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One advantage of DGGS is the integration of both raster and vector data. Raster data ingestion involves just transforming the geographic coordinate of each pixel to DGGS cell index space.
API
in: polygon list with vertices defining edges to outside and holes
out: List of cell ids representing the given polygons
Challenges
geographical coordinates inside a polygon are defined only implicitly by vertices of boundaries and holes
The inverse (cell list to polygon) is trivial
Topology might be altered after conversion to DGGS, e.g. rivers disconnected to the ocean or disjoint lines intersect, like in all rasterization (Zhou et al. 2020)
concave polygons needs way more checks and add only little distortion (see here)
Applications
Ingestion of geojson
Raster data in which each pixel has a bounding box footprint
One advantage of DGGS is the integration of both raster and vector data. Raster data ingestion involves just transforming the geographic coordinate of each pixel to DGGS cell index space.
API
Challenges
Applications
Other implementations
polygonToCells
, Reimplementation in Rust, and Add additional modes for polygonToCells uber/h3#775s2region_coverer
ConvertWgs84PolygonAndAddToDggsShapes
(not maintained for >7 years)Potential requirements
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