Spatial Data Infrastructures (SDIs) are frequently used to exchange 2D & 3D data, in areas such as city planning, disaster management, urban navigation and many more. City Geography Mark-up Language (CityGML), an Open Geospatial Consortium (OGC) standard has been developed for the storage and exchange of 3D city models. Due to its encoding in XML based format, the data transfer efficiency is reduced which leads to data storage issues. The use of CityGML for analysis purposes is limited due to its inefficiency in terms of file size and bandwidth consumption. This paper introduces XML based compression technique and elaborates how data efficiency can be achieved with the use of schema-aware encoder. We particularly present CityGML Schema Aware Compressor (CitySAC), which is a compression approach for CityGML data transaction within SDI framework. Our test results show that the encoding system produces smaller file size in comparison with existing state-of-the-art compression methods. The encoding process significantly reduces the file size up to 7–10% of the original data.
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