地理空间模型输入数据自动匹配方法研究

Research on the Automatic Matching Method of Input Data for Geospatial Models

地理空间模型是地学研究中的重要工具,然而随着研究的深入,日益复杂的输入数据制备过程已成为影响地理空间模型应用和发展的严重障碍。当前数据共享快速发展,网络上已经存在大量的开放共享数据。因此,从网络开放共享数据中为地理空间模型自动匹配符合需求的数据是解决该问题的一种有效解决方案。本文提出了一种地理空间模型输入数据自动匹配方法,该方法首先通过选取统一描述因子,构建一致性描述方法,消除网络共享数据和地理空间模型在描述内容上的异构性;在此基础上,对地理空间模型输入需求和网络共享数据进行匹配计算,并通过相似度、匹配关系、匹配范围等相结合的方式精准记录两者间的匹配程度和匹配细节,为数据自动处理奠定基础;最后,针对不完全匹配数据,采用基于网络服务的数据自动处理方法消除其与地理空间模型输入需求间的差异,从而实现地理空间模型输入数据的自动匹配。土壤生产潜力模型应用实例表明,本文方法可有效实现地理空间模型输入数据的自动匹配,为解决地理空间模型输入数据制备困难问题提供参考。

Geospatial models are important tools in geoscience research.However,with the deepening of research,the increasingly complex input data preparation for geospatial models has become a serious obstacle to it’s application and development.With the rapid development of data sharing,there are a large number of open shared data on the network.Therefore,it is an effective solution to automatically match the required data for geospatial models.In this background,an automatic matching method is proposed.Firstly,the uniform describing factors are selected to construct a consistent describing method,which can eliminate the heterogeneity in describing content between shared data and geospatial model.On this basis,it calculates the matching situation between the input requirements of geospatial model and shared data,and uses the combination of similarity,matching relation,matching range and so on to record the matching degree and matching details accurately,which lays a foundation for automatic data processing.Finally,aiming at the incomplete matching data,an automatic data processing method based on network services is adopted to eliminate the differences between the incomplete matching data and the geospatial model input requirements,so as to realize the automatic data matching for the geospatial model.The case of soil productivity potential model application shows that this method can effectively realize the automatic data matching for geospatial models,and provide a reference for solving problem of preparing input data for geospatial models.