What is raster resampling primarily used for?

Raster resampling is primarily used to change the cell size of a raster dataset. This process is crucial when working with raster data, especially when combining different raster layers that may have varying cell sizes or resolutions. By resampling, you can adjust the resolution of a raster image, either to enhance its clarity by increasing the cell size (zooming in) or to reduce the amount of data being analyzed by decreasing the cell size (zooming out).

This adjustment might be necessary, for example, before overlaying different datasets, in order to ensure that they align properly and that analysis yields relevant and accurate results. Through resampling, you ensure that raster layers are compatible and that the analysis applied to them is appropriate considering their spatial representation.

Other options focus on different aspects of GIS but do not directly relate to the fundamental purpose of raster resampling. Correcting errors in data involves error correction techniques, acquiring new datasets pertains to data collection methods, and analyzing spatial relationships within networks deals with vector data and network analysis, which is distinct from the adjustments made in raster datasets.