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计算机系统应用英文版:2016,25(2):31-37
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突发水污染事件中遥感瓦片大数据存储系统
(1.西安工程大学 计算机科学学院, 西安 710048;2.西安理工大学 水资源研究所, 西安 710048;3.西安理工大学 经济与管理学院, 西安 710048)
Storage System on the Remote Sensing Tile Data Based on Big Data Technology in Sudden Water Pollution Incident
(1.College of Computer Science, Xi'an Polytechnic University, Xi'an 710048, China;2.Water Resources Research Institute, Xi'an University of Technology, Xi'an 710048, China;3.College of Economics and Management, Xi'an University of Technology, Xi'an 710048, China)
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Received:May 06, 2015    Revised:June 08, 2015
中文摘要: 突发水污染事件频发,利用GIS平台、遥感技术及水质模型对突发水污染事件进行模拟研究逐渐成为一种发展趋势.针对目前海量、异构、动态遥感数据难以快速处置和高效存储的问题,基于HBase设计和实现了突发水污染事件的遥感瓦片大数据存储系统.该系统以数字地球平台为支撑,结合遥感瓦片金字塔模型和MapReduce框架,考虑实时、动态观察事件发展态势引起的瓦片数据频繁加载特点,对遥感瓦片数据的线性四叉树编码索引进行了改进,将其同水污染数据一并存储到HBase数据库中,并通过增加缓存区来提升遥感瓦片数据的访问效率.将此系统应用于渭河陕西段突发水污染事件中,实验结果表明:改进后的索引可在200个毫秒时间内提取到水污染区域的遥感数据,引入的缓存机制使得水污染区域遥感数据的加载时间节省了近2/3.因此,该存储系统访问效率高,能够满足突发水污染事件快速应急模拟的需求.
Abstract:The sudden water pollution incidents occur frequently, so it has become a trend to do simulated research on sudden water pollution incident utilizing GIS platform, remote sensing technology and water quality model. Aiming at solving the problem that mass, heterogeneous and dynamic remote sensing data could not be disposed rapidly and stored efficiently; the storage system of remote sense tile data used in the sudden water pollution incidents was designed and implemented based on HBase. The system is supported by the digital earth platform and integrated with remote sensing tile pyramid model and MapReduce framework. The linear quad tree coding index of the remote sensing tile data was improved in this system according to the frequent load character of remote sensing tile data caused by event situation with real-time and dynamic observation and stored into HBase together with water pollution data. The access efficiency of the remote sensing tile data was increased through adding cache area. Applying this system to Weihe River sudden water pollution in Shanxi, the results showed that the improved index could extract the remote sensing data of the water pollution area within 22 milliseconds and the introduction of the caching mechanism saved almost 2/3 loading time on the remote sensing data in water pollution area. Therefore, the storage system could be accessed efficiently and it could satisfy the quick emergent simulation demand of the sudden water pollution incidents.
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基金项目:"十二五"国家水体污染控制与治理重大专项课题(2012ZX07201-006);陕西省自然科学基础研究计划(2015JQ5157);陕西省教育厅科学研究计划(14JK1293);西安工程大学博士科研启动基金(BS1330)
引用文本:
李维乾,解建仓,李建勋,李莉.突发水污染事件中遥感瓦片大数据存储系统.计算机系统应用,2016,25(2):31-37
LI Wei-Qian,XIE Jian-Cang,LI Jian-Xun,LI Li.Storage System on the Remote Sensing Tile Data Based on Big Data Technology in Sudden Water Pollution Incident.COMPUTER SYSTEMS APPLICATIONS,2016,25(2):31-37