面向大数据的地理格网分析操作模型比较

Research Progress of Array Analytics towards Big Data

格网分析操作建模,包括地理格网索引域、值域及其之间的函数定义;基于该定义的操作函数、输入与输出的形式化表达;界定了相应的格网分析技术及其应用。随着物联网和空间对地观测的发展,多维大数据的涌现,对现有2维格网分析基础设施的发展提出了挑战。本文对业界主流的各种格网操作模型进行了系统回顾和比较:首先,介绍地球科学各个领域的多维地理格网及分析需求;然后,抽象了多维格网的形式化定义元素;在此基础上,比较了国内外主要多维格网操作模型,讨论了相应格网操作的输入与输出特征,并总结了不同操作模型的表达能力,论述了格网分析操作建模的方法和需要注意的问题;最后,总结了国内外主流的格网分析语言和系统实现,并展望了其发展趋势和研究方向。

The development of Intemet of Things and Earth Observation brings big observation array data and big array analytics. This paradigm shift challenges the development of current GIS infrastructure which needs in- novative proof and design. Array Analytics is considered as one of potential solutions to address today＇ s data tsu- nami challenge. Formal definitions, such as array domain, range, the mapping function between domain and range, operators, the corresponding input and output are basic building blocks of Array Analytics theory. This pa- per focuses on the world-wide research progress of Array Analytics towards Big Data. Main Array Analytics models are reviewed and discussed by considering different array definition, operation functions, input and out- put, making it possible to explore character differentiation and summarize model expressiveness. Then, main ar- ray analytics technologies and implementations are discussed and compared by considering different models. Ac- cordingly, array analytics modeling patterns, principle issues and directions for future research are concluded as guidance for further exploration on array analytics theory research, technology improvement and domain applica- tions. National Digital Information Infrastructure Initiatives need effective array storage and analytics platforms. The research is conducted as input of further enhancement on Information Application Infrastructure, which is key backbone of GIS analytics services in terms of earth science system monitoring and forecasting, existing dig- ital construction consolidation, and GIS infrastructure improvement, so as to provide effective support to digital region construction.