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Position: Home > Articles > Spatio-temporal Information Service of Sandstorm Disaster Risk Factor Data in China during the Last 60 Years Journal of Northwest Forestry University 2015,30 (2) 158-165+195

近60年中国沙尘暴灾害风险因子时空信息服务研究

作  者:
孙伟;曹姗姗;侯瑞霞;唐小明
单  位:
中国林业科学研究院资源信息研究所;新疆农业大学计算机与信息工程学院
关键词:
沙尘暴;灾害风险因子;WebGIS;时空信息;Web服务
摘  要:
针对沙尘暴灾害研究中存在的多专题、多时相、多层次海量数据管理与分析的共性问题,研究基于时空数据模型有效组织了近60a中国沙尘暴灾害风险因子数据,利用层架构模式设计了沙尘暴灾害风险因子管理系统的体系结构,以地统计和空间分析理论为基础提出了沙尘暴气象因子专题制图方法,通过瓦片式地图技术构建了沙尘暴大数据量高性能瓦片地图服务,综合应用WebGIS理论与技术设计并实现了系统主要功能。典型应用案例分析表明,该系统的构建方法与技术在提供沙尘暴灾害风险时空数据的高效管理服务和辅助决策信息服务方面是切实有效的。
译  名:
Spatio-temporal Information Service of Sandstorm Disaster Risk Factor Data in China during the Last 60 Years
作  者:
SUN Wei;CAO Shan-shan;HOU Rui-xia;TANG Xiao-ming;College of Computer and Information Engineering,Xinjiang Agricultural University;Research Institute of Forest Resources Information Techniques,Chinese Academy of Forestry;
关键词:
sandstorm;;disaster risk factor;;WebGIS;;spatio-temporal information;;web service
摘  要:
In order to solve common problems existed in the management and analysis of spatio-tamporal massive data in sandstorm disaster research while carrying out multi-theme,multi-level and multi-temporal investigation,data of sandstorm disaster risk factor in China nearly 60 years(1951-2009)were effectively organized by utilizing the spatio-temporal data model Geodatabase,and the system structure of the information management system of sandstorm disaster risk factor(IMS-SDRF)was designed based on the tier architecture model.Furthermore,a sandstorm weather factors spatio-temporal distribution thematic mapping method was put forward according to the geo-statistics and space analysis theories in GIS,and the high-performance tile map services of sandstorm massive data were constructed by using the tile map technology.Finally,the main functions of the IMS-SDRF were designed and developed based on the comprehensive application of WebGIS theory and technology.And the typical application case analysis showed that the IMS-SDRF was feasible and effective in the efficient management and assistant decision information services of sandstorm disaster risk spatio-temporal data.

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