. Xie;Alberto M. Mestas-Nuñez;Yun Li;Qian Liu;Jingchao Yang
海冰既是气候变化的指示器，也是气候变化的放大器。高空间分辨率（HSR）图像是北极海冰研究中提取海冰物理参数、气候模型校正和验证的重要数据源。高速铁路影像数据量大、数据源异构、时空分布复杂，难以处理和管理。在本文中，北极网络基础设施（ArcCI）模块的开发，允许一个可靠的和高效的按需图像批量处理在网络上。对于这个模块，通过一个开放的数据门户收集和提供可用的相关数据集。ArcCI模块为高铁海冰图像提供了基于云计算和大数据组件的架构，包括：（1）通过文件传输协议（FTP）传输、前端上传和物理传输的数据获取;（2）基于Hadoop分布式文件系统和成熟的可操作关系数据库的数据存储;（3）分布式图像处理，包括基于对象的图像分类和海冰特征参数提取，（4）利用灵活的统计图表对提取参数的动态时空分布进行三维可视化。北极研究人员可以在开放的数据门户中搜索和查找北极海冰HSR图像和相关元数据，获取提取的冰参数，并进行交互式可视化分析。拥有大量图像的用户可以利用该服务在云上以高性能的方式处理他们的图像，并在一个地方管理和分析结果。ArcCI模块将协助领域科学家调查极地海冰，并可以很容易地转移到其他HSR图像处理研究项目。
Sea ice acts as both an indicator and an amplifier of climate change. High spatial resolution (HSR) imagery is an important data source in Arctic sea ice research for extracting sea ice physical parameters, and calibrating/validating climate models. HSR images are difficult to process and manage due to their large data volume, heterogeneous data sources, and complex spatiotemporal distributions. In this paper, an Arctic Cyberinfrastructure (ArcCI) module is developed that allows a reliable and efficient on-demand image batch processing on the web. For this module, available associated datasets are collected and presented through an open data portal. The ArcCI module offers an architecture based on cloud computing and big data components for HSR sea ice images, including functionalities of (1) data acquisition through File Transfer Protocol (FTP) transfer, front-end uploading, and physical transfer; (2) data storage based on Hadoop distributed file system and matured operational relational database; (3) distributed image processing including object-based image classification and parameter extraction of sea ice features; (4) 3D visualization of dynamic spatiotemporal distribution of extracted parameters with flexible statistical charts. Arctic researchers can search and find arctic sea ice HSR image and relevant metadata in the open data portal, obtain extracted ice parameters, and conduct visual analytics interactively. Users with large number of images can leverage the service to process their image in high performance manner on cloud, and manage, analyze results in one place. The ArcCI module will assist domain scientists on investigating polar sea ice, and can be easily transferred to other HSR image processing research projects.