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- dggs-replication-2026 hasScopeDescription "This study aims to reproduce and replicate the computational benchmark experiments from Law & Ardo (2024) "Using a discrete global grid system for a scalable, interoperable, and reproducible system of landuse mapping" (DOI: 10.1080/20964471.2024.2429847). Specifically: 1. VECTOR BENCHMARK (Figure 6): Reproduces the comparison between traditional vector overlay operations and DGGS-based methods using H3 polyfilling, testing scalability across 5-500 input layers. 2. RASTER BENCHMARK (Figure 7): - REPRODUCTION: Recreates the paper's comparison using H3 Python bindings for coordinate-to-cell conversion - REPLICATION: Implements an alternative approach using xdggs for vectorized H3 indexing The study aims to validate the paper's claims that (1) DGGS provides orders of magnitude performance improvement for vector operations, and (2) DGGS and raster methods show roughly equivalent performance for raster operations when using pre-indexed data." assertion.