Application of Spatial Data Warehouse for Agriculture: Challenge and Future Trends

Abstract

Spatial Data Warehouse (SDW) used for agricultural data is considered capable of responding to user requests in a timely manner by integrating two or more databases which contain geo-spatial data from several different data sources with analytical processing properties. Several studies have linked agriculture with technologies that have the ability to provide updated data, high performance, data availability, predictive capabilities and integrated information in supporting tactical decisions. In agriculture, data exploration using location coordinates for visualization are still challenge to be solved, because geo-spatial and agricultural environmental data do not only include maps of land-use locations, but also other characteristic such as production, population, farmers socio-economic data, etc. Trends in Spatial DW for agriculture discussed usage of SDW with Cloud, Big Data and Real time technology so that high-speed and large-volume agricultural data paths are clear, development and implementation can also be carried out efficiently. The resulting visualization dashboard using SOLAP makes it easy for users to get reliable, real-time data-oriented analysis results and reports. This study aims to present an overview and trends of SDW in agriculture, also support from GIS tools that are capable of generating various types of spatial data as a solution to increase stakeholder satisfaction.