webGeoDS — Articles

Interactive articles on spatial data science, with runnable Python and R examples built in, not just diagrams. The standalone tools distill the same checks without the reading.

Vector

Interactive articles that explain a spatial problem properly — the same map, the same runnable Python and R code, compared side by side.

Inspect → Validate → Check Topology → CRS → Buffer

Raster

Interactive articles on reading a raster file properly and computing with it — runnable Python and R code side by side, except where the browser runtime itself draws a hard line (Viewshed runs on R only; Python is shown as reference, with the reason explained plainly).

Inspect → Calculate → NDVI → Viewshed

GeoML

Machine learning on spatial data — finding groups, and predicting labels — runnable Python and R code side by side, including two real places where the two languages disagree: how a clustering result is numbered, and whether a model even classifies at all.

Spatial Clustering → Spatial Classification

Network

Turning a line layer into a graph, and seeing exactly how much a snap tolerance changes how many pieces the network actually has — runnable Python and R code side by side, plus a force-directed diagram of the graph itself.

Network from Lines

GeoStatistics

Predicting a continuous surface from sparse point samples, and filling the gaps in a surface you already have — fitting a variogram model to how similar nearby points really are, instead of just averaging distance-weighted neighbors. Runs on R only; Python is shown as reference, with the reason explained plainly.

Kriging Interpolator → Filling Raster Gaps with Cokriging