An implementation of a fast clumping algorithm.
netzel
README changes
f7d938c @ 2024-02-24 19:42:51
| Makefile | Initial commit | 2024-02-21 22:59:53 |
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| Makefile.win | Initial commit | 2024-02-21 22:59:53 |
| README.md | README changes | 2024-02-24 19:42:51 |
| clump.c | Initial commit | 2024-02-21 22:59:53 |
| data.c | Initial commit | 2024-02-21 22:59:53 |
| data.h | Initial commit | 2024-02-21 22:59:53 |
| gpl-3.0.txt | Initial commit | 2024-02-21 22:59:53 |
| main.c | Initial commit | 2024-02-21 22:59:53 |
| main.h | Initial commit | 2024-02-21 22:59:53 |
Multi-categorical Connected Component Labelling (CCL) algorithm identifies all 4- or 8- connected regions of cells sharing the same categorical values and assigns each of them a unique label.
The plClump4p, a multi-categorical CCL algorithm, is an efficient variant of a two-scan algorithm modified for use in multi-categorical rasters. It applies a divide-and-conquer technique coupled with parallel processing to a standard two-scan algorithm. Using these techniques causes that algorithm's performance is two-three orders of magnitude better than standard CCL algorithms. The specific speed up depends on the size of the data and its complexity and is greatest for very large and complex rasters.
Windows and linux binaries are included in plTools package.
The program is available under GPL v3 license.
The implemented algotithm is described in the following paper: Pawel Netzel, Tomasz F. Stepinski, 2013: Connected components labeling for giga-cell multi-categorical rasters, Computers & Geosciences, Volume 59, pp 24-30, DOI: 10.1016/j.cageo.2013.05.014.