Martin Werner

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.

8 MB

There is some noise, but the structures are clear

64 MB

Errors are already rare.

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

In addition, a sample implementation is available from GitHub at https://github.com/mwernerds/globimap.

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]

   @inproceedings{2019globimap,
     title = {GloBiMaps - A Probabilistic Data Structure for In-Memory Processing of Global Raster Datasets},
     author = {Werner, Martin},
     booktitle = {27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’19)},
     year = {2019}
   }