2021-04-23, 18:00–18:30, Track 1
PyInterpolate is designed as the Python library for geostatistics. It's role is to provide access to spatial statistics tools used in a wide range of studies. The main advantage of a package is ability to transform areal aggregates into smaller blocks with Area-to-Point Poisson Kriging technique.
PyInterpolate is designed as the Python library for geostatistics. It's role is to provide access to spatial statistics tools used in a wide range of studies.
If you’re:
- GIS expert,
- geologist,
- mining engineer,
- ecologist,
- public health specialist,
- data scientist.
Then this package may be useful for you. You could use it for:
- spatial interpolation and spatial prediction,
- alone or with machine learning libraries,
- for point and areal datasets.
Pyinterpolate allows you to perform:
- Ordinary Kriging and Simple Kriging (spatial interpolation from points),
- Centroid-based Kriging of Polygons (spatial interpolation from blocks and areas),
- Area-to-area and Area-to-point Poisson Kriging of Polygons (spatial interpolation and data deconvolution from areas to points).