LandQv1: A GIS cluster-based management information system for arable land quality big data

Abstract

In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese arable land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQv1, based on the GIS cluster to support arable land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQv1 is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQv1 with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for arable land big data analyzing in the future.