We are happy to announce that our latest research on a randomized data structure GloBiMap (Werner, 2019) for high-resolution, low-cardinality global raster information (e.g., which place on Earth contains a building) has been selected for full-paper presentation at ACM SIGSPATIAL GIS. We are excited about the positive reviews.

The following images illustrate the power by showing urban regions over Europe by color-coding 20x20 pixel patches.

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There is some noise, but the structures are clear

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Errors are already rare.

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Note that we have an error correction methodology in the paper allowing you to have an exact representation!

  1. Werner, M. (2019). GloBiMaps - A Probabilistic Data Structure for In-Memory Processing of Global Raster Datasets. In 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’19). [PDF] [BibTeX]