Abstract
GML has become an international encoding standard for exchanging geographic data. Whereas GML documents are often of huge size for containing high redundant spatial data. To reduce the cost for storing and transmitting GML documents, in this paper, we propose a nearest-neighbor delta compression method for GML spatial data. In parsing spatial data items into sequences of coordinates, ordered dictionaries are constructed to collect unique coordinates in each dimension. Coordinate points in the spatial reference system are mapped to points in the dictionary reference system. Each coordinate in the dictionaries is encoded as the floating-point offset from its previous coordinate. Each point in the boundaries of features is encoded as the reversed Z-order offset from its previous point. The proposed nearest-neighbor delta compression method is implemented in the GML compressor GDeltaC. Experiments on 20 GML documents show that GDeltaC outperforms the typical plain-text compressor gzip, the state-of-the-art XML compressor XMill, as well as the first GML compressor GPress in compression ratio.
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Wei, Q., Guan, J., Luo, M., Zou, H. (2013). A Nearest-Neighbor Delta Compression Method for GML Spatial Data. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. Communications in Computer and Information Science, vol 398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45025-9_56
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DOI: https://doi.org/10.1007/978-3-642-45025-9_56
Publisher Name: Springer, Berlin, Heidelberg
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