Spatial data warehouse design and spatial OLAP implementation for decision making of geospatial data update

Many authorities and local governments collect and maintain immense geospatial databases composed of various types of vector and raster data. These geospatial data need to be updated and monitored on a regular basis to provide accurate information. As the mapping area and the variety of data (GPS, DEM, LIDAR, aerial photography, satellite imagery, 3D building models, texture images, videos, etc.) collected for these areas increase, the maintenance costs also increases. Therefore, it is crucial to make effective costsaving decisions regarding the time, place, and type of geospatial data to be updated. In this study, geospatial data updating criteria are discussed and a multi-dimensional database model is proposed to aid the decision-making process in updating geospatial data. Based on this model, a star schema SDW (Spatial Data Warehouse) is designed and a SOLAP (Spatial OLAP) is implemented to aid in making optimal decisions regarding geospatial database updating.